Biomedical Applications – CompBioMed Conference

From Quantum AI to the Virtual Human

Emily Lumley — Thu, 29 Nov 2018 16:43:02 +0000

Invited Speakers

Prof Prineha Narang, Harvard
Dr Vivien Kendon, Durham University
Anita Ramanan, Microsoft
Prof Peter Coveney, UCL

Symposium Chair

Peter Love, Associate Professor in Department of Physics and Astronomy

Symposium Description

Advanced scientific computing projects such as the Virtual Human represent the pinnacle of ninety years of development of conventional classical computing. Quantum computers represent a completely different approach to information processing. Future quantum computers can be used for highly secure data management; to solve chemical problems in drug and materials design; and potentially solve complex optimisation problems in machine learning. In the next decade we expect quantum computers to solve problems that lie beyond capabilities of existing computers. We will assess the prospects for the advent of such machines, and their implications for projects such as the Virtual Human that are at the frontier of advanced scientific computing.

Wednesday 25th September, 13:30 – 15:30; Turing Lecture Theatre

Time	Speaker	Title
13:30	Peter Love	Introduction
13:45	Prineha Narang (Invited Speaker)	Excited-State Dynamics: Linking Classical and Quantum Approaches Abstract Preview Utilizing quantum computers for scientific discovery presents many challenges driven by the currently still-experimental nature of quantum hardware and the absence of the essential software needed to “program” this hardware in the near term. Software for quantum computing is in its infancy, and therefore the development of executable code for quantum hardware using current strategies is arduous. In this context, in the first part of the talk, I will discuss our recent demonstration of a new allocation algorithm that combines the simulated annealing method with local search of the solution space using Dijkstra’s algorithm. Our algorithm takes into account the weighted connectivity constraints of both the quantum hardware and the quantum program being compiled. Using this novel approach, we are able to optimally reduce the error rates of quantum programs on various quantum devices. In the second part of my talk, I will present a strategy to compute excited-states and reaction dynamics on NISQs. Finally, I will discuss a pathway to computing “complex” molecules, both energies and dynamics, leveraging a combination of quantum chemistry and quantum computer science approaches. Full Abstract
14:15	Vivien Kendon (Invited Speaker)	Quantum computing using continuous-time evolution Abstract Preview In the quest for more computing power, the dominant digital silicon architectures are reaching the limit of physically possible processor speeds. The heat conduction of silicon limits how fast waste heat can be extracted, in turn limiting the processor speeds. Moreover, energy consumption by computers is now a significant fraction of humanity’s energy use, and current silicon devices are orders of magnitude away from optimal in this respect. We can’t afford to apply more and more standard computers to solve the biggest problems, we need more energy-efficient computational materials, and more efficient ways to compute beyond digital. Full Abstract
14:45	Anita Ramanan and Frances Tibble (Invited Speakers)	Quantum Inspired Optimisation: Transforming Healthcare Imaging using Quantum-accelerated Algorithms Abstract Preview Join this session to learn more about Microsoft’s investment in quantum computing and see how the Microsoft Quantum team are leveraging quantum inspired optimisation techniques today to solve some of industry’s most complex problems. The session will focus on the groundbreaking collaboration between Microsoft Quantum and Case Western Reserve University to enhance MRI technology through pulse sequence optimisation, reducing scan time and improving results. Full Abstract
15:05	Crispin Keable	Atos Quantum Learning Machine: Heading towards a quantum-accelerated life science Abstract Preview The first quantum revolution, led in the early twentieth century by young Europeans of the likes of Einstein, Heisenberg and Planck, gave birth over the years to major inventions including the transistor, the laser, MRI and GPS. Today, taking advantage of Atos’ expertise in supercomputers and cyber security, Atos is fully committed to the second quantum revolution that will disrupt all our clients’ business activities in the coming decades, from medicine to agriculture through finance. However, the computer research community has come to realize that no General-Purpose Quantum Computing (GPQC) will be available on the market for 10 to 15 years. In the meantime, a lot of research and engineering steps are needed, both in terms of the hardware and software environment. Full Abstract
15:20	Peter Coveney	Quantum AI to the Virtual Human; where’s the virtual human?
15:35	REFRESHMENTS AND POSTER SESSION

Oncology

Emily Lumley — Thu, 29 Nov 2018 16:42:19 +0000

Invited Speakers

Dr Dwight Nissley, Leidos Biomedical Research, Inc
Dr Fred Streitz, Lawrence Livermore National Laboratory
Dr Georgia Tourassi, Oak Ridge National Laboratory
Dr Mari Nygard, Cancer Registry of Norway
Prof Tim Hubbard, Kings College London (tbc)

Symposium Chair

Eric Stahlberg, Director of Biomedical Informatics and Data Science

Symposium Description

There is no doubt that computing and technology are central to the future for precision oncology. Rapid advances in computational approaches including large-scale machine learning, new computing technologies, exponential growth of biomedical data, and increasing volumes of available health information are the powering a new wave of advances forming the foundations for the future for precision oncology. In order to realize the promise of these transformative advances, effective translation for clinical impact is essential in areas such as preventative screening, improved disease characterization and diagnosis, discovery of new treatments, and managing post-diagnosis patient health. The symposium will bring together leaders shaping the future of precision oncology in computing, biomedical data and health information resources and management, and clinical applications to both inform and explore avenues for accelerating the translation of research advances to improved outcomes for cancer patients.

This symposium has now been integrated into two sessions:

Molecular Medicine, Friday 27th September, 10:15 – 12:00, Turing Lecture Theatre
and
Machine Learning applications in Oncology, Friday 27th September, 13:00 – 14:00, Turing Lecture Theatre

Time	Speaker	Title
10:15	Gábor Zavodszky (Invited Speaker)	Coupling scheme for a high-performance multiscale blood flow simulation workflow Abstract preview Increasingly many scientific questions, that need modelling solutions, target processes residing on multiple scale levels. This is especially true in the domain of biomedicine, where understanding a given disease, or the effects of a treatment might involve numerous components. For a single problem blood flow mechanics can be just as important as cellular trafficking or sub-cellular biochemical signalling. One such problem presents itself with the disease of brain aneurysms. These are focal dilatations on major brain arteries with a chance to burst. The outcome of a rupture event can be devastating for the patient. The treatment usually involves endovascular brain surgery and the placement of a blood flow diverter implant, with the intent to thrombose the dilatation and therefore to close it out from the active circulation. In the following, a multiscale, multicomponent model will be presented that aims to model aspects of the thrombus formation mechanism after the medical intervention. The sub-models are fully developed and operational, and the couplings are currently under development. The model structure is discussed from the viewpoint of inter-model communication and requirements for the execution environment for the model components. Full Abstract
10:35	Sanjay Kharche	In Silico Assessment of Cardio-protection by Therapeutic Hypothermia Abstract Preview Hypothermia is known to impact multiple physiological mechanisms that include neurologic and cardiovascular systems. Therapeutic hypothermia (TH), as a mild reduction of body core temperature, has become the standard cardioprotective treatment for several patient groups, including those affected by ischemia. Patients undergoing long term treatments such as dialysis experience global ischemia in addition to the presence of localized myocardial stunning [1], which together may promote persistent ventricular fibrillation. Fibrillation avoidance or reduction of initiation risk using non-pharmacological TH may be beneficial to critically ill patients. Basic science experimental studies have shown that hypothermia prolongs cardiomyocyte action potential [2] and reduces cardiac conduction velocity. However, the clinical effectiveness of TH on arrythmia abrogation remain debated. In this study, a multi-scale computational cardiology approach was used to illuminate the effects of TH on cardiomyocytes and tissue. Full Abstract
10:50	Hector Martinez-Navarro	HPC simulations for in-silico drug testing in humans: therapeutic strategies in acute myocardial ischemia Abstract Preview Acute myocardial ischemia is a major cause of sudden cardiac death. Anti-arrhythmic treatments or side-effects associated with cancer therapies can produce cardiotoxic effects increasing the occurrence of adverse cardiac events especially in patients with coronary artery disease. In-vivo and in-vitro drug trials have associated complications regarding ethics and costs, whereas cardiotoxic evaluation in animal experiments is not necessarily translatable to humans. Full Abstract
11:05	Sanjay Kharche	Is insulating border necessary for human sinoatrial node spontaneous activity? Abstract Preview Human sinoatrial node (SAN) structure-function relationships remain poorly understood, and may be drastically dierent from those in smaller mammals. Recent studies based on histology for structure and optical mapping for function (e.g. see [1]) suggest that the human SAN may be electrically insulated from atrial tissue by an insulating border, except at four discrete exit pathways (SEPs) that permit atrial excitation by the SAN. Experimental data suggests that the funny current density is three fold lower in the human SAN as compared to small animals. The lower density of this important pacemaking ion channel may lead to SAN electrical activity suppression by the physiological atrial load in the absence of substantial SAN electrical insulation. In addition to experimental evidence, a recent computer modelling study provided some insights into the human SAN electrical function [2]. However, previous studies used simplied Fenton-Karma ionic model to simulate SAN activity, while a biophysically and anatomically detailed modelling has yet to be used to investigate the role of SEPs and human SAN behavior. In this study, a multi-scale biophysically detailed model of the human SAN is presented. The model is being used to investigate the role of SEPs, as well as relevant clinical conditions that promote bradycardia and brady-tachycardia. Full Abstract
11:20	Dwight Nissley and Frederick Streiitz (Invited Speakers)	Multiscale Modeling of RAS on Cellular Membranes Abstract Preview Cancer results from modifications to cellular decision-making processes. In normal cells, the protein-mediated signaling networks that control growth and movement are tightly regulated. However, mutations that disrupt or over-activate signaling proteins can drive uncontrolled cell growth resulting in cancer. RAS, a peripheral membrane signaling protein, is mutated in 30% of all cancers, especially those of the pancreas, colon and lung. These oncogenic mutations result in the loss of GTPase activity which in turn causes persistent engagement of effectors and enhanced or continuous growth signaling. Full Abstract
11:40	End of Session
12:00	LUNCH

