Machine learning models to predict ligand binding affinity for the orexin 1 receptor

The orexin 1 receptor (OX1R) is a G-protein coupled receptor that regulates a variety of physiological processes through interactions with the neuropeptides orexin A and B. Selective OX1R antagonists exhibit therapeutic effects in preclinical models of several behavioral disorders, including drug seeking and overeating. However, currently there are no selective OX1R antagonists approved for clinical use, fueling demand for novel compounds that act at this target. In this study, we meticulously curated a dataset comprising over 1300 OX1R ligands using a stringent filter and criteria cascade. Subsequently, we developed highly predictive quantitative structure-activity relationship (QSAR) models employing the optimized hyper-parameters for the random forest machine learning algorithm and twelve 2D molecular descriptors selected by recursive feature elimination with a 5-fold cross-validation process. The predictive capacity of the QSAR model was further assessed using an external test set and enrichment study, confirming its high predictivity. The practical applicability of our final QSAR model was demonstrated through virtual screening of the DrugBank database. This revealed two FDA-approved drugs (isavuconazole and cabozantinib) as potential OX1R ligands, confirmed by radiolabeled OX1R binding assays. To our best knowledge, this study represents the first report of highly predictive QSAR models on a large comprehensive dataset of diverse OX1R ligands, which should prove useful for the discovery and design of new compounds targeting this receptor.

Clinical Care of Patients with Neurocognitive Disorders: A Qualitative Study of the Psychiatric Residency Training Experience

OBJECTIVE

Few data describe how general psychiatry residencies prepare trainees to care for individuals with neurocognitive disorders (NCDs), despite increasing recognition of the need for psychiatrists to provide care for the growing numbers of patients with NCD. This study aims to identify training needs and approaches, as the resident experience is one important perspective that can be added to others, such as milestones developed by expert educators.

METHODS

The authors conducted three focus groups of third- and fourth-year general adult psychiatry residency trainees from three different training programs in May and June of 2021. Focus groups consisted of three to eight unique participants per group. Qualitative data analysis techniques derived in grounded theory were utilized to identify themes.

RESULTS

Four main themes emerged from the focus groups: unique challenges of NCD care, intrinsic rewards of working with families, perceived gaps in educational experiences, and limited comfort in future practice.

CONCLUSIONS

Participants expressed that aspects of NCD care were fundamentally different than care for other mental health conditions encountered in psychiatry residency. They found the progressive nature of the disease to be particularly challenging, and they also expressed challenges with clinical interviews and establishing rapport with individuals with NCDs. However, working with families was especially rewarding. Regardless of training program, participants expressed a need for additional longitudinal and diversified training opportunities to prepare them for future practice in this area.

Recent advances in drug discovery efforts targeting the sigma 1 receptor system: Implications for novel medications designed to reduce excessive drug and food seeking

Psychiatric disorders characterized by uncontrolled reward seeking, such as substance use disorders (SUDs), alcohol use disorder (AUD) and some eating disorders, impose a significant burden on individuals and society. Despite their high prevalence and substantial morbidity and mortality rates, treatment options for these disorders remain limited. Over the past two decades, there has been a gradual accumulation of evidence pointing to the sigma-1 receptor (S1R) system as a promising target for therapeutic interventions designed to treat these disorders. S1R is a chaperone protein that resides in the endoplasmic reticulum, but under certain conditions translocates to the plasma membrane. In the brain, S1Rs are expressed in several regions important for reward, and following translocation, they physically associate with several reward-related GPCRs, including dopamine receptors 1 and 2 (D1R and D2R). Psychostimulants, alcohol, as well as palatable foods, all alter expression of S1R in regions important for motivated behavior, and S1R antagonists generally decrease behavioral responses to these rewards. Recent advances in structural modeling have permitted the development of highly-selective S1R antagonists with favorable pharmacokinetic profiles, thus providing a therapeutic avenue for S1R-based medications. Here, we provide an up-to-date overview of work linking S1R with motivated behavior for drugs of abuse and food, as well as evidence supporting the clinical utility of S1R antagonists to reduce their excessive consumption. We also highlight potential challenges associated with targeting the S1R system, including the need for a more comprehensive understanding of the underlying neurobiology and careful consideration of the pharmacological properties of S1R-based drugs.

Novel Sigma 1 Receptor Antagonists as Potential Therapeutics for Pain Management

The sigma 1 receptor (S1R) is a molecular chaperone protein located in the endoplasmic reticulum and plasma membranes and has been shown to play important roles in various pathological disorders including pain and, as recently discovered, COVID-19. Employing structure- and QSAR-based drug design strategies, we rationally designed, synthesized, and biologically evaluated a series of novel triazole-based S1R antagonists. Compound 10 exhibited potent binding affinity for S1R, high selectivity over S2R and 87 other human targets, acceptable in vitro metabolic stability, slow clearance in liver microsomes, and excellent blood-brain barrier permeability in rats. Further in vivo studies in rats showed that 10 exhibited negligible acute toxicity in the rotarod test and statistically significant analgesic effects in the formalin test for acute inflammatory pain and paclitaxel-induced neuropathic pain models during cancer chemotherapy. These encouraging results promote further development of our triazole-based S1R antagonists as novel treatments for pain of different etiologies.

Identification of an irreversible PPARγ antagonist with potent anticancer activity

Melanoma is responsible for most skin cancer deaths, and its incidence continues to rise year after year. Different treatment options have been developed for melanoma depending on the stage of the disease. Despite recent advances in immuno- and targeted therapies, advanced melanoma remains incurable and thus an urgent need persists for safe and more effective melanoma therapeutics. In this study, we demonstrate that a novel compound MM902 (3-(3-(bromomethyl)-5-(4-(tert-butyl) phenyl)-1H-1,2,4-triazol-1-yl) phenol) exhibited potent efficacies in inhibiting the growth of different cancer cells, and suppressed tumor growth in a mouse xenograft model of malignant melanoma. Beginning with MM902 instead of specific targets, computational similarity- and docking-based approaches were conducted to search for known anticancer drugs whose structural features match MM902 and whose pharmacological target would accommodate an irreversible inhibitor. Peroxisome proliferator-activated receptor (PPAR) was computationally identified as one of the pharmacological targets and confirmed by in vitro biochemical assays. MM902 was shown to bind to PPARγ in an irreversible mode of action and to function as a selective antagonist for PPARγ over PPARα and PPARδ. It is hoped that MM902 will serve as a valuable research probe to study the functions of PPARγ in tumorigenesis and other pathological processes.

Comprehensive 3D-QSAR Model Predicts Binding Affinity of Structurally Diverse Sigma 1 Receptor Ligands

The Sigma 1 Receptor (S1R) has attracted intense interest as a pharmaceutical target for various therapeutic indications, including the treatment of neuropathic pain and the potentiation of opioid analgesia. Efforts by drug developers to rationally design S1R antagonists have been spurred recently by the 2016 publication of the high-resolution X-ray crystal structure of the ligand-bound human S1R. Until now, however, the absence in the published literature of a single, large-scale, and comprehensive quantitative structure-activity relationship (QSAR) model that encompasses a structurally diverse collection of S1R ligands has impaired rapid progress. To our best knowledge, the present study represents the first report of a statistically robust and highly predictive 3D-QSAR model (R2 = 0.92, Q2 = 0.62, Rpred2 = 0.81) based on the X-ray crystal structure of human S1R and constructed from a pooled compilation of 180 S1R antagonists that encompass five structurally diverse chemical families investigated using identical experimental protocols. Best practices, as recommended by the Organization for Economic Cooperation and Development (OECD: http://www.oecd.org/ ), were adopted for pooling data from disparate sources and for QSAR model development and both internal and external model validation. The practical utility of the final 3D-QSAR model was tested by virtual screening of the DrugBank database of FDA approved drugs supplemented by eight reported S1R antagonists. Among the top-ranked 40 DrugBank hits, four approved drugs which were previously unknown as S1R antagonists were tested using in vitro radiolabeled human S1R binding assays. Of these, two drugs (diphenhydramine and phenyltoloxamine) exhibited potent S1R binding affinity with Ki = 58 nM and 160 nM, respectively. As diphenhydramine is approved as an antiallergic, and phenyltoloxamine as an analgesic and sedative, each of these compounds represents a viable starting point for a drug discovery campaign aimed at the development of novel S1R antagonists for a wide range of therapeutic indications.

