ACBRC is a resource aimed to interact with the Scientific Community in order to share results and tools regarding research activities in Structural Genomics/Proteomics field. Our effort mainly consists of computational solutions for protein secondary, supersecondary and tertiary structure prediction. Moreover, we propose to identify both protein structural homologues with low sequence identity and superfold domains by assembly of elementary building block units in order to collect structural data for molecular theoretical studies. Nevertheless, we are interested to characterize physical and chemical properties of biological macromolecules in order to obtain a better understanding of the laws that govern the folding of polypeptide chains, focusing on their corresponding biological functions. Finally, we study supramolecular structure determinants modulating the redox potential Eº of metallo enzymes.
The word protein comes from Greek word protos meaning of primary importance. Proteins are essential parts of organisms: they catalyze biochemical reactions and have a leading role to metabolism, play structural or mechanical functions within cells, they are important in cell signalling, immune responses, cell-cell recognition, biomolecular transport and cell division regulation. The sequence of amino acids in a protein is defined by the sequence of a gene, which is encoded in the genetic code. Although it is relatively simple to characterize the amino acidic sequence of a purified protein, it is very hard to define its three dimensional shape. The first protein structures were solved in 1958 by Max Perutz and Sir John Cowdery Kendrew by using X-ray diffraction analysis. Common experimental methods of protein structure determination include X-ray crystallography, NMR spectroscopy, both of which can produce information at atomic resolution. Nevertheless, even Dual Polarisation Interferometry and Circular Dichroism may provide useful information to protein structure determination, but all those experimental techniques are time consuming and require a big amount of money. Moreover, several membrane proteins are difficult to crystallize and are underrepresented in the Protein Data Bank depository.
Although an increasing number of structural data collected by several laboratories is freely available, it is still not possible to design a mathematical model for predicting the three dimensional structure of proteins because of lack of a scientific paradigma. The number of possible protein conformations is extremely wide, and that the physical/chemical basis of protein structural stability is not fully understood.
Computational models for protein structure prediction are of high importance in medicine (for example, in drug design) and biotechnology (for example, in the design of novel enzymes). Every two years, the performance of current methods is assessed in the CASP experiment. Thus, there were born several structural bioinformatics projects aimed both to improve understanding of the laws that govern the macromolecular structure conformation and to speed up the research against several harmful diseases such as cancer and bacterial/viral infections. Furthermore, results obtained by such computational methods may improve knowledge in rational protein engineering, allowing the design of new highly efficient molecular prototypes, even with functions never before observed in nature, to be used in biomedicine and molecular biology.