Insights into the Interaction Mechanisms of Peptide and Non-Peptide Inhibitors with MDM2 Using Gaussian-Accelerated Molecular Dynamics Simulations and Deep Learning

被引:3
作者
Yang, Wanchun [1 ]
Wang, Jian [1 ]
Zhao, Lu [1 ]
Chen, Jianzhong [1 ]
机构
[1] Shandong Jiaotong Univ, Sch Sci, Jinan 250357, Peoples R China
来源
MOLECULES | 2024年 / 29卷 / 14期
关键词
MDM2; peptide inhibitors; Gaussian-accelerated dynamics simulations; deep learning; binding free energy; SOLVATED INTERACTION ENERGY; BOUNDARY-ELEMENT METHOD; P53; TUMOR-SUPPRESSOR; P53-MDM2; INTERACTION; CANCER-THERAPY; BINDING; DISCOVERY; AMBER; DERIVATIVES; GENERATION;
D O I
10.3390/molecules29143377
中图分类号
Q5 [生物化学]; Q7 [分子生物学];
学科分类号
071010 ; 081704 ;
摘要
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 alpha 2 and alpha 2', as well as the beta-strands and loops between alpha 2 and alpha 2'. 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 interaction energy (SIE) not only suggest that the ranking of the calculated binding free energies is in agreement with that of the experimental results, but also verify that van der Walls interactions are the primary forces responsible for inhibitor-MDM2 binding. Our findings also indicate that peptide inhibitors yield more interaction contacts with MDM2 compared to non-peptide inhibitors. Principal component analysis (PCA) and free energy landscape (FEL) analysis indicated that the piperidinone inhibitor 0Y7 shows the most pronounced impact on the free energy profiles of MDM2, with the piperidinone inhibitor demonstrating higher fluctuation amplitudes along primary eigenvectors. The hot spots of MDM2 revealed by residue-based free energy estimation provide target sites for drug design toward MDM2. This study is expected to provide useful theoretical aid for the development of selective inhibitors of MDM2 family members.
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页数:22
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