Project description:Historically synemin has been studied as an intermediate filament protein. However, synemin also binds the type II regulatory (R) subunit ? of protein kinase A (PKA) and protein phosphatase type 2A, thus participating in the PKA and phosphoinositide 3-kinase (PI3K)-Akt and signaling pathways. In addition, recent studies using transgenic mice indicate that a significant function of synemin is its role in signaling pathways in various tissues, including the heart. Recent clinical reports have shown that synemin mutations led to multiple cases of dilated cardiomyopathy. Additionally, a single case of the rare condition ulnar-mammary-like syndrome with left ventricular tachycardia due to a mutation in the synemin gene (SYNM) has been reported. Therefore, this review uses these recent studies to provide a new framework for detailed discussions on synemin tissue distribution, binding partners and synemin in disease. Differences between ?- and ?-synemin are highlighted. The studies presented here indicate that while synemin does function as an intermediate filament protein, it is unique among this large family of proteins as it is also a regulator of signaling pathways and a crosslinker. Also evident is that the dominant function(s) are isoform-, developmental-, and tissue-specific.
Project description:BackgroundEffect-size underestimation impedes biomarker identification. Long follow-up time in prospective studies attenuates effect-size estimates for transient biomarkers, while disease category-specific biomarkers are affected by merging of categories. Venous thromboembolism (VTE) encompasses deep vein thrombosis (DVT) and pulmonary embolism (PE).Objectives(i) To re-analyze untargeted proteomic data to identify biomarker candidates for future VTE that differ between DVT and PE and are attenuated by extended time between sampling and VTE. (ii) To perform targeted candidate validation.Patients/methodsA VTE case-control discovery study and a nested case-control validation study were derived from the general population surveyed in 1994-95. Plasma was obtained at study enrollment, and VTE events were registered until 2007. Untargeted proteomic data were re-analyzed for candidate discovery. Lipopolysaccharide-binding protein (LBP) was validated by enzyme-linked immunosorbent assay.ResultsElevated LBP was discovered as a candidate DVT biomarker in women with less than 3 years between blood sampling and DVT. In the validation study, the odds ratio (OR) for DVT was 2.03 (95% confidence intervals [CI]: 1.53-2.74) per standard deviation (SD) increase in LBP for women with less than 3 years between blood sampling and DVT. Adjustment for age, body mass index, and C-reactive protein attenuated the OR to 1.79 (95% CI: 1.25-2.62) per SD. In the validation study, we observed an OR for VTE of 0.47 (95% CI: 0.28-0.77) for men in the 25th to 50th percentiles when compared to the lowest quartile.ConclusionsWe discovered and validated increased LBP as a predictive biomarker for DVT in women. We found an increased VTE risk for men in the lowest quartile of LBP.
Project description:High-throughput screening (HTS) of large compound libraries has become a commonly used method for the identification of drug leads, and nonphysiological reducing agents have been widely used for HTS. However, a comparison of the difference in the HTS results based on the choice of reducing agent used and potency comparisons of selected inhibitors has not been done with the physiological reducing agent reduced glutathione (GSH). Here, we compared the effects of three reducing agents-dithiothreitol (DTT), β-mercaptoethanol (β-MCE), and tris(2-carboxyethyl)phosphine (TCEP)-as well as GSH against three drug target proteins. Approximately 100,000 compounds were computationally screened for each target protein, and experimental testing of high-scoring compounds (~560 compounds) with the four reducing agents surprisingly produced many nonoverlapping hits. More importantly, we found that various reducing agents altered inhibitor potency (IC(50)) from approximately 10 μM with one reducing agent to complete loss (IC(50)>200 μM) of inhibitory activity with another reducing agent. Therefore, the choice of reducing agent in an HTS is critical because this may lead to the pursuit of falsely identified active compounds or failure to identify the true active compounds. We demonstrate the feasibility of using GSH for in vitro HTS assays with these three target enzymes.
Project description:ObjectivesDalbavancin is a lipoglycopeptide with a long half-life, making it a promising treatment for infections requiring prolonged therapy, such as complicated Staphylococcus aureus bacteraemia. Free drug concentration is a critical consideration with prolonged treatment, since free concentration-time profiles may best correlate with therapeutic effect. In support of future clinical trials, we aimed to develop a reliable and reproducible assay for measuring free dalbavancin concentrations.MethodsThe ultracentrifugation technique was used to determine free dalbavancin concentrations in plasma at two concentrations (50 and 200 mg/L) in duplicate. Centrifuge tubes and pipette tips were treated for 24 h before use with Tween 80 to assess adsorption. Dalbavancin concentrations were analysed from the plasma samples (total) and middle layer samples (free) by LC/MS/MS with isotopically labelled internal standard. Warfarin served as a positive control with known high protein binding.ResultsMeasurement of free dalbavancin was sensitive to adsorption onto plastic. Treatment of tubes and pipette tips with ≥2% Tween 80 effectively prevented drug loss during protein binding experiments. By the ultracentrifugation method, dalbavancin's protein binding was estimated to be approximately 99%.ConclusionsDalbavancin has very high protein binding. Given dalbavancin's high protein binding, accurate measurement of free dalbavancin concentrations should be a key consideration in future exposure-response studies, especially clinical trials. Future investigations should confirm if the active fraction is best predicted by the free or total fraction.
