Literature DB >> 8877811

Molecular docking towards drug discovery.

D A Gschwend1, A C Good, I D Kuntz.   

Abstract

Fueled by advances in molecular structure determination, tools for structure-based drug design are proliferating rapidly. Lead discovery through searching of ligand databases with molecular docking techniques represents an attractive alternative to high-throughout random screening. The size of commercial databases imposes severe computational constraints on molecular docking, compromising the level of calculational detail permitted for each putative ligand. We describe alternative philosophies for docking which effectively address this challenge. With respect to the dynamic aspects of molecular recognition, these strategies lie along a spectrum of models bounded by the Lock-and-Key and Induced-Fit theories for ligand binding. We explore the potential of a rigid model in exploiting species specificity and of a tolerant model in predicting absolute ligand binding affinity. Current molecular docking methods are limited primarily by their ability to rank docked complexes; we therefore place particular emphasis on this aspect of the problem throughout our validation of docking strategies.

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Year:  1996        PMID: 8877811     DOI: 10.1002/(sici)1099-1352(199603)9:2<175::aid-jmr260>3.0.co;2-d

Source DB:  PubMed          Journal:  J Mol Recognit        ISSN: 0952-3499            Impact factor:   2.137


  34 in total

1.  The sensitivity of the results of molecular docking to induced fit effects: application to thrombin, thermolysin and neuraminidase.

Authors:  C W Murray; C A Baxter; A D Frenkel
Journal:  J Comput Aided Mol Des       Date:  1999-11       Impact factor: 3.686

2.  Deciphering common failures in molecular docking of ligand-protein complexes.

Authors:  G M Verkhivker; D Bouzida; D K Gehlhaar; P A Rejto; S Arthurs; A B Colson; S T Freer; V Larson; B A Luty; T Marrone; P W Rose
Journal:  J Comput Aided Mol Des       Date:  2000-11       Impact factor: 3.686

3.  MCDOCK: a Monte Carlo simulation approach to the molecular docking problem.

Authors:  M Liu; S Wang
Journal:  J Comput Aided Mol Des       Date:  1999-09       Impact factor: 3.686

4.  Statistical relationships among docking scores for different protein binding sites.

Authors:  R T Koehler; H O Villar
Journal:  J Comput Aided Mol Des       Date:  2000-01       Impact factor: 3.686

5.  Functional concerted motions in the bovine serum retinol-binding protein.

Authors:  P L Chau; D M van Aalten; R P Bywater; J B Findlay
Journal:  J Comput Aided Mol Des       Date:  1999-01       Impact factor: 3.686

6.  Protein ligand docking based on empirical method for binding affinity estimation.

Authors:  P Tao; L Lai
Journal:  J Comput Aided Mol Des       Date:  2001-05       Impact factor: 3.686

7.  In-silico screening using flexible ligand binding pockets: a molecular dynamics-based approach.

Authors:  Dakshanamurthy Sivanesan; Rajendram V Rajnarayanan; Jason Doherty; Nagarajan Pattabiraman
Journal:  J Comput Aided Mol Des       Date:  2005-04       Impact factor: 3.686

8.  Chemometric analysis of ligand receptor complementarity: identifying Complementary Ligands Based on Receptor Information (CoLiBRI).

Authors:  Scott Oloff; Shuxing Zhang; Nagamani Sukumar; Curt Breneman; Alexander Tropsha
Journal:  J Chem Inf Model       Date:  2006 Mar-Apr       Impact factor: 4.956

9.  Can we use docking and scoring for hit-to-lead optimization?

Authors:  Istvan J Enyedy; William J Egan
Journal:  J Comput Aided Mol Des       Date:  2008-01-09       Impact factor: 3.686

10.  An ab Initio structural model of a nucleoside permease predicts functionally important residues.

Authors:  Raquel Valdés; Shirin Arastu-Kapur; Scott M Landfear; Ujwal Shinde
Journal:  J Biol Chem       Date:  2009-05-08       Impact factor: 5.157

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