Sarcin/Ricin Domain RNA Retains Its Structure Better Than A-RNA in Adaptively Biased Molecular Dynamics Simulations.

Less than one in thirty of the RNA sequences transcribed in humans are translated into protein. The noncoding RNA (ncRNA) functions in catalysis, structure, regulation, and more. However, for the most part, these functions are poorly characterized. RNA is modular and described by motifs that include helical A-RNA with canonical Watson-Crick base-pairing as well as structures with only noncanonical base pairs. Understanding the structure and dynamics of motifs will aid in deciphering functions of specific ncRNAs. We present computational studies on a standard sarcin/ricin domain (SRD), citrus bark cracking viroid SRD, as well as A-RNA. We have applied enhanced molecular dynamics techniques that construct an inverse free-energy surface (iFES) determined by collective variables that monitor base-pairing and backbone conformation. Each SRD RNA is flanked on each side by A-RNA, allowing comparison of the behavior of these motifs in the same molecule. The RNA iFESs have single peaks, indicating that the combined motifs should denature as a single cohesive unit, rather than by regional melting. Local root-mean-square deviation (RMSD) analysis and communication propensity (CProp, variance in distances between residue pairs) reveal distinct motif properties. Our analysis indicates that the standard SRD is more stable than the viroid SRD, which is more stable than A-RNA. Base pairs at SRD to A-RNA transitions have limited flexibility. Application of CProp reveals extraordinary stiffness of the SRD, allowing residues on opposite sides of the motif to sense each other's motions.

Inflammatory adipose activates a nutritional immunity pathway leading to retinal dysfunction.

Age-related macular degeneration (AMD), the leading cause of irreversible blindness among Americans over 50, is characterized by dysfunction and death of retinal pigment epithelial (RPE) cells. The RPE accumulates iron in AMD, and iron overload triggers RPE cell death in vitro and in vivo. However, the mechanism of RPE iron accumulation in AMD is unknown. We show that high-fat-diet-induced obesity, a risk factor for AMD, drives systemic and local inflammatory circuits upregulating interleukin-1ß (IL-1ß). IL-1ß upregulates RPE iron importers and downregulates iron exporters, causing iron accumulation, oxidative stress, and dysfunction. We term this maladaptive, chronic activation of a nutritional immunity pathway the cellular iron sequestration response (CISR). RNA sequencing (RNA-seq) analysis of choroid and retina from human donors revealed that hallmarks of this pathway are present in AMD microglia and macrophages. Together, these data suggest that inflamed adipose tissue, through the CISR, can lead to RPE pathology in AMD.

RNA expression in human retina.

Recent Genome-wide Association Studies (GWASs) for eye diseases/traits have delivered a number of novel findings across a diverse range of diseases, including age-related macular degeneration (AMD), glaucoma and refractive error. However, despite this astonishing rate of success, the major challenge still remains to not only confirm that the genes implicated in these studies are truly the genes conferring protection from or risk of disease but also to define the functional roles these genes play in disease. Ongoing evidence is accumulating that the single nucleotide polymorphisms (SNPs) used in GWAS and fine mapping studies have causal effects through their influence on gene expression rather than affecting protein function. The biological interpretation of SNP regulatory effects for a tissue requires knowledge of the transcriptome for that tissue. We summarize the reasons to characterize the complete retinal transcriptome as well as the evidence to include an assessment of differences in regional retinal expression.

Computational analysis of EBNA1 "druggability" suggests novel insights for Epstein-Barr virus inhibitor design.

The Epstein-Barr Nuclear Antigen 1 (EBNA1) is a critical protein encoded by the Epstein-Barr Virus (EBV). During latent infection, EBNA1 is essential for DNA replication and transcription initiation of viral and cellular genes and is necessary to immortalize primary B-lymphocytes. Nonetheless, the concept of EBNA1 as drug target is novel. Two EBNA1 crystal structures are publicly available and the first small-molecule EBNA1 inhibitors were recently discovered. However, no systematic studies have been reported on the structural details of EBNA1 "druggable" binding sites. We conducted computational identification and structural characterization of EBNA1 binding pockets, likely to accommodate ligand molecules (i.e. "druggable" binding sites). Then, we validated our predictions by docking against a set of compounds previously tested in vitro for EBNA1 inhibition (PubChem AID-2381). Finally, we supported assessments of pocket druggability by performing induced fit docking and molecular dynamics simulations paired with binding affinity predictions by Molecular Mechanics Generalized Born Surface Area calculations for a number of hits belonging to druggable binding sites. Our results establish EBNA1 as a target for drug discovery, and provide the computational evidence that active AID-2381 hits disrupt EBNA1:DNA binding upon interacting at individual sites. Lastly, structural properties of top scoring hits are proposed to support the rational design of the next generation of EBNA1 inhibitors.

