Protein Folding

Proteins are large molecules consisting of one or more chains of amino acids and play crucial functions in a wide range of biological processes. The functional properties of proteins are largely determined by their three-dimensional structures, making it vitally important to determine or predict protein structures from amino acid sequences. Although experimental structure determination methods, such as X-ray crystallography, NMR spectroscopy and electron microscopy, can provide high-resolution structure information for proteins; they are complex and costly thus cannot keep pace with the generation of protein sequences.

The prediction of three-dimensional protein structure from amino acid sequence, also known as protein folding problem, provides valuable information for the large fraction of sequences whose structures have not been determined experimentally. Knowing protein structures can deepen our understanding of many biological processes and help diagnose and treat diseases believed to be caused by misfolded proteins, such as Alzheimer’s, Parkinson’s, Huntington’s and cystic fibrosis. However, computational protein structure prediction has been a grand challenge in computational biology for decades. According to the Science magazine, the problem remains one of the top 125 outstanding issues in modern science.