Modeling ATP-Binding Cassette G2 (ABCG2) Substrate Specificity

How well can we predict efflux by ATP-binding cassette G2? It is estimated that there will be about 1.6 million new cases of cancer and half a million cancer deaths in the US during 2015.ATP-binding cassette (ABC) efflux transporters such as ABCG2 are overexpressed in chemotherapy-resistant cancer cells. Anticancer drugs are prone to efflux by these transporters. Being able to identify drugs that are effluxed is of great interest in drug discovery.The current arsenal of methods used to detect efflux are not easily adaptable to high throughput formats and are limited in scope, making experimental analysis an expensive prospect. Hence, computational analysis of efflux is of interest. We accumulated a dataset of ABCG2 substrates and non-substrates which contains 179 substrates and 110 non-substrates. This dataset forms the basis for all studies reported herein. We attempted to identify descriptors capable of segregating substrates and non-substrates, ending up with Log P, Polar Volume, Atom Count, Radius of Gyration, Binding Energy, Length, and Width. They had significant differential distribution that could be used to build mathematical models to fulfil our goals. A statistical learning method that creates non-linear models called Support Vector Machine generated the best predictive models. This model demonstrated between 75-80% accuracy in identifying substrates and non-substrates. Importantly our model suggests mechanistic details of the efflux process; previous reports have suggested that Arg482 in ABCG2 is critical for transport of substrates. In conclusion, we were able to address efflux of chemotherapeutic agents by the ABCG2 efflux pump using a mathematical modeling approach.https://scholarscompass.vcu.edu/uresposters/1130/thumbnail.jp

On the Specificity of Heparin/Heparan Sulfate Binding to Proteins. Anion-Binding Sites on Antithrombin and Thrombin Are Fundamentally Different

Background The antithrombin–heparin/heparan sulfate (H/HS) and thrombin–H/HS interactions are recognized as prototypic specific and non-specific glycosaminoglycan (GAG)–protein interactions, respectively. The fundamental structural basis for the origin of specificity, or lack thereof, in these interactions remains unclear. The availability of multiple co-crystal structures facilitates a structural analysis that challenges the long-held belief that the GAG binding sites in antithrombin and thrombin are essentially similar with high solvent exposure and shallow surface characteristics. Methodology Analyses of solvent accessibility and exposed surface areas, gyrational mobility, symmetry, cavity shape/size, conserved water molecules and crystallographic parameters were performed for 12 X-ray structures, which include 12 thrombin and 16 antithrombin chains. Novel calculations are described for gyrational mobility and prediction of water loci and conservation. Results The solvent accessibilities and gyrational mobilities of arginines and lysines in the binding sites of the two proteins reveal sharp contrasts. The distribution of positive charges shows considerable asymmetry in antithrombin, but substantial symmetry for thrombin. Cavity analyses suggest the presence of a reasonably sized bifurcated cavity in antithrombin that facilitates a firm ‘hand-shake’ with H/HS, but with thrombin, a weaker ‘high-five’. Tightly bound water molecules were predicted to be localized in the pentasaccharide binding pocket of antithrombin, but absent in thrombin. Together, these differences in the binding sites explain the major H/HS recognition characteristics of the two prototypic proteins, thus affording an explanation of the specificity of binding. This provides a foundation for understanding specificity of interaction at an atomic level, which will greatly aid the design of natural or synthetic H/HS sequences that target proteins in a specific manner

Identification of Small-Molecule Inhibitors against Meso-2, 6-Diaminopimelate Dehydrogenase from Porphyromonas gingivalis

Species-specific antimicrobial therapy has the potential to combat the increasing threat of antibiotic resistance and alteration of the human microbiome. We therefore set out to demonstrate the beginning of a pathogen-selective drug discovery method using the periodontal pathogen Porphyromonas gingivalis as a model. Through our knowledge of metabolic networks and essential genes we identified a “druggable” essential target, meso-diaminopimelate dehydrogenase, which is found in a limited number of species. We adopted a high-throughput virtual screen method on the ZINC chemical library to select a group of potential small-molecule inhibitors. Meso-diaminopimelate dehydrogenase from P. gingivaliswas first expressed and purified in Escherichia coli then characterized for enzymatic inhibitor screening studies. Several inhibitors with similar structural scaffolds containing a sulfonamide core and aromatic substituents showed dose-dependent inhibition. These compounds were further assayed showing reasonable whole-cell activity and the inhibition mechanism was determined. We conclude that the establishment of this target and screening strategy provides a model for the future development of new antimicrobials