Dual inhibition of Staphylococcus aureus DNA gyrase and topoisomerase IV activity by phenylalanine-derived (Z)-5-arylmethylidene rhodanines.

Methicillin resistant Staphylococcus aureus (MRSA) is a major drug resistant bacteria that persists in both community and clinical settings due to growing resistance to current drug regimens. Thus, there is a continued need for novel compounds that are active against this organism. Previously, we reported that various rhodanine derivatives inhibited the supercoiling activity of DNA gyrase. In this study, we determined the effect of new phenylalanine-derived (Z)-5-arylmethylidene rhodanines (which are efficacious against MRSA) on the activity of the two type II bacterial topoisomerases, DNA gyrase and topoisomerase IV (Topo IV). Compounds 1 and 9 showed the greatest efficacy against DNA gyrase with a minimal inhibitory concentration (MIC) of 5 µM while compounds 2 and 3 were the most efficacious against Topo IV with MIC values of 0.75 µM and 0.5 µM, respectively. Induced fit docking, using the crystallographic structures of the target enzymes, indicated that these rhodanine derivatives bind to the ATPase domain of gyrB and ParE subunits on DNA gyrase and Topo IV, respectively. These new compounds were efficacious against both DNA gyrase and Topo IV. The increased efficacy of these new rhodanine compounds, as compared to other rhodanine derivatives, results from their dual inhibition of DNA gyrase and Topo IV, thereby making them good candidates for further drug design and development.

Cytotoxicity of thiazolidinedione-, oxazolidinedione- and pyrrolidinedione-ring containing compounds in HepG2 cells.

Liver damage occurred in some patients who took troglitazone (TGZ) for type II diabetes. The 2,4-thiazolidinedione (TZD) ring in TGZ's structure has been implicated in its hepatotoxicity. To further examine the potential role of a TZD ring in toxicity we used HepG2 cells to evaluate two series of compounds containing different cyclic imides. N-phenyl analogues comprised 3-(3,5-dichlorophenyl)-2,4-thiazolidinedione (DCPT); 3-(3,5-dichlorophenyl)-2,4-oxazolidinedione (DCPO) and N-(3,5-dichlorophenyl)succinimide (NDPS). Benzylic compounds, which closely resemble TGZ, included 5-(3,5-dichlorophenylmethyl)-2,4-thiazolidinedione (DCPMT); 5-(4-methoxyphenylmethyl)-2,4-thiazolidinedione (MPMT); 5-(4-methoxyphenylmethylene)-2,4-thiazolidinedione (MPMT-I); 5-(4-methoxyphenylmethyl)-2,4-oxazolidinedione (MPMO); 3-(4-methoxyphenylmethyl)succinimide (MPMS) and 3-(4-methoxyphenylmethylene)succinimide (MPMS-I). Cytotoxicity was assessed using the MTS assay after incubating the compounds (0-250µM) with HepG2 cells for 24h. Only certain TZD derivatives (TGZ, DCPT, DCPMT and MPMT-I) markedly decreased cell viability, whereas MPMT had low toxicity. In contrast, analogues without a TZD ring (DCPO, NDPS, MPMO, MPMS and MPMS-I) were not cytotoxic. These findings suggest that a TZD ring may be an important determinant of toxicity, although different structural features, chemical stability, cellular uptake or metabolism, etc., may also be involved. A simple clustering approach, using chemical fingerprints, assigned each compound to one of three classes (each containing one active compound and close homologues), and provided a framework for rationalizing the activity in terms of structure.

An SH2 domain model of STAT5 in complex with phospho-peptides define "STAT5 Binding Signatures".

