Literature DB >> 8360884

Three-dimensional quantitative structure-activity relationship of angiotesin-converting enzyme and thermolysin inhibitors. II. A comparison of CoMFA models incorporating molecular orbital fields and desolvation free energies based on active-analog and complementary-receptor-field alignment rules.

C L Waller1, G R Marshall.   

Abstract

The utility of comparative molecular field analysis (CoMFA), a three-dimensional Quantitative Structure-Activity Relationship (3-D QSAR) paradigm, as a tool to aid in the development of predictive models has been previously addressed (Depriest, S.D. et al., J. Am. Chem. Soc. 1993, in press). Although predictive correlations were obtained for angiotensin-converting and thermolysin inhibitors, certain inadequacies of the CoMFA technique were noted. Primarily, CoMFA steric and electrostatic fields alone do not fully characterize the zinc-ligand interaction. Previously, this was partially rectified by the inclusion of indicator variables into the QSAR table to designate the class of zinc-binding ligand. Recent advances in molecular modeling technology have allowed us to further address this limitation of the preceding study. Using molecular orbital fields derived from semiempirical calculations as additional descriptors in the QSAR table, predictive correlations were produced based on CoMFA and molecular orbital fields alone--indicator variables no longer being necessary. Arbitrary information concerning the alignment of molecules under study within the active-site introduces ambiguities into the CoMFA study. Crystallographic information detailing the binding mode of several thermolysin enzyme inhibitors has previously been used as a guide for the alignment of additional, noncrystallized, inhibitors. However, this process was complicated by the lack of parameters for zinc in the molecular mechanical force field. Therefore, zinc-ligand interactions were ignored during the standard minimization procedure. The use of field-fit minimization using complementary receptor fields as templates is presented as a possible solution to the problem. Predictive correlations were obtained from analyses based on this method of molecular alignment. The availability of crystallographic data for thermolysin enzyme-inhibitor complexes allowed for an alternate definition of the CoMFA region. Herein, promising results from analyses using actual receptor active-site atom probe atoms are presented.

Mesh:

Substances:

Year:  1993        PMID: 8360884     DOI: 10.1021/jm00068a017

Source DB:  PubMed          Journal:  J Med Chem        ISSN: 0022-2623            Impact factor:   7.446


  7 in total

1.  The continuous molecular fields approach to building 3D-QSAR models.

Authors:  Igor I Baskin; Nelly I Zhokhova
Journal:  J Comput Aided Mol Des       Date:  2013-05-30       Impact factor: 3.686

2.  Alignment of flexible molecules at their receptor site using 3D descriptors and Hi-PCA.

Authors:  A Berglund; M C De Rosa; S Wold
Journal:  J Comput Aided Mol Des       Date:  1997-11       Impact factor: 3.686

3.  Replacement of steric 6-12 potential-derived interaction energies by atom-based indicator variables in CoMFA leads to models of higher consistency.

Authors:  R T Kroemer; P Hecht
Journal:  J Comput Aided Mol Des       Date:  1995-06       Impact factor: 3.686

4.  A new procedure for improving the predictiveness of CoMFA models and its application to a set of dihydrofolate reductase inhibitors.

Authors:  R T Kroemer; P Hecht
Journal:  J Comput Aided Mol Des       Date:  1995-10       Impact factor: 3.686

5.  Deglycosylation, processing and crystallization of human testis angiotensin-converting enzyme.

Authors:  Kerry Gordon; Pierre Redelinghuys; Sylva L U Schwager; Mario R W Ehlers; Anastassios C Papageorgiou; Ramanathan Natesh; K Ravi Acharya; Edward D Sturrock
Journal:  Biochem J       Date:  2003-04-15       Impact factor: 3.857

6.  Comparative residue interaction analysis (CoRIA): a 3D-QSAR approach to explore the binding contributions of active site residues with ligands.

Authors:  Prasanna A Datar; Santosh A Khedkar; Alpeshkumar K Malde; Evans C Coutinho
Journal:  J Comput Aided Mol Des       Date:  2006-09-29       Impact factor: 4.179

7.  3D QSAR pharmacophore modeling, in silico screening, and density functional theory (DFT) approaches for identification of human chymase inhibitors.

Authors:  Mahreen Arooj; Sundarapandian Thangapandian; Shalini John; Swan Hwang; Jong Keun Park; Keun Woo Lee
Journal:  Int J Mol Sci       Date:  2011-12-12       Impact factor: 5.923

  7 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.