» Articles » PMID: 36674953

Identification of Potential Druggable Targets and Structure-Based Virtual Screening for Drug-like Molecules Against the Shrimp Pathogen

Overview
Journal Int J Mol Sci
Publisher MDPI
Date 2023 Jan 21
PMID 36674953
Authors
Affiliations
Soon will be listed here.
Abstract

(EHP) causes slow growth syndrome in shrimp, resulting in huge economic losses for the global shrimp industry. Despite worldwide reports, there are no effective therapeutics for controlling EHP infections. In this study, five potential druggable targets of EHP, namely, aquaporin (AQP), cytidine triphosphate (CTP) synthase, thymidine kinase (TK), methionine aminopeptidase2 (MetAP2), and dihydrofolate reductase (DHFR), were identified via functional classification of the whole EHP proteome. The three-dimensional structures of the proteins were constructed using the artificial-intelligence-based program AlphaFold 2. Following the prediction of druggable sites, the ZINC15 and ChEMBL databases were screened against targets using docking-based virtual screening. Molecules with affinity scores ≥ 7.5 and numbers of interactions ≥ 9 were initially selected and subsequently enriched based on their ADMET properties and electrostatic complementarities. Five compounds were finally selected against each target based on their complex stabilities and binding energies. The compounds CHEMBL3703838, CHEMBL2132563, and CHEMBL133039 were selected against AQP; CHEMBL1091856, CHEMBL1162979, and CHEMBL525202 against CTP synthase; CHEMBL4078273, CHEMBL1683320, and CHEMBL3674540 against TK; CHEMBL340488, CHEMBL1966988, and ZINC000828645375 against DHFR; and CHEMBL3913373, ZINC000016682972, and CHEMBL3142997 against MetAP2.The compounds exhibited high stabilities and low binding free energies, indicating their abilities to suppress EHP infections; however, further validation is necessary for determining their efficacy.

Citing Articles

Lead generation of UPPS inhibitors targeting MRSA: Using 3D-QSAR pharmacophore modeling, virtual screening, molecular docking, and molecular dynamic simulations.

Qandeel B, Mowafy S, Abouzid K, Farag N BMC Chem. 2024; 18(1):14.

PMID: 38245752 PMC: 10800075. DOI: 10.1186/s13065-023-01110-1.

References
1.
Pires D, Veloso W, Myung Y, Rodrigues C, Silk M, Rezende P . EasyVS: a user-friendly web-based tool for molecule library selection and structure-based virtual screening. Bioinformatics. 2020; 36(14):4200-4202. DOI: 10.1093/bioinformatics/btaa480. View

2.
Wu Y, Chen J, Liao G, Hu M, Zhang Q, Meng X . Down-Regulation of Lipid Metabolism in the Hepatopancreas of Shrimp upon Light and Heavy Infection of : A Comparative Proteomic Study. Int J Mol Sci. 2022; 23(19). PMC: 9570011. DOI: 10.3390/ijms231911574. View

3.
Salachan P, Jaroenlak P, Thitamadee S, Itsathitphaisarn O, Sritunyalucksana K . Laboratory cohabitation challenge model for shrimp hepatopancreatic microsporidiosis (HPM) caused by Enterocytozoon hepatopenaei (EHP). BMC Vet Res. 2017; 13(1):9. PMC: 5216530. DOI: 10.1186/s12917-016-0923-1. View

4.
Salin N, Noordin R, Al-Najjar B, Kamarulzaman E, Yunus M, Karim I . Identification of potential dual -targets anti- toxoplasma gondii compounds through structure-based virtual screening and in-vitro studies. PLoS One. 2020; 15(5):e0225232. PMC: 7244133. DOI: 10.1371/journal.pone.0225232. View

5.
Cui H, Carrero-Lerida J, Silva A, Whittingham J, Brannigan J, Ruiz-Perez L . Synthesis and evaluation of α-thymidine analogues as novel antimalarials. J Med Chem. 2012; 55(24):10948-57. PMC: 3530961. DOI: 10.1021/jm301328h. View