Virtual Screening and Experimental Testing of B1 Metallo-β-lactamase Inhibitors

The global rise of metallo-β-lactamases (MBLs) is problematic due to their ability to inactivate most β-lactam antibiotics. MBL inhibitors that could be coadministered with and restore the efficacy of β-lactams are highly sought after. In this study, we employ virtual screening of candidate MBL inhibitors without thiols or carboxylates to avoid off-target effects using the Avalanche software package, followed by experimental validation of the selected compounds. As target enzymes, we chose the clinically relevant B1 MBLs NDM-1, IMP-1, and VIM-2. Among 32 compounds selected from an approximately 1.5 million compound library, 6 exhibited IC₅₀ values less than 40 μM against NDM-1 and/or IMP-1. The most potent inhibitors of NDM-1, IMP-1, and VIM-2 had IC₅₀ values of 19 ± 2, 14 ± 1, and 50 ± 20 μM, respectively. While chemically diverse, the most potent inhibitors all contain combinations of hydroxyl, ketone, ester, amide, or sulfonyl groups. Docking studies suggest that these electron-dense moieties are involved in Zn(II) coordination and interaction with protein residues. These novel scaffolds could serve as the basis for further development of MBL inhibitors. A procedure for renaming NDM-1 residues to conform to the class B β-lactamase (BBL) numbering scheme is also included.

Small molecule inhibitors block Gas6-inducible TAM activation and tumorigenicity

TAM receptors (Tyro-3, Axl, and Mertk) are a family of three homologous type I receptor tyrosine kinases that are implicated in several human malignancies. Overexpression of TAMs and their major ligand Growth arrest-specific factor 6 (Gas6) is associated with more aggressive staging of cancers, poorer predicted patient survival, acquired drug resistance and metastasis. Here we describe small molecule inhibitors (RU-301 and RU-302) that target the extracellular domain of Axl at the interface of the Ig-1 ectodomain of Axl and the Lg-1 of Gas6. These inhibitors effectively block Gas6-inducible Axl receptor activation with low micromolar IC_50s in cell-based reporter assays, inhibit Gas6-inducible motility in Axl-expressing cell lines, and suppress H1299 lung cancer tumor growth in a mouse xenograft NOD-SCIDγ model. Furthermore, using homology models and biochemical verifications, we show that RU301 and 302 also inhibit Gas6 inducible activation of Mertk and Tyro3 suggesting they can act as pan-TAM inhibitors that block the interface between the TAM Ig1 ectodomain and the Gas6 Lg domain. Together, these observations establish that small molecules that bind to the interface between TAM Ig1 domain and Gas6 Lg1 domain can inhibit TAM activation, and support the further development of small molecule Gas6-TAM interaction inhibitors as a novel class of cancer therapeutics.

Stepping into the omics era: Opportunities and challenges for biomaterials science and engineering

The research paradigm in biomaterials science and engineering is evolving from using low-throughput and iterative experimental designs towards high-throughput experimental designs for materials optimization and the evaluation of materials properties. Computational science plays an important role in this transition. With the emergence of the omics approach in the biomaterials field, referred to as materiomics, high-throughput approaches hold the promise of tackling the complexity of materials and understanding correlations between material properties and their effects on complex biological systems. The intrinsic complexity of biological systems is an important factor that is often oversimplified when characterizing biological responses to materials and establishing property-activity relationships. Indeed, in vitro tests designed to predict in vivo performance of a given biomaterial are largely lacking as we are not able to capture the biological complexity of whole tissues in an in vitro model. In this opinion paper, we explain how we reached our opinion that converging genomics and materiomics into a new field would enable a significant acceleration of the development of new and improved medical devices. The use of computational modeling to correlate high-throughput gene expression profiling with high throughput combinatorial material design strategies would add power to the analysis of biological effects induced by material properties. We believe that this extra layer of complexity on top of high-throughput material experimentation is necessary to tackle the biological complexity and further advance the biomaterials field.

STATEMENT OF SIGNIFICANCE

In this opinion paper, we postulate that converging genomics and materiomics into a new field would enable a significant acceleration of the development of new and improved medical devices. The use of computational modeling to correlate high-throughput gene expression profiling with high throughput combinatorial material design strategies would add power to the analysis of biological effects induced by material properties. We believe that this extra layer of complexity on top of high-throughput material experimentation is necessary to tackle the biological complexity and further advance the biomaterials field.

Micellar and structural stability of nanoscale amphiphilic polymers: Implications for anti-atherosclerotic bioactivity

Atherosclerosis, a leading cause of mortality in developed countries, is characterized by the buildup of oxidized low-density lipoprotein (oxLDL) within the vascular intima, unregulated oxLDL uptake by macrophages, and ensuing formation of arterial plaque. Amphiphilic polymers (AMPs) comprised of a branched hydrophobic domain and a hydrophilic poly(ethylene glycol) (PEG) tail have shown promising anti-atherogenic effects through direct inhibition of oxLDL uptake by macrophages. In this study, five AMPs with controlled variations were evaluated for their micellar and structural stability in the presence of serum and lipase, respectively, to develop underlying structure-atheroprotective activity relations. In parallel, molecular dynamics simulations were performed to explore the AMP conformational preferences within an aqueous environment. Notably, AMPs with ether linkages between the hydrophobic arms and sugar backbones demonstrated enhanced degradation stability and storage stability, and also elicited enhanced anti-atherogenic bioactivity. Additionally, AMPs with increased hydrophobicity elicited increased atheroprotective bioactivity in the presence of serum. These studies provide key insights for designing more serum-stable polymeric micelles as prospective cardiovascular nanotherapies.

Avalanche for shape and feature-based virtual screening with 3D alignment

This report introduces a new ligand-based virtual screening tool called Avalanche that incorporates both shape- and feature-based comparison with three-dimensional (3D) alignment between the query molecule and test compounds residing in a chemical database. Avalanche proceeds in two steps. The first step is an extremely rapid shape/feature based comparison which is used to narrow the focus from potentially millions or billions of candidate molecules and conformations to a more manageable number that are then passed to the second step. The second step is a detailed yet still rapid 3D alignment of the remaining candidate conformations to the query conformation. Using the 3D alignment, these remaining candidate conformations are scored, re-ranked and presented to the user as the top hits for further visualization and evaluation. To provide further insight into the method, the results from two prospective virtual screens are presented which show the ability of Avalanche to identify hits from chemical databases that would likely be missed by common substructure-based or fingerprint-based search methods. The Avalanche method is extended to enable patent landscaping, i.e., structural refinements to improve the patentability of hits for deployment in drug discovery campaigns.

Tartaric acid-based amphiphilic macromolecules with ether linkages exhibit enhanced repression of oxidized low density lipoprotein uptake

Cardiovascular disease initiates with the atherogenic cascade of scavenger receptor- (SR-) mediated oxidized low-density lipoprotein (oxLDL) uptake. Resulting foam cell formation leads to lipid-rich lesions within arteries. We designed amphiphilic macromolecules (AMs) to inhibit these processes by competitively blocking oxLDL uptake via SRs, potentially arresting atherosclerotic development. In this study, we investigated the impact of replacing ester linkages with ether linkages in the AM hydrophobic domain. We hypothesized that ether linkages would impart flexibility for orientation to improve binding to SR binding pockets, enhancing anti-atherogenic activity. A series of tartaric acid-based AMs with varying hydrophobic chain lengths and conjugation chemistries were synthesized, characterized, and evaluated for bioactivity. 3-D conformations of AMs in aqueous conditions may have significant effects on anti-atherogenic potency and were simulated by molecular modeling. Notably, ether-linked AMs exhibited significantly higher levels of inhibition of oxLDL uptake than their corresponding ester analogues, indicating a dominant effect of linkage flexibility on pharmacological activity. The degradation stability was also enhanced for ether-linked AMs. These studies further suggested that alkyl chain length (i.e., relative hydrophobicity), conformation (i.e., orientation), and chemical stability play a critical role in modulating oxLDL uptake, and guide the design of innovative cardiovascular therapies.

