Flexible docking of peptides to class I major-histocompatibility-complex receptors.
We present a new method for docking flexible peptides to class I Major-Histocompatibility-Complex (MHC) receptors. Docking is performed in two steps: (a) The charged terminal peptide residues are located by randomly distributing multiple copies of each in volumes of approximately 150 A at either end of the binding groove, and then minimizing the system energy using a modified multiple-copy search algorithm. This is followed by (b) construction of the intervening chain using the multiple-copy bond-scaling-relaxation loop closure algorithm. In both steps, the copies tend to cluster and the size of the resulting clusters is proportional to the basin of attraction of the corresponding energy well. We show that native MHC-bound peptides have broad minima and, consequently, that misfolded, low-energy peptide conformations can be eliminated by restricting consideration to groups of peptides which cluster into broad minima. The accuracy of the method is assessed by comparing the predictions with crystallographic data for three different MHC peptide systems, at various degrees of stringency: (a) the extent to which we can determine side chain function (anchor vs. T-cell epitopes); (b) the extent to which we can determine the peptide-receptor orientation; and (c) the accuracy with which we can predict atomic coordinates. We find the method correct on (a) for 19 of the 22 non-Gly positions; the failures appearing to be a consequence of omitting solvation. Predictions related to (b) are also very encouraging, with the overall orientation of the predicted peptides being very similar to the crystal conformation, when measured by the hydrogen bonding pattern between the two. The degree of success in predicting atomic coordinates varied considerably, however, from 1.4 A for the HLA-A2 peptide to 2.7 A for the Kb peptide. The inaccuracy of the latter appears to reflect an incomplete target function, most likely the ommission of solvation. The calculations thus define the current limits of accuracy in docking flexible peptides to Class I receptors and identify the methodological improvements that must be made for the next advance in accuracy.
Rosenfeld
R
R
Department of Biomedical Engineering, Boston University College of Engineering, MA 02215-2427, USA.
Zheng
Q
Q
Vajda
S
S
DeLisi
C
C
D000465:Algorithms; D000595:Amino Acid Sequence; D000818:Animals; D002213:Capsid / Q000737:chemistry / Q000378:metabolism; D015234:HLA-A Antigens / Q000378:metabolism; D015395:Histocompatibility Antigens Class I / Q000737:chemistry / Q000378:metabolism*; D006801:Humans; D006860:Hydrogen Bonding; D009980:Influenza A virus; D051379:Mice; D008958:Models, Molecular; D008969:Molecular Sequence Data; D019590:Nucleocapsid Proteins; D009698:Nucleoproteins / Q000737:chemistry / Q000378:metabolism; D010222:Parainfluenza Virus 1, Human; D010455:Peptides / Q000737:chemistry* / Q000378:metabolism; D011487:Protein Conformation; D016601:RNA-Binding Proteins; D014758:Viral Core Proteins / Q000737:chemistry / Q000378:metabolism; D014763:Viral Matrix Proteins / Q000737:chemistry / Q000378:metabolism
D015234:HLA-A Antigens; C053029:HLA-A*68 antigen; D015395:Histocompatibility Antigens Class I; C031540:M-protein, influenza virus; C048842:NP protein, Influenza A virus; D019590:Nucleocapsid Proteins; D009698:Nucleoproteins; D010455:Peptides; D016601:RNA-Binding Proteins; D014758:Viral Core Proteins; D014763:Viral Matrix Proteins