title: Prediction of the protein folding core: application to the immunoglobulin fold.
abstract: We propose an algorithm that allows predicting residues important for the formation of the structure of globular proteins. It relies on a simulation that detects the amino acids presenting a maximum number of neighbours during the early steps of the folding process. They have been called MIR (Most Interacting Residues). Independently, description of the protein structures in fragments with closed ends shows the correlation between these extremities and the core of the globules. These fragments are of rather constant length, typically between 20 and 25 amino acids, and we have previously shown that their extremities are preferentially occupied by MIR. Introduction of rules derived from this fragment analysis of tertiary structures allows to smooth the distribution of MIR, for a better match between TEF ends and MIR. In order to assess this prediction of the folding core, a large family of structures has been used, with sequences as different as possible. A dataset of 56 immunoglobulin structures of various functions but common fold has been used in this study. This fold was chosen because it is one of the most populated with a large amount of data available on its nucleus. In the immunoglobulin domain, "functional and structural load is clearly separated: loops are responsible for binding and recognition while interactions between several residues of the buried core provide stability and fast folding"[1]. We then determined the positions susceptible of high importance for the folding process to occur and compared them to published data, either to High Throw Out Order (HTOO), Conservatism of Conservatism (CoC) or Phi value experiments. It results a reasonable agreement between the positions that we predict and experimental data. Besides, our prediction goes beyond the simple use of a null solvent accessibility of amino acids as a criterion to predict the core. We find the same quality of our prediction on the flavodoxin like superfamily.
authors: Protein Structure Prediction, IMPMC, CNRS UMR 7590, Paris 6 University, 75015 Paris, France.
authors: Nicolas
authors: N
authors: Prudhomme
authors: Jacques
authors: J
authors: Chomilier
mesh_terms: D000465:Algorithms; D000595:Amino Acid Sequence / Q000235:genetics*; D001665:Binding Sites; D019295:Computational Biology; D003198:Computer Simulation; D017124:Conserved Sequence; D007136:Immunoglobulins / Q000737:chemistry*; D007700:Kinetics; D008958:Models, Molecular; D011485:Protein Binding; D011487:Protein Conformation; D017510:Protein Folding; D012997:Solvents / Q000737:chemistry; D013329:Structure-Activity Relationship
chemical_list: D007136:Immunoglobulins; D012997:Solvents