Using multiple computer-predicted structures as molecular replacement models: application to the antiviral mini-protein LCB2.

In this report, we describe a set of structures of the engineered protein LCB2 that has been solved starting from different computer-predicted molecular replacement (MR) models. We found that AlphaFold3, AlphaFold2, MultiFOLD, Rosetta, RoseTTAFold and trRosetta all produced successful MR models for this three-helix bundle 58-residue protein, while some of the older predictors failed. To assign B factors in the MR models we used the predictor-generated confidence scores or, as a convenient alternative, the accessible surface area (ASA) values. The process of multi-start structure determination using Coot and Phenix demonstrated good convergence, leading to six structures within 0.25 Å (all-atom RMSD) of each other. Of note, structural differences between the computer-predicted MR models and the final structures can be largely attributed to a single specific crystal contact. Comparing the six structural solutions, we observe that a number of surface side chains have been solved with different conformations. Interestingly, for each individual structure the electron density is consistent with a single rotameric state and offers no direct evidence of conformational heterogeneity. Strictly speaking, this behavior constitutes a case of model bias; we argue, however, that it represents a benign side of model bias. Specifically, when we use a model where the side-chain conformation corresponds to one of the actual (significantly populated) rotameric states, this leads to an enhancement of the electron density for this particular conformation. Conversely, when we use a model with an irrelevant (low-population) side-chain conformation, it fails to produce the matching electron density. We thus conclude that the six LCB2 structures obtained in this study can be grouped into a multiconformer ensemble, where structural variations are representative of protein's conformational dynamics. Indeed, using this six-member ensemble leads to a significant drop in R