Literature DB >> 11008888

Classical QSAR and comparative molecular field analyses of the host-guest interaction of organic molecules with cyclodextrins.

T Suzuki1, M Ishida, W M Fabian.   

Abstract

The application of classical QSAR and molecular modeling analysis using Comparative Molecular Field Analysis (CoMFA) to the complexation of some natural and modified cyclodextrins (CDs) with guest molecules was examined. For 1:1 complexation systems between natural beta-CD, modified alpha-, beta-, and gamma-CD that bear one p-(dimethylamino)benzoyl (DMAB) moiety (DMAB-alpha-, beta-, and gamma-CDs) and guest molecules of widely varying chemical structures and properties, the binding constants of the complexes were successfully fitted using multiple linear regression (MLR) with hydrophobic descriptor log P (the partition coefficient between 1-octanol and water phases) and molecular connectivity indices. A non-linear dependency of binding constants on the zero-th and/or first order molecular connectivity index as a measure of size becomes apparent. The modeling performance of the CoMFA models with steric/electrostatic fields to DMAB-alpha- and beta-CD systems was comparable to those of MLR models. However, statistically significant CoMFA models for gamma-CD systems which have higher conformational flexibility of the ring could not be obtained. The CoMFA models obtained for DMAB-alpha- and beta-CD systems showed that the predominant effects were steric for the DMAB-alpha-CD system and electrostatic for the DMAB-beta-CD system, respectively.

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Year:  2000        PMID: 11008888     DOI: 10.1023/a:1008103122313

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


  9 in total

1.  Applications of Computational Chemistry to the Study of Cyclodextrins.

Authors:  Kenny B. Lipkowitz
Journal:  Chem Rev       Date:  1998-07-30       Impact factor: 60.622

2.  The Stability of Cyclodextrin Complexes in Solution.

Authors:  Kenneth A. Connors
Journal:  Chem Rev       Date:  1997-08-05       Impact factor: 60.622

3.  Comparative molecular field analysis (CoMFA). 1. Effect of shape on binding of steroids to carrier proteins.

Authors:  R D Cramer; D E Patterson; J D Bunce
Journal:  J Am Chem Soc       Date:  1988-08-01       Impact factor: 15.419

4.  Development of an automatic estimation system for both the partition coefficient and aqueous solubility.

Authors:  T Suzuki
Journal:  J Comput Aided Mol Des       Date:  1991-04       Impact factor: 3.686

5.  Conformational flexibility and receptor interaction.

Authors:  L H Janssen
Journal:  Bioorg Med Chem       Date:  1998-06       Impact factor: 3.641

6.  Evaluation of quantitative structure-activity relationship methods for large-scale prediction of chemicals binding to the estrogen receptor.

Authors:  W Tong; D R Lowis; R Perkins; Y Chen; W J Welsh; D W Goddette; T W Heritage; D M Sheehan
Journal:  J Chem Inf Comput Sci       Date:  1998 Jul-Aug

Review 7.  MOPAC: a semiempirical molecular orbital program.

Authors:  J J Stewart
Journal:  J Comput Aided Mol Des       Date:  1990-03       Impact factor: 3.686

Review 8.  Three-dimensional structure-activity relationships.

Authors:  G R Marshall; R D Cramer
Journal:  Trends Pharmacol Sci       Date:  1988-08       Impact factor: 14.819

9.  Molecular similarity indices in a comparative analysis (CoMSIA) of drug molecules to correlate and predict their biological activity.

Authors:  G Klebe; U Abraham; T Mietzner
Journal:  J Med Chem       Date:  1994-11-25       Impact factor: 7.446

  9 in total
  4 in total

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4.  Predicting complexation performance between cyclodextrins and guest molecules by integrated machine learning and molecular modeling techniques.

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  4 in total

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