Xiang-Qun Xie - US grants

DESCRIPTION (Applicant's Abstract): Since the two cannabinoid receptor subtypes (CB1, CB2) have been identified as a subgroup of the Gi protein-coupled seven-transmembrane-spanning receptor superfamily, a great effort has been directed toward understanding the molecular-level interactions between the CB receptor and its ligand, as well as designing novel cannabimimetic ligands possessing therapeutically useful biological properties but devoid of the psychotropic effects of marijuana. However, many unanswered questions about the molecular-level interactions between the receptor and the cannabimimetic ligands, the nature of the receptor active site(s), and their three-dimensional structures remain to be addressed. The objective of this research proposal is to obtain information on the molecular properties of cannabimimetic agents in membranes (in order to mimic the receptor environment) through the combined use of nuclear magnetic resonance (NMR) and computer modeling methods. Such information is of critical importance for the design of novel analogs of potential therapeutic value. The conformational properties of a judiciously chosen group of analogs related to three known cannabimimetic groups, namely arachidonylethanolamides (AEAs), aminoalkylindoles (AAIs), and pyrazoles (PRZs) will be studied using NMR methods and then refined using computer modeling approaches. 1) A special effort will be made to study the conformations of these molecules in a membrane environment. The 3D structure of the ligand in the membrane will be obtained using a variety of NMR techniques including multidimensional NMR experiments with pulse gradients, Transfer NOE and Rotational Echo Double Resonance experiments. 2) Computer modeling will be used to refine the NMR-determined conformations. Comparative Molecular Field Analysis (CoMFA) and the Active Analog Approach will be applied to examine the definition of pharmacophores and to define the active site as well as to map receptor volume. The pharmacophoric model defined by NMR experiments and theoretical calculations can be used as a guide for designing novel CB ligands and predicting the biological behavior of other untested compounds. The procedures developed will eventually be used to directly study the conformation of receptor-bound ligands in the future. Overall, the studies will provide insights into the design of a new generation of ligands possessing enhanced biological activity.

DESCRIPTION (Applicant's Abstract): Since the two cannabinoid receptor subtypes (CB1, CB2) have been identified as a subgroup of the Gi protein-coupled seven-transmembrane-spanning receptor superfamily, a great effort has been directed toward understanding the molecular-level interactions between the CB receptor and its ligand, as well as designing novel cannabimimetic ligands possessing therapeutically useful biological properties but devoid of the psychotropic effects of marijuana. However, many unanswered questions about the molecular-level interactions between the receptor and the cannabimimetic ligands, the nature of the receptor active site(s), and their three-dimensional structures remain to be addressed. The objective of this research proposal is to obtain information on the molecular properties of cannabimimetic agents in membranes (in order to mimic the receptor environment) through the combined use of nuclear magnetic resonance (NMR) and computer modeling methods. Such information is of critical importance for the design of novel analogs of potential therapeutic value. The conformational properties of a judiciously chosen group of analogs related to three known cannabimimetic groups, namely arachidonylethanolamides (AEAs), aminoalkylindoles (AAIs), and pyrazoles (PRZs) will be studied using NMR methods and then refined using computer modeling approaches. 1) A special effort will be made to study the conformations of these molecules in a membrane environment. The 3D structure of the ligand in the membrane will be obtained using a variety of NMR techniques including multidimensional NMR experiments with pulse gradients, Transfer NOE and Rotational Echo Double Resonance experiments. 2) Computer modeling will be used to refine the NMR-determined conformations. Comparative Molecular Field Analysis (CoMFA) and the Active Analog Approach will be applied to examine the definition of pharmacophores and to define the active site as well as to map receptor volume. The pharmacophoric model defined by NMR experiments and theoretical calculations can be used as a guide for designing novel CB ligands and predicting the biological behavior of other untested compounds. The procedures developed will eventually be used to directly study the conformation of receptor-bound ligands in the future. Overall, the studies will provide insights into the design of a new generation of ligands possessing enhanced biological activity.

