Literature DB >> 11688944

Evaluation of designed ligands by a multiple screening method: application to glycogen phosphorylase inhibitors constructed with a variety of approaches.

S S So1, M Karplus.   

Abstract

Glycogen phosphorylase (GP) is an important enzyme that regulates blood glucose level and a key therapeutic target for the treatment of type II diabetes. In this study, a number of potential GP inhibitors are designed with a variety of computational approaches. They include the applications of MCSS, LUDI and CoMFA to identify additional fragments that can be attached to existing lead molecules; the use of 2D and 3D similarity-based QSAR models (HQSAR and SMGNN) and of the LUDI program to identify novel molecules that may bind to the glucose binding site. The designed ligands are evaluated by a multiple screening method, which is a combination of commercial and in-house ligand-receptor binding affinity prediction programs used in a previous study (So and Karplus, J. Comp.-Aid. Mol. Des., 13 (1999), 243-258). Each method is used at an appropriate point in the screening, as determined by both the accuracy of the calculations and the computational cost. A comparison of the strengths and weaknesses of the ligand design approaches is made.

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Year:  2001        PMID: 11688944     DOI: 10.1023/a:1011945119287

Source DB:  PubMed          Journal:  J Comput Aided Mol Des        ISSN: 0920-654X            Impact factor:   3.686


  53 in total

1.  A comparative study of ligand-receptor complex binding affinity prediction methods based on glycogen phosphorylase inhibitors.

Authors:  S S So; M Karplus
Journal:  J Comput Aided Mol Des       Date:  1999-05       Impact factor: 3.686

2.  Novel approach to predicting P450-mediated drug metabolism: development of a combined protein and pharmacophore model for CYP2D6.

Authors:  M J de Groot; M J Ackland; V A Horne; A A Alex; B C Jones
Journal:  J Med Chem       Date:  1999-05-06       Impact factor: 7.446

Review 3.  Structure-based strategies for drug design and discovery.

Authors:  I D Kuntz
Journal:  Science       Date:  1992-08-21       Impact factor: 47.728

4.  Applications of neural networks in quantitative structure-activity relationships of dihydrofolate reductase inhibitors.

Authors:  T A Andrea; H Kalayeh
Journal:  J Med Chem       Date:  1991-09       Impact factor: 7.446

5.  Can we learn to distinguish between "drug-like" and "nondrug-like" molecules?

Authors:  A Ajay; W P Walters; M A Murcko
Journal:  J Med Chem       Date:  1998-08-27       Impact factor: 7.446

6.  Use of the multiple copy simultaneous search (MCSS) method to design a new class of picornavirus capsid binding drugs.

Authors:  D Joseph-McCarthy; J M Hogle; M Karplus
Journal:  Proteins       Date:  1997-09

7.  A new method for predicting binding affinity in computer-aided drug design.

Authors:  J Aqvist; C Medina; J E Samuelsson
Journal:  Protein Eng       Date:  1994-03

8.  SPROUT: recent developments in the de novo design of molecules.

Authors:  V J Gillet; W Newell; P Mata; G Myatt; S Sike; Z Zsoldos; A P Johnson
Journal:  J Chem Inf Comput Sci       Date:  1994 Jan-Feb

9.  Molecular dynamics simulation of protein denaturation: solvation of the hydrophobic cores and secondary structure of barnase.

Authors:  A Caflisch; M Karplus
Journal:  Proc Natl Acad Sci U S A       Date:  1994-03-01       Impact factor: 11.205

10.  Genetic neural networks for quantitative structure-activity relationships: improvements and application of benzodiazepine affinity for benzodiazepine/GABAA receptors.

Authors:  S S So; M Karplus
Journal:  J Med Chem       Date:  1996-12-20       Impact factor: 7.446

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  1 in total

1.  Multiple-step virtual screening using VSM-G: overview and validation of fast geometrical matching enrichment.

Authors:  Alexandre Beautrait; Vincent Leroux; Matthieu Chavent; Léo Ghemtio; Marie-Dominique Devignes; Malika Smaïl-Tabbone; Wensheng Cai; Xuegang Shao; Gilles Moreau; Peter Bladon; Jianhua Yao; Bernard Maigret
Journal:  J Mol Model       Date:  2008-01-03       Impact factor: 1.810

  1 in total

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