Opioids still remain the primary drugs for the treatment of moderate to severe pain. The analgesic effects of currently available opioid drugs are mediated through their agonist interaction with the mu opioid receptor. The use of these mu agonist opioid analgesics is severely restricted by a number of serious side effects such as development of tolerance and dependence and the potential for addiction. Recent research using opioid receptor subtype selective antagonist and agonist ligands as well as gene knock out studies have provided convincing evidence that the blockade of opioid delta receptors can diminish or prevent the side effects of mu agonist analgesics without diminishing their analgesic effects. This has provided an impetus for discovering novel nonpeptide opioid ligands possessing mixed mu agonist/delta antagonist activity since ligands endowed with such a profile have the potential of emerging as new therapeutic agents for alleviating pain without attendant tolerance and dependence side effects. Current medicinal chemistry research focusing on the design of such mixed function ligands primarily depend on ligand structure based approaches. These drug design efforts could gain a significant advantage if requirements of potent agonist and antagonist binding are delineated through development of structural models of the mu and delta receptor in the active and inactive states. The availability of increasing computational resources coupled with advances in computational modeling of G-protein coupled receptors (GPCRs) allows further exploration of the structural basis of ligand binding and activation of the opioid receptors and their heterooligomers and the rational design of new generation of opioid analgesics. To achieve these long-term goals, proposed herein is a research effort focusing on the following specific aims: (1) Develop a three dimensional models of the mu opioid receptor in the active state and delta opioid receptor in the inactive state and refine these models using enhanced conformational sampling methods (2) Develop pharmacophores for ligand binding and activation at mu receptors and binding and antagonist activity at delta receptors through structure predictions from ligand- receptor complexes (3) On the basis of the knowledge gained, design, synthesize, and evaluate new ligands with improved binding and activity profiles and refine and evaluate models on the basis of experimentally determined activity profiles and (4) Explore modeling the structures of mu-delta heterodimer complexes to gain insight into novel binding site characteristics that such interactions confer to these complexes. The proposed research therefore should enhance our fundamental knowledge and understanding of the interaction of various ligands with these receptors in addition to enhancing the prospect of designing and developing new improved ligands with the potential for emerging as potent analgesic drugs for pain relief devoid of severe side effects.
Severe and chronic pain is a debilitating medical condition that has a huge impact on the health and well-being of a large number of individuals. Although opioid drugs are potent pain relievers, their general use is severely restricted by side effects such as tolerance and dependence. The proposed research is focused on computational modeling of the opioid receptors to enable the design and discovery of new, potent opioid analgesic compounds devoid of the limiting side effects associated with the current medications.