Time	Speaker	Title
13:00	Georgia Tourassi (Invited Speaker)	Artificial Intelligence Solutions to Modernize Cancer Surveillance and Optimize Population-Level Cancer Outcomes Abstract Preview Information extraction, integration, analytics and visualization is a critical need for the Precision Medicine Initiative aimed to accelerate our understanding of individual differences in people’s genes, environment, and lifestyle and their effect on disease prevention, progression, treatment, and survival. This data-intensive challenge is collecting, integrating, and analyzing massive, multi-source, multi-scale heterogeneous patient data that must be interpreted in the context of other highly relevant but disparate data sources such as socioeconomic, environmental, lifestyle, care delivery, and community infrastructure factors (i.e., “exposome”). Full Abstract
13:30	Mari Nygard (Invited Speaker)	Towards personalised cancer prevention: The Digital Cancer Precision Prevention Initiative Abstract Preview TWe live in the information age where the flow of knowledge, including medical advice and innovations, quickly reaches each of us. However, existing recommendations for disease prevention, diagnostics and treatment are population-based, or based on highly selected randomized controlled trials, and only seldomly account for individual differences. For effective control of globally increasing morbidity and mortality due to cancer, the focus on early detection and intervention cannot be underestimated. The estimated spiraling costs of cancer treatment will challenge even the highest-income countries and underline the urgent need to develop preventive efforts. Knowledge of biological disease mechanisms along with existing individual data from national population-based health registries, biobanks and surveys can be tailored for personally designed ctions safely, efficiently and quickly. Cervical cancer screening is an excellent model system for the development of personalised strategies for cancer prevention. It has a proven strong effect for decreasing cancer burden at the population level, and the Norwegian population-based screening program has produced large amounts of individual data that is accessible by centrally organized nationwide registries. Full Abstract

Immunology

Emily Lumley — Thu, 29 Nov 2018 16:41:46 +0000

Invited Speakers

Jonathan Wagg, Roche
Omer Dushek, University of Oxford
Becca Asquith, Imperial College London

Symposium Chair

Tim Elliott, Professor of Experimental Medicine

Symposium Description

The immune system poses special challenges to a systems level understanding. Its ability to recognise specific antigens is characterised by massive combinatorial complexity; played out in a system that at the population level is highly polymorphic; with multiple cell-types that form ad hoc functional assemblies in response to potential threats to life. However, the introduction of computationally-intensive approaches like machine learning and systems modelling to experimental immunological data, gathered at various levels of complexity, is bringing us closer to predicting high-order function from measurements of components belonging to interdependent systems.

We will gather world leaders from diverse backgrounds to discuss the scientific progress that is being made integrating a wide variety of biological data to increase our understanding of immunological processes at all levels, as well as the challenges we face in the future.

Friday 27th September, 14:00 – 15:00; Turing Lecture Theatre

Time	Speaker	Title
14:00	Becca Asquith (Invited Speaker)	Immune cell dynamics & control of persistent virus infection Abstract Preview Chronic viral infections such as human immunodeficiency virus (HIV-1), hepatitis C virus (HCV) and human T cell leukemia virus (HTLV-1) are marked by huge between-individual variation in outcome. Some people infected with HIV-1 will develop AIDS in less than 5 years others will remain healthy for 10 years or more. In HCV infection, some individuals spontaneously clear the virus others develop persistent infection and subsequent risk of liver failure. Similarly in HTLV-1 infection, some individuals remain lifelong healthy carriers of the virus whilst others will develop an aggressive, rapidly fatal leukemia. Full Abstract
14:20	Omer Dushek (Invited Speakers)	Control of T cell responses by accessory receptors revealed by phenotypic modelling Abstract Preview T cells are important immune cells that are routinely being exploited for a number of different therapies. They are activated to respond when ligands bind to various receptors on their surface. This binding initiates signalling pathways that ultimately induce responses important for clearing infections and cancers. A key open question is how ligation of different surface receptors quantitatively control their responses. To address this, we have been systematically stimulating T cells with different combinations of ligands (input) and measuring their responses (output). Using systematic mathematical inference algorithms, we identify effective pathway models that intuitively explain how inputs are converted to outputs (‘causal inference’). Here, we show that T cell response outputs to constant antigen ligand input induces perfect adaptation and that ligation of different accessory receptors (CD2, CD28, LFA-1, CD27, 4-1BB, GITR, and OX40) control this phenotype differently. Initial results with the inference algorithm suggest that an incoherent feedforward coupled to a digital switch can explain perfect adaptation along with the different phenotypes observed by the different receptors. The work offers a new way to infer effective signalling pathways directly from quantitative cellular response data. Full Abstract
14:40	Jonathan Wagg (Invited Speakers)	Application of Artificial Neural Networks to Infer Pharmacological Molecular-Level Mechanisms of Drug Evoked Clinical Responses Abstract Preview The Roche Clinical Pharmacology Disease Modelling Group (CPDMG) aims to better understand the biological basis of observed inter-patient variability of the clinical responses to drugs administered both as monotherapies and in combination. Administration of drugs to human subjects drives widespread and diverse changes in their biology. However, the majority of these changes are NOT clinically relevant, generate noise and are a common source of false positive predictors of clinical response. Full Abstract
15:00	REFRESHMENTS

Organ Modelling and Simulation

Emily Lumley — Thu, 29 Nov 2018 16:39:54 +0000

Invited Speakers

Xinshan Li, University of Sheffield
Mirko Bonfanti, University College London
Alberto Marzo, University of Sheffield
Alejandro Liberos, Universidad Politecnica de Valencia

Symposium Co-Chairs

Claudia Mazza, Reader in Biomechanics
Blanca Rodriguez, Professor of Computational Medicine

Symposium Description

The Organ based symposium will showcase the most recent, exciting and impactful developments in organ-level multiscale modelling and simulation. Advancements in both knowledge of human patho-physiology and computational power have enabled the progress of organ-level modelling and simulation to impressive levels of maturity. The symposium will illustrate the state-of-the-art in several areas including cardiovascular and neuromusculoskeletal biomedicine, with a special emphasis in scientific discovery as well as clinical and industrial applications.

