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Exploring Structural Relationships between Bioactive and Commercial Chemical Space and Developing Target Hypotheses for Compound Acquisition

机译:探索生物活性与商业化学空间与复合采集发展目标假设的结构关系

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Analog series were systematically extracted from more than 650?000 bioactive compounds originating from medicinal chemistry and screening sources and more than 3.6 million commercial compounds that were not biologically annotated. Then, analog series-based (ASB) scaffolds were generated. For each scaffold from a bioactive series, a target profile was derived and ASB scaffolds shared by bioactive and commercial compounds were determined. On the basis of our analysis, large segments of commercial chemical space were not yet explored biologically. Shared ASB scaffolds established structural relationships between bioactive and commercial chemical space, and the target profiles of these scaffolds were transferred to commercially available analogs of active compounds. This made it possible to derive target hypotheses for more than 37?000 compounds without biological annotations covering more than 1000 different targets. For many molecules, alternative target assignments were available. Target hypotheses for these compounds should be of interest, for example, for hit expansion, acquisition of compounds to design or further extend focused libraries for drug discovery, or testing of expanded analog series on different targets. They can also be used to search for analogs and complement compound series during target-directed optimization. Therefore, all of the commercial molecules with new target hypotheses as well as key scaffolds identified in our analysis and their target profiles are made freely available.
机译:模拟系列从源自药用化学和筛选来源的超过650 000 000种生物活性化合物和超过360万商业化合物的生物学注释。然后,产生模拟系列(ASB)支架。对于来自生物活性系列的每个支架,衍生目标轮廓,并测定通过生物活性和商业化合物共享的ASB支架。在我们的分析的基础上,尚未在生物学上探索大量商业化学品空间。共用ASB支架建立了生物活性和商业化学空间之间的结构关系,并将这些支架的靶轮廓转移到可商业上可用的活性化合物的类似物。这使得可以获得超过37 000个化合物的目标假设,而没有生物注释覆盖超过1000种不同的靶标。对于许多分子,可以使用替代目标任务。这些化合物的靶假设应该是感兴趣的,例如,用于抗膨胀,获取化合物以设计或进一步扩展聚焦的药物发现,或者在不同靶标上测试扩增的模拟系列。它们还可用于在目标定向优化期间搜索类似物和补偿复合系列。因此,在我们的分析和目标型材中鉴定的所有商业分子以及新的目标假假设以及键的关键支架进行自由可用。

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