{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"submitter":["Yang W"],"funding":["Key Research and Development Project of the Shandong Province","Shandong Jiaotong University","Natural Science Foundation of Shandong Province"],"pagination":["3377"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC11279683"],"repository":["biostudies-literature"],"omics_type":["Unknown"],"volume":["29(14)"],"pubmed_abstract":["Inhibiting MDM2-p53 interaction is considered an efficient mode of cancer treatment. In our current study, Gaussian-accelerated molecular dynamics (GaMD), deep learning (DL), and binding free energy calculations were combined together to probe the binding mechanism of non-peptide inhibitors K23 and 0Y7 and peptide ones PDI6W and PDI to MDM2. The GaMD trajectory-based DL approach successfully identified significant functional domains, predominantly located at the helixes α2 and α2', as well as the β-strands and loops between α2 and α2'. The post-processing analysis of the GaMD simulations indicated that inhibitor binding highly influences the structural flexibility and collective motions of MDM2. Calculations of molecular mechanics-generalized Born surface area (MM-GBSA) and solvated intera"],"journal":["Molecules (Basel, Switzerland)"],"pubmed_title":["Insights into the Interaction Mechanisms of Peptide and Non-Peptide Inhibitors with MDM2 Using Gaussian-Accelerated Molecular Dynamics Simulations and Deep Learning."],"pmcid":["PMC11279683"],"funding_grant_id":["2019GGX102050","ZR2021MA069","TJXZ202204"],"pubmed_authors":["Yang W","Zhao L","Chen J","Wang J"],"additional_accession":[]},"is_claimable":false,"name":"Insights into the Interaction Mechanisms of Peptide and Non-Peptide Inhibitors with MDM2 Using Gaussian-Accelerated Molecular Dynamics Simulations and Deep Learning.","description":"Inhibiting MDM2-p53 interaction is considered an efficient mode of cancer treatment. In our current study, Gaussian-accelerated molecular dynamics (GaMD), deep learning (DL), and binding free energy calculations were combined together to probe the binding mechanism of non-peptide inhibitors K23 and 0Y7 and peptide ones PDI6W and PDI to MDM2. The GaMD trajectory-based DL approach successfully identified significant functional domains, predominantly located at the helixes α2 and α2', as well as the β-strands and loops between α2 and α2'. The post-processing analysis of the GaMD simulations indicated that inhibitor binding highly influences the structural flexibility and collective motions of MDM2. Calculations of molecular mechanics-generalized Born surface area (MM-GBSA) and solvated intera","dates":{"release":"2024-01-01T00:00:00Z","publication":"2024 Jul","modification":"2026-04-21T03:30:23.375Z","creation":"2025-04-19T13:13:08.68Z"},"accession":"S-EPMC11279683","cross_references":{"pubmed":["39064955"],"doi":["10.3390/molecules29143377"]}}