Isozyme-nonselective N-substituted bipiperidylcarboxamide acetyl-CoA carboxylase inhibitors reduce tissue malonyl-CoA concentrations,inhibit fatty acid synthesis,and increase fatty acid oxidation in cultured cells and in experimental animals

Inhibition of acetyl-CoA carboxylase (ACC), with its resultant inhibition of fatty acid synthesis and stimulation of fatty acid oxidation, has the potential to favorably affect the multitude of cardiovascular risk factors associated with the metabolic syndrome. To achieve maximal effectiveness, an ACC inhibitor should inhibit both the lipogenic tissue isozyme (ACC1) and the oxidative tissue isozyme (ACC2). Herein, we describe the biochemical and acute physiological properties of CP-610431, an isozyme-nonselective ACC inhibitor identified through high throughput inhibition screening, and CP-640186, an analog with improved metabolic stability. CP-610431 inhibited ACC1 and ACC2 with IC50s of approximately 50 nm. Inhibition was reversible, uncompetitive with respect to ATP, and non-competitive with respect to bicarbonate, acetyl-CoA, and citrate, indicating interaction with the enzymatic carboxyl transfer reaction. CP-610431 also inhibited fatty acid synthesis, triglyceride (TG) synthesis, TG secretion, and apolipoprotein B secretion in HepG2 cells (ACC1) with EC50s of 1.6, 1.8, 3.0, and 5.7 microm, without affecting either cholesterol synthesis or apolipoprotein CIII secretion. CP-640186, also inhibited both isozymes with IC50sof approximately 55 nm but was 2-3 times more potent than CP-610431 in inhibiting HepG2 cell fatty acid and TG synthesis. CP-640186 also stimulated fatty acid oxidation in C2C12 cells (ACC2) and in rat epitrochlearis muscle strips with EC50s of 57 nm and 1.3 microm. In rats, CP-640186 lowered hepatic, soleus muscle, quadriceps muscle, and cardiac muscle malonyl-CoA with ED50s of 55, 6, 15, and 8 mg/kg. Consequently, CP-640186 inhibited fatty acid synthesis in rats, CD1 mice, and ob/ob mice with ED50s of 13, 11, and 4 mg/kg, and stimulated rat whole body fatty acid oxidation with an ED50 of approximately 30 mg/kg. Taken together, These observations indicate that isozyme-nonselective ACC inhibition has the potential to favorably affect risk factors associated with the metabolic syndrome.     

Adenylate kinase AK1 knockout heart: energetics and functional performance under ischemia-reperfusion

Deletion of the major adenylate kinase AK1 isoform, which catalyzes adenine nucleotide exchange, disrupts cellular energetic economy and compromises metabolic signal transduction. However, the consequences of deleting the AK1 gene on cardiac energetic dynamics and performance in the setting of ischemia-reperfusion have not been determined. Here, at the onset of ischemia, AK1 knockout mice hearts displayed accelerated loss of contractile force compared with wild-type controls, indicating reduced tolerance to ischemic stress. On reperfusion, AK1 knockout hearts demonstrated reduced nucleotide salvage, resulting in lower ATP, GTP, ADP, and GDP levels and an altered metabolic steady state associated with diminished ATP-to-P(i) and creatine phosphate-to-P(i) ratios. Postischemic AK1 knockout hearts maintained approximately 40% of beta-phosphoryl turnover, suggesting increased phosphotransfer flux through remaining adenylate kinase isoforms. This was associated with sustained creatine kinase flux and elevated cellular glucose-6-phosphate levels as the cellular energetic system adapted to deletion of AK1. Such metabolic rearrangements, along with sustained ATP-to-ADP ratio and total ATP turnover rate, maintained postischemic contractile recovery of AK1 knockout hearts at wild-type levels. Thus deletion of the AK1 gene reveals that adenylate kinase phosphotransfer supports myocardial function on initiation of ischemic stress and safeguards intracellular nucleotide pools in postischemic recovery.     

Improved perfusion after subcritical ischemia in muscle flaps treated with vascular endothelial growth factor

Vascular endothelial growth factor (VEGF), a potent endothelial mitogen, is secreted in ischemic tissue and plays a pivotal role in angiogenesis. We studied whether VEGF administered to a rat muscle flap at the time of ischemia induction would increase microcirculatory flow to the flap. The cremaster muscle flap was isolated on its neurovascular pedicle. Ischemia was induced by clamping the vascular pedicle, and 0.2 ml of either VEGF (0.1 microg) or vehicle (phosphate-buffered saline) was immediately infused into the muscle. After 4 or 6 hours, the clamps were released, and the cremaster was placed in a pocket in the medial thigh for 24 hours. The muscle was then dissected, and microcirculatory measurements were made under intravital microscopy. Six animals were used in each of the four groups. All flaps exposed to 6 hours of ischemia, the duration considered to be critical ischemia, had no significant microcirculatory flow, regardless of treatment with VEGF. In the 4-hour ischemia group, or subcritical ischemia group, red blood cell velocity in arterioles was 14 mm/sec in muscles treated with VEGF and 9 mm/sec in controls (p = 0.02), and capillary flow was 7 per high-power field in muscles treated with VEGF versus 2 per high-power field in controls (p = 0.0005). Thus, VEGF did not alter microcirculatory flow in a muscle flap exposed to critical ischemia, but it did enhance flow to a flap exposed to subcritical ischemia.     

