Improved protein complex prediction with AlphaFold-multimer by denoising the MSA profile
Fig 3
a) Final MMscore vs structural change during the optimisation procedure as measured by the change in MMscore (ΔMMscore). The density and points represent all predictions (n = 487) and the line is the running mean with a step size of 0.05 ΔMMscore. This shows that the MMscore is unlikely to decrease with the optimisation procedure and that when the structural change is large compared to the initial prediction (measured by ΔMMscore), it is likely to obtain a higher MMscore. This is expected as the predicted structures are inaccurate using AFM (MMscore<0.75). b) Initial and AFProfile optimised structure of PDBIDs 6nnw (https://www.rcsb.org/structure/6NNW) and 6ya2 (https://www.rcsb.org/structure/6ya2). The native structure is in grey and the predicted ones are in blue. The MMscores increased from 0.44→0.96 and 0.52→0.93 and the confidences from 0.22→0.90 and 0.24→0.85, respectively, during the optimisation. c) Number of sequences in the MSA input representation generated by the AFM pipeline (MSA depth) vs the final MMscore after optimization with AFprofile. The density represents all predictions (n = 487) and the line is the running mean with a step size of 500 in MSA depth.