Predicting and Designing therapeutics against the Nipah virus

Abstract

Though every outbreak of the Nipah Virus has resulted in high mortality rates (>70% in Southeast Asia), there are no licensed drugs against it. In this study we have considered all 9 Nipah proteins as potential therapeutic targets and computationally identified putative peptides (against G, F, and M proteins) and small molecules inhibitors (against F, G, M, N, and P proteins). The computations include extensive homology/ab initio modelling, peptide design and small molecule docking. An important contribution of this study is the increased structural characterization of Nipah proteins by approximately 90% of what is deposited in the PDB. In addition, we have carried out molecular dynamics simulations on all the designed protein-peptide complexes to check for stability and to estimate binding strengths. Details, including atomic coordinates of all the proteins and their ligand bound complexes, can be accessed at http://cospi.iiserpune.ac.in/Nipah. Our strategy was to tackle the development of therapeutics on a proteome wide scale and the lead compounds identified could be attractive starting points for drug development. To this end, we have designed 4 peptide inhibitors and predicted 70 small molecules (13 with high confidence) against 3 and 5 Nipah proteins respectively. To counter the threat of drug resistance, we have analyzed the sequences of the viral strains from different outbreaks, to check whether they would be sensitive to the binding of the proposed inhibitors.\n\nAuthor SummaryNipah virus infections have killed 72-86% of the infected individuals in Bangladesh and India. The infections are spread via bodily secretions of bats, pigs and other infected individuals. Even though, the disease was first detected in the human population in 1998, there are no approved drugs/vaccines against it. In this study, we have tried to model the 3D structures of the Nipah virus proteins. We have then used these models to design/predict small inhibitory molecules that would bind them and prevent their function. We have also analyzed the different strains of the virus to identify conservation patterns of amino acids in the proteins, which in turn informs us of the efficacy of the drugs. The designed/docked compounds as well as the protein models are freely accessible for experimental validation and hypothesis testing.