利用分子相似性和蛋白质-配体相互作用的合成策略高效筛选超大型化学文库。

IF 5.6 2区 化学 Q1 CHEMISTRY, MEDICINAL
Brian Medel-Lacruz,Albert Herrero,Fernando Martín,Enric Herrero,F Javier Luque,Javier Vázquez
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引用次数: 0

摘要

超大型化学文库的快速扩张已经彻底改变了药物发现,提供了数十亿种化合物的途径。然而,这种增长对传统的虚拟筛选(VS)方法提出了相关挑战。为了解决这些限制,基于合成的方法已经成为可扩展的替代方案,利用组合化学原理优先考虑构建块而不是枚举分子。在这项工作中,我们提出了exaScreen和exaDock,两种新的基于合成的方法,分别为基于配体和基于结构的VS设计。在前一种情况下,合成子的选择是由3D疏水/亲水分布模式以及基于参与片段之间连接键的原子的四极性展开的特定合成子排列方案指导的。另一方面,基于合成的杂化化合物在几何约束对接下对结合位点的调节用于选择最佳的合成子组合。这些策略在识别活性化合物方面表现出与使用全枚举库进行的搜索相当的性能,且计算成本显著降低,为超大化学空间中的VS提供了计算效率高的策略。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Synthon-Based Strategies Exploiting Molecular Similarity and Protein-Ligand Interactions for Efficient Screening of Ultra-Large Chemical Libraries.
The rapid expansion of ultralarge chemical libraries has revolutionized drug discovery, providing access to billions of compounds. However, this growth poses relevant challenges for traditional virtual screening (VS) methods. To address these limitations, synthon-based approaches have emerged as scalable alternatives, exploiting combinatorial chemistry principles to prioritize building blocks over enumerated molecules. In this work, we present exaScreen and exaDock, two novel synthon-based methodologies designed for ligand-based and structure-based VS, respectively. In the former case, synthon selection is guided by the 3D hydrophobic/philic distribution pattern in conjunction with a specific synthon alignment protocol based on a quadrupolar expansion over the atoms that participate in the linking bonds between fragments. On the other hand, accommodation to the binding site under a geometrically restrained docking of synthon-based hybrid compounds is used in the selection of the optimal synthon combinations. These strategies exhibit comparable performance to the search performed using fully enumerated libraries in identifying active compounds with significantly lower computational cost, offering computationally efficient strategies for VS in ultralarge chemical spaces.
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来源期刊
CiteScore
9.80
自引率
10.70%
发文量
529
审稿时长
1.4 months
期刊介绍: The Journal of Chemical Information and Modeling publishes papers reporting new methodology and/or important applications in the fields of chemical informatics and molecular modeling. Specific topics include the representation and computer-based searching of chemical databases, molecular modeling, computer-aided molecular design of new materials, catalysts, or ligands, development of new computational methods or efficient algorithms for chemical software, and biopharmaceutical chemistry including analyses of biological activity and other issues related to drug discovery. Astute chemists, computer scientists, and information specialists look to this monthly’s insightful research studies, programming innovations, and software reviews to keep current with advances in this integral, multidisciplinary field. As a subscriber you’ll stay abreast of database search systems, use of graph theory in chemical problems, substructure search systems, pattern recognition and clustering, analysis of chemical and physical data, molecular modeling, graphics and natural language interfaces, bibliometric and citation analysis, and synthesis design and reactions databases.
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