ISSN:
0192-8651
Keywords:
molecular similarity
;
molecular-field matching
;
conformational clustering
;
similarity space exploration
;
nonnucleoside HIV-1 reverse transcriptase inhibitors
;
Chemistry
;
Theoretical, Physical and Computational Chemistry
Source:
Wiley InterScience Backfile Collection 1832-2000
Topics:
Chemistry and Pharmacology
,
Computer Science
Notes:
This contribution presents the development and applicability of MIMIC, a molecular-field matching program for quantitatively evaluating the similarity between molecules, in a computationally feasible way and assesses the relative orientation that maximizes their similarity. In the present version one can deal with two types of molecular-field similarities, namely steric volume and electrostatic, as well as a combined similarity that takes into account a given contribution from each of them. Besides optimization of the relative spatial orientation by maximizing these similarities, MIMIC can perform exhaustive searches to locate a global similarity maximum candidate and the set of local similarity maxima closest to it. The high accuracy of the approach permits evaluation of the similarity space coverage of each similarity maximum. In addition, the study of the relationships among similarity spaces is proposed as a strategy to better understand the linkage between the different molecular overlay solutions obtained from the use of different molecular-field representations. Finally, calculation of the atomic contributions to the total molecular similarity provides a means for locating maximum similarity loci and for constructing pharmacophore patterns. The methodological bases and a detailed description of how they were implemented in MIMIC to handle molecular matchings between large systems is presented. All current features of the program were applied to a relative ligand-binding problem between two nonnucleoside HIV-1 reverse transcriptase inhibitors. © 1997 by John Wiley & Sons, Inc. J Comput Chem 18: 934-954, 1997
Additional Material:
10 Ill.
Type of Medium:
Electronic Resource
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