Computational modeling of the bat HKU4 coronavirus 3CLpro inhibitors as a tool for the development of antivirals against the emerging Middle East respiratory syndrome (MERS) coronavirus

Areej Abuhammad; Rua'a A Al-Aqtash; Brandon J Anson; Andrew D Mesecar; Mutasem O Taha

doi:10.1002/jmr.2644

Computational modeling of the bat HKU4 coronavirus 3CL^pro inhibitors as a tool for the development of antivirals against the emerging Middle East respiratory syndrome (MERS) coronavirus

J Mol Recognit. 2017 Nov;30(11):e2644. doi: 10.1002/jmr.2644. Epub 2017 Jun 13.

Authors

Areej Abuhammad¹, Rua'a A Al-Aqtash¹, Brandon J Anson², Andrew D Mesecar^{2

3

4}, Mutasem O Taha¹

Affiliations

¹ Department of Pharmaceutical Sciences, School of Pharmacy, The University of Jordan, Amman, Jordan.
² Department of Biological Sciences, Purdue University, West Lafayette, IN, USA.
³ Department of Chemistry, Purdue University, West Lafayette, IN, USA.
⁴ Centers for Cancer Research & Drug Discovery, Purdue University, West Lafayette, IN, USA.

Abstract

The Middle East respiratory syndrome coronavirus (MERS-CoV) is an emerging virus that poses a major challenge to clinical management. The 3C-like protease (3CL^pro ) is essential for viral replication and thus represents a potential target for antiviral drug development. Presently, very few data are available on MERS-CoV 3CL^pro inhibition by small molecules. We conducted extensive exploration of the pharmacophoric space of a recently identified set of peptidomimetic inhibitors of the bat HKU4-CoV 3CL^pro . HKU4-CoV 3CL^pro shares high sequence identity (81%) with the MERS-CoV enzyme and thus represents a potential surrogate model for anti-MERS drug discovery. We used 2 well-established methods: Quantitative structure-activity relationship (QSAR)-guided modeling and docking-based comparative intermolecular contacts analysis. The established pharmacophore models highlight structural features needed for ligand recognition and revealed important binding-pocket regions involved in 3CL^pro -ligand interactions. The best models were used as 3D queries to screen the National Cancer Institute database for novel nonpeptidomimetic 3CL^pro inhibitors. The identified hits were tested for HKU4-CoV and MERS-CoV 3CL^pro inhibition. Two hits, which share the phenylsulfonamide fragment, showed moderate inhibitory activity against the MERS-CoV 3CL^pro and represent a potential starting point for the development of novel anti-MERS agents. To the best of our knowledge, this is the first pharmacophore modeling study supported by in vitro validation on the MERS-CoV 3CL^pro .

Highlights: MERS-CoV is an emerging virus that is closely related to the bat HKU4-CoV. 3CL^pro is a potential drug target for coronavirus infection. HKU4-CoV 3CL^pro is a useful surrogate model for the identification of MERS-CoV 3CL^pro enzyme inhibitors. dbCICA is a very robust modeling method for hit identification. The phenylsulfonamide scaffold represents a potential starting point for MERS coronavirus 3CL^pro inhibitors development.

Keywords: 3CLpro inhibitors; MERS; coronavirus; dbCICA; pharmacophore modeling.

Publication types

Research Support, U.S. Gov't, Non-P.H.S.

MeSH terms

Amino Acid Sequence
Animals
Antiviral Agents / pharmacology*
Betacoronavirus / drug effects
Betacoronavirus / enzymology*
Binding Sites
Chiroptera / virology*
Computer Simulation
Ligands
Middle East Respiratory Syndrome Coronavirus / drug effects*
Models, Molecular
Protease Inhibitors / chemistry
Protease Inhibitors / pharmacology*
Quantitative Structure-Activity Relationship
ROC Curve
Reproducibility of Results
Viral Proteins / antagonists & inhibitors*
Viral Proteins / chemistry

Substances

Antiviral Agents
Ligands
Protease Inhibitors
Viral Proteins