The signal transducer and activator of transcription 5 (STAT5) is a member of the STAT family of proteins, implicated in cell growth and differentiation. STAT activation is regulated by phosphorylation of protein monomers at conserved tyrosine residues, followed by binding to phospho-peptide pockets and subsequent dimerization. STAT5 is implicated in the development of severe pathological conditions, including many cancer forms. However, nowadays a few STAT5 inhibitors are known, and only one crystal structure of the inactive STAT5 dimer is publicly available. With a view to enabling structure-based drug design, we have: (1) analyzed phospho-peptide binding pockets on SH2 domains of STAT5, STAT1 and STAT3; (2) generated a model of STAT5 bound to phospho-peptides; (3) assessed our model by docking against a class of known STAT5 inhibitors (Müller et al. in ChemBioChem 9:723-727, 2008); (4) used molecular dynamics simulations to optimize the molecular determinants responsible for binding and (5) proposed unique "Binding Signatures" of STAT5. Our results put in place the foundations to address STAT5 as a target for rational drug design, from sequence, structural and functional perspectives.

Computer-aided identification of novel 3,5-substituted rhodanine derivatives with activity against Staphylococcus aureus DNA gyrase.

Methicillin resistant Staphylococcus aureus (MRSA) is among the major drug resistant bacteria that persist in both the community and clinical settings due to resistance to commonly used antimicrobials. This continues to fuel the need for novel compounds that are active against this organism. For this purpose we have targeted the type IIA bacterial topoisomerase, DNA gyrase, an essential enzyme involved in bacterial replication, through the ATP-dependent supercoiling of DNA. The virtual screening tool Shape Signatures was applied to screen a large database for agents with shape similar to Novobiocin, a known gyrase B inhibitor. The binding energetics of the top hits from this initial screen were further validated by molecular docking. Compounds with the highest score on available crystal structure of homologous DNA gyrase from Thermus thermophilus were selected. From this initial set of compounds, several rhodanine-substituted derivatives had the highest antimicrobial activity against S. aureus, as determined by minimal inhibitory concentration assays, with Novobiocin as the positive control. Further activity validation of the rhodanine compounds through biochemical assays confirmed their inhibition of both the supercoiling and the ATPase activity of DNA gyrase. Subsequent docking and molecular dynamics on the crystal structure of DNA gyrase from S. aureus when it became available, provides further rationalization of the observed biochemical activity and understanding of the receptor-ligand interactions. A regression model for MIC prediction against S. aureus is generated based on the current molecules studied as well as other rhodanines derivatives found in the literature.

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.

Modeling androgen receptor flexibility: a binding mode hypothesis of CYP17 inhibitors/antiandrogens for prostate cancer therapy.

Prostate Cancer (PCa), a leading cause of cancer death worldwide (www.cancer.gov), is a complex malignancy where a spectrum of targets leads to a diversity of PCa forms. A widely pursued therapeutic target is the Androgen Receptor (AR). As a Steroid Hormone Receptor, AR serves as activator of transcription upon binding to androgens and plays a central role in the development of PCa. AR is a structurally flexible protein, and conformational plasticity of residues in the binding-pocket is a key to its ability to accommodate ligands from various chemical classes. Besides direct modulation of AR activity by antagonists, inhibition of cytochrome CYP17 (17α-hydroxylase/17,20-lyase), essential in androgen biosynthesis, has widely been considered an effective strategy against PCa. Interestingly, Handratta et al. (2005) discovered new, potent inhibitors of CYP17 (C-17 steroid derivatives) with pure AR antagonistic properties. Although the antiandrogenic activity of their lead compound (VN/124-1) has been experimentally proven both in vitro and in vivo, no structural data are currently available to elucidate the molecular determinants responsible for these desirable dual inhibitory properties. We implemented a Structure-based Drug Design (SBDD) approach to generate a valuable hypothesis as to the binding modes of steroidal CYP17 inhibitors/antiandrogens against the AR. To deal with the plasticity of residues buried in the Ligand Binding Domain (LBD), we developed a flexible-receptor Docking protocol based on Induced-Fit (IFD) methodology (www.schrodinger.com/). Our results constitute an ideal starting point for the rational design of next-generation analogues of CYP17 inhibitors/antiandrogens as well as an attractive tool to suggest novel chemical classes of AR antagonists.

