MacFrag: segmenting large-scale molecules to obtain diverse fragments with high qualities

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Abstract

Construction of high-quality fragment libraries by segmenting organic compounds is an important part of the drug discovery paradigm. This article presents a new method, MacFrag, for efficient molecule fragmentation. MacFrag utilized a modified version of BRICS rules to break chemical bonds and introduced an efficient subgraphs extraction algorithm for rapid enumeration of the fragment space. The evaluation results with ChEMBL dataset exhibited that MacFrag was overall faster than BRICS implemented in RDKit and modified molBLOCKS. Meanwhile, the fragments acquired through MacFrag were more compliant with the ‘Rule of Three’.

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Diao, Y., Hu, F., Shen, Z., & Li, H. (2023). MacFrag: segmenting large-scale molecules to obtain diverse fragments with high qualities. Bioinformatics, 39(1). https://doi.org/10.1093/bioinformatics/btad012

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