Novel virtual screening approach for the discovery of human tyrosinase inhibitors

Tyrosinase is the key enzyme involved in the human pigmentation process, as well as the undesired browning of fruits and vegetables. Compounds inhibiting tyrosinase catalytic activity are an important class of cosmetic and dermatological agents which show high potential as depigmentation agents used for skin lightening. The multi-step protocol employed for the identification of novel tyrosinase inhibitors incorporated the Shape Signatures computational algorithm for rapid screening of chemical libraries. This algorithm converts the size and shape of a molecule, as well its surface charge distribution and other bio-relevant properties, into compact histograms (signatures) that lend themselves to rapid comparison between molecules. Shape Signatures excels at scaffold hopping across different chemical families, which enables identification of new actives whose molecular structure is distinct from other known actives. Using this approach, we identified a novel class of depigmentation agents that demonstrated promise for skin lightening product development.

Polyester monomers lack ability to bind and activate both androgenic and estrogenic receptors as determined by in vitro and in silico methods

The paper presents results from the screening of seven monomers used by Eastman Chemical to make various polymers. Ethylene glycol, diethylene glycol, polytetramethylene glycol, isophthalic acid, monosodium-5-sulfoisophthalic acid, 1,4-cyclohexanedicarboxylic acid, and dimethylcyclohexanedicarboxylate were screened for potential androgenicity or estrogenicity. The following studies were conducted: QSAR for binding to the AR and ER, in vitro Androgen Receptor Binding Assay, in vitro Estrogen Receptor Binding Assays (alpha and beta isoforms), in vitro Androgen Receptor Transactivation Assay in human cells, and in vitro Estrogen Receptor Transactivation Assay in human cells. None of the QSAR models predicted that any of the monomers possessed appreciable binding affinity for either AR or ER. Binding assays showed no evidence of interaction with either the AR or the alpha or beta ER receptors. Similarly, the AR and ER transactivation assays were negative. Moreover, six of the seven monomers have been subjected to 13-week and developmental toxicity studies in rats with no androgen- or estrogen-related effects being noted. Given the negative results of the in vitro screening assays (except PMG which demonstrated cytotoxicity) as well as available repeated dose and developmental and reproductive studies, the data suggest that none of the monomers tested exhibit androgenic or estrogenic hazards.

Abstract 1748: Novel Ig1 inhibitors of the Axl tyrosine kinase that block Gas6-inducible receptor activation

Tyro-3, Axl, and Mer (abbreviated TAMs) are a family of three homologous receptor tyrosine kinases (RTKs) expressed predominantly on myeloid-derived hematopoietic cells and epithelial cells that function as inhibitory receptors that dampen inflammatory responses and maintain tissue tolerance. Both TAMs and their ligands (vitamin K activated proteins that consist of Gas6 and Protein S) are overexpressed in many human malignancies and expression is associated with more aggressive cancer staging, drug resistance, and poorer patient survival. Based on their clinical importance, there has been considerable effort to generate anti-TAM cancer therapeutics in the form of small molecule tyrosine kinase inhibitors, monoclonal antibodies, and soluble receptor traps that capture TAM ligands and prevent receptor activation. However, whereas several tyrosine kinase inhibitors have been reported, the high degree of sequence conservation in the TAM kinase domain is associated with lack of specificity and off target effects. To generate more selective inhibitors of TAMs, we have targeted the Ig1 domain of Axl, a ligand-binding region in the extracellular domain that gives TAMs their unique structural features. From the X-ray crystallographic structure of Gas6 in complex with the human Axl ectodomain (PDB 2c5d), two unique sites were targeted that include (i) the major binding pocket around Glu59 in Axl that interacts with Arg310 and Lys312 in Gas6, and (ii) the main hydrophobic interface between the Ig1 and the Lg1 that is required for Gas6-inducible dimerization. Virtual screening of the ZINC molecular data base was performed, and several drug-like compounds were selected based on ligand-Gas6 docking. We report on the characterization of two novel types of Axl inhibitors that include a triazolo pyridazine compound that targets the Ig1 binding pocket, and a 3-cyanocoumarin compound that targets the Ig1-Lg1 interface. Both compounds show activity on human Axl reporter lines, and therefore may represent a new class of Axl inhibitors with potential applications for anticancer therapy.

Citation Format: William J. Welsh, Vladyslav Kholodovych, Raymond Birge, Tom Comollo, Stanley Kimani, Kamal Singh. Novel Ig1 inhibitors of the Axl tyrosine kinase that block Gas6-inducible receptor activation. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 1748. doi:10.1158/1538-7445.AM2014-1748

Abstract 1626: Novel trisubstituted triazoles modeled from naltrindole inhibit the proliferation of human multiple myeloma cells

Multiple myeloma (MM) is an invasive plasma cell neoplasm of malignant cells that proliferate in the bone marrow. This incurable cancer is responsible for 10% of all hematological malignancies. The American Cancer Society estimated that in 2011, 11,400 men and 9,120 women were diagnosed with MM in the United States, and 5,770 men and 4,840 women died of the disease. MM is characterized by monoclonal gammopathy, destructive bone disease, renal failure, hypercalcemia, and hematological dysfunction. The molecular pathogenesis of MM is complex. Gene expression profiling and deep genome sequencing has revealed that in many cases, chromosome translocations result in overexpression of growth regulatory genes via their juxtaposition to the immunoglobulin heavy chain locus, activation of the NF-kB pathway, activation of MYC, FGFR3, KRAS, NRAS, and loss of function mutations in the histone H3K27 demethylase gene UTX. Despite the development of new treatment agents in the last decade, including lenalidomide (an immunomodulatory drug) and bortezomib (a proteasome inhibitor), the five-year relative survival rate for MM is approximately 40%. Obviously, there is a great need for additional treatment options. Naltrindole (Nti) is a synthetic alkaloid with the pharmacological profile of a selective delta opioid receptor antagonist. Nti has also been reported to be a potent immunosuppressant. Nti suppresses the allogeneic mixed lymphocyte reaction in vitro and inhibits renal graft rejection in vivo. Subsequently, it was reported that Nti retains its immunosuppressive activity in triple mu/delta/kappa opioid receptor knockout mice, revealing a non-opioid receptor target for the immunosuppressant activity of Nti (Gaveriaux-Ruff et al., 2001). We reported previously (Mundra et al., J. Pharmacol. Exp. Ther. 342: 273-287, 2012), that Nti inhibited human MM cell proliferation in vitro and in a murine xenograft model in vivo, by interaction with a non-opioid receptor target. In the present study, we describe a novel series of triazole-based ligands derived from Nti by rational design (see Peng et al., Bioorgan. & Med. Chem. 17: 6442-6450, 2009) that competed for specific 3H-Nti binding to human U266 MM cells and inhibited MM cell proliferation in vitro. To date, 17 trisubstituted triazoles have been evaluated for their ability to inhibit MM cell proliferation. Following incubation with U266 MM cells for 72 h, the majority of MM triazoles exhibited EC50's in the 10-60 micromolar range. However, 3 of the triazoles displayed EC50's of 300-400 nM. It is hoped that further modification of these lead compounds will yield drugs with even greater efficacy. This study provides a rationale basis for further evaluation of this series of triazoles as anti-MM therapeutic agents.

