虚拟筛选
药物发现
自由能微扰
计算机科学
热力学积分
化学空间
结合能
计算化学
化学
生物信息学
物理
分子动力学
生物
原子物理学
标识
DOI:10.1021/acsmedchemlett.2c00541
摘要
Rigorous physics-based methods to calculate binding free energies of protein–ligand complexes have become a valued component of structure-based drug design. Relative and absolute binding free energy calculations have been deployed prospectively in support of solving diverse drug discovery challenges. Here we review recent applications of binding free energy calculations to fragment growing and linking, scaffold hopping, binding pose validation, virtual screening, covalent enzyme inhibition, and positional analogue scanning. Furthermore, we discuss the merits of using protein models and highlight recent efforts to replace costly binding free energy calculations with predictions from machine learning models trained on a limited number of free energy perturbation or thermodynamic integration calculations thereby allowing for extended chemical space exploration.
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