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Speaker: Prof. Antonia Mey
Topic: From catalysis to binding affinity predictions
Abstract: Molecular dynamics and machine learning can be used to characterize the connection between protein structure and their dynamics. Insights into the connections between structure and dynamics are not only key to understanding protein function, but also their link to diseases. Furthermore, they are also crucial to guide the design of drugs, small molecules specifically interacting with proteins and regulating their biological activity.
The talk will be an illustrative journey of how we can build a computational toolbox to investigate protein function. This toolbox provides atomistic insights into experimental results and can be used to make predictions when experimental data is not available. One of the key aspects of computational work, is to make sure to follow best practices to guarantee effective sharing and reproducibility of data and methods. In this context, I will highlight key examples of pitfalls, and how to avoid them.