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Alcohol binding to the odorant binding protein LUSH: multiple factors affecting binding affinities.

ABSTRACT: Density function theory (DFT) calculations have been carried out to investigate the binding of alcohols to the odorant binding protein LUSH from Drosophila melanogaster. LUSH is one of the few proteins known to bind to ethanol at physiologically relevant concentrations and where high-resolution structural information is available for the protein bound to alcohol at these concentrations. The structures of the LUSH-alcohol complexes identify a set of specific hydrogen-bonding interactions as critical for optimal binding of ethanol. A set of truncated models based on the structure of the LUSH-butanol complex were constructed for the wild-type and mutant (T57S, S52A, and T57A) proteins in complexes with a series of n-alcohols and for the apoprotein bound to water and for the ligand-free protein. Using both gas-phase calculations and continuum solvation model calculations, we found that the widely used DFT model, B3LYP, failed to reproduce the experimentally observed trend of increasing binding affinity with the increasing length of the alkyl chain in the alcohol. In contrast, the recently developed M05-2X DFT model successfully reproduced this subtle trend. Analysis of the results indicated that multiple factors contribute to the differences in alcohol binding affinity: the H-bonding with Thr57 and Ser52 (4-5 kcal/mol per H-bond), the desolvation contribution (4-6 kcal/mol for alcohols and 8-10 kcal/mol for water), and the other noncovalent interaction (1.2 kcal/mol per CH(2) group of the alcohol alkyl chain). These results reveal the outstanding potential for using the M05-2X model in calculations of protein-substrate complexes where noncovalent interactions are important.

SUBMITTER: Ader L

PROVIDER: S-EPMC4396708 | biostudies-literature | 2010 Jul

REPOSITORIES: biostudies-literature

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Alcohol binding to the odorant binding protein LUSH: multiple factors affecting binding affinities.

Ader Lauren L Jones David N M DN Lin Hai H

Biochemistry 20100701 29

Density function theory (DFT) calculations have been carried out to investigate the binding of alcohols to the odorant binding protein LUSH from Drosophila melanogaster. LUSH is one of the few proteins known to bind to ethanol at physiologically relevant concentrations and where high-resolution structural information is available for the protein bound to alcohol at these concentrations. The structures of the LUSH-alcohol complexes identify a set of specific hydrogen-bonding interactions as criti ...[more]

PMID: 20550105

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Project description:A growing number of computational tools have been developed to accurately and rapidly predict the impact of amino acid mutations on protein-protein relative binding affinities. Such tools have many applications, for example, designing new drugs and studying evolutionary mechanisms. In the search for accuracy, many of these methods employ expensive yet rigorous molecular dynamics simulations. By contrast, non-rigorous methods use less exhaustive statistical mechanics, allowing for more efficient calculations. However, it is unclear if such methods retain enough accuracy to replace rigorous methods in binding affinity calculations. This trade-off between accuracy and computational expense makes it difficult to determine the best method for a particular system or study. Here, eight non-rigorous computational methods were assessed using eight antibody-antigen and eight non-antibody-antigen complexes for their ability to accurately predict relative binding affinities (ΔΔG) for 654 single mutations. In addition to assessing accuracy, we analyzed the CPU cost and performance for each method using a variety of physico-chemical structural features. This allowed us to posit scenarios in which each method may be best utilized. Most methods performed worse when applied to antibody-antigen complexes compared to non-antibody-antigen complexes. Rosetta-based JayZ and EasyE methods classified mutations as destabilizing (ΔΔG < -0.5 kcal/mol) with high (83-98%) accuracy and a relatively low computational cost for non-antibody-antigen complexes. Some of the most accurate results for antibody-antigen systems came from combining molecular dynamics with FoldX with a correlation coefficient (r) of 0.46, but this was also the most computationally expensive method. Overall, our results suggest these methods can be used to quickly and accurately predict stabilizing versus destabilizing mutations but are less accurate at predicting actual binding affinities. This study highlights the need for continued development of reliable, accessible, and reproducible methods for predicting binding affinities in antibody-antigen proteins and provides a recipe for using current methods.

Dataset Information

Alcohol binding to the odorant binding protein LUSH: multiple factors affecting binding affinities.

Publications

Alcohol binding to the odorant binding protein LUSH: multiple factors affecting binding affinities.

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