Literature DB >> 18366021

Energy-based prediction of amino acid-nucleotide base recognition.

Anna Marabotti1, Francesca Spyrakis, Angelo Facchiano, Pietro Cozzini, Saverio Alberti, Glen E Kellogg, Andrea Mozzarelli.   

Abstract

Despite decades of investigations, it is not yet clear whether there are rules dictating the specificity of the interaction between amino acids and nucleotide bases. This issue was addressed by determining, in a dataset consisting of 100 high-resolution protein-DNA structures, the frequency and energy of interaction between each amino acid and base, and the energetics of water-mediated interactions. The analysis was carried out using HINT, a non-Newtonian force field encoding both enthalpic and entropic contributions, and Rank, a geometry-based tool for evaluating hydrogen bond interactions. A frequency- and energy-based preferential interaction of Arg and Lys with G, Asp and Glu with C, and Asn and Gln with A was found. Not only favorable, but also unfavorable contacts were found to be conserved. Water-mediated interactions strongly increase the probability of Thr-A, Lys-A, and Lys-C contacts. The frequency, interaction energy, and water enhancement factors associated with each amino acid-base pair were used to predict the base triplet recognized by the helix motif in 45 zinc fingers, which represents an ideal case study for the analysis of one-to-one amino acid-base pair contacts. The model correctly predicted 70.4% of 135 amino acid-base pairs, and, by weighting the energetic relevance of each amino acid-base pair to the overall recognition energy, it yielded a prediction rate of 89.7%. (c) 2008 Wiley Periodicals, Inc.

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Year:  2008        PMID: 18366021     DOI: 10.1002/jcc.20954

Source DB:  PubMed          Journal:  J Comput Chem        ISSN: 0192-8651            Impact factor:   3.376


  19 in total

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3.  Direct Comparison of Amino Acid and Salt Interactions with Double-Stranded and Single-Stranded DNA from Explicit-Solvent Molecular Dynamics Simulations.

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4.  Comparative Analysis of the IclR-Family of Bacterial Transcription Factors and Their DNA-Binding Motifs: Structure, Positioning, Co-Evolution, Regulon Content.

Authors:  Inna A Suvorova; Mikhail S Gelfand
Journal:  Front Microbiol       Date:  2021-06-10       Impact factor: 5.640

5.  Predicting the molecular interactions of CRIP1a-cannabinoid 1 receptor with integrated molecular modeling approaches.

Authors:  Mostafa H Ahmed; Glen E Kellogg; Dana E Selley; Martin K Safo; Yan Zhang
Journal:  Bioorg Med Chem Lett       Date:  2014-01-08       Impact factor: 2.823

6.  GntR Family of Bacterial Transcription Factors and Their DNA Binding Motifs: Structure, Positioning and Co-Evolution.

Authors:  Inna A Suvorova; Yuri D Korostelev; Mikhail S Gelfand
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7.  Design of O-acetylserine sulfhydrylase inhibitors by mimicking nature.

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8.  Web application for studying the free energy of binding and protonation states of protein-ligand complexes based on HINT.

Authors:  Alexander S Bayden; Micaela Fornabaio; J Neel Scarsdale; Glen E Kellogg
Journal:  J Comput Aided Mol Des       Date:  2009-06-25       Impact factor: 3.686

9.  Biological characterization of 3-(2-amino-ethyl)-5-[3-(4-butoxyl-phenyl)-propylidene]-thiazolidine-2,4-dione (K145) as a selective sphingosine kinase-2 inhibitor and anticancer agent.

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Journal:  PLoS One       Date:  2013-02-20       Impact factor: 3.240

10.  Applying an empirical hydropathic forcefield in refinement may improve low-resolution protein X-ray crystal structures.

Authors:  Vishal N Koparde; J Neel Scarsdale; Glen E Kellogg
Journal:  PLoS One       Date:  2011-01-05       Impact factor: 3.240

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