DESCRIPTION (provided by applicant): Since the discovery of cannabinoid (CB) receptors, cannabinoid research has witnessed rapid and important developments and renaissance. CB2 derived from human promyelicytic leukemia cell is a subtype of cannabinoid receptors. Unlike its closely related sub-type receptor CB1, which is believed to be responsible for the modulation of Q-type Ca2+ and inwardly rectifying K+ channels in CNS, CB2 receptor is expressed in high quantifies in human spleen and tonsils, and is likely to be involved in the signal transduction processes in immune system, Therefore, CB2 receptor can potentially be a target for immuno-treatments. Thus, knowledge of the 3D structure of CB receptors and the further understanding of ligand-receptor interaction will greatly aid in the rational design of specific CB2 ligands possessing potent therapeutic activities, but devoid from the undesirable side effects. However, its intrinsic membrane protein property makes it difficult to crystallize for x-ray study. Direct NMR study is also restricted due to the large protein size and slow correlation time, whereas NMR study of synthetic polypeptide is limited by available length of peptides, and low signal-to-noise (S/N) of natural abundant peptides. The objective of this proposal is to obtain the purified recombinant CB2 protein segments (transmembrane domains, or helix bundles) that are expressed in Escherichia coli (E. coli) (isotope-enriched media) for structural biology determination by NMR and computer modeling. Such studies will provide valuable experimental data to refine a 3D construct of CB2 receptor. In addition, the proposed studies will determine the structural and conformational information of the CB2 receptor segments that will shed light towards the understanding of receptor binding-activating-signaling mechanisms. Eventually, an experimental-based 3D CB2 structure will be more reliable for rational drug design. Overall, the method proposed here represents a novel combined approach of protein engineering, modem isotope aided NMR, and computer modeling for study of G-protein coupled transmembrane receptors (GPCRs) that is a large family of drug targets (approximately 45 percent of the market drugs). The work accomplished through this proposed research can potentially make a significant contribution to cannabinoid research and NMR structural biology, as well as GPCRs in general.

[unreadable] DESCRIPTION (provided by applicant): Cannabinoids (CB), a class of GPCR-targeted molecules, represent an important family of molecules with large diversity. Their uses are not limited to studying drug abuse but also to designing new drugs for cancer chemotherapy, AIDS, pain relief, muscle spasms, glaucoma, immune suppression, etc. Scientists have synthesized and bio-examined many structurally similar or dissimilar cannabimimetic ligands. Thousands of journal articles have been published regarding CB research and clinical trials. The cannabinoid community is forming its own genre of new scientific research. Unfortunately, due to the traditional method of publicizing research works in paper form, the data related to CB ligands are scattered in archival journals. This makes it very difficult to find, associate and validate reported molecules and reuse the reported research results for further studies. This problem is expected to be much more aggravating in the future as number of the scientists studying the molecules increases many-fold and the size of CB applications grows exponentially. The goal of this proposal is to develop a public repository that includes a majority of published data about cannabinoids in a structured, electronic format. By having such a database, scientists will be able to easily query and retrieve their needed ligand information and, furthermore, associate them with other related data available in public or private repositories. Our goal is not only to create the repository by collecting existing data and integrating them but also to design and implement a computational environment that facilitates the repository's future growth. In the long run, the researchers of the cannabinoid community should deposit the data by themselves and maintain the database in a collective community effort. Our goal also includes developing flexible, easy to use query interfaces for the database that are crucial to encouraging community scientists to adopt the repository for their daily study. In addition, we plan to incorporate the newest data exchange technology, XML, into the database so that the content of this database becomes more portable to third party computational environments and becomes more immune to future changes in database technology, as well. Ultimately, this proposed research project will make a significant contribution by developing a tool and a medium for information exchange and data sharing among the scientific community and beyond. [unreadable] [unreadable]

Autoimmune Diseases; Binding; Binding (Molecular Function); CB2 Receptor; CRISP; Cannabinoids; Computer Retrieval of Information on Scientific Projects Database; Crystallography, X-Ray; Crystallography, X-Ray Diffraction; Crystallography, X-Ray/Neutron; Crystallography, Xray; Disease; Disorder; Docking; Drugs; Event; Family; Funding; G Protein-Complex Receptor; G-Protein-Coupled Receptors; Goals; Grant; Hydrogen Oxide; Institution; Investigators; Isotope Labeling; Length; Ligand Binding; Ligands; Lipid Bilayers; Lipids; Lupus; MS (Multiple Sclerosis); Marihuana; Medication; Membrane; Membrane Proteins; Membrane-Associated Proteins; Modeling; Molecular Configuration; Molecular Conformation; Molecular Dynamics Simulation; Molecular Interaction; Molecular Stereochemistry; Multiple Sclerosis; NIH; National Institutes of Health; National Institutes of Health (U.S.); Pain; Painful; Pharmaceutic Preparations; Pharmaceutical Preparations; Property; Property, LOINC Axis 2; Proteins; Publications; Range; Receptor Protein; Receptor, Cannabinoid, CB2; Reporting; Research; Research Personnel; Research Resources; Researchers; Resolution; Resources; Rhodopsin; Scientific Publication; Sclerosis, Disseminated; Simulate; Single Crystal Diffraction; Source; Structure; Surface Proteins; System; System, LOINC Axis 4; Therapeutic Agents; United States National Institutes of Health; Visual Purple; Water; Work; X Ray Crystallographies; X-Ray Crystallography; autoimmune disorder; cannabinoid receptor; conformation; conformational state; design; designing; disease/disorder; drug/agent; gene product; improved; insular sclerosis; lipid bilayer membrane; member; membrane model; membrane structure; molecular dynamics; protein expression; receptor; structural biology

