Literature DB >> 27077817

Ligand-Binding Affinity Estimates Supported by Quantum-Mechanical Methods.

Ulf Ryde1, Pär Söderhjelm1.   

Abstract

One of the largest challenges of computational chemistry is calculation of accurate free energies for the binding of a small molecule to a biological macromolecule, which has immense implications in drug development. It is well-known that standard molecular-mechanics force fields used in most such calculations have a limited accuracy. Therefore, there has been a great interest in improving the estimates using quantum-mechanical (QM) methods. We review here approaches involving explicit QM energies to calculate binding affinities, with an emphasis on the methods, rather than on specific applications. Many different QM methods have been employed, ranging from semiempirical QM calculations, via density-functional theory, to strict coupled-cluster calculations. Dispersion and other empirical corrections are mandatory for the approximate methods, as well as large basis sets for the stricter methods. QM has been used for the ligand, for a few crucial groups around the ligand, for all the closest atoms (200-1000 atoms), or for the full receptor-ligand complex, but it is likely that with a proper embedding it might be enough to include all groups within ∼6 Å of the ligand. Approaches involving minimized structures, simulations of the end states of the binding reaction, or full free-energy simulations have been tested.

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Year:  2016        PMID: 27077817     DOI: 10.1021/acs.chemrev.5b00630

Source DB:  PubMed          Journal:  Chem Rev        ISSN: 0009-2665            Impact factor:   60.622


  43 in total

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Authors:  Rommie E Amaro; Adrian J Mulholland
Journal:  Nat Rev Chem       Date:  2018-04-11       Impact factor: 34.035

2.  Calculating distribution coefficients based on multi-scale free energy simulations: an evaluation of MM and QM/MM explicit solvent simulations of water-cyclohexane transfer in the SAMPL5 challenge.

Authors:  Gerhard König; Frank C Pickard; Jing Huang; Andrew C Simmonett; Florentina Tofoleanu; Juyong Lee; Pavlo O Dral; Samarjeet Prasad; Michael Jones; Yihan Shao; Walter Thiel; Bernard R Brooks
Journal:  J Comput Aided Mol Des       Date:  2016-08-30       Impact factor: 3.686

3.  Blind prediction of distribution in the SAMPL5 challenge with QM based protomer and pK a corrections.

Authors:  Frank C Pickard; Gerhard König; Florentina Tofoleanu; Juyong Lee; Andrew C Simmonett; Yihan Shao; Jay W Ponder; Bernard R Brooks
Journal:  J Comput Aided Mol Des       Date:  2016-09-19       Impact factor: 3.686

4.  On the polarization of ligands by proteins.

Authors:  Soohaeng Yoo Willow; Bing Xie; Jason Lawrence; Robert S Eisenberg; David D L Minh
Journal:  Phys Chem Chem Phys       Date:  2020-06-04       Impact factor: 3.676

5.  On the faithfulness of molecular mechanics representations of proteins towards quantum-mechanical energy surfaces.

Authors:  Gerhard König; Sereina Riniker
Journal:  Interface Focus       Date:  2020-10-16       Impact factor: 3.906

6.  How accurate is the description of ligand-protein interactions by a hybrid QM/MM approach?

Authors:  Jakub Kollar; Vladimir Frecer
Journal:  J Mol Model       Date:  2017-12-12       Impact factor: 1.810

7.  An efficient protocol for obtaining accurate hydration free energies using quantum chemistry and reweighting from molecular dynamics simulations.

Authors:  Frank C Pickard; Gerhard König; Andrew C Simmonett; Yihan Shao; Bernard R Brooks
Journal:  Bioorg Med Chem       Date:  2016-08-22       Impact factor: 3.641

8.  Binding free energies in the SAMPL6 octa-acid host-guest challenge calculated with MM and QM methods.

Authors:  Octav Caldararu; Martin A Olsson; Majda Misini Ignjatović; Meiting Wang; Ulf Ryde
Journal:  J Comput Aided Mol Des       Date:  2018-09-10       Impact factor: 3.686

9.  SAMPL6 host-guest challenge: binding free energies via a multistep approach.

Authors:  Yiğitcan Eken; Prajay Patel; Thomas Díaz; Michael R Jones; Angela K Wilson
Journal:  J Comput Aided Mol Des       Date:  2018-09-17       Impact factor: 3.686

10.  Use of Interaction Energies in QM/MM Free Energy Simulations.

Authors:  Phillip S Hudson; H Lee Woodcock; Stefan Boresch
Journal:  J Chem Theory Comput       Date:  2019-07-02       Impact factor: 6.006

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