Modeling Ligand−Receptor Interaction for Some MHC Class II HLA-DR4 Peptide Mimetic Inhibitors Using Several Molecular Docking and 3D QSAR Techniques

Abstract

The ligand-receptor interaction between some peptidomimetic inhibitors and a class II MHC peptide presenting molecule, the HLA-DR4 receptor, was modeled using some three-dimensional (3D) quantitative structure-activity relationship (QSAR) methods such as the Comparative Molecular Field Analysis (CoMFA), Comparative Molecular Similarity Indices Analysis (CoMSIA), and a pharmacophore building method, the Catalyst program. The structures of these peptidomimetic inhibitors were generated theoretically, and the conformations used in the 3D QSAR studies were defined by docking them into the known structure of HLA-DR4 receptor through the GOLD, GLIDE Rigidly, GLIDE Flexible, and Xscore programs. Some of the parameters used in these docking programs were selected by docking an X-ray ligand into the receptor and comparing the root-means-square difference (RMSD) computed between the coordinates of the X-ray and docked structure. However, the goodness of a docking result for docking a series of peptidomimetic inhibitors into the HLA-DR4 receptor was judged by comparing the Spearman's rank correlation coefficient computed between each docking result and the activity data taken from the literature. The best CoMFA and CoMSIA models were constructed using the aligned structures of the best docking result. The CoMSIA was conducted in a stepwise manner to identify some important molecular features that were further employed in a pharmacophore building process by the Catalyst program. It was found that most inhibitors of the training set were accurately predicted by the best pharmacophore model, the Hypo1 hypothesis constructed. The deviation or conflict found between the actual and predicted activities of some inhibitors of both the training and the test sets were also investigated by mapping the Hypo1 hypothesis onto the corresponding structures of the inhibitors.

Design of Glycopeptides Used to Investigate Class II MHC Binding and T-Cell Responses Associated with Autoimmune Arthritis

“…A few studies have also been presented where molecular docking, i.e. a computational method for predicting binding between a ligand and a protein, has been used in redocking experiments [25], [26] and in affinity prediction protocols [27]. In the work presented here, we have applied molecular docking not in retrospect but in the first stage to virtually screen a large set of peptides for their potential to bind to MHC II (A q ) with preserved epitopes (aiming for retained T-cell responses).…”

Quantitative Structure−Activity Relationship of Peptides Binding to the Class II Major Histocompatibility Complex Molecule AqAssociated with Autoimmune Arthritis

“…48 In addition, a 3D-QSAR model for the human DR-4 molecule has been developed by Lin and co-workers. 49 The advantage of using SMD for designing a set of peptides to investigate the importance and influence of different peptide positions by QSAR modeling is that it enables the effects of more than one molecular property at several positions to be investigated with a minimum number of peptides. It also yields information about potential interactive effects between properties at different positions and provides a sound basis for a subsequent QSAR modeling for prediction of binding.…”

pDOCK: a new technique for rapid and accurate docking of peptide ligands to Major Histocompatibility Complexes

“…The results of our validation experiments are compiled into Table 3. Peptides 1, 2, 3, 4 and 15 (Table 3) are new in this study and are collated from recent publications [34,36,37], whereas the remaining 10 were from the validation studies reported for our earlier methodology [2]. To the best of our knowledge, these results represent a sevenfold increase in the accuracy of pDOCK compared to available flexible docking techniques in the remodeling of pMHC complexes.…”