A new computational method developed to study protein dynamics

Researchers have developed the first computational method based on evolutionary principles to predict protein dynamics. These researchers are from the Structural Biology Computational Group of the Spanish National Cancer Research Centre (CNIO), led by Alfonso Valencia, together with a group led by Francesco Gervasio at the University College London (UK). Protein dynamics can explain the changes in the shape or dimensional structure that they experience in order to interact with other compounds or speed up chemical reactions. This study push the development of the computational study of protein dynamics, and it is helpful for the design of drugs and for the research about genetic disease. It is published in the journal Proceedings of the National Academy of Sciences (PNAS). As we know, proteins are crucial to the thousands of cellular functions which work in a living organism. It is chains of smaller molecules which are called amino acids that form the protein - a three-dimensional structure. By studying the co-evolution of amino acids, we can reconstruct the form or structure of these biological compounds in their natural surroundings. We can also predict physical contacts between amino acids with higher accuracy and in sufficient number by analyzing the sequences of a given family of proteins, to reconstruct the folding and structure of a protein accurately. Nevertheless, the structure won't remain changeless. It interacts with other biological compounds or with drugs, which is called protein dynamics. The study about it turns out to be extremely difficult no matter through experimental observations or computational tools. "We developed a model in which the amino acids that have a strong co-evolutionary relationship attracted each other, without further additional data," says Simone Marsili, researcher who has also participated in the project. "First, we simulate the folding process and then we can see how the simulations were able to predict the changes in shape of the proteins at different levels of complexity, including those required for kinases to function." By using the latest sequence analysis and 3D modeling technology, this new method combines experimental with genomic data. It also shows that genomic For more wonderful readings, click here:http://www.cusabio.com/Recombinant-Protein/Recombinant-Influenza-A-virus-strain-AEngland8781969-H3N2-Hemagglutinin-11089552.html