Dataset Information

Census of halide-binding sites in protein structures.

ABSTRACT: MOTIVATION:Halides are negatively charged ions of halogens, forming fluorides (F-), chlorides (Cl-), bromides (Br-) and iodides (I-). These anions are quite reactive and interact both specifically and non-specifically with proteins. Despite their ubiquitous presence and important roles in protein function, little is known about the preferences of halides binding to proteins. To address this problem, we performed the analysis of halide-protein interactions, based on the entries in the Protein Data Bank. RESULTS:We have compiled a pipeline for the quick analysis of halide-binding sites in proteins using the available software. Our analysis revealed that all of halides are strongly attracted by the guanidinium moiety of arginine side chains, however, there are also certain preferences among halides for other partners. Furthermore, there is a certain preference for coordination numbers in the binding sites, with a correlation between coordination numbers and amino acid composition. This pipeline can be used as a tool for the analysis of specific halide-protein interactions and assist phasing experiments relying on halides as anomalous scatters. AVAILABILITY AND IMPLEMENTATION:All data described in this article can be reproduced via complied pipeline published at https://github.com/rostkick/Halide_sites/blob/master/README.md. SUPPLEMENTARY INFORMATION:Supplementary data are available at Bioinformatics online.

SUBMITTER: Skitchenko RK

PROVIDER: S-EPMC7214031 | biostudies-literature | 2020 May

REPOSITORIES: biostudies-literature

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Census of halide-binding sites in protein structures.

Skitchenko Rostislav K RK Usoltsev Dmitrii D Uspenskaya Mayya M Kajava Andrey V AV Guskov Albert A

Bioinformatics (Oxford, England) 20200501 10

<h4>Motivation</h4>Halides are negatively charged ions of halogens, forming fluorides (F-), chlorides (Cl-), bromides (Br-) and iodides (I-). These anions are quite reactive and interact both specifically and non-specifically with proteins. Despite their ubiquitous presence and important roles in protein function, little is known about the preferences of halides binding to proteins. To address this problem, we performed the analysis of halide-protein interactions, based on the entries in the Pro ...[more]

PMID: 32022861

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Project description:BACKGROUND: Recognizing similarities and deriving relationships among protein molecules is a fundamental requirement in present-day biology. Similarities can be present at various levels which can be detected through comparison of protein sequences or their structural folds. In some cases similarities obscure at these levels could be present merely in the substructures at their binding sites. Inferring functional similarities between protein molecules by comparing their binding sites is still largely exploratory and not as yet a routine protocol. One of the main reasons for this is the limitation in the choice of appropriate analytical tools that can compare binding sites with high sensitivity. To benefit from the enormous amount of structural data that is being rapidly accumulated, it is essential to have high throughput tools that enable large scale binding site comparison. RESULTS: Here we present a new algorithm PocketMatch for comparison of binding sites in a frame invariant manner. Each binding site is represented by 90 lists of sorted distances capturing shape and chemical nature of the site. The sorted arrays are then aligned using an incremental alignment method and scored to obtain PMScores for pairs of sites. A comprehensive sensitivity analysis and an extensive validation of the algorithm have been carried out. A comparison with other site matching algorithms is also presented. Perturbation studies where the geometry of a given site was retained but the residue types were changed randomly, indicated that chance similarities were virtually non-existent. Our analysis also demonstrates that shape information alone is insufficient to discriminate between diverse binding sites, unless combined with chemical nature of amino acids. CONCLUSION: A new algorithm has been developed to compare binding sites in accurate, efficient and high-throughput manner. Though the representation used is conceptually simplistic, we demonstrate that along with the new alignment strategy used, it is sufficient to enable binding comparison with high sensitivity. Novel methodology has also been presented for validating the algorithm for accuracy and sensitivity with respect to geometry and chemical nature of the site. The method is also fast and takes about 1/250th second for one comparison on a single processor. A parallel version on BlueGene has also been implemented.

Dataset Information

Census of halide-binding sites in protein structures.

Publications

Census of halide-binding sites in protein structures.

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