Preclinical modeling of multi-drug cancer therapies

Anticancer drugs typically are administered in the clinic in the form of mixtures, sometimes called combinations. Only in rare cases, however, are mixtures approved as drugs. Rather, research on mixtures tends to occur after single drugs have been approved. The goal of this research project was to develop modeling approaches that would encourage rational preclinical mixture design. To this end, a series of models were developed. First, several QSAR classification models were constructed to predict the cytotoxicity, oral clearance, and acute systemic toxicity of drugs. The QSAR models were applied to a set of over 115,000 natural compounds in order to identify promising ones for testing in mixtures. Second, an improved method was developed to assess synergistic, antagonistic, and additive effects between drugs in a mixture. This method, dubbed the MixLow method, is similar to the Median-Effect method, the de facto standard for assessing drug interactions. The primary difference between the two is that the MixLow method uses a nonlinear mixed-effects model to estimate parameters of concentration-effect curves, rather than an ordinary least squares procedure. Parameter estimators produced by the MixLow method were more precise than those produced by the Median-Effect Method, and coverage of Loewe index confidence intervals was superior. Third, a model was developed to predict drug interactions based on scores obtained from virtual docking experiments. This represents a novel approach for modeling drug mixtures and was more useful for the data modeled here than competing approaches. The model was applied to cytotoxicity data for 45 mixtures, each composed of up to 10 selected drugs. One drug, doxorubicin, was a standard chemotherapy agent and the others were well-known natural compounds including curcumin, EGCG, quercetin, and rhein. Predictions of synergism/antagonism were made for all possible fixed-ratio mixtures, cytotoxicities of the 10 best-scoring mixtures were tested, and drug interactions were assessed. Predicted and observed responses were highly correlated (r2 = 0.83). Results suggested that some mixtures allowed up to an 11-fold reduction of doxorubicin concentrations without sacrificing efficacy. Taken together, the models developed in this project present a general approach to rational design of mixtures during preclinical drug development. ^

A simulation study using the hybrid statistic and the meta-analysis t-test for data with matched and unmatched subjects in the interim analysis of clinical trials

An interim analysis is usually applied in later phase II or phase III trials to find convincing evidence of a significant treatment difference that may lead to trial termination at an earlier point than planned at the beginning. This can result in the saving of patient resources and shortening of drug development and approval time. In addition, ethics and economics are also the reasons to stop a trial earlier. In clinical trials of eyes, ears, knees, arms, kidneys, lungs, and other clustered treatments, data may include distribution-free random variables with matched and unmatched subjects in one study. It is important to properly include both subjects in the interim and the final analyses so that the maximum efficiency of statistical and clinical inferences can be obtained at different stages of the trials. So far, no publication has applied a statistical method for distribution-free data with matched and unmatched subjects in the interim analysis of clinical trials. In this simulation study, the hybrid statistic was used to estimate the empirical powers and the empirical type I errors among the simulated datasets with different sample sizes, different effect sizes, different correlation coefficients for matched pairs, and different data distributions, respectively, in the interim and final analysis with 4 different group sequential methods. Empirical powers and empirical type I errors were also compared to those estimated by using the meta-analysis t-test among the same simulated datasets. Results from this simulation study show that, compared to the meta-analysis t-test commonly used for data with normally distributed observations, the hybrid statistic has a greater power for data observed from normally, log-normally, and multinomially distributed random variables with matched and unmatched subjects and with outliers. Powers rose with the increase in sample size, effect size, and correlation coefficient for the matched pairs. In addition, lower type I errors were observed estimated by using the hybrid statistic, which indicates that this test is also conservative for data with outliers in the interim analysis of clinical trials.^

Design, Synthesis and Development of Transporter Targeting Agents for Image-guided Therapy and Drug Delivery

