Rodrigues Tiago
Instituto de Medicina Molecular, Faculdade de Medicina da Universidade de Lisboa, Av. Prof. Egas Moniz, 1649-028 Lisboa, Portugal.
Org Biomol Chem. 2017 Nov 15;15(44):9275-9282. doi: 10.1039/c7ob02193c.
Natural products (NPs) present a privileged source of inspiration for chemical probe and drug design. Despite the biological pre-validation of the underlying molecular architectures and their relevance in drug discovery, the poor accessibility to NPs, complexity of the synthetic routes and scarce knowledge of their macromolecular counterparts in phenotypic screens still hinder their broader exploration. Cheminformatics algorithms now provide a powerful means of circumventing the abovementioned challenges and unlocking the full potential of NPs in a drug discovery context. Herein, I discuss recent advances in the computer-assisted design of NP mimics and how artificial intelligence may accelerate future NP-inspired molecular medicine.
天然产物是化学探针和药物设计的重要灵感来源。尽管其潜在分子结构在生物学上已得到预先验证，且在药物发现中具有相关性，但天然产物获取困难、合成路线复杂以及在表型筛选中对其大分子类似物的了解匮乏，仍然阻碍了对它们的更广泛探索。化学信息学算法如今提供了一种强大的手段，可规避上述挑战，并在药物发现背景下释放天然产物的全部潜力。在此，我将讨论天然产物模拟物计算机辅助设计的最新进展，以及人工智能如何加速未来受天然产物启发的分子医学发展。
