A Structure-guided Approach for Protein Pocket Modeling and Affinity Prediction

Binding affinity prediction is frequently addressed using computational models constructed solely with molecular structure and activity data. We present a hybrid structure-guided strategy that combines molecular similarity, docking, and multiple-instance learning such that information from protein structures can be used to inform models of structure–activity relationships. The Surflex-QMOD approach has been shown to produce accurate … Continued

Molecular Docking and 3D-quantitative Structure Activity Relationship Analyses of Peptidyl Vinyl Sulfones: Plasmodium Falciparum Cysteine Proteases Inhibitors

Comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) based on three-dimensional quantitative structure-activity relationship (3D-QSAR) studies were conducted on a series (39 molecules) of peptidyl vinyl sulfone derivatives as potential Plasmodium Falciparum cysteine proteases inhibitors. Two different methods of alignment were employed: (i) a receptor-docked alignment derived from the structure-based docking … Continued

Rethinking 3D-QSAR

The average error of pIC50 prediction reported for 140 structures in make-and-test applications of topomer CoMFA by four discovery organizations is 0.5. This remarkable accuracy can be understood to result from a topomer pose’s goal of generating field differences only at lattice intersections adjacent to intended structural change.

Theoretical Studies on the Interaction of Partial Agonists with the 5-HT2A Receptor

A series of 51 5-HT(2A) partial agonistic arylethylamines (primary or benzylamines) from different structural classes (indoles, methoxybenzenes, quinazolinediones) was investigated by fragment regression analysis (FRA), docking and 3D-QSAR approaches. The data, pEC50 values and intrinsic activities (Emax) on rat arteries, show high variability of pEC50 from 4 to 10 and of Emax from 15 to … Continued

3D-QSAR Studies and Molecular Docking on [5-(4-amino-1H-benzoimidazol-2-yl)-furan-2-yl]-phosphonic Acid Derivatives as Fructose-1,6-biphophatase Inhibitors

Fructose-1,6-biphophatase has been regarded as a novel therapeutic target for the treatment of type 2 diabetes mellitus (T2DM). 3D-QSAR and docking studies were performed on a series of [5-(4-amino-1H-benzoimidazol-2-yl)-furan-2-yl]-phosphonic acid derivatives as fructose-1,6-biphophatase inhibitors. The CoMFA and CoMSIA models using thirty-seven molecules in the training set gave rcv2 values of 0.614 and 0.598, r2 values … Continued

QMOD: Physically Meaningful QSAR

Computational methods for predicting ligand affinity where no protein structure is known generally take the form of regression analysis based on molecular features that have only a tangential relationship to a protein/ligand binding event. Such methods have utility in retrospective rationalization of activity patterns of substituents on a common scaffold, but are limited when either … Continued

Fragment-guided Approach to Incorporating Structural Information into a CoMFA Study: BACE-1 as an Example

Alzheimer’s disease is an ultimately fatal neurodegenerative disease, and BACE-1 has become an attractive validated target for its therapy, with more than a hundred crystal structures deposited in the PDB. In the present study, we present a new methodology that integrates ligand-based methods with structural information derived from the receptor. 128 BACE-1 inhibitors recently disclosed … Continued

Design of New Secreted Phospholipase A2 Inhibitors Based on Docking Calculations by Modifying the Pharmacophore Segments of the FPL67047XX Inhibitor

Docking calculations that allow the estimation of the binding energy of small ligands in the GIIA sPLA(2) active site were used in a structure-based design protocol. Four GIIA sPLA(2) inhibitors co-crystallised with the enzyme, were used for examining the enzyme active site and for testing the FlexX in SYBYL® 6.8 molecular docking program to reproduce … Continued

Using a Staged Multi-objective Optimization Approach to Find Selective Pharmacophore Models

It is often difficult to differentiate effectively between related G-protein coupled receptors and their subtypes when doing ligand-based drug design. GALAHAD uses a multi-objective scoring system to generate multiple alignments involving alternative trade-offs between the conflicting desires to minimize internal strain while maximizing pharmacophoric and steric (pharmacomorphic) concordance between ligands. The various overlays obtained can … Continued

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