The WRKY transcription factors are a class of DNA-binding proteins involved in diverse plant processes play critical roles in response to abiotic and biotic stresses. Genome-wide divergence analysis of WRKY gene family in Hordeum vulgare provided a framework for molecular evolution and functional roles. So far, the crystal structure of WRKY from barley has not been resolved; moreover, knowledge of the three-dimensional structure of WRKY domain is pre-requisites for exploring the protein-DNA recognition mechanisms. Homology modelling based approach was used to generate structures for WRKY DNA binding domain (DBD) and its variants using AtWRKY1 as a template. Finally, the stability and conformational changes of the generated model in unbound and bound form was examined through atomistic molecular dynamics (MD) simulations for 100 ns time period. In this study, we investigated the comparative binding pattern of WRKY domain and its variants with W-box cis-regulatory element using molecular docking and dynamics (MD) simulations assays. The atomic insight into WRKY domain exhibited significant variation in the intermolecular hydrogen bonding pattern, leading to the structural anomalies in the variant type and differences in the DNA-binding specificities. Based on the MD analysis, residual contribution and interaction contour, wild-type WRKY (HvWRKY46) were found to interact with DNA through highly conserved heptapeptide in the pre- and post-MD simulated complexes, whereas heptapeptide interaction with DNA was missing in variants (I and II) in post-MD complexes. Consequently, through principal component analysis, wild-type WRKY was also found to be more stable by obscuring a reduced conformational space than the variant I (HvWRKY34). Lastly, high binding free energy for wild-type and variant II allowed us to conclude that wild-type WRKY-DNA complex was more stable relative to variants I. The results of our study revealed complete dynamic and structural information about WRKY domain-DNA interactions. However, no structure base information reported to date for WRKY variants and their mechanism of interaction with DNA. Our findings highlighted the importance of selecting a sequence to generate newer transgenic plants that would be increasingly tolerance to stress conditions.

Background: Nuclear Factor kappa B (NF-κB) is a transcription factor involved in the regulation of cell signaling responses and is a key regulator of cellular processes involved in the immune response, differentiation, cell proliferation, and apoptosis. The constitutive activation of NF-κB contributes to multiple cellular outcomes and pathophysiological conditions such as rheumatoid arthritis, asthma, inflammatory bowel disease, AIDS and cancer. Thus there lies a huge therapeutic potential beneath inhibition of NF-κB signalling pathway for reducing these chronic ailments. Withania somnifera, a reputed herb in ayurvedic medicine, comprises a large number of steroidal lactones known as withanolides which show plethora of pharmacological activities like anti- inflammatory, antitumor, antibacterial, antioxidant, anticonvulsive, and immunosuppressive. Though a few studies have been reported depicting the effect of WA (withaferin A) on suppression of NF-κB activation, the mechanism behind this is still eluding the researchers. The study conducted here is an attempt to explore NF-κB signalling pathway modulating capability of Withania somnifera’s major constituent WA and to elucidate its possible mode of action using molecular docking and molecular dynamics simulations studies. Results: Formation of active IKK (IκB kinase) complex comprising NEMO (NF-κB Essential Modulator) and IKKβ subunits is one of the essential steps for NF-κB signalling pathway, non-assembly of which can lead to prevention of the above mentioned vulnerable disorders. As observed from our semi-flexible docking analysis, WA forms strong intermolecular interactions with the NEMO chains thus building steric as well as thermodynamic barriers to the incoming IKKβ subunits, which in turn pave way to naive complex formation capability of NEMO with IKKβ. Docking of WA into active NEMO/IKKβ complex using flexible docking in which key residues of the complex were kept flexible also suggest the disruption of the active complex. Thus the molecular docking analysis of WA into NEMO and active NEMO/IKKβ complex conducted in this study provides significant evidence in support of the proposed mechanism of NF-κB activation suppression by inhibition or disruption of active NEMO/IKKβ complex formation being accounted by non-assembly of the catalytically active NEMO/IKKβ complex. Results from the molecular dynamics simulations in water show that the trajectories of the native protein and the protein complexed with WA are stable over a considerably long time period of 2.6 ns. Conclusions: NF-κB is one of the most attractive topics in current biological, biochemical, and pharmacological research, and in the recent years the number of studies focusing on its inhibition/regulation has increased manifolds. Small ligands (both natural and synthetic) are gaining particular attention in this context. Our computational analysis provided a rationalization of the ability of naturally occurring withaferin A to alter the NF-κB signalling pathway along with its proposed mode of inhibition of the pathway. The absence of active IKK multisubunit complex would prevent degradation of IκB proteins, as the IκB proteins would not get phosphorylated by IKK. This would ultimately lead to non-release of NF-κB and its further translocation to the nucleus thus arresting its nefarious acts. Conclusively our results strongly suggest that withaferin A is a potent anticancer agent as ascertained by its potent NF-κB modulating capability. Moreover the present MD simulations made clear the dynamic structural stability of NEMO/IKKβ in complex with the drug WA, together with the inhibitory mechanism.