The purpose of this study was to design, synthesize and develop novel transporter targeting agents for image-guided therapy and drug delivery. Two novel agents, N4-guanine (N4amG) and glycopeptide (GP) were synthesized for tumor cell proliferation assessment and cancer theranostic platform, respectively. N4amG and GP were synthesized and radiolabeled with 99mTc and 68Ga. The chemical and radiochemical purities as well as radiochemical stabilities of radiolabeled N4amG and GP were tested. In vitro stability assessment showed both 99mTc-N4amG and 99mTc-GP were stable up to 6 hours, whereas 68Ga-GP was stable up to 2 hours. Cell culture studies confirmed radiolabeled N4amG and GP could penetrate the cell membrane through nucleoside transporters and amino acid transporters, respectively. Up to 40% of intracellular 99mTc-N4amG and 99mTc-GP was found within cell nucleus following 2 hours of incubation. Flow cytometry analysis revealed 99mTc-N4amG was a cell cycle S phase-specific agent. There was a significant difference of the uptake of 99mTc-GP between pre- and post- paclitaxel-treated cells, which suggests that 99mTc-GP may be useful in chemotherapy treatment monitoring. Moreover, radiolabeled N4amG and GP were tested in vivo using tumor-bearing animal models. 99mTc-N4amG showed an increase in tumor-to-muscle count density ratios up to 5 at 4 hour imaging. Both 99mTc-labeled agents showed decreased tumor uptake after paclitaxel treatment. Immunohistochemistry analysis demonstrated that the uptake of 99mTc-N4amG was correlated with Ki-67 expression. Both 99mTc-N4amG and 99mTc-GP could differentiate between tumor and inflammation in animal studies. Furthermore, 68Ga-GP was compared to 18F-FDG in rabbit PET imaging studies. 68Ga-GP had lower tumor standardized uptake values (SUV), but similar uptake dynamics, and different biodistribution compared with 18F-FDG. Finally, to demonstrate that GP can be a potential drug carrier for cancer theranostics, several drugs, including doxorubicin, were selected to be conjugated to GP. Imaging studies demonstrated that tumor uptake of GP-drug conjugates was increased as a function of time. GP-doxorubicin (GP-DOX) showed a slow-release pattern in in vitro cytotoxicity assay and exhibited anti-cancer efficacy with reduced toxicity in in vivo tumor growth delay study. In conclusion, both N4amG and GP are transporter-based targeting agents. Radiolabeled N4amG can be used for tumor cell proliferation assessment. GP is a potential agent for image-guided therapy and drug delivery.

NANOPARTICLE AGGLOMERATES FOR PULMONARY DRUG DELIVERY

The Pulmonary route has been traditionally used to treat diseases of the respiratory tract. However, important research within the last two decades have shown that in addition to treating local diseases, a wide range of systemic diseases can be treated by delivering drugs to the lungs. The recent FDA approval to market Exubera, an inhalable form of insulin developed by Pfizer, to treat Diabetes, may just be the stepping stone that the pharmaceutical industry needs to market other drugs to treat systemic diseases via the lungs. However, this technology still needs repeated drug doses to control glucose levels, as the inhaled drug is cleared rapidly. Technologies have been developed where inhaled particles are capable of controlled release of drug from the lungs. An important feature of these technologies is the large geometric size of the particles that makes it difficult for the lung macrophages to clear these particles, which results in longer residence times for the particles in the lungs. Owing to the porosity, these particles have lower densities making them deliverable to the deep lungs. However, no modulation of drug release can be achieved with these technologies when more drug release may be required. This additional requirement can only be assuaged by additional dosing of the drug formulation, which can have undesirable effects due to excess loading of excipients in the lungs. In an attempt to bring about modulation of release from long residence time particles, a novel concept was developed in our laboratory that has been termed as the Agglomerated Vesicle Technology (AVT). Liposomes with encapsulated drug were agglomerated using well known cross linking chemistries to form agglomerates in the micron sized range. The large particles exhibited aerodynamic sizes in the respirable size range with minimal damage to the particles upon nebulization. By breaking the cross links between the liposomes with a cleaving agent, it was anticipated that triggered release of drug from the AVT particles could be achieved. In vivo studies done in healthy rabbits showed that post-administration modulation of drug release is possible from the AVT particles after the introduction of the cleaving agent. This study has important implications for the future development of this technology, where the AVT particles can be made “sensitive” to the product of disease. It is envisaged that a single dose of AVT containing the appropriate drug when administered to the lungs would maintain drug levels at a controlled rate over an extended period of time. When the need for more drug arises, the product of the disease would trigger the AVT particles to release more drug as needed to control the condition, thus eliminating the need for repeated drug doses and improved compliance amongst patients.