Global Diversification, Industrial Diversification, and Firm Value

Using a sample of 27,287 firm-years over the period of 1983-1993 we document an increasing trend in both the incidence and level of global diversification over time. This trend does not, however, reflect a substitution of global for industrial diversification. Global diversification results in average valuation discounts of the same magnitude as those for industrial diversification. Analysis of the changes in excess value associated with changes in diversification status reveals that increases in global diversification reduce excess value, while reductions in global diversification increase excess value

HINT, a code for understanding the interaction between biomolecules: a tribute to Donald J. Abraham

A long-lasting goal of computational biochemists, medicinal chemists, and structural biologists has been the development of tools capable of deciphering the molecule–molecule interaction code that produces a rich variety of complex biomolecular assemblies comprised of the many different simple and biological molecules of life: water, small metabolites, cofactors, substrates, proteins, DNAs, and RNAs. Software applications that can mimic the interactions amongst all of these species, taking account of the laws of thermodynamics, would help gain information for understanding qualitatively and quantitatively key determinants contributing to the energetics of the bimolecular recognition process. This, in turn, would allow the design of novel compounds that might bind at the intermolecular interface by either preventing or reinforcing the recognition. HINT, hydropathic interaction, was a model and software code developed from a deceptively simple idea of Donald Abraham with the close collaboration with Glen Kellogg at Virginia Commonwealth University. HINT is based on a function that scores atom–atom interaction using LogP, the partition coefficient of any molecule between two phases; here, the solvents are water that mimics the cytoplasm milieu and octanol that mimics the protein internal hydropathic environment. This review summarizes the results of the extensive and successful collaboration between Abraham and Kellogg at VCU and the group at the University of Parma for testing HINT in a variety of different biomolecular interactions, from proteins with ligands to proteins with DNA

Biological Characterization of 3-(2-amino-ethyl)-5-[3-(4-butoxyl-phenyl)-propylidene]-thiazolidine-2,4-dione (K145) as a Selective Sphingosine Kinase-2 Inhibitor and Anticancer Agent

In our effort to develop selective sphingosine kinase-2 (SphK2) inhibitors as pharmacological tools, a thiazolidine-2,4-dione analogue, 3-(2-amino-ethyl)-5-[3-(4-butoxyl-phenyl)-propylidene]-thiazolidine-2,4-dione(K145), was synthesized and biologically characterized. Biochemical assay results indicate that K145 is a selective SphK2 inhibitor. Molecular modeling studies also support this notion. In vitro studies using human leukemia U937 cells demonstrated that K145 accumulates in U937 cells, suppresses the S1P level, and inhibits SphK2. K145 also exhibited inhibitory effects on the growth of U937 cells as well as apoptotic effects in U937 cells, and that these effects may be through the inhibition of down-stream ERK and Akt signaling pathways. K145 also significantly inhibited the growth of U937 tumors in nude mice by both intraperitoneal and oral administration, thus demonstrating its in vivo efficacy as a potential lead anticancer agent. The antitumor activity of K145 was also confirmed in a syngeneic mouse model by implanting murine breast cancer JC cells in BALB/c mice. Collectively, these results strongly encourage further optimization of K145 as a novel lead compound for development of more potent and selective SphK2 inhibitors

Synthesis, structure–affinity relationships, and modeling of AMDA analogs at 5-HT2A and H1 receptors: Structural factors contributing to selectivity

Histamine H1 and serotonin 5-HT2A receptors present in the CNS have been implicated in various neuropsychiatric disorders. 9-Aminomethyl-9,10-dihydroanthracene (AMDA), a conformationally constrained diarylalkyl amine derivative, has affinity for both of these receptors. A structure-affinity relationship (SAFIR) study was carried out studying the effects of N-methylation, varying the linker chain length and constraint of the aromatic rings on the binding affinities of the compounds with the 5-HT2A and H1 receptors. Homology modeling of the 5-HT2A and H1 receptors suggests that AMDA and its analogs, the parent of which is a 5-HT2A antagonist, can bind in a fashion analogous to that of classical H1 antagonists whose ring systems are oriented towards the fifth and sixth transmembrane helices. The modeled orientation of the ligands are consistent with the reported site-directed mutagenesis data for 5-HT2A and H1 receptors and provide a potential explanation for the selectivity of ligands acting at both receptors

Biological Characterization of an Improved Pyrrole-Based Colchicine Site Agent Identified through Structure-Based Design s

