From Protein Structure to Function with Bioinformatics by Daniel J. Rigden

Author:Daniel J. Rigden
Language: eng
Format: epub
Publisher: Springer Netherlands, Dordrecht

Prior to the calculation of the structurally-corrected aggregation propensity, A3D performs an energy minimization of the input structure with the FoldX algorithm, intended to remove unfavourable energies arising from improper torsion angles, steric hindrance between amino acid side chains, and suboptimal rotamer configurations of residues in close vicinity. The A3D method also incorporates the FoldX energy function to allow the assessment of mutational effects on the stability of protein structures. Within the A3D workflow, the analysis of the mutational impact can be performed either before or after running the prediction of aggregation propensity on the input structure, depending on whether the aggregative properties of the wild-type (or alternative reference) structure are of interest.

The previously mentioned analyses may be performed on a static structural model, either provided directly as input or generated previously through FoldX (e.g. when only the assessment of a certain variant, bearing a specific substitution, is of interest). However, A3D also integrates the possibility to evaluate the impact of structural fluctuations on the aggregation propensity of the polypeptide. Averaging the properties of different conformers as in the SAP case is, perhaps, not be the best strategy for a realistic prediction because it could lead to underestimation of the potential of certain aggregation-prone conformer—i.e. an aggregation-prone state might trigger aggregation even when it is only transiently populated. In this sense, A3D produces a more valuable output by providing the model corresponding to the most aggregation-prone conformer. To this end, a “dynamic mode” of the method is available, which allows modelling of protein structural dynamics according to the CABS-flex protocol (Jamroz et al. 2013a). CABS-flex is a high-resolution coarse-grained molecular modelling approach that follows a Monte Carlo simulation scheme to sample backbone fluctuations. Through an extensive validation of its performance, CABS-FLEX has been shown to consistently reproduce the dynamic fluctuations of the near-native ensembles derived from all-atom MD simulations performed with a variety of force fields (Jamroz et al. 2013b). In “dynamic mode”, A3D employs this robust computational tool in order to analyze an input or FoldX-mutated structure and then generate a collection of models describing the most representative fluctuations of the chain. Next, the structurally-corrected aggregation propensity is computed by A3D on these models, and the one with the highest A3D score is returned as the output approximating the most aggregation-prone state that is populated within the polypeptide’s native-like conformational ensemble.

In this way, A3D encompasses in a single prediction tool the ensemble of features that are more relevant for the prediction of aggregation propensity in globular states (Fig. 7.4)—namely, the modulation of this propensity by the structural context, the assessment of the impact of mutations on both the tendency to aggregate and the stability of protein structure, and the evaluation of structural fluctuations. Regarding this latter point, the approach introduced in A3D for the modelling of protein conformational dynamics represents a significant advantage relative to the all-atomistic MD simulation performed by the SAP method, since the CABS-flex approach is able to equivalently reproduce the dynamic fluctuations in the near-native ensemble with a much higher computational efficiency.

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