A.M. Butlerov Institute of Chemistry, Kazan Federal University, Kremlevskaya Str. 18, 420008 Kazan, Russia.
Institute of Molecular and Translational Medicine, Faculty of Medicine and Dentistry, Palacký University and University Hospital in Olomouc, Hnevotinska 5, 77900 Olomouc, Czech Republic.
Molecules. 2018 Nov 27;23(12):3094. doi: 10.3390/molecules23123094.
Pharmacophore modeling is a widely used strategy for finding new hit molecules. Since not all protein targets have available 3D structures, ligand-based approaches are still useful. Currently, there are just a few free ligand-based pharmacophore modeling tools, and these have a lot of restrictions, e.g., using a template molecule for alignment. We developed a new approach to 3D pharmacophore representation and matching which does not require pharmacophore alignment. This representation can be used to quickly find identical pharmacophores in a given set. Based on this representation, a 3D pharmacophore ligand-based modeling approach to search for pharmacophores which preferably match active compounds and do not match inactive ones was developed. The approach searches for 3D pharmacophore models starting from 2D structures of available active and inactive compounds. The implemented approach was successfully applied for several retrospective studies. The results were compared to a 2D similarity search, demonstrating some of the advantages of the developed 3D pharmacophore models. Also, the generated 3D pharmacophore models were able to match the 3D poses of known ligands from their protein-ligand complexes, confirming the validity of the models. The developed approach is available as an open-source software tool: http://www.qsar4u.com/pages/pmapper.php and https://github.com/meddwl/psearch.
药效团模型是一种广泛用于寻找新的命中分子的策略。由于并非所有蛋白质靶标都具有可用的 3D 结构,基于配体的方法仍然很有用。目前,仅有几个免费的基于配体的药效团建模工具,并且这些工具存在很多限制,例如,需要使用模板分子进行对齐。我们开发了一种新的 3D 药效团表示和匹配方法,不需要药效团对齐。这种表示方法可用于快速在给定集合中找到相同的药效团。基于这种表示方法,开发了一种基于 3D 药效团的配体建模方法,用于搜索优先与活性化合物匹配而不与非活性化合物匹配的药效团。该方法从可用的活性和非活性化合物的 2D 结构开始搜索 3D 药效团模型。所实现的方法已成功应用于几项回顾性研究。将结果与 2D 相似性搜索进行了比较,展示了开发的 3D 药效团模型的一些优势。此外,生成的 3D 药效团模型能够匹配其蛋白-配体复合物中已知配体的 3D 构象,证实了模型的有效性。该开发的方法可作为开源软件工具使用:http://www.qsar4u.com/pages/pmapper.php 和 https://github.com/meddwl/psearch。