This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. Primary support for the subproject and the subproject's principal investigator may have been provided by other sources, including other NIH sources. The Total Cost listed for the subproject likely represents the estimated amount of Center infrastructure utilized by the subproject, not direct funding provided by the NCRR grant to the subproject or subproject staff. Project 1. We are in process of building a 1 billion of small molecule chemical (or 1B) library to facilitate the cheminformatics studies and chemical library design in aid of virtual drug screening or combinatorial chemical library design. As a part of goals, we will need to access the cluster at PSC to allow us to convert the chemical library SMILE format to 2D molecular fingerprints format, and then we can implement the 2D fingerprints into the 1B library in which we have already developed the molecular structure search engine and platform. Project2. We will continue the MD simulations to refine the predicted 3D GPCR CB2 receptor structure models (preliminary work completed with two publications). Further molecular dynamics (MD) calculations of the 3D CB2 receptor structure in membrane model (in a lipid/water simulated bilayer membrane system). Such a large biosystem requires high power computing facility that is available @PSC. In addition, we will explore the active ligand binding conformations and further evaluate the binding energy using QM approaches, including GAUSSIAN for ab initio computations

DESCRIPTION (provided by applicant): The discovery of the endogenous cannabinoid (CB) system, i.e. the CB receptors (the subtypes CB1 and CB2), endogenous ligands and enzymes for CB ligand metabolism, has triggered intensive pharmacological research into the CB receptors and the therapeutic potential of cannabinergic ligands. The CB2 receptor is known to be involved in the signal transduction cascades in the immune system, and has a great therapeutic potential for developing CB2 drugs without CB1-related psychotropic side effects for treatment of chronic neuro-pain, neuronal disorders, autoimmune diseases, and gliomas and other tumors of immune origin, thereby benefiting the millions of patients who suffer from the autoimmune/immune-related diseases for which we have no cure. Over the years, however, structural and functional studies of CB receptors have focused on predicting structures by computer modeling, identification of the specific sites for ligand binding and G-protein coupling whereas studies on experiment 3D CB structures are limited, in particular for the CB2 receptor. To understand the molecular mechanism behind these pharmacological and biochemical events, it is important to characterize the contacting points and binding domains and then elucidate the specific CB2/ligand recognition and CB2/G-protein coupling mechanisms at molecular structural level. In our published and pilot studies, we have successfully investigated the structural and conformational features of several CB2 protein functional domains; CB ligand structures and active pharmacophoric features; and agonist/antagonist recognition sites in the CB2 receptor. However, many questions still remain about CB2 receptor structure-function relationship as well as CB2 ligands and G-protein recognition mechanisms. The objective of this proposal is to identify/characterize the key residues/functional domains and elucidate their 3D structures of recognition pockets important to agonist and antagonist binding as well as G-protein coupling recognitions in the CB2 receptor by the combined biophysical and biochemical approaches. Our long term goal is to understand, in structural and functional terms, the molecular mechanisms of human CB2 activation and G-protein cell signaling process in order to facilitate the structure-based design for novel CB2 ligands. Having completed the proof-of-concept research work, we propose the specific goals and in-depth research to three aims. Aim 1: Characterize the functional domains and key residues important to the CB2 ligand recognition and derive the structural determinants of the agonist/antagonist binding domains in the transmembrane and extra-cellular segments. Aim 2: Investigate and define the structural and functional features of the important CB2 intracellular segments and key residues involving G-protein coupling and intracellular cell signaling by the biophysical approaches developed and validated in Aim 1. Aim 3: Explore full-length CB2 receptor and confirm the key residues determined in Aims 1 and 2 and verify their importance to CB2 ligand recognition and G-protein coupling by functional binding assays and site-directed mutations of the native CB2 receptor. The elucidated CB2 agonist/antagonist recognition pockets and G-protein coupling domains will be further examined by our established computer modeling and receptor docking algorithms. Our proposed research and the outcomes will shed light onto a better understanding of CB2 structure/function and its mechanism of actions, and provide the structural bases for CB2-specific drug design in future. The techniques and methods developed from the proposed CB2 receptor research will also have a significant impact to other GPCRs. PUBLIC HEALTH RELEVANCE: This proposal is to identify and elucidate their 3D structures of recognition pockets important to agonist and antagonist binding as well as G-protein coupling recognitions in the cannabinoid CB2 receptor. The long-term benefits will allow us to better understand, in structural and functional terms, the molecular mechanisms of human CB2 activation and G-protein cell signaling process in order to facilitate structure-based design for novel CB2 chemical probes.

