3 research outputs found

    Antiviral actions of natural compounds against dengue virus RNA dependent RNA polymerase: insights from molecular dynamics and Gibbs free energy landscape

    No full text
    Dengue fever, a major global health challenge, affects nearly half the world’s population and lacks effective treatments or vaccines. Addressing this, our study focused on natural compounds that potentially inhibit the dengue virus’s RNA-dependent RNA polymerase (RdRp), a crucial target in the viral replication cycle. Utilizing the MTiOpenScreen webserver, we screened 1226 natural compounds from the NP-lib database. This screening identified four promising compounds ZINC000059779788, ZINC0000044404209, ZINC0000253504517 and ZINC0000253499146), each demonstrating high negative binding energies between −10.4 and −9.9 kcal/mol, indicative of strong potential as RdRp inhibitors. These compounds underwent rigorous validation through re-docking and a detailed 100 ns molecular dynamics (MD) simulation. This analysis affirmed the dynamic stability of the protein-ligand complexes, a critical factor in the effectiveness of potential drug candidates. Additionally, we conducted essential dynamics and free energy landscape calculations to understand the structural transitions in the RdRp protein upon ligand binding, providing valuable insights into the mechanism of inhibition. Our findings present these natural molecules as promising therapeutic agents against the dengue virus. By targeting the allosteric site of RdRp, these compounds offer a novel approach to hinder the viral replication process. This research significantly contributes to the search for effective anti-dengue treatments, positioning natural compounds as potential key players in dengue virus control strategies. Communicated by Ramaswamy H. Sarma</p

    Antifungal drug discovery for targeting <i>Candida albicans</i> morphogenesis through structural dynamics study

    No full text
    In response to the escalating threat of drug-resistant fungi to human health, there is an urgent need for innovative strategies. Our focus is on addressing this challenge by exploring a previously untapped target, yeast casein kinase (Yck2), as a potential space for antifungal development. To identify promising antifungal candidates, we conducted a thorough screening of the diverse-lib drug-like molecule library, comprising 99,288 molecules. Five notable drug-like compounds with diverse-lib IDs 24334243, 24342416, 17516746, 17407455, and 24360740 were selected based on their binding energy scores surpassing 11 Kcal/mol. Our investigation delved into the interaction studies and dynamic stability of these compounds. Remarkably, all selected molecules demonstrated acceptable RMSD values during the 200 ns simulation, indicating their stable nature. Further analysis through Principal Component Analysis (PCA)-based Free Energy Landscape (FEL) revealed minimal energy transitions for most compounds, signifying dynamic stability. Notably, the two compounds exhibited slightly different behaviour in terms of energy transitions. These findings mark a significant breakthrough in the realm of antifungal drugs against C. albicans by targeting the Yck2 protein. However, it is crucial to note that additional experimental validation is imperative to assess the efficacy of these molecules as potential antifungal candidates. This study serves as a promising starting point for further exploration and development in the quest for effective antifungal solutions. Communicated by Ramaswamy H. Sarma</p

    Bioprospecting of Meliaceae family phytomolecules for the treatment of monkeypox virus infection: a QSAR modeling and MD simulation approach

    No full text
    Recent monkeypox virus (MPXV) infections show the risk of MPXV transmission that persists today and the significance of surveillance and quick response methods to stop the virus’s spread. Currently, the monkeypox virus infection is not specifically treated. In this study, QSAR models were designed using known inhibitors of cysteine proteinase from the vaccinia virus, where the Random Forest model and Ridge model had showed the best correlation between predicted and observed EC50. These models were used to screen Maliaceae family phytochemicals against MPXV cysteine proteinase. The compound, IMPHY010637 was detected in top 5 from both the QSAR screening models and showed best docked score (-8.6 kcal/mol) and thus selected for further investigation. Further, the IMPHY010637 showed interaction with the catalytic residue His241 of the protein as reported in earlier studies. The ADMET analysis of the compound showed the acceptable drug-like properties of IMPHY010637. However, these properties could be improved after experimental validation of protein-ligand binding. Both docked complex and poses created in 100 ns MD simulation of the protein-ligand complex showed the presence of multiple hydrogen bonds. RMSD and conformation analysis showed stable binding of IMPHY010637 with the cysteine proteinase of MPXV at its active site. Compared to the known inhibitor, IMPHY010637 showed better binding with the protein as observed by the PCA and MM/GBSA analysis. This study concluded IMPHY010637 as a potential inhibitor for the cysteine proteinase of MPXV using computational methods that could be tested in in-vitro experiments. Communicated by Ramaswamy H. Sarma</p
    corecore