Identification of sequence motifs involved in Dengue virus-host interactions

Compact Genetic Algorithm-Based Feature Selection for Sequence-Based Prediction of Dengue-Human Protein Interactions

Dengue Virus (DENV) infection is one of the rapidly spreading mosquito-borne viral infections in humans. Every year, around 50 million people get affected by DENV infection, resulting in 20,000 deaths. Despite the recent experiments focusing on dengue infection to understand its functionality in the human body, several functionally important DENV-human protein-protein interactions (PPIs) have remained unrecognized. This article presents a model for predicting new DENV-human PPIs by combining different sequence-based features of human and dengue proteins like the amino acid composition, dipeptide composition, conjoint triad, pseudo amino acid composition, and pairwise sequence similarity between dengue and human proteins. A Learning vector quantization (LVQ)-based Compact Genetic Algorithm (CGA) model is proposed for feature subset selection. CGA is a probabilistic technique that simulates the behavior of a Genetic Algorithm (GA) with lesser memory and time requirements. Prediction of DENV-human PPIs is performed by the weighted Random Forest (RF) technique as it is found to perform better than other classifiers. We have predicted 1013 PPIs between 335 human proteins and 10 dengue proteins. All predicted interactions are validated by literature filtering, GO-based assessment, and KEGG Pathway enrichment analysis. This study will encourage the identification of potential targets for more effective anti-dengue drug discovery.

Using bioinformatics tools for the discovery of Dengue RNA-dependent RNA polymerase inhibitors

Background

Dengue fever has rapidly manifested into a serious global health concern. The emergence of various viral serotypes has prompted the urgent need for innovative drug design techniques. Of the viral non-structural enzymes, the NS5 RNA-dependent RNA polymerase has been established as a promising target due to its lack of an enzymatic counterpart in mammalian cells and its conserved structure amongst all serotypes. The onus is now on scientists to probe further into understanding this enzyme and its mechanism of action. The field of bioinformatics has evolved greatly over recent decades, with updated drug design tools now being publically available.

Methods

In this study, bioinformatics tools were used to provide a comprehensive sequence and structural analysis of the two most prominent serotypes of Dengue RNA-dependent RNA polymerase. A list of popular flavivirus inhibitors were also chosen to dock to the active site of the enzyme. The best docked compound was then used as a template to generate a pharmacophore model that may assist in the design of target-specific Dengue virus inhibitors.

Results

Comparative sequence alignment exhibited similarity between all three domains of serotype 2 and 3.Sequence analysis revealed highly conserved regions at residues Meth530, Thr543 Asp597, Glu616, Arg659 and Pro671. Mapping of the active site demonstrated two highly conserved residues: Ser710 and Arg729. Of the active site interacting residues, Ser796 was common amongst all ten docked compounds, indicating its importance in the drug design process. Of the ten docked flavivirus inhibitors, NITD-203 showed the best binding affinity to the active site. Further pharmacophore modeling of NITD-203 depicted significant pharmacophoric elements that are necessary for stable binding to the active site.

Discussion

This study utilized publically available bioinformatics tools to provide a comprehensive framework on Dengue RNA-dependent RNA polymerase. Based on docking studies, a pharmacophore model was also designed to unveil the crucial pharmacophoric elements that are required when constructing an efficacious DENV inhibitor. We believe that this study will be a cornerstone in paving the road toward the design of target-specific inhibitors against DENV RdRp.

A synthetic peptide derived from domain III envelope glycoprotein of Dengue virus induces neutralizing antibody

Dengue virus (DENV) is an arthropod-borne human pathogen that represents a severe public health threat in both endemic and non-endemic regions. So far, there is no licensed vaccine or specific drugs available for dengue fever. A fifteen-amino-acid-long peptide that includes the NGR motif was chemically synthesized and conjugated with keyhole limpet hemocyanin. A standard immunization protocol was followed for the production of polyclonal antibodies by immunizing rabbits against the synthetic peptide. The immune response elicited high-titer polyclonal antibodies with the reactivity of the anti-peptide antibody against both synthetic peptide and four serotypes of DENV confirmed by DOT-ELISA. Neutralizing activity of anti-peptide antibody was found to be cross-reactive and effective resulting in 60% reduction of infectivity at 1:200 dilution in all four serotypes of DENV. Our findings have the potential to further improve our understanding of virus-host interactions and provide new insights into neutralizing antibodies and could also be used as a drug target.

Molecular docking NS4B of DENV 1-4 with known bioactive phyto-chemicals

Dengue disease is a global disease that has no effective treatment. The dengue virus (DENV) NS4B is a target for designing specific antivirals due to its importance in viral replication. Medicinal plants have been a savior for dengue virus as they consist of a class of phytochemicals having anti-viral activity and can pose a new approach ofstrong drug against viruses. The present study analyzes the activity of compounds against NS4B of DENV (1-4) serotypes. In this study Catechin, Cianidanol, Epicatechin, Eupatoretin, Glabranin, Laurifolin, DL-Catechin, astherapeutic agents were filtered by using Lipinski rule's five and the drug-likeness property of these agents were used for assessment of pharmacological properties. The molecular docking results presented the 2-D structures of bioactive complex, which interacted with especially conserved residues of target domains. Interestingly, we find the Catechin, Laurifolin, Cianidanol have highest binding energy against NS4B in DENV-1,2,4 which is evident by the formation of more hydrogen bonds with the amino acid residues at the binding site of the receptor. Our results revealed that the bioactive compound, especially Catechin has significant anti-dengue activities. In addition, this study may be helpful in further experimental investigations.