Browsing by Author "Lu, Pinyi"

Now showing 1 - 9 of 9
  • Thumbnail Image
    Computational Modeling-Based Discovery of Novel Classes of Anti-Inflammatory Drugs That Target Lanthionine Synthetase C-Like Protein 2
    Lu, Pinyi; Hontecillas, Raquel; Horne, William T.; Carbo, Adria; Viladomiu, Monica; Pedragosa, Mireia; Bevan, David R.; Lewis, Stephanie N.; Bassaganya-Riera, Josep (PLOS, 2012-04-11)
    Background: Lanthionine synthetase component C-like protein 2 (LANCL2) is a member of the eukaryotic lanthionine synthetase component C-Like protein family involved in signal transduction and insulin sensitization. Recently, LANCL2 is a target for the binding and signaling of abscisic acid (ABA), a plant hormone with anti-diabetic and anti-inflammatory effects. Methodology/Principal Findings: The goal of this study was to determine the role of LANCL2 as a potential therapeutic target for developing novel drugs and nutraceuticals against inflammatory diseases. Previously, we performed homology modeling to construct a three-dimensional structure of LANCL2 using the crystal structure of lanthionine synthetase component C-like protein 1 (LANCL1) as a template. Using this model, structure-based virtual screening was performed using compounds from NCI (National Cancer Institute) Diversity Set II, ChemBridge, ZINC natural products, and FDA-approved drugs databases. Several potential ligands were identified using molecular docking. In order to validate the anti-inflammatory efficacy of the top ranked compound (NSC61610) in the NCI Diversity Set II, a series of in vitro and pre-clinical efficacy studies were performed using a mouse model of dextran sodium sulfate (DSS)-induced colitis. Our findings showed that the lead compound, NSC61610, activated peroxisome proliferator-activated receptor gamma in a LANCL2- and adenylate cyclase/cAMP dependent manner in vitro and ameliorated experimental colitis by down-modulating colonic inflammatory gene expression and favoring regulatory T cell responses. Conclusions/Significance: LANCL2 is a novel therapeutic target for inflammatory diseases. High-throughput, structure-based virtual screening is an effective computational-based drug design method for discovering anti-inflammatory LANCL2-based drug candidates.
  • Thumbnail Image
    Computational modeling-based discovery of novel classes of anti-inflammatory drugs that  target lanthionine synthetase C-like protein 2
    Lu, Pinyi (Virginia Tech, 2015-12-15)
    Lanthionine synthetase C-like protein 2 (LANCL2) is a member of the LANCL protein family, which is broadly expressed throughout the body. LANCL2 is the molecular target of abscisic acid (ABA), a compound with insulin-sensitizing and immune modulatory actions. LANCL2 is required for membrane binding and signaling of ABA in immune cells. Direct binding of ABA to LANCL2 was predicted in silico using molecular modeling approaches and validated experimentally using ligand-binding assays and kinetic surface plasmon resonance studies. The therapeutic potential of the LANCL2 pathway ranges from increasing cellular sensitivity to anticancer drugs, insulin-sensitizing effects and modulating immune and inflammatory responses in the context of immune-mediated and infectious diseases. A case for LANCL2-based drug discovery and development is also illustrated by the anti-inflammatory activity of novel LANCL2 ligands such as NSC61610 against inflammatory bowel disease in mice. This dissertation discusses the value of LANCL2 as a novel therapeutic target for the discovery and development of new classes of orally active drugs against chronic metabolic, immune-mediated and infectious diseases and as a validated target that can be used in precision medicine. Specifically, in Chapter 2 of the dissertation, we performed homology modeling to construct a three-dimensional structure of LANCL2 using the crystal structure of LANCL1 as a template. Our molecular docking studies predicted that ABA and other PPAR - agonists share a binding site on the surface of LANCL2. In Chapter 3 of the dissertation, structure-based virtual screening was performed. Several potential ligands were identified using molecular docking. In order to validate the anti-inflammatory efficacy of the top ranked compound (NSC61610) in the NCI Diversity Set II, a series of in vitro and pre-clinical efficacy studies were performed using a mouse model of dextran sodium sulfate (DSS)-induced colitis. In Chapter 4 of the dissertation, we developed a novel integrated approach for creating a synthetic patient population and testing the efficacy of the novel pre-clinical stage LANCL2 therapeutic for Crohn's disease in large clinical cohorts in silico. Efficacy of treatments on Crohn's disease was evaluated by analyzing predicted changes of Crohn's disease activity index (CDAI) scores and correlations with immunological variables were evaluated. The results from our placebo-controlled, randomized, Phase III in silico clinical trial at 6 weeks following the treatment shows a positive correlation between the initial disease activity score and the drop in CDAI score. This observation highlights the need for precision medicine strategies for IBD.