Wednesday 25th September, 11:00 – 12:30, 13:30 – 15:30; Kelvin Lecture Theatre
and
Friday 27th September, 10:15 – 12:00; Kelvin Lecture Theatre

Time	Speaker	Title
11:00	Alejandro Liberos (Invited Speaker)	Use of 3D atrial models to improve signal processing in cardiac electrophysiology Abstract preview Atrial fibrillation (AF) is the most common cardiac arrhythmia, affecting more than 6 million of Europeans. In the recent years new mapping technologies have been developed such as intracardiac mapping by basket catheters, body surface potential mapping by surface electrodes or estimated epicardial mapping by solving the inverse problem of electrocardiology. Together with these mapping technologies, signal processing techniques have been developed in order to identify the mechanism that maintains AF in each individual patient. However, due to the complexity of AF it is difficult to validate such techniques with real patient data. Full Abstract
11:20	Robin Richardson	An automated pipeline for real time visualisation of blood flow during treatment of intracranial aneurysms Abstract Preview Imaging and computing technologies have advanced considerably in recent years leading to their increasing use in medical applications. Modern imaging methods allow clinicians to view the geometry of a patient’s vasculature, down to the level of individual vessels, allowing vascular malformations such as intracranial aneurysms to be located and examined. On a related front, the increasing availability and computational power of high performance computing (HPC) infrastructure now allows for detailed haemodynamic simulations to be executed [1]. Indeed, advanced software suites have already been developed for hemodynamic simulation from medical imaging, such as CRIMSON [2], including coupling to heart models [3]. The treatment of intracranial aneurysms is often performed under very short timescales. Our aim in this work is to use data which is already available and routinely collected in the process of interventions to treat patient aneurysms – such as rotational angiogram (RA) data – and combine this with high performance haemodynamics simulation codes to provide clinicians with real time visualisation of the predicted blood flow and associated wall shear stresses in the patient before and after the introduction of a flow diverting stent. We present here the fully integrated, automated pipeline we have developed to segment imaging data, localise aneurysms, simulate blood flow and provide real time visualisation to clinicians and some details of its current performance. Full Abstract
11:35	Tomas Jozsa	A cerebral circulation model for in silico clinical trials of ischaemic stroke Abstract Preview The INSIST consortium (www.insist-h2020.eu) set out to accelerate the advancement of stroke treatments by introducing in silico clinical trials which mitigate the need for resource-intensive experiments. The present work aims to contribute to INSIST by developing a cerebral circulation model that captures blood flow in the entire human brain. Progress in this field is complicated by the multi-scale nature of the flow, which stretches from small vessels with characteristic diameters of approximately 5 microns (capillaries) to large arteries with diameters of approximately 5 millimetres (e. g. internal carotid artery). Whereas it has become common practice to account for large arteries using one-dimensional network models, well-established methods are not available for a full description of the microcirculation. Therefore, this study focuses on the development of a cerebral microcirculation model and on bridging the gap between large arteries and the microcirculation. Full Abstract
11:50	Britt Van Rooij	Platelet adhesion and aggregation: Cell-resolved simulations and In vitro experiments Abstract Preview High shear thrombosis happens on a thrombogenic surface (e.g. collagen) in a high shear environment and in presence of platelets and von Willebrand factor (vWF). In literature a discussion is going on between the need of an area with high shear [1] or an area with a high shear gradient [2]. However, the in vitro experiments used in these studies are performed in different flow chambers. In those flow chambers the specific flow fields are not the same. Currently, it is not known what specific flow characteristics cause high shear thrombosis. It is known that unfolding of the von Willebrand factor is regulated by elongational flow. However, this does not explain the formation of the platelet aggregates at the apex (high shear) or just behind the apex (high shear rate gradient), where vWF would contract instead of uncoil in the flow direction. However, note that the flow behaviour on the cellular level is hardly known and could provide additional insight [3]. Full Abstract
12:05	Remy Petkantchin	A Three-dimensionnal Mesoscopic Model of Thrombolysis Abstract Preview A clot, as observed in a stroke event is made of fibrin strands that are entangled, making a solid structure blocking partially or completely the blood flow in a brain artery. In addition to the fibrin network, the clots are made of other procoagulant factors such as platelets and von Willebrand Factor (vWF) as well as red blood cells (RBC). Thrombosis is the result of the polymerization of the fibrinogen, transported by blood, into fibrin strands under the action of thrombin molecules. Thrombin is typically produced in case of body malfunction, such as injured endothelial cells, vessel walls exposed to low shear rate or hypoxia. In normal physiological conditions, the anti-thrombin that is naturally present in the blood can neutralize the thrombin and prevent from clot formation. Full Abstract
12:20	End of Session
12:30	<LUNCH

Time	Speaker	Title
13:30	Mirko Bonfanti (Invited Speaker)	Multi-scale, patient-specific modelling approaches to predict neointimal hyperplasia growth in femoro-popliteal bypass grafts Abstract preview Neointimal hyperplasia (NIH) is a major obstacle to the long-term patency of peripheral vascular grafts. The disease has a complex aetiology which is influenced, among other phenomena, by mechanical forces such as shear stresses acting on the arterial wall. The aim of this work is to use a multi-scale modelling approach to assess the impact of haemodynamic factors in NIH growth. We hypothesized that both low and oscillatory shear should be considered simultaneously when assessing the proclivity of a certain region in bypass grafts to develop NIH and we simulated NIH progression using a multi-scale computational framework that we previously developed, comparing our results to a patient specific clinical dataset (obtained with the patients’ informed consent for research and publication). Full Abstract
13:50	Gaia Franzetti	In vivo, in silico, in vitro patient-specific analysis of the haemodynamics of a Type-B Aortic Dissection Abstract Preview Aortic dissection (AD) is a serious condition that occurs when a tear in the aortic wall allows blood to flow within the layers of the vessel. The optimal treatment of ‘uncomplicated’ acute/subacute Type-B aortic dissections (uABADs) continues to be debated. uABADs are commonly managed medically, but up to 50% of the cases will develop complications requiring invasive intervention [1]. AD is a highly patient-specific pathology in which morphological features have high impact on the haemodynamics. However, there is still a limited understanding of the fluid mechanics phenomena influencing AD clinical outcomes. Flow patterns, pressure, velocities and shear stresses are at the same time difficult to measure and extremely important features for this pathology. Personalised computational fluid dynamics models (CFD) are being investigated as a tool to improve clinical outcome [2]. However, such models need to be rigorously validated in order to be translated to the clinic, and such validation procedures are currently lacking for AD. This scarcity of data may be supplemented using in silico and in vitro models, in which these parameters can be studied and compared for validation purposes. In this work, a unique in vitro and in silico framework to perform personalised analyses of Type-B AD, informed by in vivo data, is presented. Experimental flow rate and pressure waveforms, as well as detailed haemodynamics acquired via Particle Image Velocimetry (PIV), are compared at different locations against computational CFD results. Full Abstract
14:05	Bettine van Willigen	AngioSupport: an interactive tool to support coronary intervention Abstract Preview Every year about 735.000 Americans suffer from Coronary Artery Disease (CAD); one of the leading causes of death in the United States; therefore, diagnosis and treatment should be convenient and accurate with costs as low as possible. Currently, medium to high risk stable patients have been assessed based on invasive coronary angiography (ICA). In other words, ICA was the ‘gold standard’ to determine the appropriate treatment (pharmaceutical treatment, percutaneous coronary intervention (PCI), or coronary artery bypass graft (CABG)) for CAD by revealing the location and anatomy of the stenosis. This diagnostic method is based on the research of Gould et al., which demonstrates the relationship between the stenosis (lumen diameter) and ischemia (determined based on myocardial blood flow) during the hyperemic state (Gould et al., 1974). Despite the subjective visual interpretation of the clinician to interpret the ICA, the percentage stenosis defined by ICA is a decent indication for revascularization for single vessel stenosis. However, for diffuse coronary disease or multiple stenosis (Tonino et al., 2009), ICA is unreliable for the diagnosis, because hemodynamics are unpredictable based on the anatomy of the stenosis. This may result in unnecessary revascularization of patients. Full Abstract
14:20	Jon McCullough	Developments for the Efficient Self-coupling of HemeLB Abstract Preview The aim of this paper is to document recent methodological advancements that enable extreme scale simulation by HemeLB [1], our present lattice-Boltzmann (LB) based blood-flow solver. From pre-processing to simulation and finally post-processing, we demonstrate the entire work flow on SuperMUC-NG, a state-of-the-art high performance computing platform. Pre-processing involves the voxelisation of patient-specific geometries to form a large lattice consisting of up to tens of billions of sites. Our ultimate goal is to enable the simulation of virtual humans, or digital replicas, with HemeLB simulating the full arterial and venous trees and exchanging information with simulation tools responsible for capturing the behaviour of other organ systems. To create accurate digital patients, we rely on some of the recent advancements discussed here. Full Abstract
14:35	Cyril Karamaoun	Interplay between thermal transfers and degradation of the bronchial epithelium during exercise Abstract Preview Physiologists interested in the body’s behaviour at exercise now recognize that the respiratory tract is not a limiting factor of endurance performance in healthy athletes. However, after several years of intense training, a majority of them develop various exercise-induced pathologies. The importance of the repetition of bronchial epithelium loss of integrity, consequent to a sustained high level of exercise ventilation, has been recently incriminated [1]. One physiological biomarker of the loss of epithelium integrity is the measurement of the concentration of club cells proteins 16kD (CC16) in urine or blood. An increase of this biomarker after exercise has been observed to be dependent on the intensity of exercise ventilation, leading to airway dehydration [1]. Interestingly, experimental [2] and modelling [3] works have shown that the bronchial epithelium and its mucus layer are a site of non-negligible evaporation during respiration. This evaporation (or condensation, especially during expiration [3]) is driven by a heat transfer between the air and the mucus layer, due to a temperature and humidity gradient at the air-tissue interface. Full Abstract
14:50	Giulia Luraghi	Simulation of the thrombectomy procedure in a realistic intracranial artery Abstract Preview An ischemic stroke is caused by a blood clot (thrombus) in an intracranial artery that prevents the blood to supply the downstream tissues. The thrombus may originate from the heart, from atherosclerotic plaques, or from vessel wall dissections. It is a mass of platelets, fibrin, and other blood components, activated by a hemostasis mechanism, which may present different composition. Red thrombi, red blood cell (RBC) dominant, are usually generated where the blood flow is slow and the fibrin network entraps the RBCs, while white thrombi, fibrin dominant, are generated under high shear flow and inflammatory conditions. The clot composition affects strongly its mechanical properties [1]. The main diagnostic techniques used during the stroke investigation are the Computed Tomography (CT) and Magnetic Resonance Imaging (MRI). In any case, detection of the location of the intracranial occlusion must be done in a fast and accurate way to ensure speedy treatment. Treatment of acute ischemic stroke is aimed at restoring blood flow in the affected cerebral arteries as fast as possible after onset. Time is crucial in stroke, 2 million neurons are lost every second without reperfusion. Full Abstract
15:05	End of Session
15:30	REFRESHMENTS AND POSTER SESSION

