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Tessellation-based analysis of dynamic protein structures and their complexes - MoleculAR MOTions meet TEssellations (MARMOTTE).

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Tessellation-based analysis of dynamic protein structures and their complexes - MoleculAR MOTions meet TEssellations (MARMOTTE). This year has seen a breakthrough in structural bioinformatics - deep learning-based methods, most notably Google DeepMind's AlphaFold2, have demonstrated near-experimental accuracy of protein structure predictions. However, even the best protein structure prediction methods do not automatically provide knowledge about protein dynamics and protein interactions, which is often essential to understand or predict the biological functions of proteins. Those functions are performed via intermolecular interactions, and such interactions almost always involve conformational changes of engaged partners. The problem of modeling dynamic protein structures and their complexes is still largely unsolved - this project aims to significantly contribute towards its future solution by exploring the link between computational geometry, statistical physics, and machine learning. The postdoctoral researcher will develop novel methods that: given a dynamic (moving) molecu

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recordType

award

status

SIGNED

region

EU

value

195914.88

unit

EUR