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Identification of novel anti-cryptosporidial inhibitors through a combined approach of pharmacophore modeling, virtual screening, and molecular docking
- Source :
- Informatics in Medicine Unlocked, Vol 24, Iss, Pp 100583-(2021)
- Publication Year :
- 2021
- Publisher :
- Elsevier, 2021.
-
Abstract
- Background and objective Cryptosporidiosis is a diarrheal disease that affects millions of people worldwide and can cause dire effects in immunocompromised, HIV/AIDS patients and younger children. Cryptosporidium species are causative agents for cryptosporidiosis. The presently available chemotherapeutic options are not fully effective in curbing the menace of disease in all patients. The deprived experimental traceability of the pathogen, lack of a suitable in-vivo model are few factors that hindered the development of reliable chemotherapeutic options despite continuous efforts. The underway COVID-19 pandemic widens this gap as most of the scientific resources and researches shifted priority. The genome sequencing of the Cryptosporidium parvum (C. parvum) has discovered many new targets, such as Inosine 5′-Monophosphate Dehydrogenase (IMPDH), Lactate Dehydrogenase and many more. The parasite uses the host adenosine pool to synthesize guanine nucleotide in a streamlined pathway, where IMPDH catalyzes the first rate-limiting step. The present study aims to discover new anti-cryptosporidial agents that work against the IMPDH of the parasite. Methodology and results In this study, The PharmaGist ( https://bioinfo3d.cs.tau.ac.il/PharmaGist/ ) tool was deployed for the pharmacophore model generation employing previously reported Cryptosporidium parvum IMPDH (CpIMPDH) inhibitors having IC50 values ranging from 0.009 μM to 0.028 μM. The model having the highest scores was used as a 3D query for high throughput screening of the Zinc database via ZINC pharmer ( http://zincpharmer.csb.pitt.edu/ ) tool. The screened 'hits' were further subjected to molecular docking in the active site of CpIMPDH (PDB ID: 4IXH ), Lipinski's rule of 5, and SwissADME ( http://www.swissadme.ch/ ) filter. Finally, the best three 'hits' or proposed leads (ZINC09672610, ZINC16511373, and ZINC39780256) docked CpIMPDH were further subjected to 50 ns molecular dynamic simulation (MDL) analysis for stability analysis. Conclusion and significance The ZINC09672610 and ZINC39780256 compounds show excellent in-silico inhibitory efficacy against CpIMPDH. These compounds were used as a starting point for the discovery and development of new anti-cryptosporidial compounds. Future anti-cryptosporidial agents could be designed by utilizing these three molecules.
- Subjects :
- 0301 basic medicine
Virtual screening
biology
Coronavirus disease 2019 (COVID-19)
Pharmacophore
High-throughput screening
Computer applications to medicine. Medical informatics
Protein Data Bank (RCSB PDB)
R858-859.7
Cryptosporidiosis
COVID-19 pandemic
Health Informatics
Computational biology
biology.organism_classification
03 medical and health sciences
030104 developmental biology
0302 clinical medicine
Cryptosporidium parvum
030220 oncology & carcinogenesis
Molecular docking
Lipinski's rule of five
Identification (biology)
Inosine 5′-Monophosphate dehydrogenase
Subjects
Details
- Language :
- English
- ISSN :
- 23529148
- Volume :
- 24
- Database :
- OpenAIRE
- Journal :
- Informatics in Medicine Unlocked
- Accession number :
- edsair.doi.dedup.....850f797a43698e14c94195dca05d5b2e