Research Institute of Pharmaceutical Sciences, Faculty of Pharmacy, University of Karachi, Karachi-75270, Pakistan
Department of Medical Parasitology, College of Medicine, Umm Al-Qura University, Makkah, Saudi Arabia
Curr Comput Aided Drug Des. 2020;16(5):583-598. doi: 10.2174/1573409915666190827163327.
Human African trypanosomiasis is a fatal disease prevalent in approximately 36 sub-Saharan countries. Emerging reports of drug resistance in Trypanosoma brucei are a serious cause of concern as only limited drugs are available for the treatment of the disease. Pteridine reductase is an enzyme of Trypanosoma brucei.
It plays a critical role in the pterin metabolic pathway that is absolutely essential for its survival in the human host. The success of finding a potent inhibitor in structure-based drug design lies within the ability of computational tools to efficiently and accurately dock a ligand into the binding cavity of the target protein. Here we report the computational characterization of Trypanosoma brucei pteridine reductase (Tb-PR) active-site using twenty-four high-resolution co-crystal structures with various drugs. Structurally, the Tb-PR active site can be grouped in two clusters; one with high Root Mean Square Deviation (RMSD) of atomic positions and another with low RMSD of atomic positions. These clusters provide fresh insight for rational drug design against Tb-PR. Henceforth, the effect of several factors on docking accuracy, including ligand and protein flexibility were analyzed using Fred.
The online server was used to analyze the side chain flexibility and four proteins were selected on the basis of results. The proteins were subjected to small-scale virtual screening using 85 compounds, and statistics were calculated using Bedroc and roc curves. The enrichment factor was also calculated for the proteins and scoring functions. The best scoring function was used to understand the ligand protein interactions with top common compounds of four proteins. In addition, we made a 3D structural comparison between the active site of Tb-PR and Leishmania major pteridine reductase (Lm- PR). We described key structural differences between Tb-PR and Lm-PR that can be exploited for rational drug design against these two human parasites.
The results indicated that relying just on re-docking and cross-docking experiments for virtual screening of libraries isn't enough and results might be misleading. Hence it has been suggested that small scale virtual screening should be performed prior to large scale screening.
人体非洲锥虫病是一种致命疾病,流行于大约 36 个撒哈拉以南非洲国家。在布氏锥虫中出现的药物耐药性报告令人严重关切,因为只有有限的药物可用于治疗这种疾病。蝶呤还原酶是布氏锥虫的一种酶。
它在喋呤代谢途径中起着关键作用,对于其在人体宿主中的生存是绝对必要的。在基于结构的药物设计中找到一种有效的抑制剂的成功,在于计算工具能够有效地和准确地将配体对接入靶蛋白的结合腔中。在这里,我们报告了使用二十四种具有各种药物的高分辨率共晶结构对布氏锥虫蝶呤还原酶(Tb-PR)活性位点的计算特征。从结构上看,Tb-PR 活性位点可以分为两个簇;一个具有高原子位置均方根偏差(RMSD),另一个具有低原子位置 RMSD。这些簇为针对 Tb-PR 的合理药物设计提供了新的见解。此后,使用 Fred 分析了几个因素对对接准确性的影响,包括配体和蛋白质的灵活性。
使用在线服务器分析侧链灵活性,并根据结果选择了四个蛋白质。使用 85 种化合物对这些蛋白质进行小规模虚拟筛选,并使用 Bedroc 和 roc 曲线计算统计数据。还计算了蛋白质和评分函数的富集因子。使用最佳评分函数来了解四个蛋白质的前 10 个常见化合物与配体-蛋白质的相互作用。此外,我们还对 Tb-PR 的活性位点和利什曼原虫蝶呤还原酶(Lm-PR)进行了 3D 结构比较。我们描述了 Tb-PR 和 Lm-PR 之间的关键结构差异,这些差异可用于针对这两种人体寄生虫的合理药物设计。
结果表明,仅仅依靠重新对接和交叉对接实验进行库的虚拟筛选是不够的,结果可能会产生误导。因此,建议在进行大规模筛选之前先进行小规模虚拟筛选。