How inaccuracies in protein structure models affect estimates of protein-ligand interactions: computational analysis of HIV-I protease inhibitor binding.

Details

Serval ID
serval:BIB_570EC702E08D
Type
Article: article from journal or magazin.
Collection
Publications
Institution
Title
How inaccuracies in protein structure models affect estimates of protein-ligand interactions: computational analysis of HIV-I protease inhibitor binding.
Journal
Proteins
Author(s)
Thorsteinsdottir H.B., Schwede T., Zoete V., Meuwly M.
ISSN
1097-0134 (Electronic)
ISSN-L
0887-3585
Publication state
Published
Issued date
01/11/2006
Peer-reviewed
Oui
Volume
65
Number
2
Pages
407-423
Language
english
Notes
Publication types: Journal Article ; Research Support, Non-U.S. Gov't
Publication Status: ppublish
Abstract
The influence of possible inaccuracies that can arise during homology modeling of protein structures used for ligand binding studies were investigated with the molecular mechanics generalized Born surface area (MM-GBSA) method. For this, a family of well-characterized HIV-I protease-inhibitor complexes was used. Validation of MM-GBSA led to a correlation coefficient ranging from 0.72 to 0.93 between calculated and experimental binding free energies DeltaG. All calculated DeltaG values were based on molecular dynamics simulations with explicit solvent. Errors introduced into the protein structure through misplacement of side-chains during rotamer modeling led to a correlation coefficient between DeltaG(calc) and DeltaG(exp) of 0.75 compared with 0.90 for the correctly placed side chains. This is in contrast to homology models for members of the retroviral protease family with template structures ranging in sequence identity between 32% and 51%. For these protein models, the correlation coefficients vary between 0.84 and 0.87, which is considerably closer to the original protein (0.90). It is concluded that HIV-I low sequence identity with the template structure still allows creating sufficiently reliable homology models to be used for ligand-binding studies, although placement of the rotamers is a critical step during the modeling.

Keywords
Amino Acid Sequence, Computer Simulation, HIV Protease/chemistry, HIV Protease/metabolism, HIV Protease Inhibitors/chemistry, HIV Protease Inhibitors/metabolism, HIV-1/enzymology, Ligands, Models, Molecular, Molecular Sequence Data, Molecular Structure, Protein Binding, Sequence Alignment, Sequence Homology, Amino Acid, Thermodynamics
Pubmed
Web of science
Create date
05/02/2018 15:59
Last modification date
21/08/2019 6:37
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