Use of Simplified Molecular Input Line Entry System and molecular graph based descriptors in prediction and design of pancreatic lipase inhibitors

Future Medicinal Chemistry
Ashwani Kumar, Shilpi Chauhan

Abstract

The inhibition of pancreatic lipase (PL) enzyme is the most explored strategy for the treatment of obesity. The present study describes the development of quantitative structure-activity relationship (QSAR) models for a diverse set of 293 PL inhibitors by means of the Monte Carlo optimization technique. Methodology & results: The hybrid optimal descriptors were used to build QSAR models with three subsets of three splits. The developed QSAR models were further validated with corresponding external sets. The best QSAR model has the following statistical particulars: R2 = 0.752, Q LOO 2 = 0 . 736 for the test set and R2 = 0.768, Q F 1 2 = 0 . 628 , Q F 2 2 = 0 . 621 for the validation set. The developed QSAR models were robust, stable and predictive and led to the design of novel PL inhibitors.

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Citations

Oct 27, 2018·Anti-cancer Agents in Medicinal Chemistry·Alla P ToropovaJerzy Leszczynski
Mar 29, 2019·Current Computer-aided Drug Design·Andrey A Toropov, Alla P Toropova
Oct 12, 2018·Molecular Diversity·Alla P Toropova, Andrey A Toropov
Jul 22, 2018·Future Medicinal Chemistry·Chérif F Matta, Michael C Hutter
Jan 7, 2021·Journal of Biomolecular Structure & Dynamics·Kumar Sambhav ChopdarMukesh Kumar Raval
Mar 24, 2021·Environmental Science and Pollution Research International·Alla P Toropova, Andrey A Toropov

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Software Mentioned

Simplified Molecular Input Line Entry System ( SMILES )
TEST
VEGA ZZ
AutoDock Vina
MarvinSketch
Marvin Sketch
SMILES
CORrelation And Logic ( CORAL )
Open Babel tool
CORAL

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