Computer-aided molecular design of (E)-N-Aryl-2-ethene-sulfonamide analogues as microtubule targeted agents in prostate cancer

Microtubules are tube-shaped, filamentous and cytoskeletal proteins that are essential in all eukaryotic cells. Microtubule is an attractive and promising target for anticancer agents. In this study, three-dimensional quantitative structure activity relationships (3D-QSAR) including comparative molecular field analysis, CoMFA, and comparative molecular similarity indices analysis, CoMSIA, were performed on a set of 45 (E)-N-Aryl-2-ethene-sulfonamide analogues as microtubule-targeted anti-prostate cancer agents. Automated grid potential analysis, AutoGPA module in Molecular Operating Environment 2009.10 (MOE) as a new 3D-QSAR approach with the pharmacophore-based alignment was carried out on the same dataset. AutoGPA-based 3D-QSAR model yielded better prediction parameters than CoMFA and CoMSIA. Based on the contour maps generated from the models, some key features were identified in (E)-N-Aryl-2-arylethene-sulfonamide analogues that were responsible for the anti-cancer activity. Virtual screening was performed based on pharmacophore modeling and molecular docking to identify the new inhibitors from ZINC database. Seven top ranked compounds were found based on Gold score fitness function. In silico ADMET studies were performed on compounds retrieved from virtual screening in compliance with the standard ranges.     

Grid potential analysis,virtual screening studies and ADME/T profiling on N‐arylsulfonylindoles as anti‐HIV‐1 agents

A grid potential analysis employing a novel approach of 3D quantitative structure–activity relationships (QSAR) as AutoGPA module in MOE2009.10 was performed on a dataset of 42 compounds of N‐arylsulfonylindoles as anti‐HIV‐1 agents. The uniqueness of AutoGPA module is that it automatically builds the 3D‐QSAR model on the pharmacophore‐based molecular alignment. The AutoGPA‐based 3D‐QSAR model obtained in the present study gave the cross‐validated Q² value of 0.588, r²_pred value of 0.701, r²_m statistics of 0.732 and Fisher value of 94.264. The results of 3D‐QSAR analysis indicated that hydrophobic groups at R₁ and R₂ positions and electron releasing groups at R₃ position are favourable for good activity. To find similar analogues, virtual screening on ZINC database was carried out using generated AutoGPA‐based 3D‐QSAR model and showed good prediction. In addition to those mentioned earlier, in‐silico ADME absorption, distribution, metabolism and excretion profiling and toxicity risk assessment test was performed, and results showed that majority of compounds from current dataset and newly virtually screened hits generated were within their standard limit. Copyright © 2013 John Wiley & Sons, Ltd.