Abstract

Protein structure prediction from amino acid sequence has been one of the most challenging aspects in computational structural biology despite significant progress in recent years showed by critical assessment of protein structure prediction (CASP) experiments. When experimentally determined structures are unavailable, the predictive structures may serve as starting points to study a protein. If the target protein consists of homologous region, high-resolution (typically <1.5 Å) model can be built via comparative modelling. However, when confronted with low sequence similarity of the target protein (also known as twilight-zone protein, sequence identity with available templates is less than 30 %), the protein structure prediction has to be initiated from scratch. Traditionally, twilight-zone proteins can be predicted via threading or ab initio method. Based on the current trend, combination of different methods brings an improved success in the prediction of twilight-zone proteins. In this mini review, the methods, progresses and challenges for the prediction of twilight-zone proteins were discussed.

Highlights

  • Specific function and mechanism of a protein can be elucidated from the three dimensional (3D) structure of a protein

  • Their study suggests that I-TASSER is useful for low resolution protein structure prediction for twilight-zone protein

  • A query must be built from scratch by ab initio modelling when no structurally related proteins were found in the template database

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Summary

Introduction

Specific function and mechanism of a protein can be elucidated from the three dimensional (3D) structure of a protein. Computational approaches for prediction protein 3D structures can be generally divided into three categories (comparative modelling, threading and ab initio approach). Comparative modelling and threading method are categorized into TBM as they depend on the availability of a template from solved protein structures [9]. FM ( known as ab initio or de novo method) is potentially able to predict protein structures without any template [8, 10].

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