Decision tree-based identification of important molecular fragments for protein-ligand binding.

Li, Baiyi; Wang, Yunsong; Yin, Zuode; Xu, Lei; Xie, Liangxu; Xu, Xiaojun

Li, Baiyi; Wang, Yunsong; Yin, Zuode; Xu, Lei; Xie, Liangxu; Xu, Xiaojun.

Afiliación

Li B; Institute of Bioinformatics and Medical Engineering, Jiangsu University of Technology, Changzhou, China.
Wang Y; School of Electrical and Information Engineering, Jiangsu University of Technology, Changzhou, China.
Yin Z; Institute of Bioinformatics and Medical Engineering, Jiangsu University of Technology, Changzhou, China.
Xu L; Institute of Bioinformatics and Medical Engineering, Jiangsu University of Technology, Changzhou, China.
Xie L; Institute of Bioinformatics and Medical Engineering, Jiangsu University of Technology, Changzhou, China.
Xu X; Institute of Bioinformatics and Medical Engineering, Jiangsu University of Technology, Changzhou, China.

Chem Biol Drug Des ; 103(1): e14427, 2024 01.

Article en En | MEDLINE | ID: mdl-38230776

ABSTRACT

ABSTRACT

Fragment-based drug design is an emerging technology in pharmaceutical research and development. One of the key aspects of this technology is the identification and quantitative characterization of molecular fragments. This study presents a strategy for identifying important molecular fragments based on molecular fingerprints and decision tree algorithms and verifies its feasibility in predicting protein-ligand binding affinity. Specifically, the three-dimensional (3D) structures of protein-ligand complexes are encoded using extended-connectivity fingerprints (ECFP), and three decision tree models, namely Random Forest, XGBoost, and LightGBM, are used to quantitatively characterize the feature importance, thereby extracting important molecular fragments with high reliability. Few-shot learning reveals that the extracted molecular fragments contribute significantly and consistently to the binding affinity even with a small sample size. Despite the absence of location and distance information for molecular fragments in ECFP, 3D visualization, in combination with the reverse ECFP process, shows that the majority of the extracted fragments are located at the binding interface of the protein and the ligand. This alignment with the distance constraints critical for binding affinity further supports the reliability of the strategy for identifying important molecular fragments.

Asunto(s)

Proteínas; Ligandos; Reproducibilidad de los Resultados; Proteínas/química; Unión Proteica; Árboles de Decisión

Palabras clave

binding affinity; decision tree algorithms; important molecular fragments; molecular fingerprints; protein-ligand complex

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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Proteínas Tipo de estudio: Diagnostic_studies / Health_economic_evaluation / Prognostic_studies Idioma: En Revista: Chem Biol Drug Des Asunto de la revista: BIOQUIMICA / FARMACIA / FARMACOLOGIA Año: 2024 Tipo del documento: Article País de afiliación: China Pais de publicación: Reino Unido

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