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MacFrag: segmenting large-scale molecules to obtain diverse fragments with high qualities.
Diao, Yanyan; Hu, Feng; Shen, Zihao; Li, Honglin.
Afiliación
  • Diao Y; Shanghai Key Laboratory of New Drug Design, School of Pharmacy, East China University of Science and Technology, Shanghai 200237, China.
  • Hu F; Shanghai Key Laboratory of New Drug Design, School of Pharmacy, East China University of Science and Technology, Shanghai 200237, China.
  • Shen Z; Shanghai Key Laboratory of New Drug Design, School of Pharmacy, East China University of Science and Technology, Shanghai 200237, China.
  • Li H; Shanghai Key Laboratory of New Drug Design, School of Pharmacy, East China University of Science and Technology, Shanghai 200237, China.
Bioinformatics ; 39(1)2023 01 01.
Article en En | MEDLINE | ID: mdl-36637187
ABSTRACT

SUMMARY:

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'. AVAILABILITY AND IMPLEMENTATION https//github.com/yydiao1025/MacFrag. SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.
Asunto(s)

Texto completo: 1 Bases de datos: MEDLINE Asunto principal: Algoritmos / Programas Informáticos Idioma: En Revista: Bioinformatics Asunto de la revista: INFORMATICA MEDICA Año: 2023 Tipo del documento: Article País de afiliación: China

Texto completo: 1 Bases de datos: MEDLINE Asunto principal: Algoritmos / Programas Informáticos Idioma: En Revista: Bioinformatics Asunto de la revista: INFORMATICA MEDICA Año: 2023 Tipo del documento: Article País de afiliación: China