Three-dimensional quantitative structure-activity relationship (3D-QSAR) models for a novel class of piperazine-based stromelysin-1 (MMP-3) inhibitors: Applying a "divide and conquer" strategy

E. A. Amin, William Welsh

Research output: Contribution to journalArticle

47 Scopus citations

Abstract

Three-dimensional quantitative structure- activity relationship (3D-QSAR) models have been obtained using comparative molecular field analysis (CoMFA) for a novel series of piperazinebased matrix metalloproteinase inhibitors (MMPIs). The crystal structure of stromelysin-1 (MMP-3) was used to identify regions of the enzyme and inhibitors where steric and electrostatic effects correlate strongly with biological activity. A training set composed of a subset of inhibitors (#10-35), which differed only with regards to the substituent (n-alkyl, amide, carbamide and sulfonamide) on the piperazine distal nitrogen, yielded the most predictive CoMFA model, with r2 values of 0.592 (cross-validated) and 0.989 (conventional); this model was further validated using test compounds from two inhibitor subsets. Investigation of various ligand conformations, inhibitor subsets, alignment schemes and partial charge formalisms was required to obtain satisfactory models. The greatest success was achieved by incorporating inertial alignment together with manual adjustment of the enzyme-docked inhibitors to ensure complementarity between the inhibitors' substituent conformations and the structural characteristics of the MMP-3 S1-S2′ binding pockets. Key insights into the structure- activity relationship (SAR) obtained from this analysis for this inhibitor set are in agreement with experimentally observed data on stromelysin-1 biological activity and binding-site topology. In particular, the present study sheds new light on the steric and electrostatic requirements for ligand binding to the partly solvent-exposed S1-S2′ area.

Original languageEnglish (US)
Pages (from-to)3849-3855
Number of pages7
JournalJournal of Medicinal Chemistry
Volume44
Issue number23
DOIs
StatePublished - Nov 8 2001

All Science Journal Classification (ASJC) codes

  • Molecular Medicine
  • Drug Discovery

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