Citation Format: William J. Welsh, Youyi Peng, Jyoti Joshi Mundra, Julianne F. Avrutik, Thomas C. Yoon, Andrew M. Meillier, Richard D. Howells. Novel trisubstituted triazoles modeled from naltrindole inhibit the proliferation of human multiple myeloma cells. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 1626. doi:10.1158/1538-7445.AM2014-1626

Fragment-based Shape Signatures: a new tool for virtual screening and drug discovery

Since its introduction in 2003, the Shape Signatures method has been successfully applied in a number of drug design projects. Because it uses a ray-tracing approach to directly measure molecular shape and properties (as opposed to relying on chemical structure), it excels at scaffold hopping, and is extraordinarily easy to use. Despite its advantages, a significant drawback of the method has hampered its application to certain classes of problems; namely, when the chemical structures considered are large and contain heterogeneous ring-systems, the method produces descriptors that tend to merely measure the overall size of the molecule, and begin to lose selective power. To remedy this, the approach has been reformulated to automatically decompose compounds into fragments using ring systems as anchors, and to likewise partition the ray-trace in accordance with the fragment assignments. Subsequently, descriptors are generated that are fragment-based, and query and target molecules are compared by mapping query fragments onto target fragments in all ways consistent with the underlying chemical connectivity. This has proven to greatly extend the selective power of the method, while maintaining the ease of use and scaffold-hopping capabilities that characterized the original implementation. In this work, we provide a full conceptual description of the next generation Shape Signatures, and we underline the advantages of the method by discussing its practical applications to ligand-based virtual screening. The new approach can also be applied in receptor-based mode, where protein-binding sites (partitioned into subsites) can be matched against the new fragment-based Shape Signatures descriptors of library compounds.

In silico design of anti-atherogenic biomaterials

Atherogenesis, the uncontrolled deposition of modified lipoproteins in inflamed arteries, serves as a focal trigger of cardiovascular disease (CVD). Polymeric biomaterials have been envisioned to counteract atherogenesis based on their ability to repress scavenger mediated uptake of oxidized lipoprotein (oxLDL) in macrophages. Following the conceptualization in our laboratories of a new library of amphiphilic macromolecules (AMs), assembled from sugar backbones, aliphatic chains and poly(ethylene glycol) tails, a more rational approach is necessary to parse the diverse features such as charge, hydrophobicity, sugar composition and stereochemistry. In this study, we advance a computational biomaterials design approach to screen and elucidate anti-atherogenic biomaterials with high efficacy. AMs were quantified in terms of not only 1D (molecular formula) and 2D (molecular connectivity) descriptors, but also new 3D (molecular geometry) descriptors of AMs modeled by coarse-grained molecular dynamics (MD) followed by all-atom MD simulations. Quantitative structure-activity relationship (QSAR) models for anti-atherogenic activity were then constructed by screening a total of 1164 descriptors against the corresponding, experimentally measured potency of AM inhibition of oxLDL uptake in human monocyte-derived macrophages. Five key descriptors were identified to provide a strong linear correlation between the predicted and observed anti-atherogenic activity values, and were then used to correctly forecast the efficacy of three newly designed AMs. Thus, a new ligand-based drug design framework was successfully adapted to computationally screen and design biomaterials with cardiovascular therapeutic properties.

Pregnane X receptor mediates dyslipidemia induced by the HIV protease inhibitor amprenavir in mice

Human immunodeficiency virus (HIV) protease inhibitors (PIs) have been used successfully in extending the life span of people infected with HIV. The use of PIs has also been associated with dyslipidemia and an increased risk of cardiovascular disease, but the underlying mechanisms remain elusive. Several PIs have been implicated in activating the nuclear receptor pregnane X receptor (PXR), which acts as a xenobiotic sensor to regulate xenobiotic metabolism in the liver and intestine. Recent studies indicate that PXR may also play an important role in the regulation of lipid homeostasis. In the present study, we identified amprenavir, a widely used HIV PI, as a potent PXR-selective agonist. Computational docking studies combined with site-direct mutagenesis identified several key residues within the ligand-binding pocket of PXR that constitute points of interaction with amprenavir. Amprenavir efficiently activated PXR and induced PXR target gene expression in vitro and in vivo. Short-term exposure to amprenavir significantly increased plasma total cholesterol and atherogenic low-density lipoprotein cholesterol levels in wild-type mice, but not in PXR-deficient mice. Amprenavir-mediated PXR activation stimulated the expression of several key intestinal genes involved in lipid homeostasis. These findings provide critical mechanistic insight for understanding the impact of PIs on cardiovascular disease and demonstrate a potential role of PXR in mediating the adverse effects of HIV PIs in humans.

Cardiovascular outcomes and the physical and chemical properties of metal ions found in particulate matter air pollution: a QICAR study

BACKGROUND

This paper presents an application of quantitative ion character-activity relationships (QICAR) to estimate associations of human cardiovascular (CV) diseases (CVDs) with a set of metal ion properties commonly observed in ambient air pollutants. QICAR has previously been used to predict ecotoxicity of inorganic metal ions based on ion properties.

OBJECTIVES

The objective of this work was to examine potential associations of biological end points with a set of physical and chemical properties describing inorganic metal ions present in exposures using QICAR.

METHODS

Chemical and physical properties of 17 metal ions were obtained from peer-reviewed publications. Associations of cardiac arrhythmia, myocardial ischemia, myocardial infarction, stroke, and thrombosis with exposures to metal ions (measured as inference scores) were obtained from the Comparative Toxicogenomics Database (CTD). Robust regressions were applied to estimate the associations of CVDs with ion properties.

RESULTS

CVD was statistically significantly associated (Bonferroni-adjusted significance level of 0.003) with many ion properties reflecting ion size, solubility, oxidation potential, and abilities to form covalent and ionic bonds. The properties are relevant for reactive oxygen species (ROS) generation, which has been identified as a possible mechanism leading to CVDs.

CONCLUSION

QICAR has the potential to complement existing epidemiologic methods for estimating associations between CVDs and air pollutant exposures by providing clues about the underlying mechanisms that may explain these associations.

Carbohydrate composition of amphiphilic macromolecules influences physicochemical properties and binding to atherogenic scavenger receptor A

Amphiphilic macromolecules (AMs) based on carbohydrate domains functionalized with poly(ethylene glycol) can inhibit the uptake of oxidized low density lipoprotein (oxLDL) mediated by scavenger receptor A (SR-A) and counteract foam cell formation, the characteristic "atherosclerotic" phenotype. A series of AMs was prepared by altering the carbohydrate chemistry to evaluate the influence of backbone architecture on the physicochemical and biological properties. Upon evaluating the degree of polymer-based inhibition of oxLDL uptake in human embryonic kidney cells expressing SR-A, two AMs (2a and 2c) were found to have the most efficacy. Molecular modeling and docking studies show that these same AMs have the most favorable binding energies and most close interactions with the molecular model of the SR-A collagen-like domain. Thus, minor changes in the AMs' architecture can significantly affect the physicochemical properties and inhibition of oxLDL uptake. These insights can be critical for designing optimal AM-based therapeutics for the management of cardiovascular disease.

Salicylanilide inhibitors of Toxoplasma gondii

Toxoplasma gondii (T. gondii) is an apicomplexan parasite that can cause eye disease, brain disease, and death, especially in congenitally infected and immune-compromised people. Novel medicines effective against both active and latent forms of the parasite are greatly needed. The current study focused on the discovery of such medicines by exploring a family of potential inhibitors whose antiapicomplexan activity has not been previously reported. Initial screening efforts revealed that niclosamide, a drug approved for anthelmintic use, possessed promising activity in vitro against T. gondii. This observation inspired the evaluation of the activity of a series of salicylanilides and derivatives. Several inhibitors with activities in the nanomolar range with no appreciable in vitro toxicity to human cells were identified. An initial structure-activity relationship was explored. Four compounds were selected for evaluation in an in vivo model of infection, and two derivatives with potentially enhanced pharmacological parameters demonstrated the best activity profiles.

