Advances in protein tertiary structure prediction

Abstract

Proteins are composed of linear chains of amino acids that form a unique three-dimensional structure in their native environment. Such native structure favors the proteins to perform their biochemical activity. Protein is formed of some levels of structure. The primary structure of a protein is specified by the particular amino acid sequence. In an amino acid sequence, patterns of local bonding can be identified as secondary structure. The final level that forms a tertiary protein structure is composed of the mentioned elements and form after the protein folds into its native state. To find the native structure of proteins, the physicochemical principles as well as identifying the lowest free-energy states are considered as the best properties and to predict target proteins with unknown structures, the bioinformatics-based methods have earned considerable success. Protein structure prediction methods have been mainly classified into three types: ab Initio folding, comparative (homology) modeling and threading. Each mentioned method may be applied for a protein structure, depending on the existence of related experimental structures that are deposited in the PDB. Once an initial model is generated, refinement simulations are conducted to reassemble the global topology and the local structures of the protein chains. Since significant features of a model may be in regions that are structurally distinct from the template, refining of a primary model is influential. A trustful strategy is included a stereo-chemical check and discovering how the model deviates from the basic disciplines of known experimental structures.