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A QSAR model of Olanzapine derivatives as potential inhibitors for 5-HT2A Receptor

Schizophrenia is a complex, chronic mental disorder, affecting about 21 million people worldwide. It is characterized by symptoms, including distortions in thinking, perception, emotions, disorganized speech, sense of self and behavior. Recently, a numbers of marketed drugs for Schizophrenia are ava...

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Detalles Bibliográficos
Autores principales: Mitra, Pooja, Rastogi, Aishwarya, Rajpoot, Mayank, Kumar, Ajay, Srivastava, Vivek
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Biomedical Informatics 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5680715/
https://www.ncbi.nlm.nih.gov/pubmed/29162966
http://dx.doi.org/10.6026/97320630013339
Descripción
Sumario:Schizophrenia is a complex, chronic mental disorder, affecting about 21 million people worldwide. It is characterized by symptoms, including distortions in thinking, perception, emotions, disorganized speech, sense of self and behavior. Recently, a numbers of marketed drugs for Schizophrenia are available against dopamine D2 and serotonin 5-HT2A receptors. Here, we docked Olanzapine derivatives (collected from literature) with 5-HT2A Receptor using the program AutoDock 4.2. The docked protein inhibitor complex structure was optimized using molecular dynamics simulation for 5ps with the CHARMM-22 force field using NAMD (NAnoscale Molecular Dynamics program) incorporated in visual molecular dynamics (VMD 1.9.2) and then evaluating the stability of complex structure by calculating RMSD values. NAMD is a parallel, object-oriented molecular dynamics code designed for high-performance simulation of large biomolecular systems. A quantitative structure activity relationship (QSAR) model was built using energy-based descriptors as independent variable and pKi value as dependent variable of eleven known Olanzapine derivatives with 5-HT2A Receptor, yielding correlation coefficient r2 of 0.63861. The predictive performance of QSAR model was assessed using different crossvalidation procedures. Our results suggest that a ligand-receptor binding interaction for 5-HT2A receptor using a QSAR model is promising approach to design more potent 5-HT2A receptor inhibitors prior to their synthesis.