Potent inhibitors of human organic anion transporters 1 and 3 from clinical drug libraries: discovery and molecular characterization

Transporter-mediated drug-drug interactions in the kidney dramatically influence the pharmacokinetics and other clinical effects of drugs. Human organic anion transporters 1 (hOAT1) and 3 (hOAT3) are the major transporters in the basolateral membrane of kidney proximal tubules, mediating the rate-limiting step in the elimination of a broad spectrum of drugs. In the present study, we screened two clinical drug libraries against hOAT1 and hOAT3. Of the 727 compounds screened, 92 compounds inhibited hOAT1 and 262 compounds inhibited hOAT3. When prioritized based on the peak unbound plasma concentrations of these compounds, three inhibitors for hOAT1 and seven inhibitors for hOAT3 were subsequently identified with high inhibitory potency (>95%). Computational analyses revealed that inhibitors and noninhibitors can be differentiated from each other on the basis of several physicochemical features, including number of hydrogen-bond donors, number of rotatable bonds, and topological polar surface area (TPSA) for hOAT1; and molecular weight, number of hydrogen-bond donors and acceptors, TPSA, partition coefficient (log P(7.4)), and polarizability for hOAT3. Pharmacophore modeling identified two common structural features associated with inhibitors for hOAT1 and hOAT3, viz., an anionic hydrogen-bond acceptor atom, and an aromatic center separated by ∼5.7 Å. Such model provides mechanistic insights for predicting new OAT inhibitors.

Bisphenol A and its analogues activate human pregnane X receptor

BACKGROUND

Bisphenol A (BPA) is a base chemical used extensively in many consumer products. BPA and its analogues are present in environmental and human samples. Many endocrine-disrupting chemicals, including BPA, have been shown to activate the pregnane X receptor (PXR), a nuclear receptor that functions as a master regulator of xenobiotic metabolism. However, the detailed mechanism by which these chemicals activate PXR remains unknown.

OBJECTIVE

We investigated the mechanism by which BPA interacts with and activates PXR and examined selected BPA analogues to determine whether they bind to and activate PXR.

METHODS

Cell-based reporter assays, in silico ligand-PXR docking studies, and site-directed mutagenesis were combined to study the interaction between BPA and PXR. We also investigated the influence of BPA and its analogues on the regulation of PXR target genes in human LS180 cells.

RESULTS

We found that BPA and several of its analogues are potent agonists for human PXR (hPXR) but do not affect mouse PXR activity. We identified key residues within hPXR's ligand-binding pocket that constitute points of interaction with BPA. We also deduced the structural requirements of BPA analogues that activate hPXR. BPA and its analogues can also induce PXR target gene expression in human LS180 cells.

CONCLUSIONS

The present study advances our understanding of the mechanism by which BPA interacts with and activates human PXR. Activation of PXR by BPA may explain some of the adverse effects of BPA in humans.

Online chemical modeling environment (OCHEM): web platform for data storage, model development and publishing of chemical information

The Online Chemical Modeling Environment is a web-based platform that aims to automate and simplify the typical steps required for QSAR modeling. The platform consists of two major subsystems: the database of experimental measurements and the modeling framework. A user-contributed database contains a set of tools for easy input, search and modification of thousands of records. The OCHEM database is based on the wiki principle and focuses primarily on the quality and verifiability of the data. The database is tightly integrated with the modeling framework, which supports all the steps required to create a predictive model: data search, calculation and selection of a vast variety of molecular descriptors, application of machine learning methods, validation, analysis of the model and assessment of the applicability domain. As compared to other similar systems, OCHEM is not intended to re-implement the existing tools or models but rather to invite the original authors to contribute their results, make them publicly available, share them with other users and to become members of the growing research community. Our intention is to make OCHEM a widely used platform to perform the QSPR/QSAR studies online and share it with other users on the Web. The ultimate goal of OCHEM is collecting all possible chemoinformatics tools within one simple, reliable and user-friendly resource. The OCHEM is free for web users and it is available online at http://www.ochem.eu.

Logical Analysis of Data in Structure-Activity Investigation of Polymeric Gene Delivery

To date semi-empirical or surrogate modeling has demonstrated great success in the prediction of the biologically relevant properties of polymeric materials. For the first time, a correlation between the chemical structures of poly(β-amino esters) and their efficiency in transfecting DNA was established using the novel technique of logical analysis of data (LAD). Linear combination and explicit representation models were introduced and compared in the framework of the present study. The most successful regression model yielded satisfactory agreement between the predicted and experimentally measured values of transfection efficiency (Pearson correlation coefficient, 0.77; mean absolute error, 3.83). It was shown that detailed analysis of the rules provided by the LAD algorithm offered practical utility to a polymer chemist in the design of new biomaterials.

Class modeling analysis of heparin 1H NMR spectral data using the soft independent modeling of class analogy and unequal class modeling techniques

To differentiate heparin samples with varying amounts of dermatan sulfate (DS) impurities and oversulfated chondroitin sulfate (OSCS) contaminants, proton NMR spectral data for heparin sodium active pharmaceutical ingredient samples from different manufacturers were analyzed using multivariate chemometric techniques. A total of 168 samples were divided into three groups: (a) Heparin, [DS] ≤ 1.0% and [OSCS] = 0%; (b) DS, [DS] > 1.0% and [OSCS] = 0%; (c) OSCS, [OSCS] > 0% with any content of DS. The chemometric models were constructed and validated using two well-established methods: soft independent modeling of class analogy (SIMCA) and unequal class modeling (UNEQ). While SIMCA modeling was conducted using the entire set of variables extracted from the NMR spectral data, UNEQ modeling was combined with variable reduction using stepwise linear discriminant analysis to comply with the requirement that the number of samples per class exceed the number of variables in the model by at least 3-fold. Comparison of the results from these two modeling approaches revealed that UNEQ had greater sensitivity (fewer false positives) while SIMCA had greater specificity (fewer false negatives). For Heparin, DS, and OSCS, respectively, the sensitivity was 78% (56/72), 74% (37/50), and 85% (39/46) from SIMCA modeling and 88% (63/72), 90% (45/50), and 91% (42/46) from UNEQ modeling. Importantly, the specificity of both the SIMCA and UNEQ models was 100% (46/46) for Heparin with respect to OSCS; no OSCS-containing sample was misclassified as Heparin. The specificity of the SIMCA model (45/50, or 90%) was superior to that of the UNEQ model (27/50, or 54%) for Heparin with respect to DS samples. However, the overall prediction ability of the UNEQ model (85%) was notably better than that of the SIMCA model (76%) for the Heparin vs DS vs OSCS classes. The models were challenged with blends of heparin spiked with nonsulfated, partially sulfated, or fully oversulfated chondroitin sulfate A, dermatan sulfate, or heparan sulfate at the 1.0, 5.0, and 10.0 wt % levels. The results from the present study indicate that the combination of (1)H NMR spectral data and class modeling techniques (viz., SIMCA and UNEQ) represents a promising strategy for assessing the quality of commercial heparin samples with respect to impurities and contaminants. The methodologies show utility for applications beyond heparin to other complex products.

