Novel inhibitors designing against the potential drug target of Plasmodium falciparum M17 Leucyl Aminopeptidase - PfM17LAP
Dabburu, G. R.; Kumar, M.; Subbarao, N.
Show abstract
Malaria is one of the major disease of concern worldwide especially in the African regions. According to the recent WHO reports, African regions share 95% of the total deaths worldwide that occurs due to malaria. Plasmodium falciparum M17 Leucyl Aminopeptidase (PfM17LAP) plays an important role in the regulation of amino acids release and for the survival of the parasite. We performed molecular docking and simulation studies to find the potential inhibitors against PfM17LAP using ChEMBL antimalarial library. Molecular docking studies and post-docking analysis revealed that molecules CHEMBL369831 and CHEMBL176888 showed better binding than the reference molecule BESTATIN. LibDock and X-SCORES of molecules BES, CHEMBL369831 and CHEMBL176888 are 130.071, 230.38, 223.56 and -8.75 Kcal/mol, -10.90 Kcal/mol, -11.05 Kcal/mol respectively. ADMET profiling of the top ten ranked molecules was done by using the Discovery Studio. Molecular dynamic studies revealed that the complex PfM17LAP-CHEMBL369831 is stable throughout the simulation. Finally, we have reported novel inhibitors which possess more binding affinity towards PfM17LAP.
Matching journals
The top 6 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- Pharmacophore modeling, 2D-QSAR, Molecular Docking and ADME studies for the discovery of inhibitors of PBP2a in MRSA 98%
- Molecular Docking studies of Phytocompounds of Rheum emodi Wall with proteins responsible for antibiotic resistance in bacterial and fungal pathogens: In silico approach to enhance the bio-availability of antibiotics 98%
- A program to automate the discovery of drugs for West Nile and Dengue virus -- programmatic screening of over a billion compounds on PubChem, generation of drug leads and automated In Silico modelling 97%
Similar papers in this journal
- Identification of Natural Antiviral Drug Candidates Against Tilapia Lake Virus: Computational Drug Design Approaches 97%
- Molecular docking, simulation and binding free energy analysis of small molecules as PfHT1 inhibitors 97%
- Deep learning based predictive modeling to screen natural compounds against TNF-alpha for the potential management of Rheumatoid Arthritis: Virtual screening to comprehensive in silico investigation 96%
Similar papers in this journal
- Mechanistic insights into the Japanese Encephalitis Virus RNA dependent RNA polymerase protein inhibition by bioflavonoids from Azadirachta indica 95%
- Identification of multi-targeting and synergistic neuromodulators of epilepsy associated protein-targets in Ayurvedic herbs using network pharmacological approach 94%
- Machine learning prediction of antiviral-HPV protein interactions for anti-HPV pharmacotherapy 94%
Similar papers in this journal
- Mitoxantrone dihydrochloride, an FDA approved drug, binds with SARS-CoV-2 NSP1 C-terminal 95%
- Whole Genome Sequencing for Revealing the Point Mutations of SARS-CoV-2 Genome in Bangladeshi Isolates and their Structural Effects on Viral Proteins 94%
- Refining physico-chemical rules for herbicides using an antimalarial library 91%
Similar papers in this journal
- Analyses of spike protein from first deposited sequences of SARS-CoV2 from West Bengal, India 94%
- Glibenclamide, ATP and Metformin Increases the Expression of Human Bile Salt Export Pump ABCB11 94%
- SNPector: SNP inspection tool for diagnosing gene pathogenicity and drug response in a naked sequence 92%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.