Literature DB >> 26180998

Improving the LIE Method for Binding Free Energy Calculations of Protein-Ligand Complexes.

Williams E Miranda1, Sergei Yu Noskov2, Pedro A Valiente1.   

Abstract

In this work, we introduced an improved linear interaction energy (LIE) method parameterization for computations of protein–ligand binding free energies. The protocol, coined LIE-D, builds on the linear relationship between the empirical coefficient γ in the standard LIE scheme and the D parameter, introduced in our work. The D-parameter encompasses the balance (difference) between electrostatic (polar) and van der Waals (nonpolar) energies in protein–ligand complexes. Leave-one-out cross-validation showed that LIE-D reproduced accurately the absolute binding free energies for our training set of protein–ligand complexes (<|error|> = 0.92 kcal/mol, SDerror = 0.66 kcal/mol, R(2) = 0.90, QLOO(2) = 0.89, and sPRESS(LOO) = 1.28 kcal/mol). We also demonstrated LIE-D robustness by predicting accurately the binding free energies for three different protein–ligand systems outside the training data set, where the electrostatic and van der Waals interaction energies were calculated with different force fields.

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Year:  2015        PMID: 26180998     DOI: 10.1021/acs.jcim.5b00012

Source DB:  PubMed          Journal:  J Chem Inf Model        ISSN: 1549-9596            Impact factor:   4.956


  10 in total

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Journal:  J Chem Theory Comput       Date:  2017-06-23       Impact factor: 6.006

2.  Identification of Inhibitors of CD36-Amyloid Beta Binding as Potential Agents for Alzheimer's Disease.

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Journal:  ACS Chem Neurosci       Date:  2017-02-15       Impact factor: 4.418

3.  Prediction of molecular interactions and physicochemical properties relevant for vasopressin V2 receptor antagonism.

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4.  Structural basis of H2A.Z recognition by SRCAP chromatin-remodeling subunit YL1.

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Journal:  Nat Struct Mol Biol       Date:  2016-03-14       Impact factor: 15.369

5.  Comprehensive and Automated Linear Interaction Energy Based Binding-Affinity Prediction for Multifarious Cytochrome P450 Aromatase Inhibitors.

Authors:  Marc van Dijk; Antonius M Ter Laak; Jörg D Wichard; Luigi Capoferri; Nico P E Vermeulen; Daan P Geerke
Journal:  J Chem Inf Model       Date:  2017-08-23       Impact factor: 4.956

6.  d-Amino Acid Pseudopeptides as Potential Amyloid-Beta Aggregation Inhibitors.

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7.  Computing Cellulase Kinetics with a Two-Domain Linear Interaction Energy Approach.

Authors:  Kay S Schaller; Jeppe Kari; Gustavo A Molina; Kasper D Tidemand; Kim Borch; Günther H J Peters; Peter Westh
Journal:  ACS Omega       Date:  2021-01-06

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Journal:  J Mol Graph Model       Date:  2021-09-09       Impact factor: 2.518

9.  How Good is Jarzynski's Equality for Computer-Aided Drug Design?

Authors:  Kiet Ho; Duc Toan Truong; Mai Suan Li
Journal:  J Phys Chem B       Date:  2020-06-22       Impact factor: 2.991

10.  Unbinding ligands from SARS-CoV-2 Mpro via umbrella sampling simulations.

Authors:  Nguyen Minh Tam; Trung Hai Nguyen; Vu Thi Ngan; Nguyen Thanh Tung; Son Tung Ngo
Journal:  R Soc Open Sci       Date:  2022-01-26       Impact factor: 2.963

  10 in total

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