Combining (1)H NMR spectroscopy and chemometrics to identify heparin samples that may possess dermatan sulfate (DS) impurities or oversulfated chondroitin sulfate (OSCS) contaminants

Heparin is a naturally produced, heterogeneous compound consisting of variably sulfated and acetylated repeating disaccharide units. The structural complexity of heparin complicates efforts to assess the purity of the compound, especially when differentiating between similar glycosaminoglycans. Recently, heparin sodium contaminated with oversulfated chondroitin sulfate A (OSCS) has been associated with a rapid and acute onset of an anaphylactic reaction. In addition, naturally occurring dermatan sulfate (DS) was found to be present in these and other heparin samples as an impurity due to incomplete purification. The present study was undertaken to determine whether chemometric analysis of these NMR spectral data would be useful for discrimination between USP-grade samples of heparin sodium API and those deemed unacceptable based on their levels of DS, OSCS, or both. Several multivariate chemometric methods for clustering and classification were evaluated; specifically, principal components analysis (PCA), partial least squares discriminant analysis (PLS-DA), linear discriminant analysis (LDA), and the k-nearest-neighbor (kNN) method. Data dimension reduction and variable selection techniques, implemented to avoid over-fitting the training set data, markedly improved the performance of the classification models. Under optimal conditions, a perfect classification (100% success rate) was attained on external test sets for the Heparin vs OSCS model. The predictive rates for the Heparin vs DS, Heparin vs [DS+OSCS], and Heparin vs DS vs OSCS models were 89%, 93%, and 90%, respectively. In most cases, misclassifications can be ascribed to the similarity in NMR chemical shifts of heparin and DS. Among the chemometric methods evaluated in this study, we found that the LDA models were superior to the PLS-DA and kNN models for classification. Taken together, the present results demonstrate the utility of chemometric methods when applied in combination with (1)H NMR spectral analysis for evaluating the quality of heparin APIs.

Structure-based design of novel small-molecule inhibitors of Plasmodium falciparum

Malaria is endemic in most developing countries, with nearly 500 million cases estimated to occur each year. The need to design a new generation of antimalarial drugs that can combat the most drug-resistant forms of the malarial parasite is well recognized. In this study, we wanted to develop inhibitors of key proteins that form the invasion machinery of the malarial parasite. A critical feature of host-cell invasion by apicomplexan parasites is the interaction between the carboxy terminal tail of myosin A (MyoA) and the myosin tail interacting protein (MTIP). Using the cocrystal structure of the Plasmodium knowlesi MTIP and the MyoA tail peptide as input to the hybrid structure-based virtual screening approach, we identified a series of small molecules as having the potential to inhibit MTIP-MyoA interactions. Of the initial 15 compounds tested, a pyrazole-urea compound inhibited P. falciparum growth with an EC(50) value of 145 nM. We screened an additional 51 compounds belonging to the same chemical class and identified 8 compounds with EC(50) values less than 400 nM. Interestingly, the compounds appeared to act at several stages of the parasite's life cycle to block growth and development. The pyrazole-urea compounds identified in this study could be effective antimalarial agents because they competitively inhibit a key protein-protein interaction between MTIP and MyoA responsible for the gliding motility and the invasive features of the malarial parasite.

Discovery of novel alpha7 nicotinic receptor antagonists

Two distinct families of small molecules were discovered as novel alpha7 nicotinic acetylcholine receptor (nAChR) antagonists by pharmacophore-based virtual screening. These novel antagonists exhibited selectivity for the neuronal alpha7 subtype over other nAChRs and good brain penetration. Neuroprotection was demonstrated by representative compounds 7i and 8 in a mouse seizure-like behavior model induced by the nerve agent diisopropylfluorophosphate (DFP). These novel nAChR antagonists have potential use as antidote for organophosphorus nerve agent intoxication.

Identification of small molecule compounds with higher binding affinity to guanine deaminase (cypin) than guanine

Guanine deaminase (GDA; cypin) is an important metalloenzyme that processes the first step in purine catabolism, converting guanine to xanthine by hydrolytic deamination. In higher eukaryotes, GDA also plays an important role in the development of neuronal morphology by regulating dendritic arborization. In addition to its role in the maturing brain, GDA is thought to be involved in proper liver function since increased levels of GDA activity have been correlated with liver disease and transplant rejection. Although mammalian GDA is an attractive and potential drug target for treatment of both liver diseases and cognitive disorders, prospective novel inhibitors and/or activators of this enzyme have not been actively pursued. In this study, we employed the combination of protein structure analysis and experimental kinetic studies to seek novel potential ligands for human guanine deaminase. Using virtual screening and biochemical analysis, we identified common small molecule compounds that demonstrate a higher binding affinity to GDA than does guanine. In vitro analysis demonstrates that these compounds inhibit guanine deamination, and more surprisingly, affect GDA (cypin)-mediated microtubule assembly. The results in this study provide evidence that an in silico drug discovery strategy coupled with in vitro validation assays can be successfully implemented to discover compounds that may possess therapeutic value for the treatment of diseases and disorders where GDA activity is abnormal.

Human ADA3 regulates RARalpha transcriptional activity through direct contact between LxxLL motifs and the receptor coactivator pocket

The alternation/deficiency in activation-3 (ADA3) is an essential component of the human p300/CBP-associated factor (PCAF) and yeast Spt-Ada-Gcn5-acetyltransferase (SAGA) histone acetyltransferase complexes. These complexes facilitate transactivation of target genes by association with transcription factors and modification of local chromatin structure. It is known that the yeast ADA3 is required for nuclear receptor (NR)-mediated transactivation in yeast cells; however, the role of mammalian ADA3 in NR signaling remains elusive. In this study, we have investigated how the human (h) ADA3 regulates retinoic acid receptor (RAR) α-mediated transactivation. We show that hADA3 interacts directly with RARα in a hormone-dependent manner and this interaction contributes to RARα transactivation. Intriguingly, this interaction involves classical LxxLL motifs in hADA3, as demonstrated by both ‘loss’ and ‘gain’ of function mutations, as well as a functional coactivator pocket of the receptor. Additionally, we show that hADA3 associates with RARα target gene promoter in a hormone-dependent manner and ADA3 knockdown impairs RARβ2 expression. Furthermore, a structural model was established to illustrate an interaction network within the ADA3/RARα complex. These results suggest that hADA3 is a bona fide transcriptional coactivator for RARα, acting through a conserved mechanism involving direct contacts between NR boxes and the receptor’s co-activator pocket.

NetCSSP: web application for predicting chameleon sequences and amyloid fibril formation

The calculation of contact-dependent secondary structure propensity (CSSP) is a unique and sensitive method that detects non-native secondary structure propensities in protein sequences. This method has applications in predicting local conformational change, which typically is observed in core sequences of protein aggregation and amyloid fibril formation. NetCSSP implements the latest version of the CSSP algorithm and provides a Flash chart-based graphic interface that enables an interactive calculation of CSSP values for any user-selected regions in a given protein sequence. This feature also can quantitatively estimate the mutational effect on changes in native or non-native secondary structural propensities in local sequences. In addition, this web tool provides precalculated non-native secondary structure propensities for over 1 400 000 fragments that are seven-residues long, collected from PDB structures. They are searchable for chameleon subsequences that can serve as the core of amyloid fibril formation. The NetCSSP web tool is available at http://cssp2.sookmyung.ac.kr/.

Understanding nuclear receptors using computational methods

Nuclear receptors (NRs) are important targets for therapeutic drugs. NRs regulate transcriptional activities through binding to ligands and interacting with several regulating proteins. Computational methods can provide insights into essential ligand-receptor and protein-protein interactions. These in turn have facilitated the discovery of novel agonists and antagonists with high affinity and specificity as well as have aided in the prediction of toxic side effects of drugs by identifying possible off-target interactions. Here, we review the application of computational methods toward several clinically important NRs (with special emphasis on PXR) and discuss their use for screening and predicting the toxic side effects of xenobiotics.

ebTrack: an environmental bioinformatics system built upon ArrayTrack

ebTrack is being developed as an integrated bioinformatics system for environmental research and analysis by addressing the issues of integration, curation, management, first level analysis and interpretation of environmental and toxicological data from diverse sources. It is based on enhancements to the US FDA developed ArrayTrack™ system through additional analysis modules for gene expression data as well as through incorporation and linkages to modules for analysis of proteomic and metabonomic datasets that include tandem mass spectra. ebTrack uses a client-server architecture with the free and open source PostgreSQL as its database engine, and java tools for user interface, analysis, visualization, and web-based deployment. Several predictive tools that are critical for environmental health research are currently supported in ebTrack, including Significance Analysis of Microarray (SAM). Furthermore, new tools are under continuous integration, and interfaces to environmental health risk analysis tools are being developed in order to make ebTrack widely usable. These health risk analysis tools include the Modeling ENvironment for TOtal Risk studies (MENTOR) for source-to-dose exposure modeling and the DOse Response Information ANalysis system (DORIAN) for health outcome modeling. The design of ebTrack is presented in detail and steps involved in its application are summarized through an illustrative application.

