Development of a structured undergraduate research experience: Framework and implications.

Participating in undergraduate research can be a pivotal experience for students in life science disciplines. Development of critical thinking skills, in addition to conveying scientific ideas in oral and written formats, is essential to ensuring that students develop a greater understanding of basic scientific knowledge and the research process. Modernizing the current life sciences research environment to accommodate the growing demand by students for experiential learning is needed. By developing and implementing a structured, theory-based approach to undergraduate research in the life sciences, specifically biochemistry, it has been successfully shown that more students can be provided with a high-quality, high-impact research experience. The structure of this approach allowed students to develop novel, independent projects in a computational molecular modeling lab. Students engaged in an experience in which career goals, problem-solving skills, time management skills, and independence in a research lab were developed. After experiencing this approach to undergraduate research, students reported feeling challenged to think critically and prepared for future career paths. The approach allowed for a progressive learning environment where more undergraduate students could participate in publishable research. Future areas for development include implementation in a bench-top lab and extension to disciplines beyond biochemistry. In this study, it has been shown that utilizing the structured approach to undergraduate research could allow for more students to experience undergraduate research and develop into more confident, independent life scientists well prepared for graduate schools and professional research environments. © 2016 by The International Union of Biochemistry and Molecular Biology, 44(5):463-474, 2016.

Structure-Activity Relationship Studies and Molecular Modeling of Naphthalene-Based Sphingosine Kinase 2 Inhibitors.

The two isoforms of sphingosine kinase (SphK1 and SphK2) are the only enzymes that phosphorylate sphingosine to sphingosine-1-phosphate (S1P), which is a pleiotropic lipid mediator involved in a broad range of cellular processes including migration, proliferation, and inflammation. SphKs are targets for various diseases such as cancer, fibrosis, and Alzheimer's and sickle cell disease. Herein, we disclose the structure-activity profile of naphthalene-containing SphK inhibitors and molecular modeling studies that reveal a key molecular switch that controls SphK selectivity.

Phosphorylation of PPARγ Affects the Collective Motions of the PPARγ-RXRα-DNA Complex.

Peroxisome-proliferator activated receptor-γ (PPARγ) is a nuclear hormone receptor that forms a heterodimeric complex with retinoid X receptor-α (RXRα) to regulate transcription of genes involved in fatty acid storage and glucose metabolism. PPARγ is a target for pharmaceutical intervention in type 2 diabetes, and insight into interactions between PPARγ, RXRα, and DNA is of interest in understanding the function and regulation of this complex. Phosphorylation of PPARγ by cyclin-dependent kinase 5 (Cdk5) has been shown to dysregulate the expression of metabolic regulation genes, an effect that is counteracted by PPARγ ligands. We applied molecular dynamics (MD) simulations to study the relationship between the ligand-binding domains of PPARγ and RXRα with their respective DNA-binding domains. Our results reveal that phosphorylation alters collective motions within the PPARγ-RXRα complex that affect the LBD-LBD dimerization interface and the AF-2 coactivator binding region of PPARγ.

Pharmacophore modeling improves virtual screening for novel peroxisome proliferator-activated receptor-gamma ligands.

Peroxisome proliferator-activated receptor-gamma (PPARγ) is a nuclear hormone receptor involved in regulating various metabolic and immune processes. The PPAR family of receptors possesses a large binding cavity that imparts promiscuity of ligand binding not common to other nuclear receptors. This feature increases the challenge of using computational methods to identify PPAR ligands that will dock favorably into a structural model. Utilizing both ligand- and structure-based pharmacophore methods, we sought to improve agonist prediction by grouping ligands according to pharmacophore features, and pairing models derived from these features with receptor structures for docking. For 22 of the 33 receptor structures evaluated we observed an increase in true positive rate (TPR) when screening was restricted to compounds sharing molecular features found in rosiglitazone. A combination of structure models used for docking resulted in a higher TPR (40 %) when compared to docking with a single structure model (<20 %). Prediction was also improved when specific protein-ligand interactions between the docked ligands and structure models were given greater weight than the calculated free energy of binding. A large-scale screen of compounds using a marketed drug database verified the predictive ability of the selected structure models. This study highlights the steps necessary to improve screening for PPARγ ligands using multiple structure models, ligand-based pharmacophore data, evaluation of protein-ligand interactions, and comparison of docking datasets. The unique combination of methods presented here holds potential for more efficient screening of compounds with unknown affinity for PPARγ that could serve as candidates for therapeutic development.

Computational modeling-based discovery of novel classes of anti-inflammatory drugs that target lanthionine synthetase C-like protein 2.

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.

Prediction of disease and phenotype associations from genome-wide association studies.

