Danel Tomasz, Wojtuch Agnieszka, Podlewska Sabina
Faculty of Mathematics and Computer Science, Jagiellonian University, 6 Łojasiewicza Street, 30-348 Kraków, Poland.
Maj Institute of Pharmacology, Polish Academy of Sciences, Department of Medicinal Chemistry, 31-343 Kraków, Smętna Street 12, Poland.
Comput Struct Biotechnol J. 2022 Oct 6;20:5639-5651. doi: 10.1016/j.csbj.2022.10.005. eCollection 2022.
Physicochemical and pharmacokinetic compound profile has crucial impact on compound potency to become a future drug. Ligands with desired activity profile cannot be used for treatment if they are characterized by unfavourable physicochemical or ADMET properties. In the study, we consider metabolic stability and focus on selected subtypes of cytochrome P450 - proteins, which take part in the first phase of compound transformations in the organism. We develop a protocol for generation of new potential inhibitors of selected cytochrome isoforms. Its subsequent stages are composed of generation and assessment of new derivatives of known cytochrome inhibitors, docking and evaluation of the compound possible inhibition on the basis of the obtained ligand-protein complexes. Besides the library of new potential agents inhibiting particular cytochrome subtypes, we also prepare a graph neural network that predicts the change in activity for all modifications of the starting molecule. In addition, we perform a systematic statistical study on the influence of particular substitutions on the potential inhibition properties of generated compounds (both mono- and di-substitutions are considered), provide explanations of the inhibitory predictions and prepare an on-line visualization platform enabling manual inspection of the results. The developed methodology can greatly support the design of new cytochrome P450 inhibitors with the overarching goal of generation of new metabolically stable compounds. It enables instant evaluation of possible compound-cytochrome interactions and selection of ligands with the highest potential of possessing desired biological activity.
物理化学和药代动力学化合物概况对化合物成为未来药物的效力具有至关重要的影响。具有所需活性概况的配体如果具有不利的物理化学或ADMET性质,则不能用于治疗。在这项研究中,我们考虑代谢稳定性,并专注于细胞色素P450蛋白的选定亚型,这些蛋白参与生物体中化合物转化的第一阶段。我们开发了一种生成选定细胞色素同工型新潜在抑制剂的方案。其后续阶段包括已知细胞色素抑制剂新衍生物的生成和评估、基于获得的配体-蛋白质复合物对化合物可能抑制作用的对接和评估。除了抑制特定细胞色素亚型的新潜在药物库外,我们还制备了一个图神经网络,该网络可预测起始分子所有修饰的活性变化。此外,我们对特定取代对所生成化合物潜在抑制特性的影响进行了系统的统计研究(考虑了单取代和双取代),对抑制预测进行了解释,并准备了一个在线可视化平台,以便人工检查结果。所开发的方法可以极大地支持新型细胞色素P450抑制剂的设计,总体目标是生成新的代谢稳定化合物。它能够即时评估可能的化合物-细胞色素相互作用,并选择具有最高潜力拥有所需生物活性的配体。