Literature DB >> 16376828

Predicting protein druggability.

Philip J Hajduk1, Jeffrey R Huth, Christin Tse.   

Abstract

The ability to predict whether a particular protein can bind with high affinity and specificity to small, drug-like compounds based solely on its 3D structure has been a longstanding goal of structural biologists and computational scientists. The promise is that an accurate prediction of protein druggability can capitalize on the huge investments already made in structural genomics initiatives by identifying highly druggable proteins and using this information in target identification and validation campaigns. Here we discuss the potential utility of tools that characterize protein targets and describe strategies for the optimal integration of protein druggability data with bioinformatic approaches to target selection.

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Year:  2005        PMID: 16376828     DOI: 10.1016/S1359-6446(05)03624-X

Source DB:  PubMed          Journal:  Drug Discov Today        ISSN: 1359-6446            Impact factor:   7.851


  76 in total

Review 1.  Finding the sweet spot: the role of nature and nurture in medicinal chemistry.

Authors:  Michael M Hann; György M Keserü
Journal:  Nat Rev Drug Discov       Date:  2012-04-30       Impact factor: 84.694

Review 2.  Target assessment for antiparasitic drug discovery.

Authors:  Julie A Frearson; Paul G Wyatt; Ian H Gilbert; Alan H Fairlamb
Journal:  Trends Parasitol       Date:  2007-10-24

3.  Design of protein membrane interaction inhibitors by virtual ligand screening, proof of concept with the C2 domain of factor V.

Authors:  Kenneth Segers; Olivier Sperandio; Markus Sack; Rainer Fischer; Maria A Miteva; Jan Rosing; Gerry A F Nicolaes; Bruno O Villoutreix
Journal:  Proc Natl Acad Sci U S A       Date:  2007-07-23       Impact factor: 11.205

4.  Lessons for fragment library design: analysis of output from multiple screening campaigns.

Authors:  I-Jen Chen; Roderick E Hubbard
Journal:  J Comput Aided Mol Des       Date:  2009-06-03       Impact factor: 3.686

Review 5.  Computational methods in drug discovery.

Authors:  Gregory Sliwoski; Sandeepkumar Kothiwale; Jens Meiler; Edward W Lowe
Journal:  Pharmacol Rev       Date:  2013-12-31       Impact factor: 25.468

6.  2P2I HUNTER: a tool for filtering orthosteric protein-protein interaction modulators via a dedicated support vector machine.

Authors:  Véronique Hamon; Raphael Bourgeas; Pierre Ducrot; Isabelle Theret; Laura Xuereb; Marie Jeanne Basse; Jean Michel Brunel; Sebastien Combes; Xavier Morelli; Philippe Roche
Journal:  J R Soc Interface       Date:  2013-11-06       Impact factor: 4.118

7.  Using protein-ligand docking to assess the chemical tractability of inhibiting a protein target.

Authors:  Richard A Ward
Journal:  J Mol Model       Date:  2010-03-11       Impact factor: 1.810

Review 8.  Application of NMR and molecular docking in structure-based drug discovery.

Authors:  Jaime L Stark; Robert Powers
Journal:  Top Curr Chem       Date:  2012

9.  Design of a multi-purpose fragment screening library using molecular complexity and orthogonal diversity metrics.

Authors:  Wan F Lau; Jane M Withka; David Hepworth; Thomas V Magee; Yuhua J Du; Gregory A Bakken; Michael D Miller; Zachary S Hendsch; Venkataraman Thanabal; Steve A Kolodziej; Li Xing; Qiyue Hu; Lakshmi S Narasimhan; Robert Love; Maura E Charlton; Samantha Hughes; Willem P van Hoorn; James E Mills
Journal:  J Comput Aided Mol Des       Date:  2011-05-21       Impact factor: 3.686

10.  Differences between high- and low-affinity complexes of enzymes and nonenzymes.

Authors:  Heather A Carlson; Richard D Smith; Nickolay A Khazanov; Paul D Kirchhoff; James B Dunbar; Mark L Benson
Journal:  J Med Chem       Date:  2008-10-01       Impact factor: 7.446

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