Identification of dengue viral RNA-dependent RNA polymerase inhibitor using computational fragment-based approaches and molecular dynamics study

Abstract

Dengue is a major public health concern in tropical and subtropical countries of the world. There are no specific drugs available to treat dengue. Even though several candidates targeted both viral and host proteins to overcome dengue infection, they have not yet entered into the later stages of clinical trials. In order to design a drug for dengue fever, newly emerged fragment-based drug designing technique was applied. RNA-dependent RNA polymerase, which is essential for dengue viral replication is chosen as a drug target for dengue drug discovery. A cascade of methods, fragment screening, fragment growing, and fragment linking revealed the compound [2-(4-carbamoylpiperidin-1-yl)-2-oxoethyl]8-(1,3-benzothiazol-2-yl)naphthalene-1-carboxylate as a potent dengue viral polymerase inhibitor. Both strain energy and binding free energy calculations predicted that this could be a better inhibitor than the existing ones. Molecular dynamics simulation studies showed that the dengue polymerase–lead complex is stable and their interactions are consistent throughout the simulation. The hydrogen-bonded interactions formed by the residues Arg792, Thr794, Ser796, and Asn405 are the primary contributors for the stability and the rigidity of the polymerase–lead complex. This might keep the polymerase in closed conformation and thus inhibits viral replication. Hence, this might be a promising lead molecule for dengue drug designing. Further optimization of this lead molecule would result in a potent drug for dengue.

Keywords:

• dengue
• RNA-dependent RNA polymerase
• fragment-based drug designing
• fragment growing
• fragment linking
• lead molecule
• substructure search
• neighborhood search
• fragment library
• molecular dynamics simulation

Acknowledgments

We thank High Performance Computing and Indian Institute of Technology Madras for computational facilities and Department of Biotechnology (DBT), Government of India, New Delhi, for Bioinformatics Infrastructure Facility (Madras University and Indian Institute of Technology Madras). We thank Professor KK. Balasubramanian for fruitful discussions.

Disclosure statement

The authors declare that they have no conflict of interest.

Funding

This work was supported by the Department of Science and Technology (DST), Government of India, New Delhi [grant number SR/WOS/LS62/2013].