At the end of 2020, results for the CASP14 (Critical Assessment for protein Structure Prediction) were released. Just like in 2018, DeepMind Technologies won the competition with their deep (machine) learning based AlphaFold prediction models. However, the leap in prediction accuracy now raised the performance to a level that had several big names in the field consider the protein structure prediction task as ‘solved’.
Architectural details, code and trained AlphaFold models were released by DeepMind in 2021. Given the high computational cost of deep learning algorithms, specialized hardware and software are required. Online solutions are available but come with considerable disadvantages. Therefore, the Flemish Supercomputer Center (VSC) provides high performance computing facilities, on which AlphaFold is installed and fully operational. This course gives a solid introduction on how AlphaFold can be easily and swiftly accessed using the HPC.
Next to AlphaFold, RoseTTAFold has been published alongside in the summer of 2021. This tutorial will be extended with more background information on RoseTTAFold as well as a practical guide for the HPC.
This tutorial material was created by Jasper Zuallaert (VIB-UGent), with the help of Alexander Botzki (VIB) and Kenneth Hoste (UGent). For questions and remarks, feel free to contact jasper.zuallaert@vib-ugent.be or bits@vib.be.
This work is licensed under a Creative Commons Attribution 4.0 International License.
