Literature DB >> 1631047

A robust and efficient automated docking algorithm for molecular recognition.

N Kasinos1, G A Lilley, N Subbarao, I Haneef.   

Abstract

A completely automated method is described for determining the most likely mode of binding of two (macro)molecules from the knowledge of their three-dimensional structures alone. The method is based on well-known graph theoretical techniques and has been used successfully to determine and rationalize the binding of a number of known macromolecular complexes. In this article we present results for a special case of the general molecular recognition problem--given the information concerning the particular atoms involved in the binding for one of the molecules, the algorithm can correctly identify the corresponding (contacting) atoms of the other molecule. The approach used can be easily extended to the general molecular recognition problem and requires the extraction of maximal common subgraphs. In these studies the docking of the macromolecules was achieved without the aid of computer graphics or other visual aids. The algorithm has been used to determine the correct mode of binding of a protein antigen to an antibody in approximately 100 min on a DEC micro VAX 3600.

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Year:  1992        PMID: 1631047     DOI: 10.1093/protein/5.1.69

Source DB:  PubMed          Journal:  Protein Eng        ISSN: 0269-2139


  4 in total

1.  Reaching the global minimum in docking simulations: a Monte Carlo energy minimization approach using Bezier splines.

Authors:  J Y Trosset; H A Scheraga
Journal:  Proc Natl Acad Sci U S A       Date:  1998-07-07       Impact factor: 11.205

2.  Flexible ligand docking using a genetic algorithm.

Authors:  C M Oshiro; I D Kuntz; J S Dixon
Journal:  J Comput Aided Mol Des       Date:  1995-04       Impact factor: 3.686

3.  Prediction of the three-dimensional structures of the nerve growth factor and epidermal growth factor binding proteins (kallikreins) and an hypothetical structure of the high molecular weight complex of epidermal growth factor with its binding protein.

Authors:  B Bax; M Blaber; G Ferguson; M J Sternberg; P H Walls
Journal:  Protein Sci       Date:  1993-08       Impact factor: 6.725

4.  Identification and energetic ranking of possible docking sites for pterin on dihydrofolate reductase.

Authors:  A A Bliznyuk; J E Gready
Journal:  J Comput Aided Mol Des       Date:  1998-07       Impact factor: 3.686

  4 in total

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