By Alexandre Bonvin
This year the Nobel Prize in Chemistry was awarded to David Baker for computational protein design and Demis Hassabis and John Jumper for protein structure prediction. BioExcel warmly congratulates the Nobel Prize winners!
These research areas are of high interest to BioExcel as structure prediction is often key to providing starting models for biomolecular simulations. The development of Alphafold and its derivatives has clearly revolutionalized the field of (computational) structural biology, giving us access to structural models of almost all (or part of) proteins. Such tools enable for example the modelling of antibody structures from sequence only, which can provide starting models for GROMACS MD simulations or for HADDOCK-driven prediction of antibody-antigen complexes as demonstrated in a recent BioExcel publication by Giulini et al., “Towards the accurate modelling of antibody-antigen complexes from sequence using machine learning and information-driven docking.” Similarly, protein design and engineering fall under BioExcel’s software development and research activities. For example, within the BioExcel Building Blocks (BioBB) new libraries are being developed that integrate proteinMPNN, the protein design AI software developed in the Baker group. And if you want to test or further optimize some of the designs with rigorous free energy calculations, our PMX tool is the way to go.
