Literature DB >> 8045288

Amino acid preferences at protein binding sites.

H O Villar1, L M Kauvar.   

Abstract

An analysis of the amino acid distribution at protein binding sites was carried out using 50 diverse macromolecules for which crystallographic data with a bound ligand are available. The purpose of this study is to determine whether differential trends in amino acid distributions exist at binding sites compared to other regions in the proteins. The results indicate that some residues, particularly Arg, His, Trp and Tyr are substantially more frequent at the binding sites, compared to the number of times these residues are present in proteins generally. These effects go beyond the differences seen comparing surface exposed residues to bulk protein. The resemblance in the residue utilization at the binding sites of unrelated proteins restricts the possible types of interactions with ligands, possibly accounting for the repetition of substructural motifs in chemicals with diverse pharmacological action. Further, the use of these diagnostic features may permit identification of ligand binding pockets in a protein structure deduced from sequence information or from data in the absence of a ligand. Some of these findings complement and extend previously described trends for antibody binding sites.

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Year:  1994        PMID: 8045288     DOI: 10.1016/0014-5793(94)00648-2

Source DB:  PubMed          Journal:  FEBS Lett        ISSN: 0014-5793            Impact factor:   4.124


  16 in total

1.  Arginine mutations in antibody complementarity-determining regions display context-dependent affinity/specificity trade-offs.

Authors:  Kathryn E Tiller; Lijuan Li; Sandeep Kumar; Mark C Julian; Shekhar Garde; Peter M Tessier
Journal:  J Biol Chem       Date:  2017-08-04       Impact factor: 5.157

2.  Protein evolution: intrinsic preferences in peptide bond formation: a computational and experimental analysis.

Authors:  Subramania Ranganathan; Dinabandhu Kundu; S D Vudayagiri
Journal:  J Biosci       Date:  2003-12       Impact factor: 1.826

Review 3.  Redox platforms in cancer drug discovery and development.

Authors:  Kenneth D Tew; Danyelle M Townsend
Journal:  Curr Opin Chem Biol       Date:  2010-11-11       Impact factor: 8.822

4.  Exploring functional roles of multibinding protein interfaces.

Authors:  Manoj Tyagi; Benjamin A Shoemaker; Stephen H Bryant; Anna R Panchenko
Journal:  Protein Sci       Date:  2009-08       Impact factor: 6.725

5.  Clonal Deletion Prunes but Does Not Eliminate Self-Specific αβ CD8(+) T Lymphocytes.

Authors:  Wong Yu; Ning Jiang; Peter J R Ebert; Brian A Kidd; Sabina Müller; Peder J Lund; Jeremy Juang; Keishi Adachi; Tiffany Tse; Michael E Birnbaum; Evan W Newell; Darrell M Wilson; Gijsbert M Grotenbreg; Salvatore Valitutti; Stephen R Quake; Mark M Davis
Journal:  Immunity       Date:  2015-05-19       Impact factor: 31.745

Review 6.  The importance of being tyrosine: lessons in molecular recognition from minimalist synthetic binding proteins.

Authors:  Shohei Koide; Sachdev S Sidhu
Journal:  ACS Chem Biol       Date:  2009-05-15       Impact factor: 5.100

Review 7.  Functional protein nanostructures: a chemical toolbox.

Authors:  Seah Ling Kuan; Fernando R G Bergamini; Tanja Weil
Journal:  Chem Soc Rev       Date:  2018-11-19       Impact factor: 54.564

8.  Synthetic antibodies from a four-amino-acid code: a dominant role for tyrosine in antigen recognition.

Authors:  Frederic A Fellouse; Christian Wiesmann; Sachdev S Sidhu
Journal:  Proc Natl Acad Sci U S A       Date:  2004-08-11       Impact factor: 11.205

9.  Molecular docking studies of natural immunomodulators indicate their interactions with the CD40L of CD40/CD40L pathway and CSF1R kinase domain of microglia.

Authors:  Shashank Kumar Maurya; Rajnikant Mishra
Journal:  J Mol Model       Date:  2022-03-24       Impact factor: 1.810

10.  Identification of binding pockets in protein structures using a knowledge-based potential derived from local structural similarities.

Authors:  Valerio Bianchi; Pier Federico Gherardini; Manuela Helmer-Citterich; Gabriele Ausiello
Journal:  BMC Bioinformatics       Date:  2012-03-28       Impact factor: 3.169

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