Independent evaluation of AlphaFold-Multimer

AlphaFold2 has been widely reported as a fantastic leap forward in the prediction of protein structures from sequence, when sequence has enough homologs to build a reasonable multiple sequence alignment.  When AlphaFold2 was released (Jumper et al. 2021) there were several independent reports of how it could also be used for the prediction of structures of protein complexes despite the fact that it was not trained to do so (Bryant et al., 2021;Ko and Lee, 2021;Mirdita et al. 2022). Together with the lab of Arne Elofsson, in work led byDavid Burke in our group and Patrick Bryant in Arne's group, we have shown that it can be applied in reasonably large scale to predict structures of protein complexes for known human interactions (Burke et al. 2021). There is a lot to investigate still but it is clear that this is an extremely exciting direction of research since that lead to a major advances in the structural analysis of cell biology, evolution, biotechnology, etc. Soon after these first reports, DeepMind released an AlphaFold version that was re-trained specifically for prediction of structures of protein complex - AlphaFold-Multimer (Evans et al. 2021). Given that they reported an even higher success rate with this specifically trained model we were quite excited to give this a try. David Burke selected a set of 650 pairs of human proteins from theHu.MAP dataset, known to physically interact and for which the experimental structure has been solved. A structure ...
Source: Evolution of Cellular Networks - Category: Cytology Tags: original research Source Type: blogs