title: Identification of novel hits as highly prospective dual agonists for mu and kappa opioid receptors: an integrated in silico approach.
abstract: Opioid agonists are used clinically for the treatment of acute and chronic pain, however, their clinical use is limited due to the presence of undesired side effects. Dual agonists, simultaneously targeting mu and kappa opioid receptors, show fewer side effects than that of selective agonists. In the present work, 2D- and 3D- Quantitative Structure Activity Relationship studies were performed on a series of aminomorphinan derivatives as dual agonists, using a wide range of descriptors. The aim of the study was to identify the structural requirements for the activity of these compounds towards mu and kappa opioid receptors and using the models, with best external predictability, for predicting the activities of new hits obtained from shape based virtual screening of drug like compounds from ZINC database. Genetic algorithm-based GFA and G/PLS techniques were used to derive the 2D-QSAR models. Common feature-based pharmacophore was used for aligning the compounds for 3D-QSAR. All the models were validated both internally and externally using statistical metrics. The coverage estimation of the models was carried out with applicability domain calculation. Six enriched hits were identified as novel prospective dual agonist based on good Blood Brain Barrier permeability and their activities towards mu and kappa opioid receptors, predicted by the best QSAR models. The known potent dual agonist, cyclorphan, and two highly prospective dual agonists were docked to both the receptors and binding free energies were calculated using MMGBSA. Molecular dynamics studies were performed on the docked complexes with both the receptors to establish stability of the complexes.
authors.affiliation: a Structural Biology and Bioinformatics Division , CSIR-Indian Institute of Chemical Biology , Kolkata 700032 , India.
authors.forename: Indrani
authors.initials: I
authors.lastname: Bera
authors.affiliation: b National Institute of Pharmaceutical Education and Research , Kolkata 700032 , India.
authors.forename: Mrinal Vishwas
authors.initials: MV
authors.lastname: Marathe
authors.affiliation: a Structural Biology and Bioinformatics Division , CSIR-Indian Institute of Chemical Biology , Kolkata 700032 , India.
authors.forename: Pavan V
authors.initials: PV
authors.lastname: Payghan
authors.affiliation: a Structural Biology and Bioinformatics Division , CSIR-Indian Institute of Chemical Biology , Kolkata 700032 , India.
authors.forename: Nanda
authors.initials: N
authors.lastname: Ghoshal
mesh_terms: D001812:Blood-Brain Barrier / Q000187:drug effects; D006801:Humans; D062105:Molecular Docking Simulation; D056004:Molecular Dynamics Simulation; D009019:Morphinans / Q000737:chemistry* / Q000627:therapeutic use; D046912:Multiprotein Complexes / Q000737:chemistry*; D011485:Protein Binding; D021281:Quantitative Structure-Activity Relationship; D017473:Receptors, Opioid, kappa / Q000819:agonists / Q000737:chemistry*; D017450:Receptors, Opioid, mu / Q000819:agonists / Q000737:chemistry*
chemical_list: D009019:Morphinans; D046912:Multiprotein Complexes; D017473:Receptors, Opioid, kappa; D017450:Receptors, Opioid, mu; C084603:cyclorphan
keywords: MD simulations; docking; dual agonists; opioids; quantitative structure–activity relationship; virtual screening