Literature DB >> 29435780

Protein-ligand interfaces are polarized: discovery of a strong trend for intermolecular hydrogen bonds to favor donors on the protein side with implications for predicting and designing ligand complexes.

Sebastian Raschka1, Alex J Wolf1, Joseph Bemister-Buffington1, Leslie A Kuhn2,3.   

Abstract

Understanding how proteins encode ligand specificity is fascinating and similar in importance to deciphering the genetic code. For protein-ligand recognition, the combination of an almost infinite variety of interfacial shapes and patterns of chemical groups makes the problem especially challenging. Here we analyze data across non-homologous proteins in complex with small biological ligands to address observations made in our inhibitor discovery projects: that proteins favor donating H-bonds to ligands and avoid using groups with both H-bond donor and acceptor capacity. The resulting clear and significant chemical group matching preferences elucidate the code for protein-native ligand binding, similar to the dominant patterns found in nucleic acid base-pairing. On average, 90% of the keto and carboxylate oxygens occurring in the biological ligands formed direct H-bonds to the protein. A two-fold preference was found for protein atoms to act as H-bond donors and ligand atoms to act as acceptors, and 76% of all intermolecular H-bonds involved an amine donor. Together, the tight chemical and geometric constraints associated with satisfying donor groups generate a hydrogen-bonding lock that can be matched only by ligands bearing the right acceptor-rich key. Measuring an index of H-bond preference based on the observed chemical trends proved sufficient to predict other protein-ligand complexes and can be used to guide molecular design. The resulting Hbind and Protein Recognition Index software packages are being made available for rigorously defining intermolecular H-bonds and measuring the extent to which H-bonding patterns in a given complex match the preference key.

Entities:  

Keywords:  Drug design; Interaction patterns; Ligand optimization; Lipinski’s Rule of 5; Protein–ligand recognition; Specificity determinants

Mesh:

Substances:

Year:  2018        PMID: 29435780     DOI: 10.1007/s10822-018-0105-2

Source DB:  PubMed          Journal:  J Comput Aided Mol Des        ISSN: 0920-654X            Impact factor:   3.686


  30 in total

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Authors:  Sunil K Panigrahi; Gautam R Desiraju
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Authors:  Maria I Zavodszky; Anjali Rohatgi; Jeffrey R Van Voorst; Honggao Yan; Leslie A Kuhn
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Review 9.  Humans as the world's greatest evolutionary force.

Authors:  S R Palumbi
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Authors:  Aqeel Ahmed; Richard D Smith; Jordan J Clark; James B Dunbar; Heather A Carlson
Journal:  Nucleic Acids Res       Date:  2014-11-06       Impact factor: 16.971

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