Application of screening methods, shape signatures and engineered biosensors in early drug discovery process.

PURPOSE: In this study, two unreported estrogen antagonists were identified using a combination of computational screening and a simple bacterial estrogen sensor. METHODS: Molecules here presented were initially part of a group obtained from a library of over a half million chemical compounds, using the Shape Signatures method. The structures within this group were then clustered and compared to known antagonists based on their physico-chemical parameters, and possible binding modes of the compounds to the Estrogen Receptor alpha (ER alpha) were analyzed. Finally, thirteen candidate compounds were purchased, and two of them were shown to behave as potential subtype-selective estrogen antagonists using a set of bacterial estrogen biosensors, which included sensors for ER alpha, ER beta, and a negative control thyroid hormone beta biosensor. These activities were then analyzed using an ELISA assay against activated ER alpha in human MCF-7 cell extract. RESULTS: Two new estrogen receptor antagonists were detected using in silico Shape Signatures method with an engineered subtype-selective bacterial estrogen biosensor and commercially available ELISA assay. Additional thyroid biosensor control experiments confirmed no compounds interacted with human thyroid receptor beta. CONCLUSIONS: This work demonstrates an effective combination of computational analysis and simple bacterial screens for rapid identification of potential hormone-like therapeutics.

Shape Signatures: speeding up computer aided drug discovery.

Identifying potential lead molecules is becoming a more automated process. We review Shape Signatures, a tool that is effective and easy to use compared with most computer aided drug design techniques. Laboratory researchers can apply this in silico technique cost-effectively without the need for specialized computer backgrounds. Identifying a potential lead molecule requires database screening, and this becomes rate-limiting once the database becomes too large. The use of Shape Signatures eliminates this concern and offers molecule screening rates that are in advance of any currently available method. Shape Signatures provides a conduit for researchers to conduct rapid identification of potential active molecules, and studies with this tool can be initiated with only one bioactive lead or receptor site.

Evidence for a strong selenium-aromatic interaction derived from crystallographic data and ab initio quantum chemical calculations.

Increasing attention is being paid to the role of selenium, both as an essential component required for the activity of many enzymes and in the context of selenium-based pharmaceutical agents. A wide range of therapeutics that include selenium are on the market and under development, such as antihypertensive, anticancerogenic, antiviral, and immunosuppressive agents. Computer-aided drug design (CADD) has proven to be an important tool for the development of new drugs. Many CADD techniques, including docking, molecular dynamics simulation, and other receptor-based approaches, require an accurate understanding of the nature of the intermolecular forces that act to stabilize protein-ligand complexes; moreover, a quantitative assessment of these interactions furthers our efforts to rationalize the drug design process. In this paper, we consider one class of interaction involving selenium, that between Se and aromatic rings. Prior work has shown that interactions between divalent sulfur and aromatic rings are observed much more frequently than would be expected on the basis of chance, both in protein structures and the crystal structures of organic compounds that include these moieties. Recent studies on the optimization of inhibitor-protein binding also suggest that sulfur-aromatic interactions are important in stabilizing these complexes and may be crucial focal point for CADD. Given that selenium and sulfur have similar chemistry, and that selenium is significantly more polarizable, we propose that Se-aromatic interactions may also play an important stabilizing role in the structure of folded proteins and in drug-protein complexes. We have tested this hypothesis against data from the Cambridge Crystallographic Database and ab initio quantum chemical calculations. We have found evidence that selenium does interact strongly with aromatic rings and may play a role analogous to sulfur in stabilizing protein folds. In addition, selenium should be considered along with sulfur in rational drug design strategies that seek to improve binding to target protein sites that include aromatic rings.

Molecular dynamics of a biophysical model for beta2-adrenergic and G protein-coupled receptor activation.

