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Exhaustive sampling of the fragment space associated to a molecule leading to the generation of conserved fragments.
Chemical Biology & Drug Design ( IF 3 ) Pub Date : 2017-12-12 , DOI: 10.1111/cbdd.13129
Kathrin Heikamp 1 , Fabio Zuccotto 1 , Michael Kiczun 1 , Peter Ray 1 , Ian H Gilbert 1
Affiliation  

The first step in hit optimization is the identification of the pharmacophore, which is normally achieved by deconstruction of the hit molecule to generate "deletion analogues." In silico fragmentation approaches often focus on the generation of small fragments that do not describe properly the fragment space associated to the deletion analogues. We present significant modifications to the molecular fragmentation programme molBLOCKS, which allows the exhaustive sampling of the fragment space associated with a molecule to generate all possible molecular fragments. This generates larger fragments, by combining the smallest fragments. Additionally, it has been modified to deal with the problem of changing pharmacophoric properties through fragmentation, by highlighting bond cuts. The modified molBLOCKS programme was used on a set of drug compounds, where it generated more unique fragments than standard fragmentation approaches by increasing the number of fragments derived per compound. This fragment set was found to be more diverse than those generated by standard fragmentation programmes and was relevant to drug discovery as it contains the key fragments representing the pharmacophoric elements associated with ligand recognition. The use of dummy atoms to highlight bond cuts further increases the information content of fragments by visualizing their previous bonding pattern.

中文翻译:

对与分子相关的片段空间进行详尽的采样,导致保守片段的生成。

命中优化的第一步是药效团的识别,这通常是通过解构命中分子以生成“删除类似物”来实现的。计算机碎片方法通常侧重于小片段的生成,这些小片段不能正确描述与删除类似物相关的片段空间。我们对分子碎片程序 molBLOCKS 进行了重大修改,它允许对与分子相关的碎片空间进行详尽的采样,以生成所有可能的分子碎片。这通过组合最小的片段来生成更大的片段。此外,它还经过修改,通过强调键切割来解决通过片段化改变药效团特性的问题。修改后的 molBLOCKS 程序用于一组药物化合物,通过增加每种化合物衍生的片段数量,它比标准片段化方法生成更多独特的片段。人们发现该片段集比标准片段化程序生成的片段更加多样化,并且与药物发现相关,因为它包含代表与配体识别相关的药效元件的关键片段。使用虚拟原子来突出显示键合切割,通过可视化其先前的键合模式进一步增加了片段的信息内容。
更新日期:2017-12-12
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