Project description:We developed a method called residue contact frequency (RCF), which uses the complex structures generated by the protein-protein docking algorithm ZDOCK to predict interface residues. Unlike interface prediction algorithms that are based on monomers alone, RCF is binding partner specific. We evaluated the performance of RCF using the area under the precision-recall (PR) curve (AUC) on a large protein docking Benchmark. RCF (AUC = 0.44) performed as well as meta-PPISP (AUC = 0.43), which is one of the best monomer-based interface prediction methods. In addition, we test a support vector machine (SVM) to combine RCF with meta-PPISP and another monomer-based interface prediction algorithm Evolutionary Trace to further improve the performance. We found that the SVM that combined RCF and meta-PPISP achieved the best performance (AUC = 0.47). We used RCF to predict the binding interfaces of proteins that can bind to multiple partners and RCF was able to correctly predict interface residues that are unique for the respective binding partners. Furthermore, we found that residues that contributed greatly to binding affinity (hotspot residues) had significantly higher RCF than other residues.
Project description:Accurate ligand-protein binding affinity prediction, for a set of similar binders, is a major challenge in the lead optimization stage in drug development. In general, docking and scoring functions perform unsatisfactorily in this application. Docking calculations, followed by molecular dynamics simulations and free energy calculations can be applied to improve the predictions. However, for targets with large, flexible binding sites, with no experimentally determined binding modes for a set of ligands, insufficient sampling can decrease the accuracy of the free energy calculations. Cytochrome P450s, a protein family of major importance for drug metabolism, is an example of a challenging target for binding affinity predictions. As a result, the choice of starting structure from the docking solutions becomes crucial. In this study, an iterative scheme is introduced that includes multiple independent molecular dynamics simulations to obtain weighted ensemble averages to be used in the linear interaction energy method. The proposed scheme makes the initial pose selection less crucial for further simulation, as it automatically calculates the relative weights of the various poses. It also properly takes into account the possibility that multiple binding modes contribute similarly to the overall affinity, or of similar compounds occupying very different poses. The method was applied to a set of 12 compounds binding to cytochrome P450 2C9 and it displayed a root mean-square error of 2.9 kJ/mol.
Project description:Density function theory (DFT) calculations have been carried out to investigate the binding of alcohols to the odorant binding protein LUSH from Drosophila melanogaster. LUSH is one of the few proteins known to bind to ethanol at physiologically relevant concentrations and where high-resolution structural information is available for the protein bound to alcohol at these concentrations. The structures of the LUSH-alcohol complexes identify a set of specific hydrogen-bonding interactions as critical for optimal binding of ethanol. A set of truncated models based on the structure of the LUSH-butanol complex were constructed for the wild-type and mutant (T57S, S52A, and T57A) proteins in complexes with a series of n-alcohols and for the apoprotein bound to water and for the ligand-free protein. Using both gas-phase calculations and continuum solvation model calculations, we found that the widely used DFT model, B3LYP, failed to reproduce the experimentally observed trend of increasing binding affinity with the increasing length of the alkyl chain in the alcohol. In contrast, the recently developed M05-2X DFT model successfully reproduced this subtle trend. Analysis of the results indicated that multiple factors contribute to the differences in alcohol binding affinity: the H-bonding with Thr57 and Ser52 (4-5 kcal/mol per H-bond), the desolvation contribution (4-6 kcal/mol for alcohols and 8-10 kcal/mol for water), and the other noncovalent interaction (1.2 kcal/mol per CH(2) group of the alcohol alkyl chain). These results reveal the outstanding potential for using the M05-2X model in calculations of protein-substrate complexes where noncovalent interactions are important.
Project description:Oxysterol-binding Protein (OSBP) is a human lipid-transport protein required for the cellular replication of many types of viruses, including several human pathogens. The structurally-diverse small molecule compounds OSW-1, itraconazole (ITZ), T-00127-HEV2 (THEV) and TTP-8307 (TTP) inhibit viral replication through interaction with the OSBP protein. The OSW-1 compound reduces intracellular OSBP, and the reduction of OSBP protein levels persists multiple days after the OSW-1-compound treatment is stopped. The OSW-1-induced reduction of OSBP levels inhibited Enterovirus replication prophylactically in cells. In this report, the OSBP-interacting compounds ITZ, THEV, and TTP are shown not to reduce OSBP levels in cells, unlike the OSW-1-compound, and the OSW-1 compound is determined to be the only compound capable of providing prophylactic antiviral activity in cells. Furthermore, OSW-1 and THEV inhibit the binding of 25-hydroxycholesterol (25-OHC) to OSBP indicating that these compounds bind at the conserved sterol ligand binding site. The ITZ and TTP compounds do not inhibit 25-hydroxycholesterol binding to OSBP, and therefore ITZ and TTP interact with OSBP through other, unidentified binding sites. Co-administration of the THEV compound partially blocks the cellular activity of OSW-1, including the reduction of cellular OSBP protein levels; co-administration of the ITZ and TTP compounds have minimal effect on OSW-1 cellular activity further supporting different modes of interaction with these compounds to OSBP. OSW-1, ITZ, THEV, and TTP treatment alter OSBP cellular localization and levels, but in four distinct ways. Co-administration of OSW-1 and ITZ induced OSBP cellular localization patterns with features similar to the effects of ITZ and OSW-1 treatment alone. Based on these results, OSBP is capable of interacting with multiple structural classes of antiviral small molecule compounds at different binding sites, and the different compounds have distinct effects on OSBP cellular activity.