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Benchmarking of Semiempirical Quantum-Mechanical Methods on Systems Relevant to Computer-Aided Drug Design
Author(s) -
Kristian Kříž,
Jan Řezáč
Publication year - 2020
Publication title -
journal of chemical information and modeling
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.24
H-Index - 160
eISSN - 1549-960X
pISSN - 1549-9596
DOI - 10.1021/acs.jcim.9b01171
Subject(s) - solvation , quantum chemical , benchmark (surveying) , benchmarking , biomolecule , non covalent interactions , ligand (biochemistry) , computational chemistry , computer science , quantum , drug drug interaction , set (abstract data type) , protein ligand , chemistry , drug , molecule , materials science , physics , nanotechnology , quantum mechanics , hydrogen bond , geography , business , receptor , biochemistry , geodesy , marketing , programming language , organic chemistry , psychiatry , psychology
The semiempirical quantum mechanical (SQM) methods used in drug design are commonly parametrized and tested on data sets of systems that may not be representative models for drug-biomolecule interactions in terms of both size and chemical composition. This is addressed here with a new benchmark data set, PLF547, derived from protein-ligand complexes, consisting of complexes of ligands with protein fragments (such as amino-acid side chains), with interaction energies based on MP2-F12 and DLPNO-CCSD(T) calculations. From these, composite benchmark interaction energies are also built for complexes of the ligand with the complete active site of the protein (PLA15 data set). These data sets are used to test multiple SQM methods with corrections for noncovalent interactions; the role of the solvation model in the calculations is tested as well.

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