联合进化信息与监督学习相结合,从小数据集中生成效力更强的环肽抑制剂。

IF 12.7 1区 化学 Q1 CHEMISTRY, MULTIDISCIPLINARY
ACS Central Science Pub Date : 2024-11-20 eCollection Date: 2024-12-25 DOI:10.1021/acscentsci.4c01428
Ylenia Mazzocato, Nicola Frasson, Matthew Sample, Cristian Fregonese, Angela Pavan, Alberto Caregnato, Marta Simeoni, Alessandro Scarso, Laura Cendron, Petr Šulc, Alessandro Angelini
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引用次数: 0

摘要

使用机器学习模型计算生成环肽抑制剂需要大规模的训练数据集,通常难以通过实验生成。在这里,我们证明了随机森林回归与伪似然最大化的顺序组合,直接耦合分析方法和蒙特卡罗模拟可以有效地增强肿瘤相关蛋白酶环肽抑制剂的设计管道,即使是小的实验数据集。进一步的体外研究表明,这种硅进化的环肽比以前开发的最佳肽抑制剂对该靶标更有效。环状肽与蛋白酶配合物的晶体结构与蛋白质配合物相似,具有较大的相互作用表面、受约束的肽骨架、多种分子间和分子内相互作用,具有良好的结合亲和力和选择性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Combination of Coevolutionary Information and Supervised Learning Enables Generation of Cyclic Peptide Inhibitors with Enhanced Potency from a Small Data Set.

Computational generation of cyclic peptide inhibitors using machine learning models requires large size training data sets often difficult to generate experimentally. Here we demonstrated that sequential combination of Random Forest Regression with the pseudolikelihood maximization Direct Coupling Analysis method and Monte Carlo simulation can effectively enhance the design pipeline of cyclic peptide inhibitors of a tumor-associated protease even for small experimental data sets. Further in vitro studies showed that such in silico-evolved cyclic peptides are more potent than the best peptide inhibitors previously developed to this target. Crystal structure of the cyclic peptides in complex with the protease resembled those of protein complexes, with large interaction surfaces, constrained peptide backbones, and multiple inter- and intramolecular interactions, leading to good binding affinity and selectivity.

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来源期刊
ACS Central Science
ACS Central Science Chemical Engineering-General Chemical Engineering
CiteScore
25.50
自引率
0.50%
发文量
194
审稿时长
10 weeks
期刊介绍: ACS Central Science publishes significant primary reports on research in chemistry and allied fields where chemical approaches are pivotal. As the first fully open-access journal by the American Chemical Society, it covers compelling and important contributions to the broad chemistry and scientific community. "Central science," a term popularized nearly 40 years ago, emphasizes chemistry's central role in connecting physical and life sciences, and fundamental sciences with applied disciplines like medicine and engineering. The journal focuses on exceptional quality articles, addressing advances in fundamental chemistry and interdisciplinary research.
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