ABSTRACT A refined model of the colchicine site on tubulin was used to design an improved analog of the pyrrole parent compound, JG-03-14. The optimized compound, NT-7-16, was evaluated in biological assays that confirm that it has potent activities as a new colchicine site microtubule depolymerizer. NT-7-16 exhibits antiproliferative and cytotoxic activities against multiple cancer cell lines, with IC 50 values of 10-16 nM, and it is able to overcome drug resistance mediated by the expression of P-glycoprotein and the bIII isotype of tubulin. NT-7-16 initiated the concentration-dependent loss of cellular microtubules and caused the formation of abnormal mitotic spindles, leading to mitotic accumulation. The direct interaction of NT-7-16 with purified tubulin was confirmed, and it was more potent than combretastatin A-4 in these assays. Binding studies verified that NT-7-16 binds to tubulin within the colchicine site. The antitumor effects of NT-7-16 were evaluated in an MDA-MB-435 xenograft model and it had excellent activity at concentrations that were not toxic. A second compound, NT-9-21, which contains dichloro moieties in place of the 3,5-dibromo substituents of NT-7-16, had a poorer fit within the colchicine site as predicted by modeling and the Hydropathic INTeractions score. Biological evaluations showed that NT-9-21 has 10-fold lower potency than NT-7-16, confirming the modeling predictions. These studies highlight the value of the refined colchicine-site model and identify a new pyrrole-based colchicine-site agent with potent in vitro activities and promising in vivo antitumor actions

Applying an Empirical Hydropathic Forcefield in Refinement May Improve Low-Resolution Protein X-Ray Crystal Structures

BACKGROUND: The quality of X-ray crystallographic models for biomacromolecules refined from data obtained at high-resolution is assured by the data itself. However, at low-resolution, >3.0 Å, additional information is supplied by a forcefield coupled with an associated refinement protocol. These resulting structures are often of lower quality and thus unsuitable for downstream activities like structure-based drug discovery. METHODOLOGY: An X-ray crystallography refinement protocol that enhances standard methodology by incorporating energy terms from the HINT (Hydropathic INTeractions) empirical forcefield is described. This protocol was tested by refining synthetic low-resolution structural data derived from 25 diverse high-resolution structures, and referencing the resulting models to these structures. The models were also evaluated with global structural quality metrics, e.g., Ramachandran score and MolProbity clashscore. Three additional structures, for which only low-resolution data are available, were also re-refined with this methodology. RESULTS: The enhanced refinement protocol is most beneficial for reflection data at resolutions of 3.0 Å or worse. At the low-resolution limit, ≥4.0 Å, the new protocol generated models with Cα positions that have RMSDs that are 0.18 Å more similar to the reference high-resolution structure, Ramachandran scores improved by 13%, and clashscores improved by 51%, all in comparison to models generated with the standard refinement protocol. The hydropathic forcefield terms are at least as effective as Coulombic electrostatic terms in maintaining polar interaction networks, and significantly more effective in maintaining hydrophobic networks, as synthetic resolution is decremented. Even at resolutions ≥4.0 Å, these latter networks are generally native-like, as measured with a hydropathic interactions scoring tool

Bound Water at Protein-Protein Interfaces: Partners, Roles and Hydrophobic Bubbles as a Conserved Motif

Background There is a great interest in understanding and exploiting protein-protein associations as new routes for treating human disease. However, these associations are difficult to structurally characterize or model although the number of X-ray structures for protein-protein complexes is expanding. One feature of these complexes that has received little attention is the role of water molecules in the interfacial region. Methodology A data set of 4741 water molecules abstracted from 179 high-resolution (≤ 2.30 Å) X-ray crystal structures of protein-protein complexes was analyzed with a suite of modeling tools based on the HINT forcefield and hydrogen-bonding geometry. A metric termed Relevance was used to classify the general roles of the water molecules. Results The water molecules were found to be involved in: a) (bridging) interactions with both proteins (21%), b) favorable interactions with only one protein (53%), and c) no interactions with either protein (26%). This trend is shown to be independent of the crystallographic resolution. Interactions with residue backbones are consistent for all classes and account for 21.5% of all interactions. Interactions with polar residues are significantly more common for the first group and interactions with non-polar residues dominate the last group. Waters interacting with both proteins stabilize on average the proteins\u27 interaction (−0.46 kcal mol−1), but the overall average contribution of a single water to the protein-protein interaction energy is unfavorable (+0.03 kcal mol−1). Analysis of the waters without favorable interactions with either protein suggests that this is a conserved phenomenon: 42% of these waters have SASA ≤ 10 Å2 and are thus largely buried, and 69% of these are within predominantly hydrophobic environments or “hydrophobic bubbles”. Such water molecules may have an important biological purpose in mediating protein-protein interactions