2 research outputs found

    All-Atom Modeling of Protein Folding and Aggregation

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    Theoretical investigations of biorelevant processes in the life-science research require highly optimized simulation methods. Therefore, massively parallel Monte Carlo algorithms, namely MTM, were successfully developed and applied to the field of reversible protein folding allowing the thermodynamic characterization of proteins on an atomistic level. Further, the formation process of trans-membrane pores in the TatA system could be elucidated and the structure of the complex could be predicted

    High-Performance Drug Discovery: Computational Screening by Combining Docking and Molecular Dynamics Simulations

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    Virtual compound screening using molecular docking is widely used in the discovery of new lead compounds for drug design. However, this method is not completely reliable and therefore unsatisfactory. In this study, we used massive molecular dynamics simulations of protein-ligand conformations obtained by molecular docking in order to improve the enrichment performance of molecular docking. Our screening approach employed the molecular mechanics/Poisson-Boltzmann and surface area method to estimate the binding free energies. For the top-ranking 1,000 compounds obtained by docking to a target protein, approximately 6,000 molecular dynamics simulations were performed using multiple docking poses in about a week. As a result, the enrichment performance of the top 100 compounds by our approach was improved by 1.6–4.0 times that of the enrichment performance of molecular dockings. This result indicates that the application of molecular dynamics simulations to virtual screening for lead discovery is both effective and practical. However, further optimization of the computational protocols is required for screening various target proteins
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