Critical assessment of protein intrinsic disorder prediction (CAID) - Results of round 2.

Protein intrinsic disorder (ID) is a complex and context-dependent phenomenon that covers a continuum between fully disordered states and folded states with long dynamic regions. The lack of a ground truth that fits all ID flavors and the potential for order-to-disorder transitions depending on specific conditions makes ID prediction challenging. The CAID2 challenge aimed to evaluate the performance of different prediction methods across different benchmarks, leveraging the annotation provided by the DisProt database, which stores the coordinates of ID regions when there is experimental evidence in the literature. The CAID2 challenge demonstrated varying performance of different prediction methods across different benchmarks, highlighting the need for continued development of more versatile and efficient prediction software. Depending on the application, researchers may need to balance performance with execution time when selecting a predictor. Methods based on AlphaFold2 seem to be good ID predictors but they are better at detecting absence of order rather than ID regions as defined in DisProt. The CAID2 predictors can be freely used through the CAID Prediction Portal, and CAID has been integrated into OpenEBench, which will become the official platform for running future CAID challenges.

Protein conformational diversity correlates with evolutionary rate.

Native state of proteins is better represented by an ensemble of conformers in equilibrium than by only one structure. The extension of structural differences between conformers characterizes the conformational diversity of the protein. In this study, we found a negative correlation between conformational diversity and protein evolutionary rate. Conformational diversity was expressed as the maximum root mean square deviation (RMSD) between the available conformers in Conformational Diversity of Native State database. Evolutionary rate estimations were calculated using 16 different species compared with human sharing at least 700 orthologous proteins with known conformational diversity extension. The negative correlation found is independent of the protein expression level and comparable in magnitude and sign with the correlation between gene expression level and evolutionary rate. Our findings suggest that the structural constraints underlying protein dynamism, essential for protein function, could modulate protein divergence.