LQTA-R: A new 3D-QSAR methodology applied to a set of DGAT1 inhibitors. (June 2018)

• Record Type: Journal Article
• Authors: Patil, Rajesh B.; Barbosa, Euzebio G.; Sangshetti, Jaiprakash N.; Sawant, Sanjay D.; Zambre, Vishal P.
• Is Part Of: Computational biology and chemistry. Volume 74(2018)
• Page Start: 123
• Page End: 131
• Publication Date: 2018-06
• Subjects: LQTA -- 3D QSAR -- DGAT1 inhibitors -- QSARINs -- R statistical program; Chemistry -- Data processing -- Periodicals; Biology -- Data processing -- Periodicals; Biochemistry -- Data processing; Biology -- Data processing; Molecular biology -- Data processing; Periodicals; Electronic journals; 542.85
• DOI: 10.1016/j.compbiolchem.2018.02.021
• Languages: English
• ISSNs: 1476-9271

Abstract

Graphical abstract: Highlights: New scripts, LQTA-R for 3D-QSAR was developed which exploits R Statistical program. These scripts require only the aligned structures of compounds. Scripts generate hydrogen bond, LJ and Coulomb descriptors. LQTA-R scripts were applied to the dataset of DGAT-1 inhibitors. The QSAR model exhibited good predictive accuracy signifying its use in drug design. Abstract: The rapid advances in computational methods for the drug design have resulted in the accurate predictions of biological activities of ligands with or without the availability of enzyme structures. 3D-QSAR is one of the computational methods used for such purpose. Currently, freely available 3D-QSAR methods suffer the limitations like complex methodologies, difficulty in the analysis of results, applying the statistical methods and validations of models built. Present work describes simple and novel 3D-QSAR methodology, which uses bash scripts LQTA_R_LJ, LQTA_R_QQ and LQTA_R_HB using freely available R statistical program. These scripts then generate Leenard-Jones, Coulomb and Hydrogen bond descriptors. These descriptors provide the steric 3D property, electrostatic property and hydrogen bond formation capacity respectively. These scripts have been tested for the set of DGAT1 inhibitors and results showed that the 3D-QSAR models built have better predictive abilities in terms of R 2 0.735, Q 2 loo 0.635 and R 2 ext 0.715. The 3D-QSAR model suggested that the substitutions of the alkyl group at the oxadiazolyl ring at the 6th position of the pyrrolo-pyridazine ring is undesirable, on the contrary, substituted phenyl ring at 7th position is responsible for the improved DGAT1 inhibitory activity. The analysis also suggested that 6th position could be substituted with the oxadiazolyl ring or analogous heterocyclic rings, where the 3rd position of such heterocyclic rings substituted with rigid hydrophobic substitute can improve DGAT1 activity.