  • Thumbnail Image
    Dietary alpha-Eleostearic Acid Ameliorates Experimental Inflammatory Bowel Disease in Mice by Activating Peroxisome Proliferator-Activated Receptor-gamma
    Lewis, Stephanie N.; Brannan, Lera; Guri, Amir J.; Lu, Pinyi; Hontecillas, Raquel; Bassaganya-Riera, Josep; Bevan, David R. (PLOS, 2011-08-31)
    Background: Treatments for inflammatory bowel disease (IBD) are modestly effective and associated with side effects from prolonged use. As there is no known cure for IBD, alternative therapeutic options are needed. Peroxisome proliferator-activated receptor-gamma (PPARγ) has been identified as a potential target for novel therapeutics against IBD. For this project, compounds were screened to identify naturally occurring PPARγ agonists as a means to identify novel anti-inflammatory therapeutics for experimental assessment of efficacy. Methodology/Principal Findings: Here we provide complementary computational and experimental methods to efficiently screen for PPARγ agonists and demonstrate amelioration of experimental IBD in mice, respectively. Computational docking as part of virtual screening (VS) was used to test binding between a total of eighty-one compounds and PPARγ. The test compounds included known agonists, known inactive compounds, derivatives and stereoisomers of known agonists with unknown activity, and conjugated trienes. The compound identified through VS as possessing the most favorable docked pose was used as the test compound for experimental work. With our combined methods, we have identified α-eleostearic acid (ESA) as a natural PPARγ agonist. Results of ligand-binding assays complemented the screening prediction. In addition, ESA decreased macrophage infiltration and significantly impeded the progression of IBD-related phenotypes through both PPARγ-dependent and –independent mechanisms in mice with experimental IBD. Conclusions/Significance: This study serves as the first significant step toward a large-scale VS protocol for natural PPARγ agonist screening that includes a massively diverse ligand library and structures that represent multiple known target pharmacophores.
  • Thumbnail Image
    Lanthionine synthetase component C-like proteins as molecular targets for preventing and treating diseases and disorders
    (United States Patent and Trademark Office, 2015-08-11)
    The present invention relates to the field of medical treatments for diseases and disorders. More specifically, the present invention relates to the use of the lanthionine synthetase component C-like (LANCL) proteins as therapeutic targets for novel classes of anti-inflammatory, immune regulatory and antidiabetic drugs. This includes but it is not limited to abscisic acid (ABA), ABA analogs, benzimidazophenyls, repurposed drugs or drug combinations, including thiazolidinediones (TZDs); naturally occurring compounds such as conjugated diene fatty acids, conjugated triene fatty acids, isoprenoids, and natural and synthetic agonists of peroxisome proliferator-activated receptors that activate this receptor through an alternative mechanism of action involving LANCL2 or other membrane proteins to treat or prevent the common inflammatory pathogenesis underlying type 2 diabetes, atherosclerosis, cancer, some inflammatory infectious diseases such as influenza and autoimmune diseases including but not limited to inflammatory bowel disease (Crohn's disease and Ulcerative colitis), rheumatoid arthritis, multiple sclerosis and type 1 diabetes and other chronic inflammatory conditions.
