Computational Biology and Chemistry Research Group, Vicerrectorado de Investigación, Universidad Católica de Santa María.
DIFACQUIM Research Group, Department of Pharmacy, School of Chemistry, Universidad Nacional Autónoma de México.
J Vis Exp. 2024 Sep 6(211). doi: 10.3791/66349.
Chemical space is a multidimensional descriptor space that encloses all possible molecules, and at least 1 x 10 organic substances with a molecular weight below 500 Da are thought to be potentially relevant for drug discovery. Natural products have been the primary source of the new pharmacological entities marketed during the past forty years and continue to be one of the most productive sources for the creation of innovative medications. Chemoinformatics-based computational tools accelerate the drug development process for natural products. Methods including estimating bioactivities, safety profiles, ADME, and natural product likeness measurement have been used. Here, we go over recent developments in chemoinformatic tools designed to visualize, characterize, and expand the chemical space of natural compound data sets using various molecular representations, create visual representations of such spaces, and investigate structure-property relationships within chemical spaces. With an emphasis on drug discovery applications, we evaluate the open-source databases BIOFACQUIM and PeruNPDB as proof of concept.
化学空间是一个多维描述符空间，它包含了所有可能的分子，据认为，分子量低于 500 Da 的至少 1 x 10 种有机物质可能与药物发现有关。在过去的四十年中，天然产物一直是市场上新型药理实体的主要来源，并且仍然是创造创新药物的最有成效的来源之一。基于 chemoinformatics 的计算工具加速了天然产物的药物开发过程。已经使用了包括估计生物活性、安全性概况、ADME 和天然产物相似性测量在内的方法。在这里，我们回顾了最近开发的 chemoinformatic 工具，这些工具旨在使用各种分子表示形式可视化、表征和扩展天然化合物数据集的化学空间，创建这些空间的可视化表示形式，并研究化学空间内的结构-性质关系。我们重点介绍了药物发现应用，评估了 BIOFACQUIM 和 PeruNPDB 等开源数据库作为概念验证。
