Identification of hot-spot residues in protein-protein interactions by computational docking

<p>Abstract</p> <p>Background</p> <p>The study of protein-protein interactions is becoming increasingly important for biotechnological and therapeutic reasons. We can define two major areas therein: the structural prediction of protein-protein binding mode, and the identification of the relevant residues for the interaction (so called 'hot-spots'). These hot-spot residues have high interest since they are considered one of the possible ways of disrupting a protein-protein interaction. Unfortunately, large-scale experimental measurement of residue contribution to the binding energy, based on alanine-scanning experiments, is costly and thus data is fairly limited. Recent computational approaches for hot-spot prediction have been reported, but they usually require the structure of the complex.</p> <p>Results</p> <p>We have applied here normalized interface propensity (<it>NIP</it>) values derived from rigid-body docking with electrostatics and desolvation scoring for the prediction of interaction hot-spots. This parameter identifies hot-spot residues on interacting proteins with predictive rates that are comparable to other existing methods (up to 80% positive predictive value), and the advantage of not requiring any prior structural knowledge of the complex.</p> <p>Conclusion</p> <p>The <it>NIP </it>values derived from rigid-body docking can reliably identify a number of hot-spot residues whose contribution to the interaction arises from electrostatics and desolvation effects. Our method can propose residues to guide experiments in complexes of biological or therapeutic interest, even in cases with no available 3D structure of the complex.</p

Modeling the Ternary Complex TCR-Vβ/CollagenII(261–273)/HLA-DR4 Associated with Rheumatoid Arthritis

BACKGROUND: It is known that genetic predisposition to rheumatoid arthritis (RA) is associated with the MHC class II allele HLA-DR4 and that residues 261–273 of type II collagen (huCollp261) represent an immunodominant T cell epitope restricted by the DR4 molecule. Despite recent advances in characterization of MHC and T cell receptor (TCR) contacts to this epitope, the atomic details of TCR/huCollp261/HLA-DR4 ternary complex are not known. METHODOLOGY/PRINCIPAL FINDINGS: Here we have used computational modeling to get insight into this interaction. A three-dimensional model of the TCR Vβ domain from a DR4(+) patient affected by RA has been derived by homology modeling techniques. Subsequently, the structure of the TCR Vβ domain in complex with huCollp261/HLA-DR4 was obtained from a docking approach in conjunction with a filtering procedure based on biochemical information. The best complex from the docking experiments was then refined by 20 ns of molecular dynamics simulation in explicit water. The predicted model is consistent with available experimental data. Our results indicate that residues 97–101 of CDR3β are critical for recognition of huCollp261/HLA-DR4 by TCR. We also show that TCR contacts on p/MHC surface affect the conformation of the shared epitope expressed by DR alleles associated with RA susceptibility. CONCLUSIONS/SIGNIFICANCE: This work presents a three-dimensional model for the ternary complex TCR-Vβ/collagenII(261–273)/HLA-DR4 associated with rheumatoid arthritis that can provide insights into the molecular mechanisms of self reactivity