Literature DB >> 14713191

A novel scoring function for molecular docking.

A E Muryshev1, D N Tarasov, A V Butygin, O Yu Butygina, A B Aleksandrov, S M Nikitin.   

Abstract

We present a novel scoring function for docking of small molecules to protein binding sites. The scoring function is based on a combination of two main approaches used in the field, the empirical and knowledge-based approaches. To calibrate the scoring function we used an iterative procedure in which a ligand's position and its score were determined self-consistently at each iteration. The scoring function demonstrated superiority in prediction of ligand positions in docking tests against the commonly used Dock, FlexX and Gold docking programs. It also demonstrated good accuracy of binding affinity prediction for the docked ligands.

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Year:  2003        PMID: 14713191     DOI: 10.1023/b:jcam.0000005766.95985.7e

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


  13 in total

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2.  A general and fast scoring function for protein-ligand interactions: a simplified potential approach.

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Review 5.  Structure-based virtual screening: an overview.

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Review 6.  A review of protein-small molecule docking methods.

Authors:  R D Taylor; P J Jewsbury; J W Essex
Journal:  J Comput Aided Mol Des       Date:  2002-03       Impact factor: 3.686

7.  Scoring noncovalent protein-ligand interactions: a continuous differentiable function tuned to compute binding affinities.

Authors:  A N Jain
Journal:  J Comput Aided Mol Des       Date:  1996-10       Impact factor: 3.686

8.  Development and validation of a genetic algorithm for flexible docking.

Authors:  G Jones; P Willett; R C Glen; A R Leach; R Taylor
Journal:  J Mol Biol       Date:  1997-04-04       Impact factor: 5.469

9.  The development of a simple empirical scoring function to estimate the binding constant for a protein-ligand complex of known three-dimensional structure.

Authors:  H J Böhm
Journal:  J Comput Aided Mol Des       Date:  1994-06       Impact factor: 3.686

10.  A geometric approach to macromolecule-ligand interactions.

Authors:  I D Kuntz; J M Blaney; S J Oatley; R Langridge; T E Ferrin
Journal:  J Mol Biol       Date:  1982-10-25       Impact factor: 5.469

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6.  HIGA: A Running History Information Guided Genetic Algorithm for Protein-Ligand Docking.

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