Impact of Kidney Function on the Blood Proteome and on Protein Cardiovascular Risk Biomarkers in Patients With Stable Coronary Heart Disease.

Background Chronic kidney disease (CKD) confers increased cardiovascular risk, not fully explained by traditional factors. Proteins regulate biological processes and inform the risk of diseases. Thus, in 938 patients with stable coronary heart disease from the Heart and Soul cohort, we quantified 1054 plasma proteins using modified aptamers (SOMAscan) to: (1) discern how reduced glomerular filtration influences the circulating proteome, (2) learn of the importance of kidney function to the prognostic information contained in recently identified protein cardiovascular risk biomarkers, and (3) identify novel and even unique cardiovascular risk biomarkers among individuals with CKD. Methods and Results Plasma protein levels were correlated to estimated glomerular filtration rate (eGFR) using Spearman-rank correlation coefficients. Cox proportional hazard models were used to estimate the association between individual protein levels and the risk of the cardiovascular outcome (first among myocardial infarction, stroke, heart failure hospitalization, or mortality). Seven hundred and nine (67.3%) plasma proteins correlated with eGFR at P<0.05 (ρ 0.06-0.74); 218 (20.7%) proteins correlated with eGFR moderately or strongly (ρ 0.2-0.74). Among the previously identified 196 protein cardiovascular biomarkers, just 87 remained prognostic after correction for eGFR. Among patients with CKD (eGFR <60 mL/min per 1.73 m2), we identified 21 protein cardiovascular risk biomarkers of which 8 are unique to CKD. Conclusions CKD broadly alters the composition of the circulating proteome. We describe protein biomarkers capable of predicting cardiovascular risk independently of glomerular filtration, and those that are prognostic of cardiovascular risk specifically in patients with CKD and even unique to patients with CKD.

The Impact of the Glomerular Filtration Rate on the Human Plasma Proteome.

PURPOSE: The application of proteomics in chronic kidney disease (CKD) can potentially uncover biomarkers and pathways that are predictive of disease. EXPERIMENTAL DESIGN: Within this context, this study examines the relationship between the human plasma proteome and glomerular filtration rate (GFR) as measured by iohexol clearance in a cohort from Sweden (n = 389; GFR range: 8-100 mL min-1 /1.73 m2 ). A total of 2893 proteins are quantified using a modified aptamer assay. RESULTS: A large proportion of the proteome is associated with GFR, reinforcing the concept that CKD affects multiple physiological systems (individual protein-GFR correlations listed here). Of these, cystatin C shows the most significant correlation with GFR (rho = -0.85, p = 1.2 × 10-97 ), establishing strong validation for the use of this biomarker in CKD diagnostics. Among the other highly significant protein markers are insulin-like growth factor-binding protein 6, neuroblastoma suppressor of tumorigenicity 1, follistatin-related protein 3, trefoil factor 3, and beta-2 microglobulin. These proteins may indicate an imbalance in homeostasis across a variety of cellular processes, which may be underlying renal dysfunction. CONCLUSIONS AND CLINICAL RELEVANCE: Overall, this study represents the most extensive characterization of the plasma proteome and its relation to GFR to date, and suggests the diagnostic and prognostic value of proteomics for CKD across all stages.

Discovery of 7-tetrahydropyran-2-yl chromans: ß-site amyloid precursor protein cleaving enzyme 1 (BACE1) inhibitors that reduce amyloid ß-protein (Aß) in the central nervous system.

In an attempt to increase selectivity vs Cathepsin D (CatD) in our BACE1 program, a series of 1,3,4,4a,10,10a-hexahydropyrano[4,3-b]chromene analogues was developed. Three different Asp-binding moieties were examined: spirocyclic acyl guanidines, aminooxazolines, and aminothiazolines in order to modulate potency, selectivity, efflux, and permeability. Using structure-based design, substitutions to improve binding to both the S3 and S2' sites of BACE1 were explored. An acyl guanidine moiety provided the most potent analogues. These compounds demonstrated 10-420 fold selectivity for BACE1 vs CatD, and were highly potent in a cell assay measuring Aß1-40 production (5-99 nM). They also suffered from high efflux. Despite this undesirable property, two of the acyl guanidines achieved free brain concentrations (Cfree,brain) in a guinea pig PD model sufficient to cover their cell IC50s. Moreover, a significant reduction of Aß1-40 in guinea pig, rat, and cyno CSF (58%, 53%, and 63%, respectively) was observed for compound 62.

Technique for generating three-dimensional alignments of multiple ligands from one-dimensional alignments.

We describe and demonstrate a method for the simultaneous, fully flexible alignment of multiple molecules with a common biological activity. The key aspect of the algorithm is that the alignment problem is first solved in a lower dimensional space, in this case using the one-dimensional representations of the molecules. The three-dimensional alignment is then guided by constraints derived from the one-dimensional alignment. We demonstrate using 10 hERG channel blockers, with a total of 72 rotatable bonds, that the one-dimensional alignment is able to effectively isolate key conserved pharmacophoric features and that these conserved features can effectively guide the three-dimensional alignment. Further using 10 estrogen receptor agonists and 5 estrogen receptor antagonists with publicly available cocrystal structures we show that the method is able to produce superpositions comparable to those derived from crystal structures. Finally, we demonstrate, using examples from peptidic CXCR3 agonists, that the method is able to generate reasonable binding hypotheses.

