Alotaiq Nasser, Dermawan Doni
Health Sciences Research Center (HSRC), Imam Mohammad Ibn Saud Islamic University (IMSIU), Riyadh 13317, Saudi Arabia.
Department of Applied Biotechnology, Faculty of Chemistry, Warsaw University of Technology, 00-661 Warsaw, Poland.
Int J Mol Sci. 2025 Jan 8;26(2):462. doi: 10.3390/ijms26020462.
This study evaluates the performance of various structure prediction tools and molecular docking platforms for therapeutic peptides targeting coronary artery disease (CAD). Structure prediction tools, including AlphaFold 3, I-TASSER 5.1, and PEP-FOLD 4, were employed to generate accurate peptide conformations. These methods, ranging from deep-learning-based (AlphaFold) to template-based (I-TASSER 5.1) and fragment-based (PEP-FOLD), were selected for their proven capabilities in predicting reliable structures. Molecular docking was conducted using four platforms (HADDOCK 2.4, HPEPDOCK 2.0, ClusPro 2.0, and HawDock 2.0) to assess binding affinities and interactions. A 100 ns molecular dynamics (MD) simulation was performed to evaluate the stability of the peptide-receptor complexes, along with Molecular Mechanics/Poisson-Boltzmann Surface Area (MM/PBSA) calculations to determine binding free energies. The results demonstrated that Apelin, a therapeutic peptide, exhibited superior binding affinities and stability across all platforms, making it a promising candidate for CAD therapy. Apelin's interactions with key receptors involved in cardiovascular health were notably stronger and more stable compared to the other peptides tested. These findings underscore the importance of integrating advanced computational tools for peptide design and evaluation, offering valuable insights for future therapeutic applications in CAD. Future work should focus on in vivo validation and combination therapies to fully explore the clinical potential of these therapeutic peptides.
本研究评估了针对冠状动脉疾病（CAD）的治疗性肽的各种结构预测工具和分子对接平台的性能。使用包括AlphaFold 3、I-TASSER 5.1和PEP-FOLD 4在内的结构预测工具来生成准确的肽构象。这些方法从基于深度学习的（AlphaFold）到基于模板的（I-TASSER 5.1）和基于片段的（PEP-FOLD），因其在预测可靠结构方面已被证实的能力而被选用。使用四个平台（HADDOCK 2.4、HPEPDOCK 2.0、ClusPro 2.0和HawDock 2.0）进行分子对接，以评估结合亲和力和相互作用。进行了100纳秒的分子动力学（MD）模拟，以评估肽-受体复合物的稳定性，并进行分子力学/泊松-玻尔兹曼表面积（MM/PBSA）计算以确定结合自由能。结果表明，治疗性肽Apelin在所有平台上均表现出优异的结合亲和力和稳定性，使其成为CAD治疗的有希望的候选药物。与测试的其他肽相比，Apelin与心血管健康相关关键受体的相互作用明显更强且更稳定。这些发现强调了整合先进的计算工具进行肽设计和评估的重要性，为CAD未来的治疗应用提供了有价值的见解。未来的工作应集中在体内验证和联合疗法上，以充分探索这些治疗性肽的临床潜力。