  • Thumbnail Image
    Modeling the Role of Lanthionine Synthetase C-Like 2 (LANCL2) in the Modulation of Immune Responses to Helicobacter pylori Infection
    Leber, Andrew; Bassaganya-Riera, Josep; Tubau-Juni, Nuria; Zoccoli-Rodriguez, Victoria; Viladomiu, Monica; Abedi, Vida; Lu, Pinyi; Hontecillas, Raquel (PLOS, 2016-12-09)
    Immune responses to Helicobacter pylori are orchestrated through complex balances of host-bacterial interactions, including inflammatory and regulatory immune responses across scales that can lead to the development of the gastric disease or the promotion of beneficial systemic effects. While inflammation in response to the bacterium has been reasonably characterized, the regulatory pathways that contribute to preventing inflammatory events during H. pylori infection are incompletely understood. To aid in this effort, we have generated a computational model incorporating recent developments in the understanding of H. pylori-host interactions. Sensitivity analysis of this model reveals that a regulatory macrophage population is critical in maintaining high H. pylori colonization without the generation of an inflammatory response. To address how this myeloid cell subset arises, we developed a second model describing an intracellular signaling network for the differentiation of macrophages. Modeling studies predicted that LANCL2 is a central regulator of inflammatory and effector pathways and its activation promotes regulatory responses characterized by IL-10 production while suppressing effector responses. The predicted impairment of regulatory macrophage differentiation by the loss of LANCL2 was simulated based on multiscale linkages between the tissue-level gastric mucosa and the intracellular models. The simulated deletion of LANCL2 resulted in a greater clearance of H. pylori, but also greater IFNγ responses and damage to the epithelium. The model predictions were validated within a mouse model of H. pylori colonization in wild-type (WT), LANCL2 whole body KO and myeloid-specific LANCL2-/- (LANCL2Myeloid) mice, which displayed similar decreases in H. pylori burden, CX3CR1+ IL-10-producing macrophages, and type 1 regulatory (Tr1) T cells. This study shows the importance of LANCL2 in the induction of regulatory responses in macrophages and T cells during H. pylori infection.
  • Thumbnail Image
    Modeling-Enabled Characterization of Novel NLRX1 Ligands
    Lu, Pinyi; Hontecillas, Raquel; Abedi, Vida; Kale, Shiv D.; Leber, Andrew; Heltzel, Chase; Langowski, Mark; Godfrey, Victoria; Philipson, Casandra; Tubau-Juni, Nuria; Carbo, Adria; Girardin, Stephen; Uren, Aykut; Bassaganya-Riera, Josep (PLOS, 2015-12-29)
    Nucleotide-binding domain and leucine-rich repeat containing (NLR) family are intracellular sentinels of cytosolic homeostasis that orchestrate immune and inflammatory responses in infectious and immune-mediated diseases. NLRX1 is a mitochondrial-associated NOD-like receptor involved in the modulation of immune and metabolic responses. This study utilizes molecular docking approaches to investigate the structure of NLRX1 and experimentally assesses binding to naturally occurring compounds from several natural product and lipid databases. Screening of compound libraries predicts targeting of NLRX1 by conjugated trienes, polyketides, prenol lipids, sterol lipids, and coenzyme A-containing fatty acids for activating the NLRX1 pathway. The ligands of NLRX1 were identified by docking punicic acid (PUA), eleostearic acid (ESA), and docosahexaenoic acid (DHA) to the C-terminal fragment of the human NLRX1 (cNLRX1). Their binding and that of positive control RNA to cNLRX1 were experimentally determined by surface plasmon resonance (SPR) spectroscopy. In addition, the ligand binding sites of cNLRX1 were predicted in silico and validated experimentally. Target mutagenesis studies demonstrate that mutation of 4 critical residues ASP677, PHE680, PHE681, and GLU684 to alanine resulted in diminished affinity of PUA, ESA, and DHA to NLRX1. Consistent with the regulatory actions of NLRX1 on the NF-κB pathway, treatment of bone marrow derived macrophages (BMDM)s with PUA and DHA suppressed NF-κB activity in a NLRX1 dependent mechanism. In addition, a series of pre-clinical efficacy studies were performed using a mouse model of dextran sodium sulfate (DSS)-induced colitis. Our findings showed that the regulatory function of PUA on colitis is NLRX1 dependent. Thus, we identified novel small molecules that bind to NLRX1 and exert anti-inflammatory actions.
  • Thumbnail Image
    Nutritional protective mechanisms against gut inflammation
    Viladomiu, Monica; Hontecillas, Raquel; Yuan, Lijuan; Lu, Pinyi; Bassaganya-Riera, Josep (Elsevier, 2013-01-15)
    Inflammatory bowel disease (IBD) is a debilitating and widespread immune-mediated illness characterized by excessive inflammatory and effector mucosal responses leading to tissue destruction at the gastrointestinal tract. Interactions among the immune system, the commensal microbiota and the host genotype are thought to underlie the pathogenesis of IBD. However, the precise etiology of IBD remains unknown. Diet-induced changes in the composition of the gut microbiome can modulate the induction of regulatory versus effector immune responses at the gut mucosa and improve health outcomes. Therefore, manipulation of gut microbiota composition and the local production of microbial-derived metabolites by using prebiotics, probiotics and dietary fibers is being explored as a promising avenue of prophylactic and therapeutic intervention against gut inflammation. Prebiotics and fiber carbohydrates are fermented by resident microflora into short chain fatty acids (SCFAs) in the colon. SCFAs then activate peroxisome proliferator-activated receptor (PPAR)γ, a nuclear transcription factor with widely demonstrated anti-inflammatory efficacy in experimental IBD. The activation of PPARγ by naturally ocurring compounds such as conjugated linoleic acid, pomegranate seed oil-derived punicic acid, eleostearic acid and abscisic acid has been explored as nutritional interventions that suppress colitis by directly modulating the host immune response. The aim of this review is to summarize the status of innovative nutritional interventions against gastrointestinal inflammation, their proposed mechanisms of action, preclinical and clinical efficacy as well as bioinformatics and computational modeling approaches that accelerate discovery in nutritional and mucosal immunology research.