Time	Speaker	Title
10:15	Alberto Marzo (Invited Speaker)	The role of haemodynamics and peripheral vasculature in vessel constriction after aneurysm treatment with flow-diverter stents Abstract preview Treatment of intracranial aneurysms with flow diverter stents (FDS) can lead to calibre changes of the jailed vessels in a subacute phase. The reason some branches remain unchanged and others are affected by narrowing or occlusion is unknown. This study investigates the influence of resistance to flow on FDS-induced haemodynamic modifications in typical aneurysm locations in bifurcating arteries. Full Abstract
10:35	Jazmin Aguado-Sierra	The anatomically detailed human ventricles versus the simplified human anatomies: why shape and sex matters. Abstract Preview Computational modelling is becoming increasingly important towards the understanding, the diagnosis and the treatment of patients worldwide. It is a fact that modellers have been employing every last bit of information available to them to personalise and parameterise such models to increase their accuracy towards clinical applications. Data acquisition in the clinical scenario is many times hindered by monetary, ethical, time constraints, or simply the fact that there are some variables that are impossible to measure in-vivo. In this talk, we analyse the effect of trabeculae and papillary muscles on electrophysiology simulations of the male and female hearts. The aim is to characterise the effects of lack of anatomical resolution on the study of Ventricular Tachycardia. Furthermore, we analyse the role of gender phenotype on such simulations. Results show that anatomical detail and gender phenotype does really matter and provide different outcomes on computer simulation studies.
10:50	Raymond Padmos	Connecting Arterial Blood Flow to Tissue Perfusion for In Silico Trials of Acute Ischaemic Stroke Abstract Preview Predicting infarct volume is necessary to develop in silico trials for the treatment of acute ischaemic stroke. This requires modelling of blood flow across length scales incorporating three orders of magnitude, from the large arteries, to the arterioles, the pial surface vessels, to the penetrating vessels and the microcirculation. Blood flow in large vessels are typically modelled using lumped parameter or 1-D blood flow models, whereas the microcirculation is typically modelled as a porous medium[1]. However, the patient-specic geometry of large vessels is known, the features of the microcirculation are captured statistically. Therefore, there is an information gap between the large vessels and the microcirculation. Here, we present a method to couple blood flow in large blood vessels to cerebral tissue perfusion. A tissue perfusion model is also being developed but is outside the scope of this abstract1. For more details and derivations of the models, see [1, 2]. Full Abstract
11:05	Yun Bing	A novel multi-scale, multi-compartment model of oxygen transport – Towards in-silico clinical trials in the entire human brain Abstract Preview The in-silico clinical trials for the treatment of acute ischemic stroke (INSIST) consortium is a multi-disciplinary, multi-sectorial undertaking aiming to advance the understanding and treatment of ischemic stroke through computational simulations and clinical trials. The work presented here is a part of this project which aims to model oxygen transport and metabolism in the entire human brain. This will form the backbone of the in-silico trials as this model, coupled with the multi-scale model of the blood flow in the human brain presented elsewhere in this conference1, will predict regions of hypoxia post-stroke, and hence will predict tissue death. This can then be validated against an available large database of stroke patients. Full Abstract
11:20	Andrew Narracott	Delivering the CT2S computational workflow directly to the clinic Abstract Preview In recent years there have been significant developments in the application of computational workflows to enhance the clinical decision-making process. Many of these applications have been led by groups with an engineering focus and direct delivery of workflows within the clinical environment remains relatively uncommon. Due to the complex nature of patient specific anatomy and physiology, central to the effective development of state-of-the-art computational tools, workflows often require High Performance Computing (HPC) approaches and infrastructure to produce accurate, clinically relevant, output parameters. To improve clinical uptake of such technologies there is a need to provide direct access to such workflows to clinical end-users without exposing the complexity of the underlying HPC environment. This abstract describes the development of a software framework to deliver an existing HPC computational workflow Computed Tomography to Strength (CT2S), which provides quantitative metrics of bone strength based on CT images, directly to the clinical end-user. This provides the opportunity to initiate the request for computational analysis directly from the clinic, and returning an analysis report directly to the requesting clinician. Full Abstract
11:35	Xinshan Li (Invited Speaker)	A finite element investigation of the positioning of Arabin® cerclage pessary in the prevention of spontaneous preterm birth Abstract Preview Spontaneous preterm birth (SPTB) is strongly associated with cervical funnelling. The condition is multifactorial and leads to global peri and neonatal mortality and morbidity [1,2], with the less developed countries being most affected due to a lack of management strategies. There exist a few treatment options for SPTB, including cervical cerclage [4], hormonal therapy using progesterone, and Arabin® cerclage pessary [3]. The Arabin® cerclage pessary has been widely used due to its low cost and ease of insertion. However, the mechanical interaction between the cervix and the pessary is not well understood [5]. Therefore, the aim of this study is to conduct preliminary investigation into: (a) the mechanical effect of the pessary on reducing cervix funelling, and (b) the effect of various pessary positions on supporting the cervix. Full Abstract
11:55	End of Session
12:00	LUNCH