BACKGROUND: Genome wide association studies (GWAS) have proven useful as a method for identifying genetic variations associated with diseases. In this study, we analyzed GWAS data for 61 diseases and phenotypes to elucidate common associations based on single nucleotide polymorphisms (SNP). The study was an expansion on a previous study on identifying disease associations via data from a single GWAS on seven diseases. METHODOLOGY/PRINCIPAL FINDINGS: Adjustments to the originally reported study included expansion of the SNP dataset using Linkage Disequilibrium (LD) and refinement of the four levels of analysis to encompass SNP, SNP block, gene, and pathway level comparisons. A pair-wise comparison between diseases and phenotypes was performed at each level and the Jaccard similarity index was used to measure the degree of association between two diseases/phenotypes. Disease relatedness networks (DRNs) were used to visualize our results. We saw predominant relatedness between Multiple Sclerosis, type 1 diabetes, and rheumatoid arthritis for the first three levels of analysis. Expected relatedness was also seen between lipid- and blood-related traits. CONCLUSIONS/SIGNIFICANCE: The predominant associations between Multiple Sclerosis, type 1 diabetes, and rheumatoid arthritis can be validated by clinical studies. The diseases have been proposed to share a systemic inflammation phenotype that can result in progression of additional diseases in patients with one of these three diseases. We also noticed unexpected relationships between metabolic and neurological diseases at the pathway comparison level. The less significant relationships found between diseases require a more detailed literature review to determine validity of the predictions. The results from this study serve as a first step towards a better understanding of seemingly unrelated diseases and phenotypes with similar symptoms or modes of treatment.

Dietary α-eleostearic acid ameliorates experimental inflammatory bowel disease in mice by activating peroxisome proliferator-activated receptor-γ.

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.

Molecular modeling of lanthionine synthetase component C-like protein 2: a potential target for the discovery of novel type 2 diabetes prophylactics and therapeutics.

The rates of type 2 diabetes (T2D) are rising to epidemic proportions in the US and worldwide. While current T2D medications are efficacious, significant side effects have limited their use and availability. Our laboratory has discovered that abscisic acid (ABA) exerts anti-diabetic effects, in part, by activating peroxisome proliferator-activated receptor γ (PPAR γ). However, since ABA does not bind to the ligand-binding domain (LBD) of PPAR γ, the mechanism of activation of PPAR γ by ABA remains unknown. Lanthionine synthetase component C-like protein 2 (LANCL2) was predicted to be a novel target for the binding and signaling of ABA in human granulocytes and rat insulinoma cells. The goal of this study was to determine whether LANCL2 is a molecular target of ABA and other PPAR γ agonists. To this end 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 γ agonists (e.g., rosiglitazone and pioglitazone) share a binding site on the surface of LANCL2. The identification of a binding site for PPAR γ agonists will facilitate the high-throughput virtual screening of large compound libraries and may shed new light on alternative mechanisms of PPAR γ activation.

Abscisic acid regulates inflammation via ligand-binding domain-independent activation of peroxisome proliferator-activated receptor gamma.

Abscisic acid (ABA) has shown efficacy in the treatment of diabetes and inflammation; however, its molecular targets and the mechanisms of action underlying its immunomodulatory effects remain unclear. This study investigates the role of peroxisome proliferator-activated receptor γ (PPAR γ) and lanthionine synthetase C-like 2 (LANCL2) as molecular targets for ABA. We demonstrate that ABA increases PPAR γ reporter activity in RAW 264.7 macrophages and increases ppar γ expression in vivo, although it does not bind to the ligand-binding domain of PPAR γ. LANCL2 knockdown studies provide evidence that ABA-mediated activation of macrophage PPAR γ is dependent on lancl2 expression. Consistent with the association of LANCL2 with G proteins, we provide evidence that ABA increases cAMP accumulation in immune cells. ABA suppresses LPS-induced prostaglandin E(2) and MCP-1 production via a PPAR γ-dependent mechanism possibly involving activation of PPAR γ and suppression of NF-κB and nuclear factor of activated T cells. LPS challenge studies in PPAR γ-expressing and immune cell-specific PPAR γ null mice demonstrate that ABA down-regulates toll-like receptor 4 expression in macrophages and T cells in vivo through a PPAR γ-dependent mechanism. Global transcriptomic profiling and confirmatory quantitative RT-PCR suggest novel candidate targets and demonstrate that ABA treatment mitigates the effect of LPS on the expression of genes involved in inflammation, metabolism, and cell signaling, in part, through PPAR γ. In conclusion, ABA decreases LPS-mediated inflammation and regulates innate immune responses through a bifurcating pathway involving LANCL2 and an alternative, ligand-binding domain-independent mechanism of PPAR γ activation.

Virtual Screening as a Technique for PPAR Modulator Discovery.

Virtual screening (VS) is a discovery technique to identify novel compounds with therapeutic and preventive efficacy against disease. Our current focus is on the in silico screening and discovery of novel peroxisome proliferator-activated receptor-gamma (PPARgamma) agonists. It is well recognized that PPARgamma agonists have therapeutic applications as insulin sensitizers in type 2 diabetes or as anti-inflammatories. VS is a cost- and time-effective means for identifying small molecules that have therapeutic potential. Our long-term goal is to devise computational approaches for testing the PPARgamma-binding activity of extensive naturally occurring compound libraries prior to testing agonist activity using ligand-binding and reporter assays. This review summarizes the high potential for obtaining further fundamental understanding of PPARgamma biology and development of novel therapies for treating chronic inflammatory diseases through evolution and implementation of computational screening processes for immunotherapeutics in conjunction with experimental methods for calibration and validation of results.