Literature DB >> 28413946

Kinetics of Ligand Binding Through Advanced Computational Approaches: A Review.

Alex Dickson1, Pratyush Tiwary2, Harish Vashisth3.   

Abstract

Ligand residence times and binding rates have been found to be useful quantities to consider during drug design. The underlying structural and dynamic determinants of these kinetic quantities are difficult to discern. Driven by developments in computational hardware and simulation methodologies, molecular dynamics (MD) studies on full binding and unbinding pathways have emerged recently, showing these structural and dynamic determinants in atomic detail. However, the long timescales related to drug binding and release are still prohibitive to conventional MD simulation. Here we discuss a suite of enhanced sampling methods that have been applied to the study of full ligand binding or unbinding pathways, and reveal the kinetics of drug binding and/or release. We divide these sampling methods into three families (trajectory parallelization, metadynamics, and temperature- based methods), and discuss recent applications of each, as well as their basic theoretical underpinnings including how kinetic information is extracted. We then present an outlook for how the field could evolve, and how the rich variety of sampling methods discussed here can be leveraged in the future for computationally driven drug design. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Keywords:  Drug design; Kinetics; Metadynamics; Molecular dynamics; NMR; Simulation methodologies

Mesh:

Substances:

Year:  2017        PMID: 28413946     DOI: 10.2174/1568026617666170414142908

Source DB:  PubMed          Journal:  Curr Top Med Chem        ISSN: 1568-0266            Impact factor:   3.295


  13 in total

Review 1.  Mutagenesis computer experiments in pentameric ligand-gated ion channels: the role of simulation tools with different resolution.

Authors:  Alessandro Crnjar; Federico Comitani; Claudio Melis; Carla Molteni
Journal:  Interface Focus       Date:  2019-04-19       Impact factor: 3.906

2.  Predicting ligand binding affinity using on- and off-rates for the SAMPL6 SAMPLing challenge.

Authors:  Tom Dixon; Samuel D Lotz; Alex Dickson
Journal:  J Comput Aided Mol Des       Date:  2018-08-23       Impact factor: 3.686

Review 3.  Molecular Dynamics Simulation for All.

Authors:  Scott A Hollingsworth; Ron O Dror
Journal:  Neuron       Date:  2018-09-19       Impact factor: 17.173

4.  The bZIP mutant CEBPB (V285A) has sequence specific DNA binding propensities similar to CREB1.

Authors:  Sreejana Ray; Aniekanabasi Ufot; Nima Assad; Jocelyn Singh; Stewart R Durell; Aleksey Porollo; Desiree Tillo; Charles Vinson
Journal:  Biochim Biophys Acta Gene Regul Mech       Date:  2019-02-27       Impact factor: 4.490

5.  Estimation of binding rates and affinities from multiensemble Markov models and ligand decoupling.

Authors:  Yunhui Ge; Vincent A Voelz
Journal:  J Chem Phys       Date:  2022-04-07       Impact factor: 3.488

Review 6.  Molecular Dynamic Simulations and Molecular Docking as a Potential Way for Designed New Inhibitor Drug without Resistance.

Authors:  Jafar Aghajani; Poopak Farnia; Parissa Farnia; Jalaledin Ghanavi; Ali Akbar Velayati
Journal:  Tanaffos       Date:  2022-01

Review 7.  Thermodynamics and Kinetics of Drug-Target Binding by Molecular Simulation.

Authors:  Sergio Decherchi; Andrea Cavalli
Journal:  Chem Rev       Date:  2020-10-02       Impact factor: 60.622

8.  Mapping the Ligand Binding Landscape.

Authors:  Alex Dickson
Journal:  Biophys J       Date:  2018-09-29       Impact factor: 4.033

9.  Machine Learning Analysis of τRAMD Trajectories to Decipher Molecular Determinants of Drug-Target Residence Times.

Authors:  Daria B Kokh; Tom Kaufmann; Bastian Kister; Rebecca C Wade
Journal:  Front Mol Biosci       Date:  2019-05-24

10.  Encounter complexes and hidden poses of kinase-inhibitor binding on the free-energy landscape.

Authors:  Suyong Re; Hiraku Oshima; Kento Kasahara; Motoshi Kamiya; Yuji Sugita
Journal:  Proc Natl Acad Sci U S A       Date:  2019-08-26       Impact factor: 11.205

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