Archana Singh, Irin Sarah Jacob, Vikas Gautam, Sarika N Suryawanshi
Department of Pharmacoinformatics, National Institute of Pharmaceutical Education and Research (NIPER), EPIP Campus, Industrial Area, Hajipur – 844102, Bihar, India.
Malaria remains one of the most prevalent infectious parasitic diseases worldwide killing almost one million people a year over the last decade. The public health burden of malaria is one of the greatest of any infectious agent. Plasmodium protozoan parasites are the causative agents of malaria and it is transmitted to humans through the female Anopheles mosquitoes. Among the various species, Plasmodium falciparum is responsible for the most lethal form of human malaria. Plasmodium falciparum malaria kills around 1 million children and causes 300-500 million clinical episodes of malaria annually. Aspartate aminotransferases catalyse the conversion of aspartate and α-ketoglutarate into oxaloacetate and glutamate which are key enzymes in the nitrogen metabolism of all organisms. The Plasmodium falciparum aspartate aminotransferase (PfAspAT) plays a pivotal role in energy metabolism and in the de novo biosynthesis of pyrimidines and it can be utilized as a potential target to search new leads against it. In the present study, we have utilized X-ray structure of the PfAspAT which is a homodimer crystallised at a resolution of 2.8 A (3K7Y). The structure was analysed, minimised using OPLS 2005 and prepared by Protein Preparation Wizard of Schrodinger 9.2. The validation of prepared protein 3D structure was done by Procheck and the percentage of disallowed region in Ramachandran plot was found negligible. Glide module of Schrodinger 9.2 was utilized for receptor grid generation which surrounds the active site residues as suggested by the literature. In the next step, compounds were downloaded from drug compound databases like PubChem. Compounds and Zinc database: These compound libraries were processed to achieve stable conformations in minimized or optimized states; this task was completed by LigPrep module of Schrodinger 9.2. Compounds are filtered in terms of Lipinski Rule, Reactive functional groups and other various filters of QikProp. These libraries were given as an input to the Virtual Screening Workflow of Schrodinger 9.2, which assembles High Throughput Virtual Screening (HTVS), Standard precision (SP), and Extra precision (XP) in the sequential events, allowing to find highest GScore and rank the top hits against the same receptor. Top compounds were recorded with their detailed predicted ADMET profile. With the results as per the prediction studies, it is believed that the reported molecules may serve as potent inhibitors against the target after biological assays and trials in future. Read more…