Literature DB >> 27248478

Elucidation of Nonadditive Effects in Protein-Ligand Binding Energies: Thrombin as a Case Study.

Gaetano Calabrò1, Christopher J Woods2, Francis Powlesland1, Antonia S J S Mey1, Adrian J Mulholland3, Julien Michel1.   

Abstract

Accurate predictions of free energies of binding of ligands to proteins are challenging partly because of the nonadditivity of protein-ligand interactions; i.e., the free energy of binding is the sum of numerous enthalpic and entropic contributions that cannot be separated into functional group contributions. In principle, molecular simulations methodologies that compute free energies of binding do capture nonadditivity of protein-ligand interactions, but efficient protocols are necessary to compute well-converged free energies of binding that clearly resolve nonadditive effects. To this end, an efficient GPU-accelerated implementation of alchemical free energy calculations has been developed and applied to two congeneric series of ligands of the enzyme thrombin. The results show that accurate binding affinities are computed across the two congeneric series and positive coupling between nonpolar R(1) substituents and a X = NH3(+) substituent is reproduced, albeit with a weaker trend than experimentally observed. By contrast, a docking methodology completely fails to capture nonadditive effects. Further analysis shows that the nonadditive effects are partly due to variations in the strength of a hydrogen-bond between the X = NH3(+) ligands family and thrombin residue Gly216. However, other partially compensating interactions occur across the entire binding site, and no single interaction dictates the magnitude of the nonadditive effects for all the analyzed protein-ligand complexes.

Entities:  

Mesh:

Substances:

Year:  2016        PMID: 27248478     DOI: 10.1021/acs.jpcb.6b03296

Source DB:  PubMed          Journal:  J Phys Chem B        ISSN: 1520-5207            Impact factor:   2.991


  11 in total

1.  AFD: an application for bi-molecular interaction using axial frequency distribution.

Authors:  Saad Raza; Syed Sikander Azam
Journal:  J Mol Model       Date:  2018-03-06       Impact factor: 1.810

2.  Using the fast fourier transform in binding free energy calculations.

Authors:  Trung Hai Nguyen; Huan-Xiang Zhou; David D L Minh
Journal:  J Comput Chem       Date:  2017-12-22       Impact factor: 3.376

3.  Blinded predictions of standard binding free energies: lessons learned from the SAMPL6 challenge.

Authors:  Michail Papadourakis; Stefano Bosisio; Julien Michel
Journal:  J Comput Aided Mol Des       Date:  2018-08-29       Impact factor: 3.686

4.  Visualizing protein-ligand binding with chemical energy-wise decomposition (CHEWD): application to ligand binding in the kallikrein-8 S1 Site.

Authors:  Saad Raza; Kara E Ranaghan; Marc W van der Kamp; Christopher J Woods; Adrian J Mulholland; Syed Sikander Azam
Journal:  J Comput Aided Mol Des       Date:  2019-04-15       Impact factor: 3.686

Review 5.  Predicting Binding Free Energies: Frontiers and Benchmarks.

Authors:  David L Mobley; Michael K Gilson
Journal:  Annu Rev Biophys       Date:  2017-04-07       Impact factor: 12.981

6.  A computationally designed binding mode flip leads to a novel class of potent tri-vector cyclophilin inhibitors.

Authors:  Alessio De Simone; Charis Georgiou; Harris Ioannidis; Arun A Gupta; Jordi Juárez-Jiménez; Dahlia Doughty-Shenton; Elizabeth A Blackburn; Martin A Wear; Jonathan P Richards; Paul N Barlow; Neil Carragher; Malcolm D Walkinshaw; Alison N Hulme; Julien Michel
Journal:  Chem Sci       Date:  2018-10-23       Impact factor: 9.825

7.  Molecular Dynamics Simulation Framework to Probe the Binding Hypothesis of CYP3A4 Inhibitors.

Authors:  Yusra Sajid Kiani; Kara E Ranaghan; Ishrat Jabeen; Adrian J Mulholland
Journal:  Int J Mol Sci       Date:  2019-09-10       Impact factor: 5.923

8.  Effect of set up protocols on the accuracy of alchemical free energy calculation over a set of ACK1 inhibitors.

Authors:  José M Granadino-Roldán; Antonia S J S Mey; Juan J Pérez González; Stefano Bosisio; Jaime Rubio-Martinez; Julien Michel
Journal:  PLoS One       Date:  2019-03-12       Impact factor: 3.240

9.  Impact of domain knowledge on blinded predictions of binding energies by alchemical free energy calculations.

Authors:  Antonia S J S Mey; Jordi Juárez Jiménez; Julien Michel
Journal:  J Comput Aided Mol Des       Date:  2017-11-13       Impact factor: 3.686

10.  The nature of ligand efficiency.

Authors:  Peter W Kenny
Journal:  J Cheminform       Date:  2019-01-31       Impact factor: 5.514

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.