A Survey of Protein Fold Recognition Algorithms

Abstract

Problem statement: Predicting the tertiary structure of proteins from their linear sequence is really a big challenge in biology. This challenge is related to the fact that the traditional computational methods are not powerful enough to search for the correct structure in the huge conformational space. This inadequate capability of the computational methods, however, is a major obstacle in facing this problem. Trying to solve the problem of the protein fold recognition, most of the researchers have examined the use of the protein threading technique. This problem is known as NP-hard; researchers have used various methods such as neural networks, Monte Carlo, support vector machine and genetic algorithms to solve it. Some researchers tried the use of the parallel evolutionary methods for protein fold recognition but it is less well known. Approach: We reviewed various algorithms that have been developed for protein structure prediction by threading and fold recognition. Moreover, we provided a survey of parallel evolutionary methods for protein fold recognition. Results: The findings of this survey showed that evolutionary methods can be used to resolve the protein fold recognition problem. Conclusion: There are two aspects of protein fold recognition problem: First is the computational difficulty and second is that current energy functions are still not accurate enough to calculate the free energy of a given conformation.