Wednesday, February 15, 2017 465a Symposium: Protein Dynamics and Allostery example, in-silico models of human cardiac electrophysiology are being considered by the FDA for prediction of proarrhythmic cardiotoxicity as a 2285-Symp core component of the preclinical assessment phase of all new drugs. How- Coupled Residue-Residue Dynamics in Protein Allosteric Mechanisms ever, one issue that exists with current models is that they each respond Donald Hamelberg. differently to insults such as drug block of ion channels or mutation of cardiac Department of Chemistry, Georgia State University, Atlanta, GA, USA. ion channel genes. Clearly this poses a problem in relation to the utility of Although the relationship between structure and function in biomolecules is these models in making quantitative predictions that are physiologically or well established, it is not always adequate to provide a complete understanding clinically meaningful. To examine this in detail we tested the ability of three of biomolecular function. The dynamical fluctuations of biomolecules can also models of the human ventricular action potential, the O’hara-Rudy the Grandi- play an essential role in function. Detailed understanding of how conforma- Bers and the Ten Tusscher models, to reproduce the clinical phenotype of tional dynamics orchestrates function in allosteric regulation of recognition different subtypes of the long QT syndrome. All models, in their original and catalysis at atomic resolution remains ambiguous. The overarching goal form, produce markedly different and unrealistic predictions of QT prolonga- is to understand how biomolecular dynamics are coupled to function by using tion. To address this, we used a global optimization approach to constrain ex- atomistic molecular simulations to complement experiments. In this talk, we isting in silico models to clinical datasets. After optimization, all models have will discuss computational studies on members of a ubiquitous family of en- similar current densities during the action potential, despite differences in ki- zymes that catalyze peptidyl-prolyl bonds and regulate many sub-cellular pro- netic properties of the channels in the different models, and closely reproduced cesses. We analyze large amount of time-dependent multi-dimensional data the prolongation of repolarization seen in clinical data. We suggest that models with a coarse-grained approach and map key dynamical features within individ- optimized using this approach can be utilized with more confidence in clinical ual macrostates by defining dynamics in terms of residue-residue contacts. The and preclinical applications such as prediction of proarrhythmic risk as part of effects of substrate binding are observed to be largely sensed at a location over in silico drug screening, examining pathogenic interactions of electrical 15 A˚ from the active site, implying its importance in allostery. Using NMR ex- dysfunction and structural alteration in the myocardium and assessing the periments, we confirm that a dynamic cluster of residues in this distal region is impact of genetic variants in ion channel genes in contributing to heart rhythm directly coupled to the active site. Furthermore, the dynamical network of inter- disturbances. residue contacts is coupled and temporally dispersed. Mapping these dynamical 2288-Symp features and the coupling of dynamics to function has crucial ramifications in Towards in Silico Drug Trials using Human Multiscale Cardiac Models understanding allosteric regulation in enzymes and proteins in general. Blanca Rodriguez. 2286-Symp University of Oxford, Oxford, United Kingdom. Entropy in Molecular Recognition by Proteins In silico physiological modelling and simulation provide a cheap, useful tool Joshua Wand. for drug safety and efficacy assessment. In this presentation, we will show ev- Biochemistry & Biophysics, University of Pennsylvania, Philadelphia, idence of the potential of human multiscale models of the heart for the evalu- PA, USA. ation of drug safety and efficacy. At a fundamental level, biological processes are most often controlled using mo- We will illustrate how in silico trials can be conducted to assess drug safety and lecular recognition by proteins. Protein-ligand interactions impact critical events efficacy with consideration of population variability and disease conditions. ranging from the catalytic action of enzymes, the assembly of macromolecular Methodological progress for in silico trials is based on the maturity of multi- structures, complex signaling and allostery, transport phenomena, force genera- scale models of human physiology, availability of human recordings to cali- tion and so on. The physical origin of high affinity interactions involving proteins brate the human