Molecular Medicine

Emily Lumley — Thu, 29 Nov 2018 16:37:20 +0000

Invited Speakers

Dr Katharina Meier, Bayer
Dr Gerhard König, ETH Zürich
Dr Donald Weaver, Krembil Research Institute
Prof Jonathan Essex, University of Southampton
Dr Christina Schindler, Merck

Symposium Co-Chairs

Peter Coveney, Professor of Physical Chemistry
Herman Van Vlijmen, Head of Molecular Sciences

Symposium Description

Recent developments in both technology and algorithms have led to increased interest in biomedical applications of molecular modelling and simulation techniques in a wide range of fields from biosensor design, to drug discovery and personalized medicine. Advances have come from both physics based mechanistic modelling, including quantum mechanical, molecular dynamics and Monte Carlo methods for free energy, residence time and kinetic parameter estimation, and data driven approaches, including bioinformatics and machine learning. The convergence and the interaction of these two disciplines is likely to prove fruitful and productive.The symposium aims to encompass the wide range of exciting current work in this domain. Topics for consideration include but are not limited to, small molecule docking and free energy calculations, estimation of rate parameters for binding processes, biosensor modelling, antibody design, de novo molecule generation and protein / DNA structure-function relationships.

Thursday 26th September, 10:15 – 12:00, 13:00 – 15:00, 15:30 – 17:00; Kelvin Lecture Theatre