THE ROLE OF TAK1 IN PANCREATIC CANCER DEVELOPMENT

Pancreatic cancer is the fourth leading cause of cancer-related mortality in the United States and the fifth leading cause of cancer-related mortality worldwide. Pancreatic cancer is a big challenge in large due to the lack of early symptoms. In addition, drug resistance is a major obstacle to the success of chemotherapy in pancreatic cancer. The underlying mechanism of drug resistance in human pancreatic cancers is not well understood. Better understanding of the mechanism of molecular pathways in human pancreatic cancers can help to identify the novel therapeutic target candidates, and develop the new preventive and clinic strategies to improve patient survival. We discovered that TAK1 is overexpressed in pancreatic cancer cell lines and patient tumor tissues. We demonstrated that the elevated activity of TAK1 is caused by its binding partner TAB1. Knocking down of TAK1 in pancreatic cancer cells with RNAi technique resulted in cell apoptosis and significantly reduces the size of tumors in mice and made a chemotherapy drug more potent. Targeting the kinase activity of TAK1 with the selective inhibitor LY2610956 strongly synergized in vitro with the antitumor activity of gemcitabine, oxaliplatin, or irinotecan on pancreatic cancer cells. These findings highlighted that TAK1 could be a potential therapeutic target for pancreatic cancer. We also demonstrated that TAK activity is regulated by its binding protein TAB1. We defined a minimum TAB1 sequence which is required and sufficient for TAK1 kinase activity. We created a recombinant TAK1-TAB1 C68 fusion form which has highly kinase activity. This active form could is used for screening TAK1 inhibitors. In addition, several posttranslational modifications were identified in our study. The acetylation of lysine 158 on TAK1 is required for kinase activity. This site is conserved throughout all of kinase. Our findings may reveal a new mechanism by which kinase activity is regulated.

Patterns of alcohol and illicit substance use in the United States and Mexico. Substantive and methodologic issues in the cross-national analysis of alcohol and drug use data

This research examines prevalence of alcohol and illicit substance use in the United States and Mexico and associated socio-demographic characteristics. The sources of data for this study are public domain data from the U.S. National Household Survey of Drug Abuse, 1988 (n = 8814), and the Mexican National Survey of Addictions, 1988 (n = 12,579). In addition, this study discusses methodologic issues in cross-cultural and cross-national comparison of behavioral and epidemiologic data from population-based samples. The extent to which patterns of substance abuse vary among subgroups of the U.S. and Mexican populations is assessed, as well as the comparability and equivalence of measures of alcohol and drug use in these national samples.^ The prevalence of alcohol use was somewhat similar in the two countries for all three measures of use: lifetime, past year and past year heavy use, (85.0%, 68.1%, 39.6% and 72.6%, 47.7% and 45.8% for the U.S. and Mexico respectively). The use of illegal substances varied widely between countries, with U.S. respondents reporting significantly higher levels of use than their Mexican counterparts. For example, reported use of any illicit substance in lifetime and past year was 34.2%, 11.6 for the U.S., and 3.3% and 0.6% for Mexico. Despite these differences in prevalence, two demographic characteristics, gender and age, were important correlates of use in both countries. Men in both countries were more likely to report use of alcohol and illicit substances than women. Generally speaking, a greater proportion of respondents in both countries 18 years of age or older reported use of alcohol for all three measures than younger respondents; and a greater proportion of respondents between the ages of 18 and 34 years reported use of illicit substances during lifetime and past year than any other age group.^ Additional substantive research investigating population-based samples and at-risk subgroups is needed to understand the underlying mechanisms of these associations. Further development of cross-culturally meaningful survey methods is warranted to validate comparisons of substance use across countries and societies. ^

PHENOTYPIC ASSOCIATION OF GENE AMPLIFICATION WITH MULTIPLE DRUG RESISTANCE IN VINCRISTINE RESISTANT CHINESE HAMSTER OVARY CELLS

