MC-1288

Existing crystal structure data has indicated that 1alpha,25-dihydroxyvitamin D(3) (1alpha,25(OH)(2) D(3)) and its analogues bind the ligand-binding pocket (LBP) of the human vitamin D receptor in a very similar fashion. Because docking of a ligand into the LBP is a more flexible process than crystallography can monitor, we analyzed 1alpha,25(OH)(2)D(3), its 20-epi derivative MC1288, the two side-chain analogues Gemini and Ro43-83582 (a hexafluoro-derivative) by molecular dynamics simulations in a complex with the vitamin D receptor ligand-binding domain and a co-activator peptide. Superimposition of the structures showed that the side chain of MC1288, the first side chain of the conformation II of Gemini, the second side chain of Ro43-83582 in conformation I and the first side chain of Ro43-83582 in conformation II take the same agonistic position as the side chain of 1alpha,25(OH)(2)D(3). Compared with the LBP of the natural hormone MC1288 reduced the volume by 17%, and Gemini expanded it by 19%. The shrinking of the LBP of MC1288 and its expansion to accommodate the second side chain of Gemini or Ro43-83582 is the combined result of minor movements of more than 30 residues and major movements of a few critical amino acids. The agonist-selective recognition of anchoring OH groups by the conformational flexible residues Ala-303, Leu-309, and His-397 was confirmed by in vitro assays. In summary, variations in the volume of agonists lead to adaptations in the volume of the LBP and alternative contacts of anchoring OH-groups.

Targacept active conformation search (TACS) is a novel variation of well-established three-dimensional quantitative structure--activity relationship methodologies that seeks to determine probable conformation(s) of ligands bound to their protein targets. A combination of affinity or activity data and energetically accessible conformational ensembles, each conformer described by three-dimensional (3-D) sensitive descriptors, forms the basis of the TACS data model. Recursive pruning is used to reduce the size of both the conformational ensemble and the descriptor space until the TACS data model contains just enough information to determine probable conformation(s) of ligands bound to their protein targets. The TACS algorithm is comprised of five components: (1) conformational ensemble generation, (2) 3-D sensitive descriptor calculation, (3) ensemble descriptor preprocessing, (4) model generation, and (5) prediction of bound conformation(s). Significantly, this method precludes the need for subjective or objective molecular alignment. We report the application of this technique to five benchmark protein-ligand couples where the conformation of a bound ligand has been previously established using X-ray crystallography: 9-cis-retinoic (1) and 9-trans-retinoic acid (2), both agonists for the retinoic acid receptor gamma, compounds KH1060 (3) and MC1288 (4), which bind to the vitamin D3 receptor, and R04 (5), an inhibitor bound to human rhinovirus 14 thermolysin. The binding conformations predicted by TACS were compared to the crystallographic structures extracted from their respective binding sites using root-mean-squared deviation (rmsd) criteria. Three of the conformations found using TACS were within crystallographic error. 9-cis-Retinoic acid, 9-trans-retinoic acid, and MC1288, when superimposed on their crystallographic structures, gave rmsd values of 0.22, 0.17, and 0.34 A, respectively. The rmsd values for KH1060 (1.54 A) and R04 (1.01 A) were larger but still reasonable.