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Spectacular progress is observed in the field of computational simulation of protein structure and interaction driven by advanced and innovative computer algorithms, massive parallel grid computing, and community-wide experiments such as CASP. Illustrated with examples and applications an overview over recent methods and advances will be given:
Progress in de novo protein structure prediction using the ROSETTA algorithm as monitored in the recent CASP experiments will be presented. Leveraging this progress, application of such algorithms for protein structure determination from sparse and/or low-resolution experimental NMR, EPR, and cryo-EM data will be demonstrated. Serotonin transporter is a neurotransmitter transporter which is targeted by several anti-depressiva as well as illicit compounds, such as cocaine and MDMA. Substrate specificity is predicted by employing a novel computational algorithm to fully flexible dock small molecules into a structural model based on LeuTAa, a bacterial homolog of neurotransmitter transporters. Selective allosteric potentiators of the metabotropic glutamate receptor mGluR5 have exciting potential for development of novel treatment strategies for schizophrenia. Coupled chem-informatics/machine learning approaches are used for quantify structure activity analysis of high-throughput screening results. Application of these models for identification of novel lead compounds is illustrated. Protein design offers the exciting potential to engineer proteins for custom applications. Progress in the field is illustrated by computational designing and validating experimentally a TIM barrel fold that is fully symmetric in sequence and structure. Novel avenues to protein therapeutics are explored on the example of computationally designed mimics of the last-resort antibiotic Vancomycin. |
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