title: A knowledge-based approach for identification of drugs against vivapain-2 protein of Plasmodium vivax through pharmacophore-based virtual screening with comparative modelling.
abstract: Malaria is one of the most infectious diseases in the world. Plasmodium vivax, the pathogen causing endemic malaria in humans worldwide, is responsible for extensive disease morbidity. Due to the emergence of resistance to common anti-malarial drugs, there is a continuous need to develop a new class of drugs for this pathogen. P. vivax cysteine protease, also known as vivapain-2, plays an important role in haemoglobin hydrolysis and is considered essential for the survival of the parasite. The three-dimensional (3D) structure of vivapain-2 is not predicted experimentally, so its structure is modelled by using comparative modelling approach and further validated by Qualitative Model Energy Analysis (QMEAN) and RAMPAGE tools. The potential binding site of selected vivapain-2 structure has been detected by grid-based function prediction method. Drug targets and their respective drugs similar to vivapain-2 have been identified using three publicly available databases: STITCH 3.1, DrugBank and Therapeutic Target Database (TTD). The second approach of this work focuses on docking study of selected drug E-64 against vivapain-2 protein. Docking reveals crucial information about key residues (Asn281, Cys283, Val396 and Asp398) that are responsible for holding the ligand in the active site. The similarity-search criterion is used for the preparation of our in-house database of drugs, obtained from filtering the drugs from the DrugBank database. A five-point 3D pharmacophore model is generated for the docked complex of vivapain-2 with E-64. This study of 3D pharmacophore-based virtual screening results in identifying three new drugs, amongst which one is approved and the other two are experimentally proved. The ADMET properties of these drugs are found to be in the desired range. These drugs with novel scaffolds may act as potent drugs for treating malaria caused by P. vivax.
authors: Department of Bioinformatics, MMV, Banaras Hindu University, Varanasi, 221005, India, manojiids@gmail.com.
authors: Manoj Kumar
authors: MK
authors: Yadav
authors: Amisha
authors: A
authors: Singh
authors: D
authors: D
authors: Swati
mesh_terms: D000595:Amino Acid Sequence; D000962:Antimalarials / Q000737:chemistry* / Q000378:metabolism / Q000494:pharmacology*; D001665:Binding Sites; D020134:Catalytic Domain; D057056:Cysteine Proteases / Q000737:chemistry* / Q000235:genetics / Q000378:metabolism; D015853:Cysteine Proteinase Inhibitors / Q000737:chemistry* / Q000494:pharmacology*; D016208:Databases, Factual; D004353:Drug Evaluation, Preclinical / Q000295:instrumentation / Q000379:methods*; D006801:Humans; D016780:Malaria, Vivax / Q000469:parasitology; D008958:Models, Molecular; D008969:Molecular Sequence Data; D010966:Plasmodium vivax / Q000737:chemistry / Q000187:drug effects / Q000201:enzymology* / Q000235:genetics; D015800:Protozoan Proteins / Q000037:antagonists & inhibitors / Q000737:chemistry* / Q000235:genetics / Q000378:metabolism; D016415:Sequence Alignment
chemical_list: D000962:Antimalarials; D015853:Cysteine Proteinase Inhibitors; D015800:Protozoan Proteins; D057056:Cysteine Proteases