  • Thumbnail Image
    Preventive and Prophylactic Mechanisms of Action of Pomegranate Bioactive Constituents
    Viladomiu, Monica; Hontecillas, Raquel; Lu, Pinyi; Bassaganya-Riera, Josep (Hindawi, 2013-04-30)
    Pomegranate fruit presents strong anti-inflammatory, antioxidant, antiobesity, and antitumoral properties, thus leading to an increased popularity as a functional food and nutraceutical source since ancient times. It can be divided into three parts: seeds, peel, and juice, all of which seem to have medicinal benefits. Several studies investigate its bioactive components as a means to associate them with a specific beneficial effect and develop future products and therapeutic applications. Many beneficial effects are related to the presence of ellagic acid, ellagitannins (including punicalagins), punicic acid and other fatty acids, flavonoids, anthocyanidins, anthocyanins, estrogenic flavonols, and flavones, which seem to be its most therapeutically beneficial components. However, the synergistic action of the pomegranate constituents appears to be superior when compared to individual constituents. Promising results have been obtained for the treatment of certain diseases including obesity, insulin resistance, intestinal inflammation, and cancer. Although moderate consumption of pomegranate does not result in adverse effects, future studies are needed to assess safety and potential interactions with drugs that may alter the bioavailability of bioactive constituents of pomegranate as well as drugs. The aim of this review is to summarize the health effects and mechanisms of action of pomegranate extracts in chronic inflammatory diseases.
  • Thumbnail Image
    Supervised learning methods in modeling of CD4+ T cell heterogeneity
    Lu, Pinyi; Abedi, Vida; Mei, Yongguo; Hontecillas, Raquel; Hoops, Stefan; Carbo, Adria; Bassaganya-Riera, Josep (2015-09-04)
    Background Modeling of the immune system – a highly non-linear and complex system – requires practical and efficient data analytic approaches. The immune system is composed of heterogeneous cell populations and hundreds of cell types, such as neutrophils, eosinophils, macrophages, dendritic cells, T cells, and B cells. Each cell type is highly diverse and can be further differentiated into subsets with unique and overlapping functions. For example, CD4+ T cells can be differentiated into Th1, Th2, Th17, Th9, Th22, Treg, Tfh, as well as Tr1. Each subset plays different roles in the immune system. To study molecular mechanisms of cell differentiation, computational systems biology approaches can be used to represent these processes; however, the latter often requires building complex intracellular signaling models with a large number of equations to accurately represent intracellular pathways and biochemical reactions. Furthermore, studying the immune system entails integration of complex processes which occur at different time and space scales. Methods This study presents and compares four supervised learning methods for modeling CD4+ T cell differentiation: Artificial Neural Networks (ANN), Random Forest (RF), Support Vector Machines (SVM), and Linear Regression (LR). Application of supervised learning methods could reduce the complexity of Ordinary Differential Equations (ODEs)-based intracellular models by only focusing on the input and output cytokine concentrations. In addition, this modeling framework can be efficiently integrated into multiscale models. Results Our results demonstrate that ANN and RF outperform the other two methods. Furthermore, ANN and RF have comparable performance when applied to in silico data with and without added noise. The trained models were also able to reproduce dynamic behavior when applied to experimental data; in four out of five cases, model predictions based on ANN and RF correctly predicted the outcome of the system. Finally, the running time of different methods was compared, which confirms that ANN is considerably faster than RF. Conclusions Using machine learning as opposed to ODE-based method reduces the computational complexity of the system and allows one to gain a deeper understanding of the complex interplay between the different related entities.