Dihydrofolate reductase (DHFR) is a well-known enzyme of the folate metabolic pathway and it is a validated drug target for leishmaniasis. However, only a few leads are reported against Leishmania donovani DHFR (LdDHFR), and thus, there is a need to identify new inhibitors. In this article, pharmacoinformatic tools such as molecular docking, virtual screening, absorption, distribution, metabolism, excretion, and toxicity (ADMET) profiling, and molecular dynamics (MD) simulations were utilized to identify potential LdDHFR inhibitors. Initially, a natural DHFR substrate (dihydrofolate), a classical DHFR inhibitor (methotrexate), and a potent LdDHFR inhibitor, that is, “5-(3-(octyloxy)benzyl)pyrimidine-2,4-diamine” (LEAD) were docked in the active site of the LdDHFR and MD simulated to understand the binding mode characteristics of the substrates/inhibitors in the LdDHFR. The shape of the LEAD molecule was used as a query for shape-based virtual screening, while the three-dimensional structure of LdDHFR was utilized for docking-based virtual screening. In silico ADMET factors were also considered during virtual screening. These two screening processes yielded 25 suitable hits, which were further validated for their selectivity toward LdDHFR using molecular docking and prime molecular mechanics/generalized born surface area analysis in the human DHFR (HsDHFR). Best six hits, which were selective and energetically favorable for the LdDHFR, were chosen for MD simulations. The MD analysis showed that four of the hits exhibited very good binding affinity for LdDHFR with respect to HsDHFR, and two hits were found to be more selective than the reported potent LdDHFR inhibitor. The present study thus identifies hits that can be further designed and modified as potent LdDHFR inhibitors.

中文翻译：

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使用药物信息学方法鉴定 LdDHFR 酶的选择性抑制剂

二氢叶酸还原酶 (DHFR) 是叶酸代谢途径中的一种众所周知的酶，它是利什曼病的有效药物靶点。然而，只有少数针对多诺瓦利什曼原虫DHFR ( Ld DHFR) 的先导物被报道，因此需要鉴定新的抑制剂。在本文中，利用分子对接、虚拟筛选、吸收、分布、代谢、排泄和毒性 (ADMET) 分析以及分子动力学 (MD) 模拟等药物信息学工具来识别潜在的Ld DHFR 抑制剂。最初，天然 DHFR 底物（二氢叶酸）、经典的 DHFR 抑制剂（甲氨蝶呤）和有效的LdDHFR 抑制剂，即“5-(3-(octyloxy)benzyl)pyrimidine-2,4-diamine”(LEAD) 停靠在Ld DHFR 和 MD的活性位点模拟以了解底物的结合模式特征/ Ld DHFR 中的抑制剂。LEAD分子的形状被用作基于形状的虚拟筛选的查询，而Ld DHFR的三维结构被用于基于对接的虚拟筛选。在虚拟筛选期间还考虑了计算机 ADMET 因素。这两个筛选过程产生了 25 个合适的命中，使用分子对接和素分子力学/人类 DHFR 中的广义出生表面积分析进一步验证了它们对Ld DHFR的选择性（HsDHFR)。为 MD 模拟选择了对Ld DHFR有选择性且在能量上有利的最佳六次命中。MD 分析表明，就Hs DHFR而言，四个命中对Ld DHFR表现出非常好的结合亲和力，并且发现两个命中比报道的强效Ld DHFR 抑制剂更具选择性。因此，本研究确定了可以进一步设计和修改为有效Ld DHFR 抑制剂的命中。