Fast small molecule similarity searching with multiple alignment profiles of molecules represented in one-dimension.

Multiple sequence alignment has proven to be a powerful method for creating protein and DNA sequence alignment profiles. These profiles of protein families are useful tools for identifying conserved motifs, such as the catalytic triad of the serine protease family or the seven transmembrane helices of the G-protein coupled receptor family. Ultimately, the understanding of the critical motifs within a family is useful for identifying new members of the family. Due to the complexity of protein-ligand recognition, no universally accepted method exists for clustering small molecules into families with the same or similar biological activity. A combination of the concept of multiple sequence alignment and the 1-dimensional molecular representation described earlier offers a new method for profiling sets of small molecules with the same biological activity. These small molecule profiles can isolate key commonalities within the set of bioactive compounds much like a multiple sequence alignment can isolate critical motifs within a protein family. The small molecule profiles then make useful tools for searching small molecule databases for new compounds with the same biological activity. The technique is demonstrated here using the human ether-a-go-go potassium channel and the kinase SRC.

Elucidation of the Na+, K+-ATPase digitalis binding site.

Despite controversy over their use and the potential for toxic side effects, cardiac glycosides have remained an important clinical component for the treatment for congestive heart failure (CHF) and supraventricular arrhythmias since the effects of Digitalis purpurea were first described in 1785. While there is a wealth of information available with regard to the effects of these drugs on their pharmacological receptor, the Na(+), K(+)-ATPase, the exact molecular mechanism of digitalis binding and inhibition of the enzyme has remained elusive. In particular, the absence of structural knowledge about Na(+), K(+)-ATPase has thwarted the development of improved therapeutic agents with larger therapeutic indices via rational drug design approaches. Here, we propose a binding mode for digoxin and several analogues to the Na(+), K(+)-ATPase. A 3D-structural model of the extracellular loop regions of the catalytic alpha1-subunit of the digitalis-sensitive sheep Na(+), K(+)-ATPase was constructed from the crystal structure of an E(1)Ca(2+) conformation of the SERCA1a and a consensus orientation for digitalis binding was inferred from the in silico docking of a series of steroid-based cardiotonic compounds. Analyses of species-specific enzyme affinities for ouabain were also used to validate the model and, for the first time, propose a detailed model of the digitalis binding site.

Computational models for predicting the binding affinities of ligands for the wild-type androgen receptor and a mutated variant associated with human prostate cancer.

In the present study, values of the binding energy (BE) were calculated for the rat androgen receptor on a data set of 25 steroidal and nonsteroidal compounds for which published values of the observed binding affinity (K(i)) are available. A correlation between BE and pK(i) was evident (r(2) = 0.50) for the entire data set and became more pronounced when the steroids and nonsteroids were plotted separately (r(2) congruent with 0.76). Including BE as an additional descriptor to supplement the default steric-electrostatic descriptors in comparative molecular field analysis dramatically improved the predictive ability of the resulting three-dimensional quantitative structure-activity relationship models. We also demonstrate that the observed loss in ligand specificity between the wild-type (wt) AR and the T877A mutant AR associated with androgen-independent prostate cancer is reflected in decreased BE values (i.e., higher binding affinity) for the antiandrogen pharmaceutical hydroxyflutamide and for several nonandrogenic endogenous steroids, most notably cortisol, corticosterone, 17beta-estradiol, progesterone, and 17alpha-hydroxyprogesterone.

Interaction of organophosphate pesticides and related compounds with the androgen receptor.

Identification of several environmental chemicals capable of binding to the androgen receptor (AR) and interfering with its normal function has heightened concern about adverse effects across a broad spectrum of environmental chemicals. We previously demonstrated AR antagonist activity of the organophosphate (OP) pesticide fenitrothion. In this study, we characterized AR activity of analogues of fenitrothion to probe the structural requirements for AR activity among related chemicals. AR activity was measured using HepG2 human hepatoma cells transfected with human AR plus an androgen-responsive luciferase reporter gene, MMTV-luc. AR antagonist activity decreased as alkyl chain length of the phosphoester increased, whereas electron-donating properties of phenyl substituents of the tested compounds did not influence AR activity. Oxon derivatives of fenitrothion, which are more likely to undergo hydrolytic degradation, had no detectable AR antagonist activity. Molecular modeling results suggest that hydrogen-bond energies and the maximum achievable interatomic distance between two terminal H-bond capable sites may influence both the potential to interact with the AR and the nature of the interaction (agonist vs. antagonist) within this series of chemicals. This hypothesis is supported by the results of recent AR homology modeling and crystallographic studies relative to agonist- and antagonist-bound AR complexes. The present results are placed in the context of structure-activity knowledge derived from previous modeling studies as well as studies aimed toward designing nonsteroidal antiandrogen pharmaceuticals. Present results extend understanding of the structural requirements for AR activity to a new class of nonsteroidal, environmental, OP-related chemicals.