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3. Binding Modes of Ligands Using Enhanced Sampling (BLUES): Rapid Decorrelation of Ligand Binding Modes via Nonequilibrium Candidate Monte Carlo

Author

Gill, Samuel C, Lim, Nathan M, Grinaway, Patrick B, Rustenburg, Ariën S, Fass, Josh, Ross, Gregory A, Chodera, John D, and Mobley, David L

Subjects
Medicinal and Biomolecular Chemistry, Chemical Sciences, Generic health relevance, Binding Sites, Ligands, Molecular Dynamics Simulation, Monte Carlo Method, Muramidase, Protein Binding, Protein Structure, Tertiary, Thermodynamics, Toluene, Water, Physical Sciences, Engineering, Chemical sciences, Physical sciences
Abstract

Accurately predicting protein-ligand binding affinities and binding modes is a major goal in computational chemistry, but even the prediction of ligand binding modes in proteins poses major challenges. Here, we focus on solving the binding mode prediction problem for rigid fragments. That is, we focus on computing the dominant placement, conformation, and orientations of a relatively rigid, fragment-like ligand in a receptor, and the populations of the multiple binding modes which may be relevant. This problem is important in its own right, but is even more timely given the recent success of alchemical free energy calculations. Alchemical calculations are increasingly used to predict binding free energies of ligands to receptors. However, the accuracy of these calculations is dependent on proper sampling of the relevant ligand binding modes. Unfortunately, ligand binding modes may often be uncertain, hard to predict, and/or slow to interconvert on simulation time scales, so proper sampling with current techniques can require prohibitively long simulations. We need new methods which dramatically improve sampling of ligand binding modes. Here, we develop and apply a nonequilibrium candidate Monte Carlo (NCMC) method to improve sampling of ligand binding modes. In this technique, the ligand is rotated and subsequently allowed to relax in its new position through alchemical perturbation before accepting or rejecting the rotation and relaxation as a nonequilibrium Monte Carlo move. When applied to a T4 lysozyme model binding system, this NCMC method shows over 2 orders of magnitude improvement in binding mode sampling efficiency compared to a brute force molecular dynamics simulation. This is a first step toward applying this methodology to pharmaceutically relevant binding of fragments and, eventually, drug-like molecules. We are making this approach available via our new Binding modes of ligands using enhanced sampling (BLUES) package which is freely available on GitHub.

Published
2018

5. 11th German Conference on Chemoinformatics (GCC 2015) : Fulda, Germany. 8-10 November 2015.

Author

Fechner, Uli, de Graaf, Chris, Torda, Andrew E, Güssregen, Stefan, Evers, Andreas, Matter, Hans, Hessler, Gerhard, Richmond, Nicola J, Schmidtke, Peter, Segler, Marwin HS, Waller, Mark P, Pleik, Stefanie, Shea, Joan-Emma, Levine, Zachary, Mullen, Ryan, van den Broek, Karina, Epple, Matthias, Kuhn, Hubert, Truszkowski, Andreas, Zielesny, Achim, Fraaije, Johannes Hans, Gracia, Ruben Serral, Kast, Stefan M, Bulusu, Krishna C, Bender, Andreas, Yosipof, Abraham, Nahum, Oren, Senderowitz, Hanoch, Krotzky, Timo, Schulz, Robert, Wolber, Gerhard, Bietz, Stefan, Rarey, Matthias, Zimmermann, Markus O, Lange, Andreas, Ruff, Manuel, Heidrich, Johannes, Onlia, Ionut, Exner, Thomas E, Boeckler, Frank M, Bermudez, Marcel, Firaha, Dzmitry S, Hollóczki, Oldamur, Kirchner, Barbara, Tautermann, Christofer S, Volkamer, Andrea, Eid, Sameh, Turk, Samo, Rippmann, Friedrich, Fulle, Simone, Saleh, Noureldin, Saladino, Giorgio, Gervasio, Francesco L, Haensele, Elke, Banting, Lee, Whitley, David C, Oliveira Santos, Jana Sopkova-de, Bureau, Ronan, Clark, Timothy, Sandmann, Achim, Lanig, Harald, Kibies, Patrick, Heil, Jochen, Hoffgaard, Franziska, Frach, Roland, Engel, Julian, Smith, Steven, Basu, Debjit, Rauh, Daniel, Kohlbacher, Oliver, Essex, Jonathan W, Bodnarchuk, Michael S, Ross, Gregory A, Finkelmann, Arndt R, Göller, Andreas H, Schneider, Gisbert, Husch, Tamara, Schütter, Christoph, Balducci, Andrea, Korth, Martin, Ntie-Kang, Fidele, Günther, Stefan, Sippl, Wolfgang, Mbaze, Luc Meva'a, Simoben, Conrad V, Lifongo, Lydia L, Judson, Philip, Barilla, Jiří, Lokajíček, Miloš V, Pisaková, Hana, Simr, Pavel, Kireeva, Natalia, Petrov, Alexandre, Ostroumov, Denis, Solovev, Vitaly P, Pervov, Vladislav S, and Friedrich, Nils-Ole