Resistance of tumors to pharmacologic agents poses a significant problem in the treatment of human malignancies. This study overviews the scope of clinical resistance and focuses upon current research attempts toward investigation of the phenomenon of multidrug resistance (MDR).^ The objective of this investigation was to determine whether gene amplification had a role in the development of the MDR phenotype in Chinese hamster ovary cells (CHO) primarily selected for resistance to vincristine (VCR). A DNA fragment, previously shown to be amplified in two independently derived Chinese hamster cell lines exhibiting the MDR phenotype, was also amplified in VCR hamster lines. Sequences flanking this fragment were shown to contain coding information for a 4.3 kb transcript overproduced in VCR cells. These sequences were not enriched in double minute DNA preparations isolated from VCR cells. There was an approximately forty-fold increase in both the level of gene amplification and transcript overproduction in the VCR cell lines, independent of the level of primary resistance. This DNA amplification and overproduction of the 4.3 kb transcript was also demonstrated in CHO cells independently selected for resistance to Adriamycin and vinblastine.^ All the DNA sequences of two hamster cDNA clones containing 785 and 932 base pair inserts showed direct homology to the published mouse mdr sequences (about 90%). This sequence conservation held for only portions of the gene when the human mdr1 sequences were compared with those from either the mouse or hamster.^ Somatic cell hybrids, constructed between VCR CHO cells and sensitive murine cells, were used to determine whether there was a functional relationship between the chromosome bearing the amplified sequences and the MDR phenotype. Concordant segregation between vincristine resistance, the MDR phenotype, the presence of MDR-associated amplified sequences, overexpression of the mRNA encoded by these sequences, overexpression of the mRNA encoded by these sequences, and CHO chromosome Z1 was consistent with the hypothesis that there is an amplified gene on chromosome Z1 of the VCR CHO cells which is responsible for MDR in these cells. ^

Prevalence and risk factors for human immunodefiency virus and hepatitis C virus co-infection among drug users in innercity neighborhoods in Houston, Texas

Background. There are 200,000 HIV/HCV co-infected people in the US and IDUs are at highest risk of exposure. Between 52-92% of HIV infected IDUs are chronically infected with HCV. African Americans and Hispanics bear the largest burden of co-infections. Furthermore HIV/HCV co-infection is associated with high morbidity and mortality if not treated. The present study investigates the demographic, sexual and drug related risk factors for HIV/HCV co-infection among predominantly African American injecting and non-injecting drug users living in two innercity neighborhoods in Houston, Texas. ^ Methods. This secondary analysis used data collected between February 2004 and June 2005 from 1,889 drug users. Three case-comparison analyses were conducted to investigate the risk factors for HIV/HCV co-infection. HIV mono-infection, HCV mono-infection and non-infection were compared to HIV/HCV co-infection to build multivariate logistic regression models. Race/ethnicity and age were forced into each model regardless of significance in the univariate analysis. ^ Results. The overall prevalence of HIV/HCV co-infection was 3.9% while 39.8% of HIV infected drug users were co-infected with HCV and 10.7% of HCV infected drug users were co-infected with HIV. Among HIV infected IDUs the prevalence of HCV was 71.7% and among HIV infected NIDUs the prevalence of HCV was 24%. In the multivariate analysis, HIV/HCV co-infection was associated with injecting drug use when compared to HIV mono-infection, with MSM when compared to HCV mono-infection and with injecting drug use as well as MSM when compared to non-infection. ^ Conclusion. HIV/HCV co-infection was associated with a combination of sexual and risky injecting practices. More data on the prevalence and risk factors for co-infection among minority populations is urgently needed to support the development of targeted interventions and treatment options. Additionally there should be a focus on promoting safer sex and injecting practices among drug users as well as the expansion of routine testing for HIV and HCV infections in this high risk population.^

Process to develop a State Model Law to reduce prescription drug trafficking while protecting pain management

This paper will discuss the intersection of pill mills and the under-treatment of pain, while addressing the unintended consequence that cracking down on pill mills actually has on medical professionals' treatment of legitimate pain in clinical settings. Moreover, the impact each issue has on the spectrum of related policy, regulatory issues and legislation will be analyzed while addressing the national impact on medical care. Lastly, this paper will outline a process to develop a State Model Law on this subject. This process will include suggestions for the future and how we can move forward to adequately address public safety needs and how we can attempt to mitigate the unintended impact prescription drug trafficking has had on a patient's right to appropriate pain management. This balance is achievable and this paper will address ways we can find this elusive balancing point through the development of a State Model Law. ^

