Literature DB >> 8648645

X-SITE: use of empirically derived atomic packing preferences to identify favourable interaction regions in the binding sites of proteins.

R A Laskowski1, J M Thornton, C Humblet, J Singh.   

Abstract

A new empirically based method for predicting favourable interaction regions within the binding sites of proteins is presented. The method uses spatial distributions of atomic contact preferences derived from a non-homologous dataset of 83 high-resolution protein structures. The contact preferences are obtained for 26 different atom types relative to 163 different types of three-atom fragments. Each fragment consists of a triplet of bonded atoms, 1-2-3, which defines a reference frame for the three-dimensional distributions. In this way, directional, as well as distance, information is retained. Once derived, the distribution can be applied in a predictive manner. Given a protein's binding site, each distribution is transformed on to the three-atom fragments of the constituent residues and, when combined, can identify the favourable interaction regions for each different atom type. These predicted regions can then form the basis either for the modification of known inhibitors or for the search and design of new ones. Five known protein-ligand complexes are used to demonstrate the validity and usefulness of the approach. The results show that the method provides a powerful tool both in understanding how a given ligand exploits the interactions available to it in an active site and in helping to design improved, or novel, protein ligands.

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Year:  1996        PMID: 8648645     DOI: 10.1006/jmbi.1996.0311

Source DB:  PubMed          Journal:  J Mol Biol        ISSN: 0022-2836            Impact factor:   5.469


  14 in total

1.  Selective inhibition of 6-phosphogluconate dehydrogenase from Trypanosoma brucei.

Authors:  M Bertelli; E El-Bastawissy; M H Knaggs; M P Barrett; S Hanau; I H Gilbert
Journal:  J Comput Aided Mol Des       Date:  2001-05       Impact factor: 3.686

2.  Flexible docking under pharmacophore type constraints.

Authors:  Sally A Hindle; Matthias Rarey; Christian Buning; Thomas Lengaue
Journal:  J Comput Aided Mol Des       Date:  2002-02       Impact factor: 3.686

3.  A Bayesian molecular interaction library.

Authors:  Ville-Veikko Rantanen; Mats Gyllenberg; Timo Koski; Mark S Johnson
Journal:  J Comput Aided Mol Des       Date:  2003-07       Impact factor: 3.686

4.  Gaussian mapping of chemical fragments in ligand binding sites.

Authors:  Kun Wang; Marta Murcia; Pere Constans; Carlos Pérez; Angel R Ortiz
Journal:  J Comput Aided Mol Des       Date:  2004-02       Impact factor: 3.686

5.  RNA base-amino acid interaction strengths derived from structures and sequences.

Authors:  B Lustig; S Arora; R L Jernigan
Journal:  Nucleic Acids Res       Date:  1997-07-01       Impact factor: 16.971

6.  Simple knowledge-based descriptors to predict protein-ligand interactions. methodology and validation.

Authors:  M L Verdonk; G Klebe
Journal:  J Comput Aided Mol Des       Date:  2000-11       Impact factor: 3.686

7.  Rationalizing fragment based drug discovery for BACE1: insights from FB-QSAR, FB-QSSR, multi objective (MO-QSPR) and MIF studies.

Authors:  Prabu Manoharan; R S K Vijayan; Nanda Ghoshal
Journal:  J Comput Aided Mol Des       Date:  2010-08-26       Impact factor: 3.686

8.  Minimal pharmacophoric elements and fragment hopping, an approach directed at molecular diversity and isozyme selectivity. Design of selective neuronal nitric oxide synthase inhibitors.

Authors:  Haitao Ji; Benjamin Z Stanton; Jotaro Igarashi; Huiying Li; Pavel Martásek; Linda J Roman; Thomas L Poulos; Richard B Silverman
Journal:  J Am Chem Soc       Date:  2008-03-06       Impact factor: 15.419

9.  SITEHOUND-web: a server for ligand binding site identification in protein structures.

Authors:  Marylens Hernandez; Dario Ghersi; Roberto Sanchez
Journal:  Nucleic Acids Res       Date:  2009-04-26       Impact factor: 16.971

10.  Prediction of carbohydrate binding sites on protein surfaces with 3-dimensional probability density distributions of interacting atoms.

Authors:  Keng-Chang Tsai; Jhih-Wei Jian; Ei-Wen Yang; Po-Chiang Hsu; Hung-Pin Peng; Ching-Tai Chen; Jun-Bo Chen; Jeng-Yih Chang; Wen-Lian Hsu; An-Suei Yang
Journal:  PLoS One       Date:  2012-07-25       Impact factor: 3.240

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