Protein Tertiary Structures: Prediction from Amino Acid Sequences

نویسنده

  • Hongyu Zhang
چکیده

Proteins are polypeptide chains consisting of a large number of amino acid residues that are covalently linked together via amide bonds. The order in which the 20 different amino acids are arranged in a protein chain is also called the primary structure of the protein. The polypeptide backbones of proteins exist in particular conformations known as the secondary structures. The secondary structures as well as their side-chains are then packed into three-dimensional structures referred to as the tertiary structures. The biological function of a protein is often intimately dependent upon its tertiary structure. X-ray crystallography and nuclear magnetic resonance are the two most mature experimental methods used to provide detailed information about protein structures.However, to date the majority of the proteins still do not have experimentally determined structures available. As at December 2000, there were about 14 000 structures available in the protein data bank (PDB, http://www.pdb.org), and there are about 10 106 000 sequence records sequences in GenBank (http://www.ncbi.nlm.nih.gov/Genbank). Thus theoretical methods are very important tools to help biologists obtain protein structure information. The goal of theoretical research is not only to predict the structures of proteins but also to understand howproteinmolecules fold into the native structures. The current methods for protein structure prediction can be roughly divided into three major categories: comparativemodelling; threading; and ab initioprediction. For a given target protein with unknown structure, the general procedure for predicting its structure is described in Figure 1.

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Secondary Structure Prediction Based on Statistical Mechanics

Recent genome science has been developing from two sides: one is biological evolution due to mutation of DNA sequence and the other is biological function of protein molecules formed according to amino acid sequences. We have devoted ourselves to elucidate the mechanism of protein folding, and to develop the method for protein structure prediction [1, 2]. Our method has successfully yielded the...

متن کامل

Bioinformatics study of complete amino acid sequences of neuraminidase (NA) antigen of H1N1 influenza viruses from 2006 to 2013 in Iran

Introduction: Influenza is a contagious acute viral disease of the respiratory tract that causes fever, headache, muscle aches and cough. One of the unique features of influenza virus is antigenic variation in viral protein neuraminidase (NA) which causes emergence of new virus variants. NA is responsible for the release and spread of progeny virions. Due to the continuous changes of NA genes, ...

متن کامل

GalaxyGemini: a web server for protein homo-oligomer structure prediction based on similarity

SUMMARY A large number of proteins function as homo-oligomers; therefore, predicting homo-oligomeric structure of proteins is of primary importance for understanding protein function at the molecular level. Here, we introduce a web server for prediction of protein homo-oligomer structure. The server takes a protein monomer structure as input and predicts its homo-oligomer structure from oligome...

متن کامل

Dihedral angle and secondary structure database of short amino acid fragments

UNLABELLED Dihedral angles of amino acids are of considerable importance in protein tertiary structure prediction as they define the backbone of a protein and hence almost define the protein's entire conformation. Most ab initio protein structure prediction methods predict the secondary structure of a protein before predicting the tertiary structure because three-dimensional fold consists of re...

متن کامل

Building a Knowledge-Base for Protein Function Prediction using Multistrategy Learning

Conventional techniques for protein function prediction using similarities of amino acid sequences enable us to only classify the protein functions into function groups. They usually fail to predict speci c protein functions. To overcome the limitation, in this paper, we propose a method for protein function prediction using functional feature analysis and a multistrategy learning approach to b...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2002