Elucidating the IGFBP2 signaling pathway in glioma development and progression

Diffuse gliomas are highly lethal central nervous system malignancies which, unfortunately, are the most common primary brain tumor and also the least responsive to the very few therapeutic modalities currently available to treat them. IGFBP2 is a newly recognized oncogene that is operative in multiple cancer types, including glioma, and shows promise for a targeted therapeutic approach. Elevated IGFBP2 expression is present in high-grade glioma and correlates with poor survival. We have previously demonstrated that IGFBP2 induces glioma development and progression in a spontaneous glioma mouse model, which highlighted its significance and potential for future therapy. However, we did not yet know the key physiological pathways associated with this newly characterized oncogene. We first evaluated human glioma genomics data harnessed from the publicly available Rembrandt source to identify major pathways associated with IGFBP2 expression. Integrin and ILK, among other cell migration and invasion-related pathways, were the most prominently associated. We confirmed that these pathways are regulated by IGFBP2 in glioma cells lines, and demonstrated that 1) IGFBP2 activates integrin α5β1, leading to the activation of key pathways important in glioma; 2) IGFBP2 mediates cell migration pathways through ILK; and 3) IGFBP2 activates NF-kB via an integrin α5 interaction. We then sought to determine whether this was a physiologically active signaling pathway in vivo by assessing its ability to induce glioma progression in the RCAS/tv-a spontaneous glioma mouse model. We found that ILK is a key downstream mediator of IGFBP2 that is required for the induction of glioma progression. Most significantly, a genetic therapeutic approach revealed that perturbation of any point in the pathway thwarted tumor progression, providing strong evidence that targeting the key players could potentially produce a significant benefit for human glioma patients. The elucidation of this signaling pathway is a critical step, since efforts to create a small molecule drug targeting IGFBP2 have so far not been successful, but a number of inhibitors of the other pathway constituents, including ILK, integrin and NF-kB, have been developed.

THE ALCOHOL TREATMENT PROFILE SYSTEM: ITS DEVELOPMENT AND AN EVALUATION OF ITS CAPABILITIES

The development of the Alcohol Treatment Profile System (ATPS) was described and an evaluation of its perceived value by various States was undertaken, The ATPS is a treatment needs assessment tool based on the unification of several large national epidemiologic and treatment data sets. It was developed by the National Institute on Alcohol Abuse and Alcoholism (NIAAA) and responsibility for its creation was given to the NIAAA's Alcohol Epidemiologic Data System (AEDS). The ATPS merges county-level measures of alcohol problem prevalence (the specially constructed AEDS Alcohol Problem Indicators), indicating "need" for treatment, and treatment utilization measures (the National Drug and Alcohol Treatment Utilization Survey), indicating treatment "demand." The capabilities of the ATPS in the unique planning and policy-making settings of several States were evaluated.^

Targeting TRAF6 for Cancer Therapeutical Development

Tumor necrosis factor (TNF)-Receptor Associated Factors (TRAFs) are a family of signal transducer proteins. TRAF6 is a unique member of this family in that it is involved in not only the TNF superfamily, but the toll-like receptor (TLR)/IL-1R (TIR) superfamily. The formation of the complex consisting of Receptor Activator of Nuclear Factor κ B (RANK), with its ligand (RANKL) results in the recruitment of TRAF6, which activates NF-κB, JNK and MAP kinase pathways. TRAF6 is critical in signaling with leading to release of various growth factors in bone, and promotes osteoclastogenesis. TRAF6 has also been implicated as an oncogene in lung cancer and as a target in multiple myeloma. In the hopes of developing small molecule inhibitors of the TRAF6-RANK interaction, multiple steps were carried out. Computational prediction of hot spot residues on the protein-protein interaction of TRAF6 and RANK were examined. Three methods were used: Robetta, KFC2, and HotPoint, each of which uses a different methodology to determine if a residue is a hot spot. These hot spot predictions were considered the basis for resolving the binding site for in silico high-throughput screening using GOLD and the MyriaScreen database of drug/lead-like compounds. Computationally intensive molecular dynamics simulations highlighted the binding mechanism and TRAF6 structural changes upon hit binding. Compounds identified as hits were verified using a GST-pull down assay, comparing inhibition to a RANK decoy peptide. Since many drugs fail due to lack of efficacy and toxicity, predictive models for the evaluation of the LD50 and bioavailability of our TRAF6 hits, and these models can be used towards other drugs and small molecule therapeutics as well. Datasets of compounds and their corresponding bioavailability and LD50 values were curated based, and QSAR models were built using molecular descriptors of these compounds using the k-nearest neighbor (k-NN) method, and quality of these models were cross-validated.