The major human pregnane X receptor (PXR) splice variant, PXR.2, exhibits significantly diminished ligand-activated transcriptional regulation

The pregnane X receptor (PXR; PXR.1) can be activated by structurally diverse lipophilic ligands. PXR.2, an alternatively spliced form of PXR, lacks 111 nucleotides encoding 37 amino acids in the ligand binding domain. PXR.2 bound a classic CYP3A4 PXR response element (PXRE) in electrophoretic mobility shift assays, but transfected PXR.2 failed to transactivate a CYP3A4-promoter-luciferase reporter plasmid in HepG2 cells treated with various PXR ligands. Cotransfection experiments showed that PXR.2 behaved as a dominant negative, interfering with PXR.1/rifampin activation of CYP3A4-PXRE-LUC. In HepG2 and LS180 cells stably transduced with PXR.1, PXR target genes (CYP3A4, MDR1, CYP2B6, and UGT1A1) were higher than mock-transduced cells in the absence of ligand and were further induced in the presence of rifampin. In contrast, PXR.2 stably introduced into the same host cells failed to induce target genes over levels in mock-transfected cells after drug treatment. Our homology modeling suggests that ligands bind PXR.1 more favorably, probably because of the presence of a key disordered loop region, which is missing in PXR.2. Yeast two-hybrid assays revealed that, even in the presence of ligand, the corepressors remain tightly bound to PXR.2, and coactivators are unable to bind at helix 12. In summary, PXR.2 can bind to PXREs but fails to transactivate target genes because ligands do not bind the ligand binding domain of PXR.2 productively, corepressors remain tightly bound, and coactivators are not recruited to PXR.2.

Novel microtubule polymerization inhibitor with potent antiproliferative and antitumor activity

Microtubule-stabilizing and microtubule-destabilizing agents are commonly used as anticancer agents. Although highly effective, success with these agents has been limited due to their relative insolubility, cumbersome synthesis/purification, toxic side effects, and development of multidrug resistance. Hence, the identification of improved agents that circumvent one or more of these problems is warranted. We recently described the rational design of a series of triazole-based compounds as antimitotic agents. Members of this N-substituted 1,2,4-triazole family of compounds exhibit potent tubulin polymerization inhibition and broad spectrum cellular cytotoxicity. Here, we extensively characterize the in vitro and in vivo effects of our lead compound from the series 1-methyl-5-(3-(3,4,5-trimethoxyphenyl)-4H-1,2,4-triazole-4-yl)-1H-indole, designated T115. We show that T115 competes with colchicine for its binding pocket in tubulin, produces robust inhibition of tubulin polymerization, and disrupts the microtubule network system inside the cells. In addition, T115 arrests human cancer cells in the G(2)-M phase of cell cycling, a hallmark of microtubule destabilizing drugs. T115 also inhibits cell viability of several cancer cell lines, including multidrug-resistant cell lines, in the low nanomolar range. No cytotoxicity was observed by T115 against normal human skin fibroblasts cell lines, and acute toxicity studies in normal nontumor-bearing mice indicated that T115 is well-tolerated in vivo (maximum total tolerated dose, 400 mg/kg). In a mouse xenograft model using human colorectal (HT-29) and prostate (PC3) cancer cells, T115 significantly inhibited tumor growth when administered i.p. Taken together, our results suggest that T115 is a potential drug candidate for cancer chemotherapy.

Computational discovery of novel low micromolar human pregnane X receptor antagonists

Very few antagonists have been identified for the human pregnane X receptor (PXR). These molecules may be of use for modulating the effects of therapeutic drugs, which are potent agonists for this receptor (e.g., some anticancer compounds and macrolide antibiotics), with subsequent effects on transcriptional regulation of xenobiotic metabolism and transporter genes. A recent novel pharmacophore for PXR antagonists was developed using three azoles and consisted of two hydrogen bond acceptor regions and two hydrophobic features. This pharmacophore also suggested an overall small binding site that was identified on the outer surface of the receptor at the AF-2 site and validated by docking studies. Using computational approaches to search libraries of known drugs or commercially available molecules is preferred over random screening. We have now described several new smaller antagonists of PXR discovered with the antagonist pharmacophore with in vitro activity in the low micromolar range [S-p-tolyl 3',5-dimethyl-3,5'-biisoxazole-4'-carbothioate (SPB03255) (IC(50), 6.3 microM) and 4-(3-chlorophenyl)-5-(2,4-dichlorobenzylthio)-4H-1,2,4-triazol-3-ol (SPB00574) (IC(50), 24.8 microM)]. We have also used our computational pharmacophore and docking tools to suggest that most of the known PXR antagonists, such as coumestrol and sulforaphane, could also interact on the outer surface of PXR at the AF-2 domain. The involvement of this domain was also suggested by further site-directed mutagenesis work. We have additionally described an FDA approved prodrug, leflunomide (IC(50), 6.8 microM), that seems to be a PXR antagonist in vitro. These observations are important for predicting whether further molecules may interact with PXR as antagonists in vivo with potential therapeutic applications.

Shape signatures: new descriptors for predicting cardiotoxicity in silico

Shape Signatures is a new computational tool that is being evaluated for applications in computational toxicology and drug discovery. The method employs a customized ray-tracing algorithm to explore the volume enclosed by the surface of a molecule and then uses the output to construct compact histograms (i.e., signatures) that encode for molecular shape and polarity. In the present study, we extend the application of the Shape Signatures methodology to the domain of computational models for cardiotoxicity. The Shape Signatures method is used to generate molecular descriptors that are then utilized with widely used classification techniques such as k nearest neighbors ( k-NN), support vector machines (SVM), and Kohonen self-organizing maps (SOM). The performances of these approaches were assessed by applying them to a data set of compounds with varying affinity toward the 5-HT(2B) receptor as well as a set of human ether-a-go-go-related gene (hERG) potassium channel inhibitors. Our classification models for 5-HT(2B) represented the first attempt at global computational models for this receptor and exhibited average accuracies in the range of 73-83%. This level of performance is comparable to using commercially available molecular descriptors. The overall accuracy of the hERG Shape Signatures-SVM models was 69-73%, in line with other computational models published to date. Our data indicate that Shape Signatures descriptors can be used with SVM and Kohonen SOM and perform better in classification problems related to the analysis of highly clustered and heterogeneous property spaces. Such models may have utility for predicting the potential for cardiotoxicity in drug discovery mediated by the 5-HT(2B) receptor and hERG.

Ligand specificity and evolution of liver X receptors

Liver X receptors (LXRs) are key regulators of lipid and cholesterol metabolism in mammals. Little is known, however, about the function and evolution of LXRs in non-mammalian species. The present study reports the cloning of LXRs from African clawed frog (Xenopus laevis), Western clawed frog (Xenopus tropicalis), and zebrafish (Danio rerio), and their functional characterization and comparison with human and mouse LXRs. Additionally, an ortholog of LXR in the chordate invertebrate Ciona intestinalis was cloned and functionally characterized. Ligand specificities of the frog and zebrafish LXRs were very similar to LXRalpha and LXRbeta from human and mouse. All vertebrate LXRs studied were activated robustly by the synthetic ligands T-0901317 and GW3965 and by a variety of oxysterols. In contrast, Ciona LXR was not activated by T-0901317 or GW3965 but was activated by a limited number of oxysterols, as well as some androstane and pregnane steroids. Pharmacophore analysis, homology modeling, and docking studies of Ciona LXR predict a receptor with a more restricted ligand-binding pocket and less intrinsic disorder in the ligand-binding domain compared to vertebrate LXRs. The results suggest that LXRs have a long evolutionary history, with vertebrate LXRs diverging from invertebrate LXRs in ligand specificity.