Time	Speaker	Title
10:15	Gerhard König (Invited Speaker)	On the faithfulness of molecular mechanics representations in multi-scale free energy simulations Abstract preview Computer simulations are an indispensable tool in the drug development process to predict binding free energies, solubilities, and membrane permeability of drug candidates. Although the targets are very dierent, all free energy simulations share some common features and challenges. The two fundamental prerequisites for the determination of free energies are the accurate description of inter- and intramolecular interactions, and the adequate sampling of all relevant microstates. These two requirements are in conflict with each other, since a more sophisticated description of molecular interactions entails an increase of the computational costs, which inhibits the capability to search through a multitude of dierent possible conformations. In terms of the balance between those two requirements, one can distinguish two major classes of computational methods: a) classical force elds based on molecular mechanics (MM), which are fast and well suited for sampling, but involve approximations that limit their reliability b) quantum-mechanical methods (QM), which are based on molecular orbital calculations and combine a heavy computational burden with highly accurate interaction strengths. Full Abstract
10:35	David Wright	Entropy estimation methods in ensemble end-point binding free energy simulations Abstract Preview Fragment-based lead generation (FBLG) involves scanning a library of low molecular weight compounds (fragments) to see if they bind to the target of interest and using those that do as building blocks to create create higher affinity molecules. A frequent strategy is to link multiple fragments binding different regions of the protein. FBLG represents an attractive application for in silico binding anity calculations, but the need to obtain comparable values from different binding modes represents a considerable challenge for many computational techniques. We evaluate the performance of our range of ensemble simulation based binding free energy calculation protocols, called ESMACS (enhanced sampling of molecular dynamics with approximation of continuum solvent). In studies of drugs binding to a single site these protocols have been shown to produce results which correlate well with experiment (correlation coecients >0.7) and provide robust uncertainty estimates. Full Abstract
10:50	Philip Fowler	Rapid, qualitative prediction of antimicrobial resistance by alchemical free energy methods Abstract Preview The evolution of resistance to antibiotics was predicted by Fleming in his Nobel Prize speech and is now accepted as posing a threat to modern medicine requiring urgent and concerted action. Helping clinicians make appropriate treatment decisions by improving the coverage, portability, speed, accuracy and cost of species identification and drug susceptibility testing will be an important part of the solution. A promising approach is to sequence the genome of any infecting pathogen(s) found in a clinical sample and, by looking up genetic variants found in genes known to confer resistance to the action of antibiotics, return a prediction of the effectiveness, or otherwise, of a panel of antibiotics to the clinician. The exemplar for this approach is tuberculosis, partly because its growth rate is so slow that culture-based clinical microbiology can take up to two months to return a result to the clinician, and partly because its genetics is simpler than other pathogens and therefore the current second-generation sequencing technologies work well. Genetics clinical microbiology has been shown to be cheaper, faster and probably more accurate than traditional culture-based clinical microbiology for the drug susceptibility testing of tuberculosis1 and, in addition, facilitates the rapid identification of to phenotype have been carefully and extensively developed, a potential weakness remains: such an approach is fundamentally inferential and so cannot make a prediction when it encounters a genetic variant not present in the catalogue, such as is the case for rare genetic mutations. Full Abstract
11:05	Christina Schindler (Invited Speaker)	Opportunities and challenges for free energy calculations in drug design Abstract Preview Free energy calculations have become a powerful addition to the computational chemist’s toolbox to support structure-based drug design in hit-to-lead and lead optimization stages of drug discovery projects. Methodological advances, the availability of less expensive large computational resources and automated workflows have opened up the possibility to apply the technology in an industry context at large scale. In 2016, we started a large initiative at Merck KGaA to thoroughly investigate the potential of free energy calculations for compound optimization and to define best practices for using this technology. Here, we present prospective data from using FEP+ in 10 drug active discovery projects at Merck KGaA over the course of three years and compare this performance to results obtained on a new, challenging benchmark of five pharmaceutically relevant targets. We further discuss opportunities and challenges and highlight use cases and conditions that can maximize the impact of the method. Full Abstract
11:25	Katya Ahmad	Accurate and Precise Predictions of the Influence of Salt Concentration on the Conformational Stability and Membrane-Binding Modes of Multifunctional DNA Nanopores using Ensemble-Based Coarse-Grained Molecular Dynamics Abstract Preview Pore-forming protein analogues have been fabricated from triethylene glycol-cholesterol modified DNA sequences, which hybridize to form cholesterol anchored DNA nanopores (TEG-C NP’s). These versatile nanopores can be chemically tuned to exhibit an array of functionalities with a broad range of potential applications in biomedicine e.g. novel ligand controlled and light-controlled drug delivery systems[1,2,3]. The interactions between TEG-C NP’s and membrane lipids are pivotal to their function, but these interactions remain poorly understood. Here we use an ensemble-based, coarse-grained molecular dynamics (CG-MD) protocol to gather detailed, reproducible data on the structure and dynamics of TEG-C NP’s at two experimentally relevant ionic concentrations, allowing us to calculate reliable pore dimensions and perform comprehensive fluctuation analyses on membrane-spanning TEG-C NP’s, as well as TEG-C NP’s in free solution. Thus we can confidently characterise the influence of ionic concentration and membrane encapsulation on the dimensions, structural and mechanical properties of TEG-C NP’s, and pinpoint areas of constriction, strain and stability within their structure. Collecting ensembles of micro-second long trajectories of a membranespanning TEG-C NP allows us to observe a comprehensive spread of large-scale motions available to the TEG-C NP at these timescales and draw parallels with what is observed in experiment. Full Abstract
11:40	Jonathan Essex (Invited Speaker)	The Role of Water in Mediating Biomolecular Binding: From Water Locations to Their Impact on Binding Affinity Abstract Preview Water plays an intimate role in protein-ligand binding, not only through solvation/desolvation effects, but more subtly through the formation of direct interactions between the protein and ligand in the binding site. The targeting of bound water molecules for displacement as part of ligand optimization is a long invoked paradigm based around the release of configurational entropy, but there are many examples where displacing water leads to a loss in ligand binding affinity. Quantitatively accurate approaches to address this problem are arguable inadequate – water displacement and ligand interactions are intimately related and difficult to disentangle both experimentally and, hitherto, computationally. We have a long-standing interest in developing and using Grand Canonical Monte Carlo (GCMC) simulation approaches to explore water binding in protein-ligand systems. Through GCMC we are able to locate water molecules with good accuracy when compared against crystal structures. More significantly, the simulations clearly demonstrate the important role of water cooperativity; the mutual tabilization of water molecules means that individual water molecules cannot always be considered in isolation, but rather as part of a network. GCMC allows water binding sites and network binding free energies to be simultaneously calculated. In addition, by combining GCMC with alchemical perturbations of the ligand, networks of bound water molecules are able to adapt and maintain equilibrium with bulk water as the perturbation proceeds. Furthermore, the ability to extract active-site hydration free energies allows the deconvolution of protein-ligand binding free energies into separate protein- and water-mediated components, thereby providing rich, additional detail to the structure-activity relationship (SAR). In this presentation, the underlying methodology GCMC methodology will be described, together with examples of its application to water placement, binding free energy calculations, and protein-ligand affinity prediction Full Abstract
12:00	LUNCH
Time	Speaker	Title
13:00	Katharina Meier (Invited Speaker)	Computational Molecular Design in Pharmaceutical Drug Discovery Abstract preview The incorporation of computational approaches into the early drug design process is a relatively young discipline compared to the long-standing history of drug discovery research. Considerable advances in hardware architecture, speed, accuracy and usability of computational algorithms have paved the way towards a quickly developing branch of research within the pharmaceutical industry. This talk will provide a general overview of computational molecular design in a pharmaceutical industry setting, highlight recent methodological advances and discuss their impact on real-world drug discovery projects. Full Abstract
13:20	Andrew Potterton	An Ensemble-Based SMD Workflow that Predicts the Residence Time of A2A Receptor Ligands Abstract Preview Drug-target residence time, the lifetime of the ligand-receptor complex, is said to be better than binding affinity at predicting in vivo efficacy. Computational prediction of drug-target residence time, using standard molecular dynamics (MD), is challenging as experimental dissociation times are approximately 107 longer than the simulation times that are currently feasible. We therefore applied steered MD (SMD) to forcibly speed up ligand dissociation. To ensure the interactions of the dissociating ligand with the receptor residues and water, Figure 1, are reproducible, ensemble analysis was performed. We applied this method to 17 ligands of a prototypical GPCR (G protein-coupled receptor), all of which had associated published experimental kinetic binding data. Our results reveal that the computationally-calculated change in ligand-water interaction energy correlates strongly with experimentally-determined residence time (R2 = 0.79). Further, the residues that interact with the dissociating ligand in these simulations are known experimentally to affect binding affinity and residence time. These experimental data indicate that our ensemble-based SMD protocol[1] is a novel, rapid and reproducible method for the rationalisation and determination of drug-target relative residence time. Full Abstract
13:35	Jason Clark	Clustering analysis of synthetic retinoid dockingRetinoids are a class of vitamin-A derived molecules with endogenous roles in cell proliferation and differentiation. Abstract Preview Recent research has suggested retinoids may hold promise for therapeutic use in motor neuron diseases such as amyotrophic lateral sclerosis (ALS) by promotion of neuronal survival. Despite promising therapeutic potential, little is known about the complex signalling pathways which govern retinoid’s mechanism of action. Endogenous retinoids such as all-trans-retinoic acid (ATRA) are inherently vulnerable to photodegradation and isomerism due to their polyene structure, making their use as a research tool problematic. As such we utilise a range photostable, fluorescent synthetic retinoid analogues we are currently developing between Durham University and LightOx to investigate the retinoid mode of action. In parallel with biological testing, ligand docking and molecular dynamics (MD) simulations form a vital part of our continued research into these compounds. As part of our docking analysis, we have developed a root-mean-square deviation (RMSD)-based clustering script to group and identify commonly occurring ligand-docked protein structures, which we hypothesise will allow for enhanced identification of promising docked solutions via less resource-intensive methods before moving data to resource-intensive MD simulations. This workflow not only introduces a new approach for docking analysis but allows for faster and simpler identification of unique protein-ligand docked solutions. Full Abstract
13:50	Aban Shuaib	Analysis of mechanotransduction dynamics during combined mechanical stimulation and modulation of mechanotransduction cascade uncover hidden information within the signalling noise Abstract Preview Osteoporosis is a bone disease characterised by brittle bone and increased fracture incidence. The disease is globally a high burden on health systems which continues to increase with an aging society. There are limited treatments for osteoporosis with just two FDA approved pharmacological agents in the USA. Furthermore the drug discovery pipeline has limited success in producing novel and efficacious molecules. Osteoporosis arises due to changes in bone architecture, mineral density (BMD) and strength. These characteristics are believed to be affected by bio-mechanical stimulations. Such signals are sensed by bone cells in the bone remodelling unit and translated to cellular responses which ultimately maintain healthy bone. Recently, dual bio-mechanical stimulation with intermittent parathyroid hormone (PTH) treatment and mechanical stimulation were shown to increase BMD and bone formation in mice, thus suggesting a promising treatment for osteoporosis 1,2. However, the exact regimes to induce potent therapeutic effects are yet uncharacterised. This is partly due to incomplete understanding of cellular and molecular mechanisms which sense and integrate the dual signals into a cellular response (i.e. mechanotransduction) which evolve into increased BMD, strength and growth at the tissue level. Full Abstract
14:05	Silvia Acosta Gutierrez	Understanding induced conformational plasticity in G-protein coupled receptors selective pathway activation Abstract Preview G-protein coupled receptors (GPCRs) constitute the most important drug target family and account for 30% of the FDA approved drugs1. This large family of receptors detect a remarkably diverse array of molecules outside the cell and initiate a variety of intracellular signalling pathways in response. The transmembrane nature and intrinsic flexibility of GPCRs makes their crystallization difficult. But a number of technical advances, aiming to rigidify the receptor have allowed their crystallization increasing the number of available structures. Despite this breakthrough in crystallography, which lead to the Nobel prize in chemistry to Lefkowitz and Kobilka in 20122,3, these structures are unlikely to cover the conformational diversity of this family of receptors and must be complemented with other techniques to reveal the intrinsic dynamics of the process. We are only starting to understand the role of ligand induced conformational changes (allostery) in GPCRs and there remains a great deal to be discovered in order to facilitate fundamental understanding of the role of allostery and the potential of new allosteric drugs4,5. Here we present a combination of state-of-the-art molecular dynamics enhanced sampling techniques and force fields to understand at an atomistic level how ligands and intracellular partners affect the energy and interconversion rates of GPCRs conformational repertoire. Our study is focused on a prototypical class A GPCR, the adenosine receptor A2a, which is relevant to the occurrence, development and treatment of brain ischemic damage and degenerative disorders, due to its role as neuronal and synaptic function modulator. Full Abstract
14:20	Alya Arabi	Quantitative Evaluation of Bioisosteres in Drug Design Abstract Preview Drug design is fraught with challenges. The biological activity of a drug molecule can be considerably affected even with the minor changes in its structure. However, among the common substitutions in drug molecules that lead to adjusted pharmacokinetic and pharmacodynamic properties without affecting the biological activity is bioisosterism. Using the quantum theory of atoms in molecules (QTAIM), this study highlights a newly discovered indicator to evaluate quantitatively the similarities among nonclassical bioisosteres, namely carboxilyc acid, tetrazole [1], squarate [2], sulfonamide [3], isoxazole, oxadiazole, oxazolidinedione, and thiazolidinedione groups. The bioisosteric groups had remarkably close average electron densities regardless of the capping group or the protonation state of the molecule (see Figure below). The electrostatic potential maps, which represent the classical qualitative approach of explaining the bioisosteric activity, or in other words the “key & lock” interactions between the receptor and the drug, did not show the similarities in some cases. Full Abstract
14:35	Hannah Bruce Macdonald	Adaptive sampling for alchemical free energy calculations and applications for drug design Abstract Preview Binding free energy calculations (BFE’s) are routinely used in drug design to accurately predict the binding free energy of small molecules to drug targets,1 however the cost of simulation often prohibits their application to smaller sets of molecules. Groups of molecules are typically compared through free energy maps, where each ligand may be compared to at least two other small molecules, however the decision process involved in the generation of this map is un-rigorous. Certain calculations between pairs of ligands or even a given atom-mapping protocol will converge faster than others, proportional to the thermodynamic length of the specific transformations. Using perturbations with large thermodynamic lengths is inefficient,2 however it is not possible to calculate thermodynamic length a priori, and can only be established post simulation.3 Typically, the generation of a ligand free energy map involves naïve reasoning over which pairs of ligands to compare, while the efficiency of the chosen pairings, and therefore the overall quality of the map is only apparent post simulation. Each perturbation is generally simulated using ‘equal allocation’ whereby the same length of simulation is used for each perturbation. Full Abstract
14:50	End of Session
15:00	REFRESHMENTS
Time	Speaker	Title
15:30	Donald Weaver (Invited Speaker)	In Silico Search for Endogenous Inhibitors of Protein Misfolding Abstract preview Protein misfolding is a fundamental disease process implicated in many human disorders, particularly dementias such as Alzheimer’s disease, but also in diabetes and specific types of heart and kidney failure. Proteins are the structural and functional workhouse molecules of the human body – beneficial activities that are dependent upon the protein being folded into a correct shape. Since protein shape is central to health, it is reasonable to postulate the existence of compounds endogenous to the human body which ameliorate the pathological consequences of protein misfolding; the concept of searching for endogenous anti-protein misfolding compounds is unique. We have used an in silico high throughput screen of small molecules endogenous in the human brain to identify multiple classes of agents capable of inhibiting the aberrant protein misfolding implicated in the pathogenesis of Alzheimer’s dementia. We then extend this discovery to show that these endogenous compounds also inhibit the misfolding of proteins implicated in diabetes, thereby demonstrating that these agents are not disease specific and are applicable to multiple classes of protein misfolding diseases, including two of the most significant disorders afflicting humankind, namely dementia and diabetes.Full Abstract
15:50	Alexander Gheorghiu	The influence of base pair tautomerism on single point mutations in aqueous DNA Abstract Preview The human genome consists of approximately 3 billion base pairs, stored as nucleic acid sequences. Due to its vast complexity, the genome is fragile – unsurprisingly the DNA within is susceptible to change. The mutations that occur in these DNA sequences are crucial to both natural evolution and the occurrence of genetic diseases. While some of these changes might be a consequence of exposure to high energy electromagnetic fields or other forms of radiation, mutations may also arise due to mistakes during the DNA replication process. Although remarkably accurate, the high-fidelity DNA replication process generates base substitution errors at a rate of 10-4 to 10-5 per replicated nucleotide. However, due to >various intrinsic repair mechanisms, errors in human genome replication are actually less frequent (approx. ~10-8 to 10-10 per replicated nucleotide). These replication errors, known as p>oint mutations, may occur as a result of wobble base pairing, Hoogsteen (anti-syn) base pairing, ionisation and tautomerisation (the frequency of each is uncertain). Full Abstract
16:05	Othmane Bouhali	Monte Carlo modelling of a VARIAN 2300C/D photon accelerator Abstract Preview Clinical beam accelerators are widely used in radiation therapy facilities to provide the adequate beams for treatment. The success of the treatment depends on the accuracy of the dose calculated and radiation administered. In this work we conduct a comprehensive modelling of the Varian Clinac 2300C/D from electron beam generation to target response, using GATE simulation toolkit. To validate our numerical model, Gamma Index parameter is used to compare the simulation results against the experimental measurements. Results from Percent Depth Dose and Dose Profile are presented and discussed. This Monte Carlo model and the accuracy of these results can be extended to accurately calculate the dose distribution in real treatment planning systems. Full Abstract
16:20	Eleni Fitsiou	Molecular Organization of Tight Junction Protein Strands: Molecular Dynamics Simulation of the Self-Assembly of Extracellular Domain Particles of Claudin 1 Abstract Preview Tight junctions are cell-cell contact structures found in epithelial and endothelial tissues, located at the contact region between neighbouring cells, towards their apical side. They regulate the permeability of small molecules and ions through the intercellular space (paracellular pathway) by either blocking their passage or allowing some molecules with appropriate charge and size to go through. A functional tight junction barrier is critical to the physiology of the body. Its dysregulation can lead to pathologies such as inflammation, metastasis and edema [1]. For instance, mice that lack a key tight junction protein, claudin 1, die after birth due to excessive water loss across the skin. Tight junctions are also the target of several viruses including the hepatitis C virus and bacteria such as the bacterium Clostridium perfringens that produces the enterotoxin responsible for food poisoning. They are also targets of strategies for enhancing drug delivery of large molecules including proteins across the gastrointestinal tract. Further, there are numerous hereditary diseases that are linked with mutations of tight junction proteins, which include hypomagnesemia, deafness, neonatal sclerosing cholangitis with ichthyosis and familiar hypercholanemia.Full Abstract
16:35	End of Session
17:00	END OF DAY 2