Human hematopoietic stem cells (HSC) transplantation is currently being used as regenerative medicine for the treatment of congenital deficiencies and malignant diseases as well as cancers and other disorders of the blood and immune systems. However, despite all the enthusiasm surrounding HSC biology and therapeutics, the potential of HSC-based therapies has yet to be fully realized. A major roadblock of broader use of the adult stem cells is the limited number of HSC per harvest for therapeutic benefit and their poorly understood expansion and differentiation behavior in response to proliferative stimuli. In vitro expansion of HSC remains a major challenge for wide applications of HSC transplantation for patients. Our studies show that p18, a member of the cyclin-dependent kinase (CDK) inhibitors (CKI), is a potent negative regulator of HSC self- renewal. Thus, we hypothesize that p18 is a unique drug target, and that small molecules capable of blocking p18 function and interfering with p18/CDK6 interactions are likely to be potent drugs for activating HSC self- renewal. Our objective is to screen/identify p18 inhibitors that act by disrupting p18/CDK6 interactions, thus activating HSC self-renewal and increasing the quantity of active stem cells, and to use them as chemical probes for mechanism studies of HSC self-renewal. The feasibility of the proposed innovative research is supported by the proof-of-principle pilot data obtained by well-established research teams that have complementary expertise for the proposed research. Considering the limited throughput capacity of the current HSC bone-marrow culture protocol, we propose first to use our established in silico screening approach for initial screening to generate p18-focused lead sublibraries (Aim 1). We also apply NMR assays to screen/validate and characterize the p18 hits and their binding interactions with the protein in order to generate p18-active subsets (Aim 2A). Also, the small subsets of validated p18-targeting compounds will then be confirmed by extensive HSC functional assays (Aim 2B). Through these, the compounds that are capable of increasing the number of active stem cells in the bone-marrow culture will be identified as leads. The discovered leads are then used as specific chemical probes for studies of p18/CDK6 interactions and signaling mechanisms of the G1-phase of the cell cycle. As a future plan, the identified leads will be further optimized by chemistry modification and SAR medicinal chemistry studies to improve the potency and cell toxicity. Our long- term goal is to identify/design CKI p18-specific small molecule effectors that can either maintain/stimulate self- renewal of hematopoietic stem cells in a predictable manner, and ultimately to develop new drugs for HSC therapies. Achieving this goal will have a significant impact on stem cell drug research development in general.

DESCRIPTION (provided by applicant): We propose to establish a NIDA Center of Excellence for Computational Drug Abuse Research (CDAR) between the University of Pittsburgh (Pitt) and (CMU), with the goal of advancing and ensuring the productive and broad usage of state-of-the-art computational technologies that will facilitate and enhance drug abuse (DA) research, both in the local (Pittsburgh) area and nationwide. To this end, we will develop/integrate tools for DA-domain-specific chemical-to-protein-to-genomics mapping using cheminformatics, computational biology and computational genomics methods by centralizing computational chemical genomics (or chemogenomics) resources while also making them available on a cloud server. The Center will foster collaboration and advance knowledge-based translational research and increase the effectiveness of ongoing funded research project (FRPs) via the following Research Support Cores: (1) The Computational Chemogenomics Core for DA (CC4DA) will help address polydrug addiction/polypharmacology by developing new chemogenomics tools and by compiling the data collected/generated, along with those from other Cores, into a DA knowledge-based chemogenomics (DA-KB) repository that will be made accessible to the DA community. (2) The Computational Biology Core (CB4DA) will focus on developing a resource for structure-based investigation of the interactions among substances of DA and their target proteins, in addition to assessing the drugability of receptors and transporters involved in DA and addiction. These activities will be complemented by quantitative systems pharmacology methods to enable a systems-level approach to DA research. (3) The Computational Genomics Core (CG4DA) will carry out genome-wide discovery of new DA targets, markers, and epigenetic influences using developed machine learning models and algorithms. (4) The Administrative Core will coordinate Center activities, provide management to oversee the CDAR activities in consultation with the Scientific Steering Committee (SSC) and an External Advisory Board (EAB), ensure the effective dissemination of software/data among the Cores and the FRPs, and establish mentoring mechanisms to train junior researchers. Overall, the Center will strive to achieve the long-term goal of translating advances in computational chemistry, biology and genomics toward the development of novel personalized DA therapeutics.