P53, a tumor suppressor protein, has been proven to regulate the cell cycle, apoptosis, and DNA repair to prevent malignant transformation. MDM2 regulates activity of p53 and inhibits its binding to DNA. In the present study, we elucidated the MDM2 inhibition potential of polyphenols (Apigenin, Fisetin, Galangin and Luteolin) by MD simulation and MM/PBSA free energy calculations. All polyphenols bind to hydrophobic groove of MDM2 and the binding was found to be stable throughout MD simulation. Luteolin showed the highest negative binding free energy value of -173.80 kJ/mol followed by Fisetin with value of -172.25 kJ/mol. It was found by free energy calculations, that hydrophobic interactions (vdW energy) have major contribution in binding free energy.

Tuberculosis is one the oldest known affliction of mankind caused by the pathogenMycobacterium tuberculosis. Till date, there is no absolute single treatment available to deal with the pathogen, which has acquired a great potential to develop drug resistance rapidly. BCG is the only anti-tuberculosis vaccine available till date which displays limited global efficacy due to genetic variation and concurrent pathogen infections. Extracellular vesicles or exosomes vesicle (EVs) lie at the frontier cellular talk between pathogen and the host, and therefore play a significant role in establishing pathogenesis. In the present study, an in-silico approach has been adopted to construct a multi-epitope vaccine from selected immunogenic EVs proteins to elicit a cellular as well as a humoral immune response. Our designed vaccine has wide population coverage and can effectively compensate for the genetic variation among different populations. For maximum efficacy and minimum adverse effects possibilities the antigenic, non-allergenic and non-toxic B-cell, HTL and CTL epitopes from experimentally proven EVs proteins were selected for the vaccine construct. TLR4 agonist RpfE served as an adjuvant for the vaccine construct. The vaccine construct structure was modelled, refined and docked on TLR4 immune receptor. The designed vaccine construct displayed safe usage and exhibits a high probability to elicit the critical immune regulators, like B cells, T-cells and memory cells as displayed by the in-silico immunization assays. Therefore, it can be further corroborated using in vitro and in vivo assays to fulfil the global need for a more efficacious anti-tuberculosis vaccine.

Adverse drug reactions (ADRs) have become one of the primary reasons for the failure of drugs and a leading cause of deaths. Owing to the severe effects of ADRs, there is an urgent need for the generation of effective models which can accurately predict ADRs during early stages of drug development based on integration of various features of drugs. In the current study, we have focused on neurological ADRs and have used various properties of drugs that include biological properties (targets, transporters and enzymes), chemical properties (substructure fingerprints), phenotypic properties (side effects (SE) and therapeutic indications) and a combinations of the two and three levels of features. We employed relief-based feature selection technique to identify relevant properties and used machine learning approach to generated learned model systems which would predict neurological ADRs prior to preclinical testing. Additionally, in order to explain the efficiency and applicability of the models, we tested them to predict the ADRs for already existing anti-Alzheimer drugs and uncharacterized drugs, respectively in side effect resource (SIDER) database. The generated models were highly accurate and our results showed that the models based on chemical (accuracy 93.20%), phenotypic (accuracy 92.41%) and combination of three properties (accuracy 94.18%) were highly accurate while the models based on biological properties (accuracy 82.11%) were highly informative.