Genomics

Emily Lumley — Thu, 29 Nov 2018 16:35:47 +0000

Invited Speakers

Prof. Nik Maniatis, University College London
Dr Toby Andrew, Imperial College London
Dr Maria Secrier, University College London
Dr Igor Ruiz De Los Mozos, Francis Crick Institute

Symposium Co-Chairs:

Nikolas Maniatis, Professor of Human Genetics
Andrea Townsend-Nicholson, Professor of Biochemistry & Molecular Biology

Symposium Description

The sequencing of the human genome, published 50 years after the discovery of the structure of DNA, has had a paradigm-shifting impact on a broad range of disciplines. Today, advances in DNA sequencing technologies and in the computational processors, storage and analyses underpinning these have seen the cost of sequencing an individual’s genome drop to the levels needed for this technology to form part of a suite of healthcare tests. Future developments in DNA sequencing will make genome sequencing even less expensive, placing us well and truly in the post-genomic era of biomedicine.

Traditionally, genomics has been the area of biomedical research that was an early adopter of computational methodologies and has the highest concentration of computational biologists. Despite this, the widespread adoption of high performance computing resources remains the province of few researchers in the domain. In this symposium we shall examine the state-of-the-art in genomics research, how this has paved the way for new applications of molecular medicine and how high performance computing can inform applied genomics research to bring transformative changes to clinical practice and personalised medicine.

