Identification and design of vinyl sulfone inhibitors against Cryptopain1-a cysteine protease from cryptosporidiosis-causing Cryptosporidium parvum
Banerjee, A.
Show abstract
Cryptosporidiosis, a disease marked by diarrhea in adults and stunted growth in children, is associated with the unicellular protozoan pathogen Cryptosporidium; often the species parvum. Cryptopain-1, a cysteine protease characterized in the genome of Cryptosporidium parvum, had been earlier shown to be inhibited by a vinyl sulfone compound called K11777 (or K-777). Cysteine proteases have long been established as valid drug targets, which can be covalently and selectively inhibited by vinyl sulfones. This computational study was initiated to identify purchasable vinyl sulfone compounds, which could possibly inhibit cryptopain-1 with higher efficacy than K11777. Docking simulations screened a number of such possibly better inhibitors. The work was furthered to probe the enzymatic pocket of cryptopain-1, through in-silico mutations, to derive a map of receptor-ligand interactions in the docked complexes. The idea was to provide crucial clues to aid the design of inhibitors, which would be able to bind the protease well by making favorable interactions with important residues of the enzyme. The analyses dictated placement of ligands towards the front of the enzymatic cleft, and disfavored interactions deep within. The S1 and S2 subsites of the enzyme preferred to remain occupied by polar ligand subgroups. Reasonably distanced ring systems and polar backbones of ligands were desired across the cleft. Large as well as inflexible subgroups were not tolerated. Double ringed systems such as substituted napthalene, especially in S1, were exceptions though. The S2 subsite, which is typically a specificity determinant in papain (C1) family cysteine proteases such as cathepsin L-like cryptopain-1, can possibly accommodate polar and hydrophobic ligand subgroups alike.
Matching journals
The top 9 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- Molecular Elucidation of Pancreatic Elastase Inhibition by Baicalein 97%
- De novo drug designing coupled with brute force screening and structure guided lead optimization gives highly specific inhibitor of METTL3: a potential cure for Acute Myeloid Leukaemia 96%
- Molecular and functional characterization of buffalo nasal epithelial odorant binding proteins and their structural insights by in-silico and biochemical approach 96%
Similar papers in this journal
- 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 97%
- Molecular docking, simulation and binding free energy analysis of small molecules as PfHT1 inhibitors 96%
- Prediction of Essential Binding Domains for the Endocannabinoid N-Arachidonoylethanolamine (AEA) in the Brain Cannabinoid CB1 receptor 96%
Similar papers in this journal
Similar papers in this journal
- Utilizing Heteroatom Types and Numbers from Extensive Ligand Libraries to Develop Novel hERG Blocker QSAR Models Using Machine Learning-based Classifiers 97%
- Chalcogen derivatives for the treatment of African trypanosomiasis: biological evaluation of thio and seleno- semicarbazones and their azole derivatives 96%
- Molecular Glue-Design-Evaluator (MOLDE): An Advanced Method for In-Silico Molecular Glue Design 94%
Similar papers in this journal
- Elucidation of Structural Mechanism of ATP Inhibition at the AAA1 Subunit of Cytoplasmic Dynein 1 Using a Chemical "Toolkit" 97%
- Structural Models for a Series of Allosteric Inhibitors of IGF1R Kinase 96%
- Two ligand-binding sites on SARS-CoV-2 non-structural protein 1 revealed by fragment-based x-ray screening 94%
"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.