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Identification of potential PKC inhibitors through pharmacophore designing, 3D-QSAR and molecular dynamics simulations targeting Alzheimer's disease.
J Biomol Struct Dyn. 2018 11; 36(15):4029-4044.JB

Abstract

Protein kinases are ubiquitously expressed as Serine/Threonine kinases, and play a crucial role in cellular activities. Protein kinases have evolved through stringent regulation mechanisms. Protein kinases are also involved in tauopathy, thus are important targets for developing Anti-Alzheimer's disease compounds. Structures with an indole scaffold turned out to be potent new leads. With the aim of developing new inhibitors for human protein kinase C, here we report the generation of four point 3D geometric featured pharmacophore model. In order to identify novel and potent PKCθ inhibitors, the pharmacophore model was screened against 80,000,00 compounds from various chemical databases such as., ZINC, SPEC, ASINEX, which resulted in 127 compound hits, and were taken for molecular docking filters (HTVS, XP docking). After in-depth analysis of binding patterns, induced fit docking (flexible) was employed for six compounds along with the cocrystallized inhibitor. Molecular docking study reveals that compound 6F found to be tight binder at the active site of PKCθ as compared to the cocrystal and has occupancy of 90 percentile. MM-GBSA also confirmed the potency of the compound 6F as better than cocrystal. Molecular dynamics results suggest that compound 6F showed good binding stability of active sites residues similar to cocrystal 7G compound. Present study corroborates the pharmacophore-based virtual screening, and finds the compound 6F as a potent Inhibitor of PKC, having therapeutic potential for Alzheimer's disease. Worldwide, 46.8 million people are believed to be living with Alzheimer's disease. When elderly population increases rapidly and neurodegenerative burden also increases in parallel, we project the findings from this study will be useful for drug developing efforts targeting Alzheimer's disease.

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Publisher Full Text (DOI)

Authors+Show Affiliations

Iqbal S
a Centre of Advanced Study in Crystallography and Biophysics , University of Madras, Guindy Campus , Chennai 600025 , Tamil Nadu , India.
Anantha Krishnan D
a Centre of Advanced Study in Crystallography and Biophysics , University of Madras, Guindy Campus , Chennai 600025 , Tamil Nadu , India. b Bioinformatics Infrastructure Facility , University of Madras, Guindy Campus , Chennai 600025 , Tamil Nadu , India.
Gunasekaran K
a Centre of Advanced Study in Crystallography and Biophysics , University of Madras, Guindy Campus , Chennai 600025 , Tamil Nadu , India. b Bioinformatics Infrastructure Facility , University of Madras, Guindy Campus , Chennai 600025 , Tamil Nadu , India.

MeSH

Alzheimer DiseaseCatalytic DomainDatabases, ChemicalDrug DesignGene ExpressionHigh-Throughput Screening AssaysHumansHydrogen BondingKineticsLigandsMolecular Docking SimulationMolecular Dynamics SimulationNootropic AgentsProtein BindingProtein Conformation, alpha-HelicalProtein Conformation, beta-StrandProtein Interaction Domains and MotifsProtein Kinase C-thetaProtein Kinase InhibitorsPyrrolesQuantitative Structure-Activity RelationshipThermodynamics

Pub Type(s)

