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用于相对自由能扰动计算的HelixFold3预测全结构基准测试

Benchmarking HelixFold3-Predicted Holo Structures for Relative Free Energy Perturbation Calculations.

作者信息

Furui Kairi, Ohue Masahito

机构信息

Department of Computer Science, School of Computing, Institute of Science Tokyo, Yokohama 226-8501, Japan.

出版信息

ACS Omega. 2025 Mar 11;10(11):11411-11420. doi: 10.1021/acsomega.4c11413. eCollection 2025 Mar 25.

Abstract

Free energy perturbation (FEP) calculations are a powerful tool for predicting binding affinities in drug discovery, but their accuracy heavily depends on accurate protein-ligand complex structures. While AlphaFold2 revolutionized protein structure prediction, its inability to predict holo structures limits its application in structure-based drug design. AlphaFold3 and its reproduction HelixFold3 demonstrated the ability to predict protein complexes with various binding partners, including small molecules. In this study, we evaluated HelixFold3's ability to predict protein-ligand complexes using eight targets from Wang et al.'s FEP benchmark set. Our analysis revealed that HelixFold3 outperformed the existing methods, including AlphaFold2, in predicting binding site conformations. Notably, the prediction of holo structures yielded a higher binding site accuracy compared to apo structures. FEP calculations using both HelixFold3-predicted holo and apo structures achieved accuracy comparable to that of calculations using crystal structures. Furthermore, HelixFold3 successfully predicted complex structures for novel derivatives not present in its training data, and FEP calculations using these predicted structures maintained reliable accuracy. These results suggest that HelixFold3-predicted structures can effectively substitute for crystal structures in early stage drug discovery.

摘要

自由能微扰(FEP)计算是药物研发中预测结合亲和力的强大工具,但其准确性在很大程度上依赖于准确的蛋白质-配体复合物结构。虽然AlphaFold2彻底改变了蛋白质结构预测,但它无法预测全酶结构限制了其在基于结构的药物设计中的应用。AlphaFold3及其复制品HelixFold3展示了预测与各种结合伙伴(包括小分子)形成的蛋白质复合物的能力。在本研究中,我们使用Wang等人的FEP基准集中的八个靶点评估了HelixFold3预测蛋白质-配体复合物的能力。我们的分析表明,在预测结合位点构象方面,HelixFold3优于包括AlphaFold2在内的现有方法。值得注意的是,与无配体结构相比,全酶结构的预测产生了更高的结合位点准确性。使用HelixFold3预测的全酶和无配体结构进行的FEP计算达到了与使用晶体结构计算相当的准确性。此外,HelixFold3成功预测了其训练数据中不存在的新型衍生物的复合物结构,并且使用这些预测结构进行的FEP计算保持了可靠的准确性。这些结果表明,HelixFold3预测的结构可以在药物发现的早期阶段有效替代晶体结构。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b805/11947795/6970cf6bd642/ao4c11413_0001.jpg

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