Peroxysome proliferator-activated receptors (PPARs) have grown greatly in importance due to their role in the metabolic profile. Among three subtypes (α, γ and δ), we here consider the least investigated δ subtype to explore the molecular fingerprints of selective PPARδ agonists. Validated QSAR models (regression based 2D-QSAR, HQSAR and KPLS) and molecular docking with dynamics analyses support the inference of classification-based Bayesian and recursive models. Chemometric studies indicate that the presence of ether linkages and heterocyclic rings has optimum influence in imparting selective bioactivity. Pharmacophore models and docking with molecular dynamics analyses postulate the occurrence of aromatic rings, HB acceptor and a hydrophobic region as crucial molecular fragments for development of PPARδ modulators. Multi-chemometric studies suggest the essential structural requirements of a molecule for imparting potent and selective PPARδ modulation. © 2015 Taylor & Francis.

ACHINTYA SAHA

Chemical Technology

A NANDY

K ROY

University of Calcutta (informally known as Calcutta University or CU) is a collegiate public state university located in Kolkata, West Bengal, India.&nbsp;Within India it is recognized as a &quot;Five-Star University&quot; and accredited &quot;A&quot; Grade by National Assessment and Accreditation Council.

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The University of Calcutta has secured the Fifth position among the Universities of India in the prestigious &quot;Indian University Ranking 2019&quot; list, released by the NIRF of the Ministry of Human Resource Development, Government of India.

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It was established on 24 January 1857, and was one of the first institutions in Asia to be established as a multidisciplinary and Western-style university. Its alumni and faculty include several heads of state, heads of government, social reformers, prominent artists, only academy award winner and Dirac medal winner in India, many Fellows of the Royal Society and five Nobel laureates as of 2019 which is highest in South Asia.

University Of Calcutta

Exploring molecular fingerprints of selective PPARδ agonists through comparative and validated chemometric techniques.

SAR and QSAR in Environmental Research

Peroxisome proliferator-activated gamma receptor is an attractive therapeutic target involving various types of metabolic syndrome. Viewing the importance of peroxisome proliferator-activated gamma receptor modulators, ligand and energetically optimized pharmacophores (e-pharmacophore), hologram-based quantitative structural activity relationships, and classification-based Bayesian models were developed, followed by molecular docking, mechanics, and dynamic analyses to search for essential structural requirements in the molecules for potent and selective peroxisome proliferator-activated gamma receptor modulation. Both ligand and e-pharmacophore models suggest that aromatic ring feature plays the crucial role, whereas the hologram-based quantitative structural activity relationships study indicates that phenyl and indole aromatic rings are essential scafolds for imparting selective peroxisome proliferator-activated gamma receptor modulation. Further, the e-pharmacophore model, molecular docking, and dynamics studies depict the importance of a carboxyl group for modulating peroxisome proliferator-activated gamma receptor agonistic activity through generating strong H-bonds with the active amino acid residues (His323, Tyr327, His449, and Tyr473, etc). The multi chemometrics modeling studies provide some insight into the prime structural features responsible for significant agonistic property of peroxisome proliferator-activated gamma receptor ligands.

Medicinal Chemistry Research

Structural exploration of PPAR gamma modulators through pharmacophore mapping, fragment-based design, docking, and molecular dynamics simulation analyses

Peroxisome proliferator-activated gamma receptor is an attractive therapeutic target involving various types of metabolic syndrome. Viewing the importance of peroxisome proliferator-activated gamma receptor modulators, ligand and energetically optimized pharmacophores (e-pharmacophore), hologram-based quantitative structural activity relationships, and classification-based Bayesian models were developed, followed by molecular docking, mechanics, and dynamic analyses to search for essential structural requirements in the molecules for potent and selective peroxisome proliferator-activated gamma receptor modulation. Both ligand and e-pharmacophore models suggest that aromatic ring feature plays the crucial role, whereas the hologram-based quantitative structural activity relationships study indicates that phenyl and indole aromatic rings are essential scafolds for imparting selective peroxisome proliferator-activated gamma receptor modulation. Further, the e-pharmacophore model, molecular docking, and dynamics studies depict the importance of a carboxyl group for modulating peroxisome proliferator-activated gamma receptor agonistic activity through generating strong H-bonds with the active amino acid residues (His323, Tyr327, His449, and Tyr473, etc). The multi chemometrics modeling studies provide some insight into the prime structural features responsible for significant agonistic property of peroxisome proliferator-activated gamma receptor ligands. © 2016, Springer Science+Business Media New York.