Journal Article

Language

eng

PubMed ID

29182053

Citation

Iqbal, Saleem, et al. "Identification of Potential PKC Inhibitors Through Pharmacophore Designing, 3D-QSAR and Molecular Dynamics Simulations Targeting Alzheimer's Disease." Journal of Biomolecular Structure & Dynamics, vol. 36, no. 15, 2018, pp. 4029-4044.
Iqbal S, Anantha Krishnan D, Gunasekaran K. Identification of potential PKC inhibitors through pharmacophore designing, 3D-QSAR and molecular dynamics simulations targeting Alzheimer's disease. J Biomol Struct Dyn. 2018;36(15):4029-4044.
Iqbal, S., Anantha Krishnan, D., & Gunasekaran, K. (2018). Identification of potential PKC inhibitors through pharmacophore designing, 3D-QSAR and molecular dynamics simulations targeting Alzheimer's disease. Journal of Biomolecular Structure & Dynamics, 36(15), 4029-4044. https://doi.org/10.1080/07391102.2017.1406824
Iqbal S, Anantha Krishnan D, Gunasekaran K. Identification of Potential PKC Inhibitors Through Pharmacophore Designing, 3D-QSAR and Molecular Dynamics Simulations Targeting Alzheimer's Disease. J Biomol Struct Dyn. 2018;36(15):4029-4044. PubMed PMID: 29182053.
* Article titles in AMA citation format should be in sentence-case
TY - JOUR T1 - Identification of potential PKC inhibitors through pharmacophore designing, 3D-QSAR and molecular dynamics simulations targeting Alzheimer's disease. AU - Iqbal,Saleem, AU - Anantha Krishnan,Dhanabalan, AU - Gunasekaran,Krishnasamy, Y1 - 2017/12/13/ PY - 2017/11/29/pubmed PY - 2019/6/21/medline PY - 2017/11/29/entrez KW - AD, Alzheimer’s disease KW - Alzheimer’s disease KW - CPH, common pharmacophore hypothesis KW - HBD, hydrogen bond donor KW - IFD, induced fit docking KW - MD, molecular dynamics simulation KW - MM-GBSA KW - MM-GBSA, molecular mechanics generalized born surface area KW - PBVS KW - PBVS, pharmacophore-based virtual screening KW - PKC, protein kinase C KW - PKCθ KW - PSA, polar surface area KW - RMSD, root-mean-square deviation KW - RMSF, root-mean-square fluctuation KW - ROC, receiver operating characteristic KW - SD, standard deviation KW - XP, extra precision KW - molecular dynamics simulation KW - pyrrole KW - staurosporine SP - 4029 EP - 4044 JF - Journal of biomolecular structure & dynamics JO - J Biomol Struct Dyn VL - 36 IS - 15 N2 - Protein kinases are ubiquitously expressed as Serine/Threonine kinases, and play a crucial role in cellular activities. Protein kinases have evolved through stringent regulation mechanisms. Protein kinases are also involved in tauopathy, thus are important targets for developing Anti-Alzheimer's disease compounds. Structures with an indole scaffold turned out to be potent new leads. With the aim of developing new inhibitors for human protein kinase C, here we report the generation of four point 3D geometric featured pharmacophore model. In order to identify novel and potent PKCθ inhibitors, the pharmacophore model was screened against 80,000,00 compounds from various chemical databases such as., ZINC, SPEC, ASINEX, which resulted in 127 compound hits, and were taken for molecular docking filters (HTVS, XP docking). After in-depth analysis of binding patterns, induced fit docking (flexible) was employed for six compounds along with the cocrystallized inhibitor. Molecular docking study reveals that compound 6F found to be tight binder at the active site of PKCθ as compared to the cocrystal and has occupancy of 90 percentile. MM-GBSA also confirmed the potency of the compound 6F as better than cocrystal. Molecular dynamics results suggest that compound 6F showed good binding stability of active sites residues similar to cocrystal 7G compound. Present study corroborates the pharmacophore-based virtual screening, and finds the compound 6F as a potent Inhibitor of PKC, having therapeutic potential for Alzheimer's disease. Worldwide, 46.8 million people are believed to be living with Alzheimer's disease. When elderly population increases rapidly and neurodegenerative burden also increases in parallel, we project the findings from this study will be useful for drug developing efforts targeting Alzheimer's disease. SN - 1538-0254 UR - https://www.unboundmedicine.com/medline/citation/29182053/Identification_of_potential_PKC_inhibitors_through_pharmacophore_designing_3D_QSAR_and_molecular_dynamics_simulations_targeting_Alzheimer's_disease_ DB - PRIME DP - Unbound Medicine ER -