Project summary Our goal is to develop artificial intelligent (AI) analytics models to facilitate personalized treatment plans for Alzheimer?s disease (AD) patients with most common comorbidities, such as cardiovascular diseases (CVD), diabetes mellitus (DM) and depression. AD is a neurodegenerative disease that progressively causes memory loss and cognitive impairment. While current treatments have shown some amelioration of symptoms, the effects have been transient and limited to a small percentage of patients. Moreover, disease-modifying drugs based on our current understanding of disease mechanisms have all shown negative results in clinical trials. Part of the failure is due to the heterogeneity in the disease mechanism, of which we do not yet have a clear understanding. Additionally, increasing evidence has indicated that comorbidities of AD share common disease pathways with AD, and medications used for these diseases may also alter the cognitive functions in AD patients. However, few studies have assessed combinations of these medications in treatments for AD. In this study, we will address this problem by retrospectively analyzing the observational data collected by the University of Pittsburgh Alzheimer?s Disease Research Center (ADRC). In Aim 1, we plan to statistically investigate the effects of different medications when used in combination with anti-AD medications on the trajectory of cognitive decline. If specific drug combination(s) are found to have a potential synergistic effect against cognitive decline, we will further study the underlying mechanisms using molecular systems pharmacology methods in Aim 2. In Aim 3, we will focus on establishing a clinical decision support system that facilitates individualized treatment for AD patients with these common comorbidities. We will build a Bayesian Network model that can predict the disease progression based patient and treatment information provided by the ADRC data set. The model will be learned and tested based on the ADRC dataset using the Tetrad software package. We will then apply methodologies of decision theory and search for a treatment combination that leads to the optimal treatment outcomes for specific patients. Collectively, these studies will contribute to a discovery of novel drug combinations for treating AD patients with comorbidities, and generate ideas for a clinical decision support system that can facilitate personalized medicine for these patients.

Cannabinoid receptor subtype 2 (CB2) is a class-A family G protein-coupled receptor (GPCR), located primarily in immune-associated tissues but also in specific regions of the brain, and implicated in several inflammatory diseases and addiction. Drugs targeting CB2 are attractive treatment alternatives for chronic neurological pain and neuroinflammatory autoimmune diseases since they avoid deleterious psychotropic effects that are associated with CB1. While drug development efforts have been primarily focused on small molecules targeting the orthosteric site, limitations of poor selectivity, lack of efficacy, and development of resistance have hampered such effort. At present, there is great interests in identifying GPCR allosteric modulators that either enhance (positive allosteric modulators, or PAMs) or inhibit (negative allosteric modulators, or NAMs) agonist-induced receptor activity. PAMs/NAMs often exhibit improved subtype selectivity and spatiotemporal sensitivity, as well as potential biased signaling properties compared to orthosteric ligands. We have recently reported a 3.2 Å cryo-EM structure of the agonist-bound human CB2-Gi complex. Based on such progress, the overall goals of this proposal are to obtain a structural understanding of CB2 allosteric modulation and use our integrated computational and experimental medicinal chemistry/biology approaches to design and synthesize novel allosteric modulators for the development of CB2-specific small-molecules with potential to treat CB2-associated maladies. Thus, we first propose to elucidate the structural basis for the action of CB2 allosteric modulators by cryo-EM and X-ray crystallography approaches. To achieve the goal, we will advance our established methods for structural studies on CB2 to obtain structure of CB2 with known PAMs or NAMs. Subsequently, we plan to perform in silico design of novel CB2 allosteric modulators by our established molecular fingerprint machine-learning (ML) computing algorithms and receptor docking approaches, on basis of our reported chemogenomics cannabinoid molecular information database (CBID) and 3D CB2-Gi cryo-EM structure; a virtual allosteric modulator library will be constructed using our fragment-based design (FBD) method and our established ML-classifiers and features-ranking will be applied for selection of virtual hits. Results will be correlated with CB2 structure-based modulator design via adapting the structural information obtained from our recent CB2-Gi cryo-EM structure and our novel molecular complex characterizing system (MCCS) algorithm. Finally, we will carry out medicinal chemistry synthesis of CB2 PAM and NAM ligands and validate them by radiometric binding and cellular functional assays. With the proof-of-evidence of our recent discovery of a putative CB2 NAM, successful completion of these Aims will provide unprecedented structural information on CB2 allosteric pockets, identify promising new CB2 allosteric modulators, and help to elucidate CB2 signaling and pharmacology.