Subjects
Macromolecular and Materials Chemistry
Published
2016

10. Improving rapid affinity calculations for drug-protein interactions

Author

Ross, Gregory A., Biggin, Philip, and Garrett, Morris

Subjects
615.1, Computational chemistry, Computational biochemistry, Molecular biophysics (biochemistry), docking, scoring-function, drug-design, water, molecular-modelling, simulations, hydrophobicity
Abstract

The rationalisation of drug potency using three-dimensional structures of protein-ligand complexes is a central paradigm in medicinal research. For over two decades, a major goal has been to find the rules that accurately relate the structure of any protein-ligand complex to its affinity. Addressing this problem is of great concern to the pharmaceutical industry, which uses virtual screens to computationally assay up to many millions of compounds against a protein target. A fast and trustworthy affinity estimator could potentially streamline the drug discovery process, reducing reliance on expensive wet lab experiments, speeding up the discovery of new hits and aiding lead optimization. Water plays a critical role in drug-protein interactions. To address the often ambiguous nature of water in binding sites, a water placement method was developed and found to be in good agreement with X-ray crystallography, neutron diffraction data and molecular dynamics simulations. The method is fast and has facilitated a large scale study of the statistics of water in ligand binding sites, as well as the creation of models pertaining to water binding free energies and displacement propensities, which are of particular interest to medicinal chemistry. Structure-based scoring functions employing the explicit water models were developed. Surprisingly, these attempts were no more accurate than the current state of the art, and the models suffered from the same inadequacies which have plagued all previous scoring functions. This suggests a unifying cause behind scoring function inaccuracy. Accordingly, mathematical analyses on the fundamental uncertainties in structure-based modelling were conducted. Using statistical learning theory and information theory, the existence of inherent errors in empirical scoring functions was proven. Among other results, it was found that even the very best generalised structure-based model is significantly limited in its accuracy, and protein-specific models are always likely to be better. The theoretical framework developed herein hints at modelling strategies that operate at the leading edge of achievable accuracy.

Published
2013

11. Preface

Author

Ross Gregory

Published
2015

13. Contents

Author

Ross Gregory

Published
2015

31. Small-molecule targeting of MUSASHI RNA-binding activity in acute myeloid leukemia

Author

Minuesa, Gerard, Albanese, Steven K., Xie, Wei, Kazansky, Yaniv, Worroll, Daniel, Chow, Arthur, Schurer, Alexandra, Park, Sun-Mi, Rotsides, Christina Z., Taggart, James, Rizzi, Andrea, Naden, Levi N., Chou, Timothy, Gourkanti, Saroj, Cappel, Daniel, Passarelli, Maria C., Fairchild, Lauren, Adura, Carolina, Glickman, J. Fraser, Schulman, Jessica, Famulare, Christopher, Patel, Minal, Eibl, Joseph K., Ross, Gregory M., Bhattacharya, Shibani, Tan, Derek S., Leslie, Christina S., Beuming, Thijs, Patel, Dinshaw J., Goldgur, Yehuda, Chodera, John D., and Kharas, Michael G.

Published
2019
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50. OPLS4: Improving Force Field Accuracy on Challenging Regimes of Chemical Space

Author

Lu, Chao, primary, Wu, Chuanjie, additional, Ghoreishi, Delaram, additional, Chen, Wei, additional, Wang, Lingle, additional, Damm, Wolfgang, additional, Ross, Gregory A., additional, Dahlgren, Markus K., additional, Russell, Ellery, additional, Von Bargen, Christopher D., additional, Abel, Robert, additional, Friesner, Richard A., additional, and Harder, Edward D., additional

Published
2021
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