This study analyzes 16 molecular dynamic simulations of a biophysical model for beta(2)-adrenergic (B2AR) and G protein-coupled receptor (GPCR) activation. In this model, a highly conserved cysteine residue, C106 (C3.25 or CysIII:01), provides a free sulfhydryl or thiol group in an acid-base equilibrium between uncharged (RSH) and charged (RS(-)) states that functions as an electrostatic molecular switch for receptor activation. The transition of C106 in the B2AR between acid and base states significantly changes the helical/transmembrane (TM) domain interactions and the electrostatic interaction energy differences (DeltaDeltaE(EL)). The DeltaDeltaE(EL) changes correlate well with the experimentally observed ligand efficacies. The TM interaction energies display patterns compatible with those previously recognized as responsible for GPCR activation. Key differences between the agonist, epinephrine, and the antagonist, pindolol, are seen for the TM3 x 6, TM3 x 4, TM6 x 7 and TM1 x 7 interaction energies. Pindolol also produces a weaker DeltaDeltaE(EL) interaction and less TM interaction energy changes, which are important differences between the agonist and antagonist ligands. The D115E mutant with pindolol displays a greater DeltaDeltaE(EL) and TM interactions than for the wild-type B2AR with pindolol. This explains the higher activity of pindolol in the D115E mutant. The constitutively active D130A mutant displays TM interaction patterns similar to those for the activating ligands implying a common pattern for receptor activation. These findings support the broad concept of protean agonism and demonstrate the potential for allosteric modulation. They also demonstrate that this two-state model agrees with many previous experimental and theoretical observations of GPCRs.

Comparison of methods for the prediction of the metabolic sites for CYP3A4-mediated metabolic reactions.

Predictions of the metabolic sites for new chemical entities, synthesized or only virtual, are important in the early phase of drug discovery to guide chemistry efforts in the synthesis of new compounds with reduced metabolic liability. This information can now be obtained from in silico predictions, and therefore, a thorough and unbiased evaluation of the computational techniques available is needed. Several computational methods to predict the metabolic hot spots are emerging. In this study, metabolite identification using MetaSite and a docking methodology, GLUE, were compared. Moreover, the published CYP3A4 crystal structure and computed CYP3A4 homology models were compared for their usefulness in predicting metabolic sites. A total of 227 known CYP3A4 substrates reported to have one or more metabolites adding up to 325 metabolic pathways were analyzed. Distance-based fingerprints and four-point pharmacophore derived from GRID molecular interaction fields were used to characterize the substrate and protein in MetaSite and the docking methodology, respectively. The CYP3A4 crystal structure and homology model with the reactivity factor enabled achieved a similar prediction success (78%) using the MetaSite method. The docking method had a relatively lower prediction success (approximately 57% for the homology model), although it still may provide useful insights for interactions between ligand and protein, especially for uncommon reactions. The MetaSite methodology is automated, rapid, and has relatively accurate predictions compared with the docking methodology used in this study.

Shape signatures: a new approach to computer-aided ligand- and receptor-based drug design.

A unifying principle of rational drug design is the use of either shape similarity or complementarity to identify compounds expected to be active against a given target. Shape similarity is the underlying foundation of ligand-based methods, which seek compounds with structure similar to known actives, while shape complementarity is the basis of most receptor-based design, where the goal is to identify compounds complementary in shape to a given receptor. These approaches can be extended to include molecular descriptors in addition to shape, such as lipophilicity or electrostatic potential. Here we introduce a new technique, which we call shape signatures, for describing the shape of ligand molecules and of receptor sites. The method uses a technique akin to ray-tracing to explore the volume enclosed by a ligand molecule, or the volume exterior to the active site of a protein. Probability distributions are derived from the ray-trace, and can be based solely on the geometry of the reflecting ray, or may include joint dependence on properties, such as the molecular electrostatic potential, computed over the surface. Our shape signatures are just these probability distributions, stored as histograms. They converge rapidly with the length of the ray-trace, are independent of molecular orientation, and can be compared quickly using simple metrics. Shape signatures can be used to test for both shape similarity between compounds and for shape complementarity between compounds and receptors and thus can be applied to problems in both ligand- and receptor-based molecular design. We present results for comparisons between small molecules of biological interest and the NCI Database using shape signatures under two different metrics. Our results show that the method can reliably extract compounds of shape (and polarity) similar to the query molecules. We also present initial results for a receptor-based strategy using shape signatures, with application to the design of new inhibitors predicted to be active against HIV protease.