变构调节
鉴定(生物学)
计算机科学
蛋白质功能
药物发现
注释
功能(生物学)
计算生物学
药物靶点
蛋白质配体
配体(生物化学)
机器学习
化学
人工智能
生物
生物信息学
生物化学
受体
遗传学
植物
基因
酶
作者
Ying Xia,Xiaoyong Pan,Hong‐Bin Shen
标识
DOI:10.1016/j.sbi.2024.102793
摘要
Protein-ligand binding site prediction is critical for protein function annotation and drug discovery. Biological experiments are time-consuming and require significant equipment, materials, and labor resources. Developing accurate and efficient computational methods for protein-ligand interaction prediction is essential. Here, we summarize the key challenges associated with ligand binding site (LBS) prediction and introduce recently published methods from their input features, computational algorithms, and ligand types. Furthermore, we investigate the specificity of allosteric site identification as a particular LBS type. Finally, we discuss the prospective directions for machine learning-based LBS prediction in the near future.
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