Isa Mustafa Alhaji, Kappo Abidemi Paul
Molecular Biophysics and Structural Biology (MBSB) Group, Department of Biochemistry, University of Johannesburg, Auckland Park Kingsway Campus, Johannesburg 2006, South Africa.
Molecular Biophysics and Structural Biology (MBSB) Group, Department of Biochemistry, University of Johannesburg, Auckland Park Kingsway Campus, Johannesburg 2006, South Africa.
Comput Biol Med. 2025 Aug;194:110443. doi: 10.1016/j.compbiomed.2025.110443. Epub 2025 Jun 3.
Protein-protein interactions (PPIS) are critical in proteostasis, stress response, and disease progression. Targeting the interaction between Hsp70.14 and BAG2, a co-chaperone implicated in oncogenic survival, offers a promising therapeutic approach. This study employed a comprehensive in silico framework to identify bioactive antimicrobial peptides (AMPS) capable of disrupting the Hsp70.14-BAG2 interaction. In this study, we present an integrated in silico pipeline combining deep learning-based peptide screening, molecular docking, molecular dynamics (MD) simulations, and MM-GBSA free energy analysis to identify antimicrobial peptides (AMPS) capable of disrupting the Hsp70.14-BAG2 interaction. Peptides were shortlisted from an extensive public database using stringent physicochemical and safety filters, yielding candidates with high therapeutic potential. DBAASPS_19370 and DBAASPS_17167 exhibited more favourable binding free energies and lower dissociation constants than the reference Hsp70.14-BAG2 complex. Molecular dynamics simulations revealed that one lead peptide demonstrated superior complex stability, characterised by compact structure, reduced flexibility, and solvent exposure. MM/GBSA calculations further validated these observations, revealing the most favourable free energy profile for DBAASPS_19370 compared to the other complexes. Interface analysis showed improved atomic packing, enhanced residue participation, and better solvation energetics in the selected peptide complexes. These findings highlight DBAASPS_19370 as a potent AMP candidate capable of competitively inhibiting BAG2 and disrupting its interaction with Hsp70.14, offering a rational avenue for chaperone-targeted therapeutic development. Future work may explore in vitro validation and structural optimization of this peptide to support its translational potential.
蛋白质-蛋白质相互作用（PPIs）在蛋白质稳态、应激反应和疾病进展中至关重要。靶向热休克蛋白70.14（Hsp70.14）与BAG2（一种与致癌生存相关的共伴侣蛋白）之间的相互作用，提供了一种很有前景的治疗方法。本研究采用了一个全面的计算机模拟框架，以识别能够破坏Hsp70.14 - BAG2相互作用的生物活性抗菌肽（AMPs）。在本研究中，我们提出了一个集成的计算机模拟流程，结合基于深度学习的肽筛选、分子对接、分子动力学（MD）模拟和MM - GBSA自由能分析，以识别能够破坏Hsp70.14 - BAG2相互作用的抗菌肽（AMPs）。使用严格的物理化学和安全性筛选标准，从一个广泛的公共数据库中筛选出肽，得到具有高治疗潜力的候选肽。与参考的Hsp70.14 - BAG2复合物相比，DBAASPS_19370和DBAASPS_17167表现出更有利的结合自由能和更低的解离常数。分子动力学模拟表明，一种先导肽表现出卓越的复合物稳定性，其特征为结构紧凑、灵活性降低和溶剂暴露减少。MM/GBSA计算进一步验证了这些观察结果，揭示了与其他复合物相比，DBAASPS_19370具有最有利的自由能分布。界面分析表明，在选定的肽复合物中，原子堆积得到改善，残基参与度增强，溶剂化能更好。这些发现突出了DBAASPS_19370作为一种有效的AMP候选物，能够竞争性抑制BAG2并破坏其与Hsp70.14的相互作用，为靶向伴侣蛋白的治疗开发提供了一条合理途径。未来的工作可以探索该肽的体外验证和结构优化，以支持其转化潜力。