models from the ionic to the whole organ level, and our continues to be the subject of intense investigation. Conformational entropy rep- ability to simulate the consequences of diseases such as myocardial ischemia, resents perhaps the last piece of the thermodynamic puzzle that governs protein heart failure and inherited disease conditions. We will show results using structure, stability, dynamics and function. The presence and importance of in- experimentally-calibrated populations of models and high performance ternal conformational entropy in proteins has been debated for decades but has computing simulations of diseased human hearts, and their comparison to resisted experimental quantification. Over the past few years we have introduced, experimental datasets. In summary, in silico trials using human multiscale car- developed and validated an NMR-based approach that uses a dynamical proxy to diac models provide a useful, mechanistic tool for the preclinical assessment of determine changes in conformational entropy. This new approach, which we drugs, which enriches and complements current approaches. term the NMR ‘‘entropy meter,’’ requires few assumptions, is empirically cali- brated and is apparently robust and universal. Using this ‘‘entropy meter,’’ it 2289-Symp can now be quantitatively shown that proteins retain considerable conforma- Predictive Computational Pharmacology: From Atom to Rhythm tional entropy in their native functional states and that this conformational en- Colleen E. Clancy. tropy can play a decisive role in the thermodynamics of molecular recognition Department of Pharmacology, University of California, Davis, Davis, by proteins. Recent results show that changes conformational entropy of a pro- CA, USA. tein upon binding a high affinity ligand is highly system specific and can vary Common paroxysmal electrical diseases that affect millions of people world- from strongly inhibiting to even strongly promoting binding and everything in wide are notoriously difficult to manage with drug therapy, and some drugs in- between. Thus one cannot possibly understand comprehensively how proteins tended for therapy can even exacerbate disease. A vital hindrance to safe and work without knowledge of the breadth and underlying principles of the role effective drug treatment of excitable disorders is that there is currently no of conformational entropy in protein function. This approach also allows for way to predict how drugs with complex interactions and multiple subcellular the refinement of empirical coefficients that relate changes in accessible surface targets will alter the emergent electrical activity of cells and tissues. Our area to changes in the entropy of water and the determination of the loss of work involves the development of a novel quantitative systems pharmacology rotational-translational entropy in high affinity protein complexes. Supported approach derived from a combination of experiments, computational biology, by the NIH and the Mathers Foundation. high performance computing and clinical observation that allows for probing the mechanisms of action of drugs in the settings of one of the most common Symposium: Computational Cardiology excitable diseases: cardiac arrhythmias. These new tools can be applied to pre- clinical screening of compounds for therapeutic benefit or harm. A computer- 2287-Symp based approach can be used to determine mechanisms of drugs, with a specific Using Clinical Datasets to Optimize Models of Human Ventricular Elec- focus to conduct failure analysis for once promising drugs that have failed clin- trophysiology: Implications for In Silico Drug Screening ically. Finally, models are applied to demonstrate utility in guiding therapy for Adam P. Hill1, Stefan A. Mann2, Mohammad S. Imtiaz1, Matthew D. Perry3, specific clinical situations and to identify optimal ‘‘polypharmacy’’ to inform Jamie I. Vandenberg3. the common practice of clinical empirical mixing and matching of drugs to 1Computational Cardiology, Victor Chang Cardiac Research Institute, create multidrug therapeutic regimens. The computational processes that we Sydney, Australia, 2Cytocentrics Bioscience GmbH, Cologne, Germany, have developed are paradigms for how the explosion in systems and computa- 3Molecular Cardiology and Biophysics, Victor Chang Cardiac Research tional biology can be utilized to assist drug-screening, determination of mech- Institute, Sydney, Australia. anisms and to guide therapy. The eventual goal is a scalable, automated Recent advances in Computational Cardiology mean we can now examine the platform that will interact with other cutting edge technologies to serve pur- causes, mechanisms and impact of cardiac dysfunction in silico, particularly in poses in industry, academia and