Structural exploration of PPARÎ³ modulators through pharmacophore mapping, fragment-based design, docking, and molecular dynamics simulation analyses

Aminopeptidase N (APN) inhibitors have been reported to be effective in treating of life threatening diseases including cancer. Validated ligand- and structure-based pharmacophore mapping approaches were combined with Bayesian modeling and recursive partitioning to identify structural and physicochemical requirements for highly active APN inhibitors. Based on the assumption that ligand- and structure-based pharmacophore models are complementary, the efficacy of 'multiple pharmacophore screening' for filtering true positive virtual hits was investigated. These multiple pharmacophore screening methods were utilized to search novel virtual hits for APN inhibition. The number of hits was refined and reduced by recursive partitioning, drug-likeliness, pharmacokinetic property prediction, and comparative molecular-docking studies. Four compounds were proposed as the potential virtual hits for APN enzyme inhibition. © 2013 Springer Science+Business Media Dordrecht.

Fulltext

Molecular Diversity

Exploration of structural and physicochemical requirements and search of virtual hits for aminopeptidase N inhibitors

Objectives and Methods Matrix metalloproteinase-2 (MMP-2) is a potential target in metastases. Regression (conventional 2D QSAR) and classification (recursive partitioning (RP), Bayesian modelling) QSAR, pharmacophore mapping and 3D QSAR (comparative molecular field analysis and comparative molecular similarity analysis) were performed on 202 MMP-2 inhibitors. Key findings Quality of the regression models was justified by internal (Q2) and external (R2Pred) cross-validation parameters. Stepwise regression was used to develop linear model (Q2 = 0.822, R 2Pred = 0.667). Genetic algorithm developed linear (Q 2 = 0.845, R2Pred = 0.638) and spline model (Q2 = 0.882, R2Pred = 0.644). The RP and Bayesian models showed cross-validated area under receiver operating characteristic curve (AUCROC-CV) of 0.805 and 0.979 respectively. QSAR models depicted importance of descriptors like five-membered rings, fractional positively charged surface area, lipophilocity and so on. Higher molecular volume was found to be detrimental. Pharmacophore mapping was performed with two tools - Hypogen and PHASE. Both models indicated that one hydrophobic and three hydrogen bond acceptor features are essential. The Pharmacophore-aligned structures were used for CoMFA (Q2 of 0.586 and R2Pred of 0.689) and CoMSIA (Q2 of 0.673 and R2Pred of 0.758), results of which complied with the other analyses. Conclusions All modelling techniques were compared to each other. The current study may help in designing novel MMP-2 inhibitors. © 2013 Royal Pharmaceutical Society.

Journal of Pharmacy and Pharmacology

Exploring QSAR and pharmacophore mapping of structurally diverse selective matrix metalloproteinase-2 inhibitors

β-Amyloid precursor protein cleavage enzyme (BACE) has been shown to be an attractive therapeutic target to control Alzheimer's disease (AD). Inhibition of β-secretase enzyme can prevent the deposition of Aβ (β-amyloid) peptides, which is thought to be the major cause of AD. The present study has been considered to explore 3D-QSAR, HQSAR, and pharmacophore mapping studies of BACE inhibitors. Contour maps of 3D-QSAR studies (CoMFA: R 2 = 0.998, se = 0.067, Q 2 = 0.765, R pred 2 = 0.772, r m 2 = 0.739; CoMSIA: R 2 = 0.992, se = 0.125, Q 2 = 0.730, R pred 2 = 0.713, r m 2 = 0.687) explain the importance of steric and electrostatic, along with hydrogen-bond (HB) acceptor and donor for binding affinity to BACE. HQSAR study (R 2 = 0.941, se = 0.326, Q 2 = 0.792, R pred 2 = 0.713, r m 2 = 0.709) indicates the important fragments of the molecular fingerprints that might be crucial for binding affinity. Pharmacophore space modeling (R 2 = 0.937, rmsd = 0.937, Q 2 = 0.935, R pred 2 = 0.709, r m 2 = 0.837) describes that HB acceptor, donor, hydrophobic, and steric are the important features for interaction with receptor cavity. Finally, the models are adjudged through the docking study elucidating the interactions between the receptor and the ligand, indicating the structural requirements of potent BACE inhibitors. © 2013 Springer Science+Business Media New York.

Journal	Data powered by TypesetSAR and QSAR in Environmental Research
Publisher	Data powered by TypesetTaylor and Francis Ltd.
ISSN	1062-936X
Open Access	No