Wednesday 25th September, 13:30 – 15:30; Watson Watt Room

Time	Speaker	Title
13:30	Maria Secrier (Invited Speaker)	Reconstructing mutational histories of oesophageal cancer Abstract Preview Mutational processes contributing to the development of cancer emerge from various risk factors of the disease and impose specific imprints of somatic alterations in the genomes of cancer patients. These mutational footprints, called “signatures”, can be read from the tumour sequencing data and reveal the main sources of DNA damage driving neoplastic progression. In this sense, they can be considered a form of evidence for historical mutational events that have acted during tumour evolution. I will discuss some of the insights we have obtained into the development and progression of oesophageal adenocarcinoma, an aggressive disease with limited treatment options, by tracking mutational signatures in human cancer tissues as well as 3D cell models of this malignancy. Using this strategy applied to whole-genome sequencing data from 129 cases, we have previously uncovered three subtypes of oesophageal cancer with distinct aetiologies related to DNA damage repair deficiencies, ageing and oxidative stress, and with different therapeutic options. Further, we have shown that organoids grown in vitro from patients’ tumours effectively recapitulate the genomic and transcriptomic profiles of the tumours of origin, and thus constitute a suitable model for this cancer type. By tracking the evolution of mutational processes during organoid culture growth we were also able to demonstrate a dynamic clonal architecture that mimics well the extensive intratumour heterogeneity observed in this cancer. Tracing mutational signature trajectories from early to later stages of cancer development in both primary tumours and organoid systems unveils a refined picture of evolution in this cancer, with frequent bottlenecks (~60% of cases) where mutational pressures shift. Finally, we suggest that the observed genomic signatures and their specific temporal dynamics could be further exploited for patient stratification in the clinic. Full Abstract
13:50	Igor Ruiz de Los Mozos (Invited Speaker)	CDK11 binds chromatin and mRNAs of replication dependent histones regulating their expression. Abstract preview Expression of canonical, replication-dependent histones (RDH) is highly regulated during the cell cycle echoing their main role during cell division and epigenetic inheritance. RDH genes produce the only non-polyadenylated transcripts and for their correct expression recruit a battery of alternative 3’ end processing factors. Exploiting metaplots, positional heat maps and computational methods, we decipher CDK11 binding along RDH mRNA and DNA identifying it as key player in the molecular regulation of RDH biogenesis. Full Abstract
14:10	Nik Maniatis (Invited Speaker)	The power of high-resolution population-specific genetic maps to dissect the genetic architecture of complex diseases: Type 2 Diabetes as an example Abstract Preview Metric genetic maps in Linkage Disequilibrium Units (LDU) are analogous to Linkage maps in cM but at a much higher marker resolution. LDU blocks represent areas of conserved LD and low haplotype diversity, while steps (increasing LDU distances) define LD breakdown, primarily caused by recombination, since crossover profiles agree precisely with the corresponding LDU steps. However, LDU maps do not only capture recombination events but the detailed linkage disequilibrium information of the population in question. We recently constructed the LDU genetic maps in Europeans and African-Americans and applied these to large T2D case-control samples in order to estimate accurate locations for putative functional variants in both populations. Replicated T2D locations were tested for evidence of being regulatory locations using adipose expression. We identified 111 novel loci associated with T2D-susceptibility locations, 93 of which are cosmopolitan (co-localised on genetic maps for both populations) and 18 are European-specific. We also found that many previously known T2D signals are also risk loci in African-Americans and we obtained more refined causal locations for these signals than the published lead SNPs. Using the same LDU methods, we also showed that the majority of these T2D locations are also regulatory locations (eQTLs) conferring the risk of T2D via the regulation of expression levels for a very large number (266) of cis-regulated genes. We identified a highly significant overlap between T2D and regulatory locations with chromatin marks for different tissues/cells. Sequencing a sample of our locations provided candidate functional variants that precisely co-locate pancreatic islet enhancers, leading to our conclusions that population specific genetic maps can: (i) provide commensurability when making comparisons between different populations and SNP-arrays; (ii) provide precise location estimates on the genetic map for potential functional variants, since these estimates are more efficient than using physical maps and (iii) effectively integrate disease-associated loci in different populations with gene expression and cell-specific regulatory annotation, by providing precision in co-localisation. Full Abstract
14:30	Toby Andrew (Invited Speaker)	Genetic fine-mapping and targeted sequencing to investigate allelic heterogeneity and molecular function at genomic disease susceptibility loci for Type 2 Diabetes Abstract Preview Empirical genomic studies and long-established genetic theory show that complex traits – including many common diseases – are likely to be polygenic with numerous non-coding variants conferring risk of disease via the regulation of gene expression1 and post-translational modification2. Using high-resolution genetic maps3, we have identified 173 Type 2 Diabetes (T2D) precise disease susceptibility location estimates4 and using gene expression quantitative trait loci (eQTL) analyses for subcutaneous adipose tissue, have shown strong evidence that approximately two thirds of these closely collocate (± 50Kb) of eQTL location estimates that regulate the expression neighbouring cis-genes (within ±1.5Mb of the disease locus; see Figure 1)4. Our follow up analyses show that ~80 of the 111 T2D disease loci are also eQTLs that regulate the expression of nuclear encoded mitochondrial cis-genes with the eQTLs showing a high degree of co-location with in silico functional annotation. In this talk I will discuss our current understanding of the genetic and allelic architecture of T2D and illustrate this with results from genomic analyses and follow-up fine-mapping studies conducted by our research groups. In particular, we are investigating two interesting novel loci for evidence of complex association with T2D and mitochondrial function. The first locus, a 79kb stretch in intron 3 of FGF14, was observed to harbour eQTL for genes including PCCA, for which the encoded carboxylase catalyses a terminal step in both branched chain amino acid (BCAA) catabolism and odd-chain fatty acid oxidation; two pathways relevant to T2D aetiology. The second is a predicted eQTL for the fatty acid dehydrogenase ACAD11. Full Abstract
14:50	Hannah Maude	Pathway analysis reveals genetic regulation of mitochondrial function and branched-chain amino acid catabolism in Type 2 Diabetes Abstract Preview In recent years, the number of genetic loci found to be associated with T2D has increased substantially, mostly through large-scale genome-wide association studies (GWAS). Recent work has, however, highlighted an underappreciated contribution of rare variants and variants in areas of low linkage disequilibrium (LD) to complex disease heritability1,2, both of which are difficult to map using single-SNP tests of association. High-resolution genetic maps offer increased power to detect associations in areas of low LD and were recently used to map and replicate 111 novel loci associated with T2D3. Co-location of eQTL (genetic ‘expression quantitative trait loci’ which associate with gene expression levels) with disease loci (genetic loci that associate with risk of T2D), based on population-specific LD, was used to identify genes regulated by disease-associated variants (cis-genes). A co-localization approach overcomes difficulties in replicating lead SNPs between studies, making it an effective tool to identify likely cis-genes and the corresponding biological pathways implicated in heritable risk of disease. In this work, a total of 255 nominally significant disease loci were co-located with adipose eQTL and cis-genes were studied at the individual and pathway level. Specifically, we aimed to address the hypothesis that changes in mitochondrial function are a heritable, causal risk factor for T2D, by searching for cis-genes involved in mitochondrial function. Full Abstract
15:00	Karoline Kuchenbaecker	Trans-ethnic colocalization: A novel approach to assess the transferability of trait loci across populations Abstract Preview Most previous genome-wide association studies for complex traits were based on samples with European ancestry. Consequently, it is important to determine the transferability of findings to other ancestry groups. Here we ask the fundamental question whether causal variants for lipids are shared between populations. Differences in linkage disequilibrium structure, allele frequencies and sample size make it difficult to assess replication for individual loci. Therefore, we propose a new strategy to assess evidence for shared causal variants between two populations: trans-ethnic colocalization (TEColoc). We re-purposed a method originally developed for colocalization of GWAS and eQTL results: Joint Likelihood Mapping (JLIM). In order to assess its performance for GWAS results from samples with different ancestry, we carried out a simulation study. UK Biobank (UKB) was used as a European ancestry reference Full Abstract
15:10	Julia Ramírez	The Genetic Architecture of T-wave Morphology Restitution Abstract Preview Cardiovascular (CV) mortality is the main cause of death in the general population1. The analysis of the electrocardiogram (ECG) has potential for non-invasive diagnosis and prediction of CV risk. ECG markers are heritable and statistical genetic methods are available to estimate the cumulative contribution of genetic factors to CV events via genetic risk scores (GRSs)2. The T-wave morphology restitution (TMR)3 is an ECG marker that quantifies the rate of variation of the T-wave morphology with heart rate and has shown to be a strong predictor of sudden cardiac death in chronic heart failure patients3. We hypothesize that the interaction between repolarization dynamics and CV risk has a genetic component and that TMR can be used to capture it. The objective was to identify single-nucleotide variants (SNVs) significantly associated with TMR using genome-wide association studies (GWASs) and to develop genetic risk scores (GRSs) to evaluate their association with CV risk. Full Abstract
15:20	Stefan van Diujvenboden	Genetic architecture of QT dynamics and resting QT in the general population Abstract Preview The resting QT interval, an electrocardiographic measure of myocardial repolarisation, is a heritable risk factor for cardiovascular (CV) events and genetic studies have provided new insights into the underlying biology[1]. Patient studies have reported that QT adaptation to heart rate (QT dynamics) improves cardiac risk prediction[2], but its prognostic value in the general population remains to be investigated. Furthermore, it is well recognised that the QT interval is a heritable trait and characterisation of genetic variation has provided new insights and suggests candidate genes that could predispose to CV risk. However, common variants thus far reported leave an important part of its heritability unexplained. In addition, the genetic architecture underlying QT dynamics has not been explored and might further inform about new biological mechanisms that specifically target rate adaptation of the QT interval. The objectives of this work were: (1) Evaluate the CV prognostic value of QT dynamics in the general population, (2) discover genetic variants associated with QT dynamics and (3) further investigate the genetic basis and biology of resting QT interval. Full Abstract
15:30	REFRESHMENTS AND POSTER SESSION