Literature DB >> 22316151

Computational drug design targeting protein-protein interactions.

Rachelle J Bienstock1.   

Abstract

Novel discoveries in molecular disease pathways within the cell, combined with increasing information regarding protein binding partners has lead to a new approach in drug discovery. There is interest in designing drugs to modulate protein-protein interactions as opposed to solely targeting the catalytic active site within a single enzyme or protein. There are many challenges in this new approach to drug discovery, particularly since the protein-protein interface has a larger surface area, can comprise a discontinuous epitope, and is more amorphous and less well defined than the typical drug design target, a small contained enzyme-binding pocket. Computational methods to predict modes of protein-protein interaction, as well as protein interface hot spots, have garnered significant interest, in order to facilitate the development of drugs to successfully disrupt and inhibit protein-protein interactions. This review summarizes some current methods available for computational protein-protein docking, as well as tabulating some examples of the successful design of antagonists and small molecule inhibitors for protein-protein interactions. Several of these drugs are now beginning to appear in the clinic.

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Year:  2012        PMID: 22316151     DOI: 10.2174/138161212799436449

Source DB:  PubMed          Journal:  Curr Pharm Des        ISSN: 1381-6128            Impact factor:   3.116


  19 in total

Review 1.  Integrative systems and synthetic biology of cell-matrix adhesion sites.

Authors:  Eli Zamir
Journal:  Cell Adh Migr       Date:  2016-02-06       Impact factor: 3.405

Review 2.  Small molecules, big targets: drug discovery faces the protein-protein interaction challenge.

Authors:  Duncan E Scott; Andrew R Bayly; Chris Abell; John Skidmore
Journal:  Nat Rev Drug Discov       Date:  2016-04-11       Impact factor: 84.694

3.  BP-Dock: a flexible docking scheme for exploring protein-ligand interactions based on unbound structures.

Authors:  Ashini Bolia; Z Nevin Gerek; S Banu Ozkan
Journal:  J Chem Inf Model       Date:  2014-03-04       Impact factor: 4.956

Review 4.  Cancer genome landscapes.

Authors:  Bert Vogelstein; Nickolas Papadopoulos; Victor E Velculescu; Shibin Zhou; Luis A Diaz; Kenneth W Kinzler
Journal:  Science       Date:  2013-03-29       Impact factor: 47.728

5.  Correlating protein hot spot surface analysis using ProBiS with simulated free energies of protein-protein interfacial residues.

Authors:  Nejc Carl; Milan Hodošček; Blaž Vehar; Janez Konc; Bernard R Brooks; Dušanka Janežič
Journal:  J Chem Inf Model       Date:  2012-10-08       Impact factor: 4.956

6.  2P2Idb: a structural database dedicated to orthosteric modulation of protein-protein interactions.

Authors:  Marie Jeanne Basse; Stéphane Betzi; Raphaël Bourgeas; Sofia Bouzidi; Bernard Chetrit; Véronique Hamon; Xavier Morelli; Philippe Roche
Journal:  Nucleic Acids Res       Date:  2012-11-30       Impact factor: 16.971

7.  Insights into the Interactions of Fasciola hepatica Cathepsin L3 with a Substrate and Potential Novel Inhibitors through In Silico Approaches.

Authors:  Lilian Hernández Alvarez; Dany Naranjo Feliciano; Jorge Enrique Hernández González; R O Soares; Rosemberg de Oliveira Soares; Diego Enry Barreto Gomes; Pedro Geraldo Pascutti
Journal:  PLoS Negl Trop Dis       Date:  2015-05-15

Review 8.  One cannot rule them all: Are bacterial toxins-antitoxins druggable?

Authors:  Wai Ting Chan; Dolors Balsa; Manuel Espinosa
Journal:  FEMS Microbiol Rev       Date:  2015-03-21       Impact factor: 16.408

9.  A systems biology-based investigation into the pharmacological mechanisms of wu tou tang acting on rheumatoid arthritis by integrating network analysis.

Authors:  Yanqiong Zhang; Danhua Wang; Shufang Tan; Haiyu Xu; Chunfang Liu; Na Lin
Journal:  Evid Based Complement Alternat Med       Date:  2013-03-28       Impact factor: 2.629

Review 10.  Rational prediction with molecular dynamics for hit identification.

Authors:  Sara E Nichols; Robert V Swift; Rommie E Amaro
Journal:  Curr Top Med Chem       Date:  2012       Impact factor: 3.295

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