Lešnik Samo, Konc Janez
Faculty of Chemistry and Chemical Technology, University of Maribor, Maribor, Slovenia.
National Institute of Chemistry, Ljubljana, Slovenia.
Methods Mol Biol. 2020;2089:1-28. doi: 10.1007/978-1-0716-0163-1_1.
Computational methods that predict and evaluate binding of ligands to receptors implicated in different pathologies have become crucial in modern drug design and discovery. Here, we describe protocols for using the recently developed package of computational tools for similarity-based drug discovery. The ProBiS stand-alone program and web server allow superimposition of protein structures against large protein databases and predict ligands based on detected binding site similarities. GenProBiS allows mapping of human somatic missense mutations related to cancer and non-synonymous single nucleotide polymorphisms and subsequent visual exploration of specific interactions in connection to these mutations. We describe protocols for using LiSiCA, a fast ligand-based virtual screening software that enables easy screening of large databases containing billions of small molecules. Finally, we show the use of BoBER, a web interface that enables user-friendly access to a large database of bioisosteric and scaffold hopping replacements.
预测和评估配体与涉及不同病理的受体结合的计算方法在现代药物设计和发现中变得至关重要。在这里，我们描述了使用最近开发的基于相似性的药物发现计算工具包的方案。ProBiS独立程序和网络服务器允许将蛋白质结构与大型蛋白质数据库进行叠加，并根据检测到的结合位点相似性预测配体。GenProBiS允许绘制与癌症和非同义单核苷酸多态性相关的人类体细胞错义突变图谱，并随后对与这些突变相关的特定相互作用进行可视化探索。我们描述了使用LiSiCA的方案，LiSiCA是一种基于配体的快速虚拟筛选软件，能够轻松筛选包含数十亿小分子的大型数据库。最后，我们展示了BoBER的使用，BoBER是一个网络界面，可让用户方便地访问生物电子等排体和骨架跃迁替代物的大型数据库。
