Literature DB >> 32058713

Sampling Conformational Changes of Bound Ligands Using Nonequilibrium Candidate Monte Carlo and Molecular Dynamics.

Sukanya Sasmal1, Samuel C Gill2, Nathan M Lim1, David L Mobley2,1.   

Abstract

Flexible ligands often have multiple binding modes or bound conformations that differ by rotation of a portion of the molecule around internal rotatable bonds. Knowledge of these binding modes is important for understanding the interactions stabilizing the ligand in the binding pocket, and other studies indicate it is important for calculating accurate binding affinities. In this work, we use a hybrid molecular dynamics (MD)/nonequilibrium candidate Monte Carlo (NCMC) method to sample the different binding modes of several flexible ligands and also to estimate the population distribution of the modes. The NCMC move proposal is divided into three parts. The flexible part of the ligand is alchemically turned off by decreasing the electrostatics and steric interactions gradually, followed by rotating the rotatable bond by a random angle and then slowly turning the ligand back on to its fully interacting state. The alchemical steps prior to and after the move proposal help the surrounding protein and water atoms in the binding pocket relax around the proposed ligand conformation and increase move acceptance rates. The protein-ligand system is propagated using classical MD in between the NCMC proposals. Using this MD/NCMC method, we were able to correctly reproduce the different binding modes of inhibitors binding to two kinase targets-c-Jun N-terminal kinase-1 and cyclin-dependent kinase 2-at a much lower computational cost compared to conventional MD and umbrella sampling. This method is available as a part of the BLUES software package.

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Year:  2020        PMID: 32058713      PMCID: PMC7325746          DOI: 10.1021/acs.jctc.9b01066

Source DB:  PubMed          Journal:  J Chem Theory Comput        ISSN: 1549-9618            Impact factor:   6.006


  44 in total

1.  Quantifying uncertainty and sampling quality in biomolecular simulations.

Authors:  Alan Grossfield; Daniel M Zuckerman
Journal:  Annu Rep Comput Chem       Date:  2009-01-01

Review 2.  Prediction of protein-ligand binding affinity by free energy simulations: assumptions, pitfalls and expectations.

Authors:  Julien Michel; Jonathan W Essex
Journal:  J Comput Aided Mol Des       Date:  2010-05-28       Impact factor: 3.686

3.  PTRAJ and CPPTRAJ: Software for Processing and Analysis of Molecular Dynamics Trajectory Data.

Authors:  Daniel R Roe; Thomas E Cheatham
Journal:  J Chem Theory Comput       Date:  2013-06-25       Impact factor: 6.006

4.  Aminopyridine-based c-Jun N-terminal kinase inhibitors with cellular activity and minimal cross-kinase activity.

Authors:  Bruce G Szczepankiewicz; Christi Kosogof; Lissa T J Nelson; Gang Liu; Bo Liu; Hongyu Zhao; Michael D Serby; Zhili Xin; Mei Liu; Rebecca J Gum; Deanna L Haasch; Sanyi Wang; Jill E Clampit; Eric F Johnson; Thomas H Lubben; Michael A Stashko; Edward T Olejniczak; Chaohong Sun; Sarah A Dorwin; Kristi Haskins; Cele Abad-Zapatero; Elizabeth H Fry; Charles W Hutchins; Hing L Sham; Cristina M Rondinone; James M Trevillyan
Journal:  J Med Chem       Date:  2006-06-15       Impact factor: 7.446

5.  Free Energy Methods in Drug Design: Prospects of "Alchemical Perturbation" in Medicinal Chemistry.

Authors:  Billy J Williams-Noonan; Elizabeth Yuriev; David K Chalmers
Journal:  J Med Chem       Date:  2017-08-04       Impact factor: 7.446

6.  Perspective: Alchemical free energy calculations for drug discovery.

Authors:  David L Mobley; Pavel V Klimovich
Journal:  J Chem Phys       Date:  2012-12-21       Impact factor: 3.488

7.  D3R Grand Challenge 3: blind prediction of protein-ligand poses and affinity rankings.

Authors:  Zied Gaieb; Conor D Parks; Michael Chiu; Huanwang Yang; Chenghua Shao; W Patrick Walters; Millard H Lambert; Neysa Nevins; Scott D Bembenek; Michael K Ameriks; Tara Mirzadegan; Stephen K Burley; Rommie E Amaro; Michael K Gilson
Journal:  J Comput Aided Mol Des       Date:  2019-01-10       Impact factor: 3.686

Review 8.  Binding of small-molecule ligands to proteins: "what you see" is not always "what you get".

Authors:  David L Mobley; Ken A Dill
Journal:  Structure       Date:  2009-04-15       Impact factor: 5.006

9.  Structure-guided discovery of cyclin-dependent kinase inhibitors.

Authors:  Thierry O Fischmann; Alan Hruza; José S Duca; Lata Ramanathan; Todd Mayhood; William T Windsor; Hung V Le; Timothy J Guzi; Michael P Dwyer; Kamil Paruch; Ronald J Doll; Emma Lees; David Parry; Wolfgang Seghezzi; Vincent Madison
Journal:  Biopolymers       Date:  2008-05       Impact factor: 2.505

10.  Enhanced Monte Carlo Sampling through Replica Exchange with Solute Tempering.

Authors:  Daniel J Cole; Julian Tirado-Rives; William L Jorgensen
Journal:  J Chem Theory Comput       Date:  2014-01-17       Impact factor: 6.006

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  4 in total

1.  An overview of the SAMPL8 host-guest binding challenge.

Authors:  Martin Amezcua; Jeffry Setiadi; Yunhui Ge; David L Mobley
Journal:  J Comput Aided Mol Des       Date:  2022-10-14       Impact factor: 4.179

2.  Enhancing Sampling of Water Rehydration on Ligand Binding: A Comparison of Techniques.

Authors:  Yunhui Ge; David C Wych; Marley L Samways; Michael E Wall; Jonathan W Essex; David L Mobley
Journal:  J Chem Theory Comput       Date:  2022-02-11       Impact factor: 6.578

3.  Reversibly Sampling Conformations and Binding Modes Using Molecular Darting.

Authors:  Samuel C Gill; David L Mobley
Journal:  J Chem Theory Comput       Date:  2020-12-08       Impact factor: 6.006

4.  Enhancing water sampling of buried binding sites using nonequilibrium candidate Monte Carlo.

Authors:  Teresa Danielle Bergazin; Ido Y Ben-Shalom; Nathan M Lim; Sam C Gill; Michael K Gilson; David L Mobley
Journal:  J Comput Aided Mol Des       Date:  2020-09-24       Impact factor: 3.686

  4 in total

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