Critical Features of Fragment Libraries for Protein Structure Prediction.

Raphael Trevizani,Karina Baptista Dos Santos,Fábio Lima Custódio,Laurent Emmanuel Dardenne,Yang Zhang

doi:10.1371/journal.pone.0170131

Raphael Trevizani, Karina Baptista Dos Santos + Show 3 more

Open Access

https://doi.org/10.1371/journal.pone.0170131

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Abstract

The use of fragment libraries is a popular approach among protein structure prediction methods and has proven to substantially improve the quality of predicted structures. However, some vital aspects of a fragment library that influence the accuracy of modeling a native structure remain to be determined. This study investigates some of these features. Particularly, we analyze the effect of using secondary structure prediction guiding fragments selection, different fragments sizes and the effect of structural clustering of fragments within libraries. To have a clearer view of how these factors affect protein structure prediction, we isolated the process of model building by fragment assembly from some common limitations associated with prediction methods, e.g., imprecise energy functions and optimization algorithms, by employing an exact structure-based objective function under a greedy algorithm. Our results indicate that shorter fragments reproduce the native structure more accurately than the longer. Libraries composed of multiple fragment lengths generate even better structures, where longer fragments show to be more useful at the beginning of the simulations. The use of many different fragment sizes shows little improvement when compared to predictions carried out with libraries that comprise only three different fragment sizes. Models obtained from libraries built using only sequence similarity are, on average, better than those built with a secondary structure prediction bias. However, we found that the use of secondary structure prediction allows greater reduction of the search space, which is invaluable for prediction methods. The results of this study can be critical guidelines for the use of fragment libraries in protein structure prediction.

Highlights

It is estimated that less than 30% of human protein structures have been empirically determined, and the amount for other species is significantly lower [1]
This study investigates some crucial features of a fragment library in the reconstruction of the native structure, isolated from the limitations of ab initio methods, such as an imprecise energy function and optimization algorithms
We suggest the use of secondary structure prediction is relevant to protein structure prediction (PSP) methods because it effectively reduces the search space by sparing only the fragments with a similar secondary structure

Summary

Introduction

It is estimated that less than 30% of human protein structures have been empirically determined, and the amount for other species is significantly lower [1] This is primarily due to the difficulties and costs associated with experimental techniques, such as NMR and X-ray diffraction. Fragment Libraries for Protein Structure Prediction for protein structure prediction (PSP) Among such tools, comparative modeling yields the best results when the target sequence has a high degree of sequence similarity with proteins available in structural databases. Comparative modeling yields the best results when the target sequence has a high degree of sequence similarity with proteins available in structural databases When such homologous structures are not available, an ab initio approach is required

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