Structural characterization of the zinc binding domain in cytosolic PSD-95 interactor (cypin): Role of zinc binding in guanine deamination and dendrite branching

Dendrite morphology regulates how a postsynaptic neuron receives information from presynaptic neurons. The specific patterning of dendrite branches is promoted by extrinsic and intrinsic factors that trigger the activation of functional signaling pathways. However, most of the regulating factors and the biochemical mechanisms involved in regulating dendrite branching are unknown. Our laboratory previously reported that cypin (cytosolic PSD-95 interactor) plays an active role in regulating dendrite branching in hippocampal neurons. Cypin-promoted increases in dendrite number are dependent on guanine deaminase activity. In order to identify the specific structural role of zinc-binding in cypin-mediated dendrite branching and guanine deaminase activity, we employed computational homology modeling techniques to construct a three dimensional structural model of cypin. Analysis of the protein-ion sequestration scaffold of this model identified several histidines and aspartic acid residues responsible for zinc binding. Single substitution mutations in these specific sites completely disrupted the guanine deaminase enzymatic activity and rendered cypin unable to promote dendrite branching in rat hippocampal neurons. The specific zinc ion-binding function of each residue in the protein scaffold was also confirmed by Inductively Coupled Plasma-Optic Emission Spectrometry. Inspection of our structural model confirmed that His82 and His84 coordinate with the zinc ion, together with His240, His279, and Asp330, residues that until now were unknown to play a role in this regard. Furthermore, promotion of dendrite branching by cypin is zinc-dependent.

Evolution of the bile salt nuclear receptor FXR in vertebrates

Bile salts, the major end metabolites of cholesterol, vary significantly in structure across vertebrate species, suggesting that nuclear receptors binding these molecules may show adaptive evolutionary changes. We compared across species the bile salt specificity of the major transcriptional regulator of bile salt synthesis, the farnesoid X receptor (FXR). We found that FXRs have changed specificity for primary bile salts across species by altering the shape and size of the ligand binding pocket. In particular, the ligand binding pockets of sea lamprey (Petromyzon marinus) and zebrafish (Danio rerio) FXRs, as predicted by homology models, are flat and ideal for binding planar, evolutionarily early bile alcohols. In contrast, human FXR has a curved binding pocket best suited for the bent steroid ring configuration typical of evolutionarily more recent bile acids. We also found that the putative FXR from the sea squirt Ciona intestinalis, a chordate invertebrate, was completely insensitive to activation by bile salts but was activated by sulfated pregnane steroids, suggesting that the endogenous ligands of this receptor may be steroidal in nature. Our observations present an integrated picture of the coevolution of bile salt structure and of the binding pocket of their target nuclear receptor FXR.

Structural model of the Plasmodium CDK, Pfmrk, a novel target for malaria therapeutics

Malaria, with 300-500 million clinical cases resulting in 1-3 million fatalities a year, is one of the most deadly tropical diseases. As current antimalarial therapeutics become increasingly ineffective due to parasitic resistance, there exists an urgent need to develop and pursue new therapeutic strategies. Recent genome sequencing and molecular cloning projects have identified several enzymes from Plasmodium (P.) falciparum that may represent novel drug targets, including a family of proteins that are homologous to the mammalian cyclin-dependent kinases (CDKs). CDKs are essential for the control of the mammalian cell cycle and, based on the conservation of the CDKs across species, the plasmodial CDKs are expected to play a crucial role in parasitic growth. Here we present a 3D structural model of Pfmrk, a putative human CDK activating kinase (CAK) homolog in P. falciparum. Notable features of the present structural model include: (1) parameterization of the Mg2+ hexacoordination system using ab initio quantum chemical calculations to accurately represent the ATP-kinase interaction; and (2) comparison between the docking scores and measured binding affinities for a series of oxindole-based Pfmrk inhibitors of known activity. Detailed analysis of inhibitor-Pfmrk binding interactions enabled us to identify specific residues (viz. Met66, Met75, Met91, Met94 and Phe143) within the Pfmrk binding pocket that may play an important role in inhibitor binding affinity and selectivity. The availability of this Pfmrk structural model, together with insights gained from analysis of ligand-receptor interactions, should promote the rational design of potent and selective Pfmrk inhibitors as antimalarial therapeutics.

CSSP2: An improved method for predicting contact-dependent secondary structure propensity

The calculation of contact-dependent secondary structure propensity (CSSP) has been reported to sensitively detect non-native beta-strand propensities in the core sequences of amyloidogenic proteins. Here we describe a noble energy-based CSSP method implemented on dual artificial neural networks that rapidly and accurately estimate the potential for the non-native secondary structure formation in local regions of protein sequences. In this method, we attempted to quantify long-range interaction patterns in diverse secondary structures by potential energy calculations and decomposition on a pairwise per-residue basis. The calculated energy parameters and seven-residue sequence information were used as inputs for artificial neural networks (ANNs) to predict sequence potential for secondary structure conversion. The trained single ANN using the >(i, i+/-4) interaction energy parameter exhibited 74% accuracy in predicting the secondary structure of test sequences in their native energy state, while the dual ANN-based predictor using (i, i+/-4) and >(i, i+/-4) interaction energies showed 83% prediction accuracy. The present method provides a simple and accurate tool for predicting sequence potential for secondary structure conversions without using 3D structural information.

Prediction of Fibrinogen Adsorption for Biodegradable Polymers: Integration of Molecular Dynamics and Surrogate Modeling

This work is a part of a series of publications devoted to the development of surrogate (semi-empirical) models for the prediction of fibrinogen adsorption onto polymer surfaces. Since fibrinogen is one of the key proteins involved in platelet activation and the formation of thrombosis, the modeling of fibrinogen adsorption on the surface of blood contacting medical devices is of high theoretical and practical significance. We report here, for the first time, on the incorporation three-dimensional structures of polymers obtained from atomistic simulations into conventional mesoscopic-scale calculations. Low energy conformations derived from Molecular Dynamics simulations for 45 representatives of a combinatorial library of polyarylates were used in an improved modeling procedure (referred to as "3D surrogate model") instead of simplistic two-dimensional representations of polymer structures, which were used in several previous models (collectively referred to as "2D surrogate models"). In the framework of this 3D model we created 12 model sets of polymers to account for their chirality, conformational diversity and the structural influence of a solvent. For each polymer set, three-dimensional molecular descriptors were generated and then ranked with respect to the experimental fibrinogen adsorption data by means of a Monte Carlo Decision Tree. The most significant descriptors identified by Decision Tree and the experimental dataset were utilized to predict fibrinogen adsorption using an Artificial Neural Network (ANN). The best prediction achieved by the 3D surrogate model demonstrated a noticeable improvement in the predictive quality as compared to the previously used 2D model (as evidenced by the increase in the average Pearson correlation coefficient from 0.67+/-0.13 to 0.54+/-0.12). The predictive quality of the 3D surrogate model compares favorably with the best results previously reported for extended 2D model that combines an ANN with Partial Least Squares (PLS) regression and principal component (PC) analysis. The significance of the newly developed 3D model is that it allows high accuracy prediction of fibrinogen adsorption without the need for experimentally derived descriptors and it has better predictive quality than the original 2D surrogate model due to utilization of realistic polymer representations.