Laboratorio de Biología Computacional y Diseño de Proteínas, Centro de Estudio de Proteínas (CEP), Facultad de Biología, Universidad de La Habana, Cuba.
J Trop Med. 2011;2011:657483. doi: 10.1155/2011/657483. Epub 2011 Jul 3.
The development of efficient and selective antimalariais remains a challenge for the pharmaceutical industry. The aspartic proteases plasmepsins, whose inhibition leads to parasite death, are classified as targets for the design of potent drugs. Combinatorial synthesis is currently being used to generate inhibitor libraries for these enzymes, and together with computational methodologies have been demonstrated capable for the selection of lead compounds. The high structural flexibility of plasmepsins, revealed by their X-ray structures and molecular dynamics simulations, made even more complicated the prediction of putative binding modes, and therefore, the use of common computational tools, like docking and free-energy calculations. In this review, we revised the computational strategies utilized so far, for the structure-function relationship studies concerning the plasmepsin family, with special focus on the recent advances in the improvement of the linear interaction estimation (LIE) method, which is one of the most successful methodologies in the evaluation of plasmepsin-inhibitor binding affinity.
高效且选择性的抗疟疾药物的开发仍然是制药行业面临的一项挑战。天冬氨酸蛋白酶类(Plasmepsins)被认为是设计强效药物的靶点,其抑制剂会导致寄生虫死亡。目前,组合合成被用于生成这些酶的抑制剂文库,并且与计算方法学一起已经被证明能够用于选择先导化合物。天冬氨酸蛋白酶类的 X 射线结构和分子动力学模拟揭示了其高度的结构灵活性,这使得对可能的结合模式的预测更加复杂,因此,即使是使用常见的计算工具,如对接和自由能计算,也变得更加困难。在这篇综述中,我们回顾了迄今为止用于研究 Plasmepsin 家族的结构-功能关系的计算策略,特别关注最近在改进线性相互作用估计(LIE)方法方面的进展,该方法是评估 Plasmepsin-抑制剂结合亲和力的最成功的方法之一。