PROSTATE CANCER STEM CELLS: DRUG TOLERANCE, EXPERIMENTAL RECONSTITUTION AND CASTRATION RESISTANCE

Prostate cancer (PCa) is one of the leading malignancies affecting men in the Western world. Although tremendous effort has been made towards understanding PCa development and developing clinical treatments in the past decades, the exact mechanisms of PCa are still not clearly understood. Emerging evidence has postulated that a population of stem cell-like cells inside a tumor, termed ‘cancer stem cells (CSCs)’, may be the cells responsible for tumor initiation, progression, recurrence, metastasis and therapy resistance. Like CSC studies in other cancer types, it has been reported that PCa also contains CSCs. However, there remain several unresolved questions that need to be clarified. First, the relationship between prostate CSCs (PCSCs) and therapy resistance (chemo- and radio-) is not known. Herein, we have found that not all CSCs are drug-tolerant, and not all drug-tolerant cells are CSCs. Second, whether primary human PCa (HPCa) actually contain PCSCs remains unclear, due to the well-known fact that we have yet to establish a reliable assay system that can reproducibly and faithfully reconstitute tumor regeneration from single HPCa cells. Herein, after utilizing more than 114 HPCa samples we have provided evidence that immortalized bone marrow-derived stromal cells (Hs5) can help dissociated HPCa cells generate undifferentiated tumors in immunodeficient NOD/SCID-IL2Rγ-/- mice, and the undifferentiated PCa cells seem to have a survival advantage to generate tumors. Third, the evolution of PCa from androgen dependent to the lethally castration resistant (CRPC) stage remains enigmatic, and the cells responsible for CRPC development have not been identified. Herein, we have found a putative cell population, ALDH+CD44+α2β1+ PCa cells that may represent a cell-of-origin for CRPC. Taken together, our work has improved our understanding of PCSC properties, possibly highlighting a potential therapeutic target for CRPC.

Development of HIF-1α/HIF-1β heterodimerization inhibitors using a novel bioluminescence reporter assay system for in vitro high throughput screening and in vivo imaging

Tumor growth often outpaces its vascularization, leading to development of a hypoxic tumor microenvironment. In response, an intracellular hypoxia survival pathway is initiated by heterodimerization of hypoxia-inducible factor (HIF)-1α and HIF-1β, which subsequently upregulates the expression of several hypoxia-inducible genes, promotes cell survival and stimulates angiogenesis in the oxygen-deprived environment. Hypoxic tumor regions are often associated with resistance to various classes of radio- or chemotherapeutic agents. Therefore, development of HIF-1α/β heterodimerization inhibitors may provide a novel approach to anti-cancer therapy. To this end, a novel approach for imaging HIF-1α/β heterodimerization in vitro and in vivo was developed in this study. Using this screening platform, we identified a promising lead candidate and further chemically derivatized the lead candidate to assess the structure-activity relationship (SAR). The most effective first generation drug inhibitors were selected and their pharmacodynamics and anti-tumor efficacy in vivo were verified by bioluminescence imaging (BLI) of HIF-1α/β heterodimerization in the xenograft tumor model. Furthermore, the first generation drug inhibitors, M-TMCP and D-TMCP, demonstrated efficacy as monotherapies, resulting in tumor growth inhibition via disruption of HIF-1 signaling-mediated tumor stromal neoangiogenesis.

Advanced Protein Modeling Method: Benchmarking and Applications in Computer-Aided Drug Discovery

Development of homology modeling methods will remain an area of active research. These methods aim to develop and model increasingly accurate three-dimensional structures of yet uncrystallized therapeutically relevant proteins e.g. Class A G-Protein Coupled Receptors. Incorporating protein flexibility is one way to achieve this goal. Here, I will discuss the enhancement and validation of the ligand-steered modeling, originally developed by Dr. Claudio Cavasotto, via cross modeling of the newly crystallized GPCR structures. This method uses known ligands and known experimental information to optimize relevant protein binding sites by incorporating protein flexibility. The ligand-steered models were able to model, reasonably reproduce binding sites and the co-crystallized native ligand poses of the β2 adrenergic and Adenosine 2A receptors using a single template structure. They also performed better than the choice of template, and crude models in a small scale high-throughput docking experiments and compound selectivity studies. Next, the application of this method to develop high-quality homology models of Cannabinoid Receptor 2, an emerging non-psychotic pain management target, is discussed. These models were validated by their ability to rationalize structure activity relationship data of two, inverse agonist and agonist, series of compounds. The method was also applied to improve the virtual screening performance of the β2 adrenergic crystal structure by optimizing the binding site using β2 specific compounds. These results show the feasibility of optimizing only the pharmacologically relevant protein binding sites and applicability to structure-based drug design projects.