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A series of pyrrolopyridinones was designed and synthesized as constrained analogs of the pyrazole CB-1 antagonist rimonabant. Certain examples exhibited very potent hCB-1 receptor binding affinity and functional antagonism with Ki and Kb values below 10 nM, and with high selectivity for CB-1 over CB-2 (>100-fold). A representative analog was established to cause significant appetite suppression and reduction in body weight gain in industry-standard rat models used to develop new therapeutics for obesity.

A fundamental fact in the drug development process is that physical quantity of chemical substance is needed for experimental determinations. Information that could guide the course of a drug discovery program, in particular the penultimate ADME parameters % oral bioavailability (%F) and CNS permeability (BBB) are not explicitly determined until after large capital, human and time resources have been invested in a particular chemical series to produce the substance. To assure better go/no-go decisions and to protect the risks of a process that necessitates a considerable "front-loading" of resources, project teams are turning to computational methods to estimate these parameters. Herein we provide a detailed review of "holistic" in silico methods toward the estimation of %F and BBB. An unbiased description of the scope and limitations of their installation and application will be given in the context of an on going pharmaceutical project.

Computational methods are currently available to estimate oral bioavailability, solubility, metabolism, toxicity, pKa, blood-brain barrier permeability and other ADME and physicochemical parameters. Decisions as to which methods to implement and to employ must be made in accordance with the stated goals of a drug discovery organization, the timeline for these goals, and the budgetary limitations as set forth to accomplish these goals. Certain methods are more attractive to the production environment of a pharmaceutical project team where early ADME and Tox information is sought to aid in drug design decisions and prioritization. Practical limitations of these methods, ease of use, utility of results, as well as their scope and limitations are discussed. Recommendations as to which parameters are best estimated by commercial products, as opposed to those that can be developed in-house, are delineated. Special attention is given to those methods that can be integrated into the current high-throughput paradigms of drug discovery programs. Together, these considerations define a 'zero-infrastructure' approach to provide ADME and Tox information during the early stages of the drug design process.

A series of 4-(N,N-diarylamino)piperidines are synthesized and evaluated for high affinity binding and selectivity to the delta-opioid receptor using a combination of 3D-QSAR and molecular docking techniques. Based on experimental ligand binding data to both mu- and delta- opioid receptors, CoMFA fields are generated and applied to identify potential ligand modifications to further optimize lead compounds. Molecular docking experiments to the delta-receptor are also reported that explain the CoMFA trends predicted as well as the differential binding and selectivity displayed by various compounds in the series. An analysis of the binding site model proposed indicates the piperidines take advantage of 3 key sites or binding domains within the delta-receptor. These include an aromatic pocket (approximately 1/3 into the receptor cavity), an aspartic acid residue (which serves as a docking point for the piperidinyl cationic amine) and a hydrophobic pocket at the extracellular boundary of the receptor cavity. Links are established between ligand modification and amino acid composition at these sites in mu and delta, providing new insight to the structural basis to binding and selectivity across the series and for related piperazines (i.e. SNC80 and BW373U86). Results are also presented that indicate delta- and mu-selectivity may be determined at alternate sites, suggesting opioid receptors may display multiple binding domains. The model is further supported by comparisons with opiate binding modes and site directed mutagenesis studies and is finally applied to suggest new strategies in ligand design.

Endomorphin-1 (Tyr-Pro-Trp-Phe-NH2) is a highly selective and potent agonist of the mu-opioid receptor. To identify structural attributes unique to this opioid peptide and potential sites of recognition, a conformational analysis has been performed using multidimensional NMR and molecular modeling techniques. The spectroscopic results, derived from experiments in both DMSO and water, indicate that endomorphin-1 exists in the cis- and trans-configuration with respect to the Pro-omega bond in approximately 25% and 75% populations, respectively. In DMSO, the cis-configuration adopts a compact sandwich conformation in which the Tyr and Trp aromatic rings pack against the proline ring, whereas the trans-configuration adopts an extended conformation. Although non-random structure was not observed in water, condensed phase molecular dynamics calculations indicate that trans-isomers dominate the population in this higher dielectric medium. Structural comparison of the cis- and trans-configurations with morphine and selective mu-peptide ligands PL-017 and D-TIPP, as well as the delta-selective peptide ligands TIPP (delta-antagonist, mu-agonist) and DPDPE were also performed and suggest the trans-isomer is likely the bioactive form. A hypothesis is proposed to explain mu- and delta-selectivity based on the presence of spatially distinct selectivity pockets among these ligands.

A series of isoindolo[2,1-a]- and pyrrolo[1,2-a]quinolines were designed and synthesized for DNA-gyrase and topoisomerase-II inhibition studies. Some of the compounds showed significant activity against the enzymes.

Design modifications to the lead HIV-PR inhibitor 1 (MDL 73,669, Ki = 5 nM) have been postulated based on a computational model of the 1/HIV-PR complex. A novel macrocyclic inhibitor 8 (MDL 104,168) wherein the P1 and P3 side chains of the original acyclic inhibitor have been joined retains good biological activity (Ki = 20 nM). NMR analysis of the precursor alcohol (S)-7 shows the conformation of the cyclic region to be very similar to that observed in the enzyme-bound 8 as determined by the computational model. Consistency of the computational model with NMR data and in vacuo molecular dynamics simulations provide the basis for postulating further modifications of the cyclic inhibitor expected to optimize its interactions with HIV-PR.