The maximum RMSD value of the native E2 protein was 1.79?nm at 33?ns and the plot of RMSD trajectories was stabilized at 40?ns. compounds in terms of potential entry inhibitor for CHIKV. Further, these results should be confirmed by comprehensive cell culture, cytotoxic assays and animal experiments. Certain derivatives of phenothiazines can also be explored in future studies for entry inhibitors against CHIKV. The present investigation thus provides insight into protein structural dynamics of the envelope protein of CHIKV. In addition the study also provides information on the dynamics of interaction of E2 protein with entry inhibitors that will contribute towards structure based drug design. and mosquitoes [3]. CHIKV is endemic in many parts of the world including Africa, Asia and tropical regions of America [43]. Nearly 94 countries were identified with substantial CHIKV infection in a recent investigation [26]. It was also estimated that around 1.3 billion people are living in risk areas for CHIKV transmission [26]. The CHIKV has been reported from more than 40 countries in the Americas with over 1 million infections in last 2?years [43]. The largest outbreak of CHIKV occurred during 2004C2009 in Indian Ocean region involving INCB39110 (Itacitinib) millions of people [41]. Chikungunya virus is a member of alphavirus genus in the Togaviridae family. The genome of CHIKV is single stranded positive sense RNA of approximately 11.8?kb in length. The genomic RNA is capped and polyadenylated, and encodes two open reading frames (ORFs) [13]. The 5 ORF encodes four non-structural proteins (nsP1, nsP2, nsP3 and nsP4) and 3 ORF encodes the structural polyprotein that is cleaved into the capsid, small polypeptide 6K, E3 and the envelope glycoproteins E2 and E1 [35]. The mature virion is 70?nm in diameter and contains trimeric spikes of E1 and E2 proteins on its surface [25]. The E2 protein is involved in attachment of the virion and E1 protein helps in viral fusion with the host cell [36]. No vaccines or antiviral drugs are available for the Chikungunya virus infection. Therefore, in realization of the true disease burden it is important to screen large number of compounds for their inhibitory effects on the INCB39110 (Itacitinib) virus. Many studies have investigated the inhibitory effect of various compounds, but none of them have been found to have significant anti-CHIKV activity in animal models [1]. In addition, the in vitro study of such large number of compounds is laborious, time consuming, and costly. Therefore, it is convenient to use the computational approaches to screen out lead compounds. Such lead compounds can then be investigated in detail using experimental approaches. A potential anti-viral strategy against CHIKV involves the inhibition of the viral entry Mouse monoclonal to Cyclin E2 that involves E1 and E2 proteins. The present investigation was thus planned to determine the structure of the E2 protein of Chikungunya virus using computational methods. Molecular docking and MD simulations of the E2 protein-inhibitors (i.e. phenothiazine and bafilomycin) was also carried out to investigate the dynamics of interaction. Identification of the inhibitors of Chikungunya virus infection will contribute towards structure based drug design approaches. Material and methods Sequence analysis The sequence of E2 protein of Chikungunya virus (S27 African strain) was retrieved from NCBI (Accession number: “type”:”entrez-nucleotide”,”attrs”:”text”:”AF339485″,”term_id”:”28193962″,”term_text”:”AF339485″AF339485). This protein sequence was studied through several bioinformatics tools for the present study. The secondary structure of the E2 protein was analyzed with Psipred [23] ( Protein glycosylation is important for secretion, localization and stability of the protein. Therefore, N-linked glycosylation sites were predicted using NetNGlyc 1.0 Server ( In addition, the O-linked glycosylation were also predicted using NetOGlyc 4.0 server ( Structure prediction and validation Homology modeling is a computational method used to predict the two as well as three dimensional structure of a protein sequence based on the template protein. The quality of generated model depends on identity between the target and template proteins. The three dimensional structure of E2 protein was identified using a Discovery Studio (DS 4.0) module MODELLER [15]. Phyre2 and iTASSER servers were used to increase the accuracy of the generated model. The most accurate model was evaluated on the basis of root mean square deviation (RMSD), C-score and TM score. The selected model was refined using CHARMm [45] and energy minimization was done using ChiRotor algorithm of DS. The GROMOS [44] algorithm implemented in DeepView [19] was used for energy minimization of the predicted E2 structure. The three dimensional models were validated by PROCHECK in SAVeS server [21, 22]. PROCHECK server validates the quality of INCB39110 (Itacitinib) the structural model by the Z-score which indicate the overall model quality. The Ramachandran plot between the psi/phi. INCB39110 (Itacitinib)