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

Halder, Amit Kumar; Saha, Achintya; Jha, Tarun

doi:10.1111/jphp.12133

Cited by 30 publications

(17 citation statements)

References 42 publications

(71 reference statements)

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“…It correlates structural and physicochemical properties with experimental activities. It is extensively used to develop predictive models for chemical compounds with experimental biological activities (Adhikari, Halder, Mondal, & Jha, 2013;Halder, Adhikari, & Jha, 2010;Halder, Saha, & Jha, 2013a, 2013bJana et al, 2011;Lewis & Wood, in press). …”

Section: D-qsar Studymentioning

confidence: 99%

“…Multiple linear regression (MLR) models (Halder et al, , 2013a(Halder et al, , 2013b were developed on the training set with the help of forward stepwise regression (F to enter = 3.0, F to remove = 2.9) (Franke, 1984). During MLR analysis, intercorrelated descriptors (correlation coefficient > .50) were discarded.…”

Section: Multiple Linear Regression (Mlr) Analysismentioning

confidence: 99%

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Stepwise development of structure–activity relationship of diverse PARP-1 inhibitors through comparative and validatedin silico modeling techniques and molecular dynamics simulation

Halder

Saha

et al. 2014

Journal of Biomolecular Structure and Dynamics

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Inhibitors of poly (ADP-ribose) polymerase-1 (PARP-1) enzyme are useful for the treatment of various diseases including cancer. Comparative in silico studies were performed on different ligand-based (2D-QSAR, Kernel-based partial least square (KPLS) analysis, Pharmacophore Search Engine (PHASE) pharmacophore mapping), and structure-based (molecular docking, MM-GBSA analyses, Gaussian-based 3D-QSAR analyses on docked poses) modeling techniques to explore the structure-activity relationship of a diverse set of PARP-1 inhibitors. Two-dimensional (2D)-QSAR highlighted the importance of charge topological index (JGI7), fractional polar surface area (JursFPSA3), and connectivity index (CIC2) along with different molecular fragments. Favorable and unfavorable fingerprints were demonstrated in KPLS analysis, whereas important pharmacophore features (one acceptor, one donor, and two ring aromatic) along with favorable and unfavorable field effects were demonstrated in PHASE-based pharmacophore model. MM-GBSA analyses revealed significance of different polar, non-polar, and solvation energies. Docking-based alignment of ligands was used to perform Gaussian-based 3D-QSAR study that further demonstrated importance of different field effects. Overall, it was found that polar interactions (hydrogen bonding, bridged hydrogen bonding, and pi-cation) play major roles for higher activity. Steric groups increase the total contact surface area but it should have higher fractional polar surface area to adjust solvation energy. Structure-based pharmacophore mapping spotted the positive ionizable feature of ligands as the most important feature for discriminating highly active compounds from inactives. Molecular dynamics simulation, conducted on highly active ligands, described the dynamic behaviors of the protein complexes and supported the interpretations obtained from other modeling analyses. The current study may be useful for designing PARP-1 inhibitors.

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Section: D-qsar Studymentioning

confidence: 99%

Section: Multiple Linear Regression (Mlr) Analysismentioning

confidence: 99%

Stepwise development of structure–activity relationship of diverse PARP-1 inhibitors through comparative and validatedin silico modeling techniques and molecular dynamics simulation

Halder

Saha

et al. 2014

Journal of Biomolecular Structure and Dynamics

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“…Therefore, designing potent and selective MMP‐2 inhibitors is still in demand to combat the dreaded disease cancer. Though several alignment‐based 3D‐QSAR studies were performed earlier on different MMP‐2 inhibitors, none of these highlighted any robust alignment dependent QSARs . Zheng et al .…”

Section: Introductionmentioning

confidence: 99%

“…However, they have aligned these compounds based on the lowest energy conformer as well as the best docking pose of the highest active compound. Halder et al . developed 3D‐QSAR CoMFA and CoMSIA models only on the PHASE pharmacophore based alignment of 202 diverse MMP‐2 inhibitors.…”

Section: Introductionmentioning

confidence: 99%

“…In the earlier study, 3D‐QSAR CoMFA and CoMSIA models were generated on 214 diverse MMP‐2 inhibitors depending on the alignment of these molecules derived from the best Hypogen‐pharmacophore model. None of these 3D‐QSAR models were developed comprising multiple types of alignment methods. In the current study, a variety of comprehensive alignment‐dependent (namely pharmacophore‐based, docking‐based and Open3DALIGN‐based alignment) 3D‐QSAR techniques have been performed to explore the structure‐property relationship of a series of glutamate‐based MMP‐2 inhibitors synthesized in the laboratory, for higher inhibitory activity.…”

Section: Introductionmentioning

confidence: 99%

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Understanding Chemico‐Biological Interactions of Glutamate MMP‐2 Inhibitors through Rigorous Alignment‐Dependent 3D‐QSAR Analyses

et al. 2017

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The current study involves different alignment techniques (pharmacophore‐based, docking‐based and Open3DALIGN‐based) extensively at the first time to build three‐dimensional quantitative structure‐activity relationship (3D‐QSAR) models on some potential glutamate‐based in house MMP‐2 inhibitors. The docking‐based alignment method yields the best 3D‐QSAR models though other alignment‐based methods also provide statistically significant and validated models. 3D‐QSAR models are correlated with molecular docking study and pharmacophore mapping. Biphenyl moiety of glutamines enters into the S1′ pocket and involves π‐π interactions with Tyr142 and His120, while none of the phenylacetyl/naphthylacetyl isoglutamines interacts with Tyr142. 3D‐QSAR models also suggest the importance of hydrophobicity and steric features of biphenyl function required for higher MMP‐2 inhibition. The sulfonyl oxygen may form potential hydrogen bonding interaction with Leu83 and Ala84 of S1' pocket. This study clearly points out that biphenylsulfonyl glutamines are favorable than phenylacetyl/naphthylacetyl isoglutamines for imparting higher MMP‐2 inhibition.

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Possible anticancer agents: synthesis, pharmacological activity, and molecular modeling studies on some 5-N -Substituted-2-N-(substituted benzenesulphonyl)-L(+)Glutamines

et al. 2017

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

Abstract: All modelling techniques were compared to each other. The current study may help in designing novel MMP-2 inhibitors.

Cited by 30 publications

References 42 publications

Stepwise development of structure–activity relationship of diverse PARP-1 inhibitors through comparative and validatedin silico modeling techniques and molecular dynamics simulation

Stepwise development of structure–activity relationship of diverse PARP-1 inhibitors through comparative and validatedin silico modeling techniques and molecular dynamics simulation

Understanding Chemico‐Biological Interactions of Glutamate MMP‐2 Inhibitors through Rigorous Alignment‐Dependent 3D‐QSAR Analyses

Possible anticancer agents: synthesis, pharmacological activity, and molecular modeling studies on some 5-N -Substituted-2-N-(substituted benzenesulphonyl)-L(+)Glutamines

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