Evaluation of Accuracy and Applicability of Protein Models: Retrospective Analysis of Biological and Biomedical Predictions

Abstract

In order to study protein function and activity structural data is required. Since experimental structures are available for just a small fraction of all known protein sequences, computational methods such as protein modelling can provide useful information. Over the last few decades we have predicted, with homology modelling methods, the structures for numerous proteins. In this study we assess the structural quality and validity of the biological and medical interpretations and predictions made based on the models. All the models had correct scaffolding and were ranked at least as correct or good by numerical evaluators even though the sequence identity with the template was as low as 8%. The biological explanations made based on models were well in line with experimental structures and other experimental studies. Retrospective analysis of homology models indicates the power of protein modelling when made carefully from sequence alignment to model building and refinement. Modelling can be applied to studying and predicting different kinds of biological phenomena and according to our results it can be done so with success.

SAAFEC: Predicting the Effect of Single Point Mutations on Protein Folding Free Energy Using a Knowledge-Modified MM/PBSA Approach

“…To determine the degree of burial of a residue in the protein, we calculated its relative solvent accessible surface area (rSASA) with NACCESS software [ 24 ]. Here, we distinguished three possible degrees of burial: buried (B, rSASA = 0), partially exposed (PE, Rsasa ≤ 0.25 and rSASA > 0), and exposed (E, rSASA > 0.25) Thus, the residues characterized as PE and E are accessible from the water, while the residues defined as B are completely buried inside the protein (see SI, Table S3 ).…”

“…These different approaches make predictions that correlate with experimental values to varying degrees, but comparing predictors is complicated because they use different databases of structures for training. In all cases, it is desirable to improve the accuracy of predictions and to provide additional information on the structural changes caused by mutation and the contribution of individual energy terms to the predicted folding free energy change [ 24 , 25 ].…”

Guidelines for reporting protein modelling studies

“…In addition to several CASP challenges also Critical Assessment of protein Function Annotation (CAFA, https://www.biofunctionprediction.org/cafa/) challenges have addressed and boosted development of methods for biological interpretation. As an example, a study describes in addition to the quality of model, relevance and accuracy of numerous biological and medical predictions made based on 15 blind prediction models (Khan and Vihinen, 2009). Example: The conserved R520 is located at the N terminus of the catalytic loop where it is structurally and functionally vital.…”