{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"submitter":["El Fadili M"],"funding":["This research was funded by the Researchers Supporting Project (No. RSPD2024R566), King Saud University, Riyadh, Saudi Arabia.","King Saud University"],"pagination":["142"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC11293250"],"repository":["biostudies-literature"],"omics_type":["Unknown"],"volume":["18(1)"],"pubmed_abstract":["Based on a structural family of thirty-two NR2B-selective N-Methyl-D-Aspartate receptor (NMDAR) antagonists, two phenylpiperazine derivatives labeled C37 and C39 were conceived thanks to molecular modeling techniques, as novel NMDAR inhibitors exhibiting the highest analgesic activities (of pIC<sub>50</sub> order) against neuropathic pain, with excellent ADME-toxicity profiles, and good levels of molecular stability towards the targeted protein of NMDA receptor. Initially, the quantitative structure-activity relationships (QSARs) models were developed using multiple linear regression (MLR), partial least square regression (PLSR), multiple non-linear regression (MNLR), and artificial neural network (ANN) techniques, revealing that analgesic activity was strongly correlated with dipole momen"],"journal":["BMC chemistry"],"pubmed_title":["In silico insights into the design of novel NR2B-selective NMDA receptor antagonists: QSAR modeling, ADME-toxicity predictions, molecular docking, and molecular dynamics investigations."],"pmcid":["PMC11293250"],"funding_grant_id":["grant no. RSPD2024R566","No. RSPD2024R566)"],"pubmed_authors":["Abuelizz HA","Kara M","Mujwar S","Elhallaoui M","El Fadili M","Er-Rahmani S","Er-Rajy M","Ajala A","Bouzammit R"],"additional_accession":[]},"is_claimable":false,"name":"In silico insights into the design of novel NR2B-selective NMDA receptor antagonists: QSAR modeling, ADME-toxicity predictions, molecular docking, and molecular dynamics investigations.","description":"Based on a structural family of thirty-two NR2B-selective N-Methyl-D-Aspartate receptor (NMDAR) antagonists, two phenylpiperazine derivatives labeled C37 and C39 were conceived thanks to molecular modeling techniques, as novel NMDAR inhibitors exhibiting the highest analgesic activities (of pIC<sub>50</sub> order) against neuropathic pain, with excellent ADME-toxicity profiles, and good levels of molecular stability towards the targeted protein of NMDA receptor. Initially, the quantitative structure-activity relationships (QSARs) models were developed using multiple linear regression (MLR), partial least square regression (PLSR), multiple non-linear regression (MNLR), and artificial neural network (ANN) techniques, revealing that analgesic activity was strongly correlated with dipole momen","dates":{"release":"2024-01-01T00:00:00Z","publication":"2024 Jul","modification":"2026-06-03T00:39:21.163Z","creation":"2025-02-19T02:27:15.919Z"},"accession":"S-EPMC11293250","cross_references":{"pubmed":["39085870"],"doi":["10.1186/s13065-024-01248-6"]}}