Gene ontology improves template selection in comparative protein docking

Structural characterization of protein-protein interactions is essential for our ability to study life processes at the molecular level. Computational modeling of protein complexes (protein docking) is important as the source of their structure and as a way to understand the principles of protein interaction. Rapidly evolving comparative docking approaches utilize target/template similarity metrics, which are often based on the protein structure. Although the structural similarity, generally, yields good performance, other characteristics of the interacting proteins (eg, function, biological process, and localization) may improve the prediction quality, especially in the case of weak target/template structural similarity. For the ranking of a pool of models for each target, we tested scoring functions that quantify similarity of Gene Ontology (GO) terms assigned to target and template proteins in three ontology domains—biological process, molecular function, and cellular component (GO-score). The scoring functions were tested in docking of bound, unbound, and modeled proteins. The results indicate that the combined structural and GO-terms functions improve the scoring, especially in the twilight zone of structural similarity, typical for protein models of limited accuracy.     

Protein models docking benchmark 2

Structural characterization of protein–protein interactions is essential for our ability to understand life processes. However, only a fraction of known proteins have experimentally determined structures. Such structures provide templates for modeling of a large part of the proteome, where individual proteins can be docked by template‐free or template‐based techniques. Still, the sensitivity of the docking methods to the inherent inaccuracies of protein models, as opposed to the experimentally determined high‐resolution structures, remains largely untested, primarily due to the absence of appropriate benchmark set(s). Structures in such a set should have predefined inaccuracy levels and, at the same time, resemble actual protein models in terms of structural motifs/packing. The set should also be large enough to ensure statistical reliability of the benchmarking results. We present a major update of the previously developed benchmark set of protein models. For each interactor, six models were generated with the model‐to‐native C^α RMSD in the 1 to 6 Å range. The models in the set were generated by a new approach, which corresponds to the actual modeling of new protein structures in the “real case scenario,” as opposed to the previous set, where a significant number of structures were model‐like only. In addition, the larger number of complexes (165 vs. 63 in the previous set) increases the statistical reliability of the benchmarking. We estimated the highest accuracy of the predicted complexes (according to CAPRI criteria), which can be attained using the benchmark structures. The set is available at http://dockground.bioinformatics.ku.edu . Proteins 2015; 83:891–897. © 2015 Wiley Periodicals, Inc.     

Text Mining for Protein Docking

The rapidly growing amount of publicly available information from biomedical research is readily accessible on the Internet, providing a powerful resource for predictive biomolecular modeling. The accumulated data on experimentally determined structures transformed structure prediction of proteins and protein complexes. Instead of exploring the enormous search space, predictive tools can simply proceed to the solution based on similarity to the existing, previously determined structures. A similar major paradigm shift is emerging due to the rapidly expanding amount of information, other than experimentally determined structures, which still can be used as constraints in biomolecular structure prediction. Automated text mining has been widely used in recreating protein interaction networks, as well as in detecting small ligand binding sites on protein structures. Combining and expanding these two well-developed areas of research, we applied the text mining to structural modeling of protein-protein complexes (protein docking). Protein docking can be significantly improved when constraints on the docking mode are available. We developed a procedure that retrieves published abstracts on a specific protein-protein interaction and extracts information relevant to docking. The procedure was assessed on protein complexes from Dockground (http://dockground.compbio.ku.edu). The results show that correct information on binding residues can be extracted for about half of the complexes. The amount of irrelevant information was reduced by conceptual analysis of a subset of the retrieved abstracts, based on the bag-of-words (features) approach. Support Vector Machine models were trained and validated on the subset. The remaining abstracts were filtered by the best-performing models, which decreased the irrelevant information for ~ 25% complexes in the dataset. The extracted constraints were incorporated in the docking protocol and tested on the Dockground unbound benchmark set, significantly increasing the docking success rate.     

Nucleotide-gated KATP channels integrated with creatine and adenylate kinases: Amplification,tuning and sensing of energetic signals in the compartmentalized cellular environment

Transmission of energetic signals to membrane sensors, such as the ATP-sensitive K+ (KATP) channel, is vital for cellular adaptation to stress. Yet, cell compartmentation implies diffusional hindrances that hamper direct reception of cytosolic energetic signals. With high intracellular ATP levels, KATP channels may sense not bulk cytosolic, but rather local submembrane nucleotide concentrations set by membrane ATPases and phosphotransfer enzymes. Here, we analyzed the role of adenylate kinase and creatine kinase phosphotransfer reactions in energetic signal transmission over the strong diffusional barrier in the submembrane compartment, and translation of such signals into a nucleotide response detectable by KATP channels. Facilitated diffusion provided by creatine kinase and adenylate kinase phosphotransfer dissipated nucleotide gradients imposed by membrane ATPases, and shunted diffusional restrictions. Energetic signals, simulated as deviation of bulk ATP from its basal level, were amplified into an augmented nucleotide response in the submembrane space due to failure under stress of creatine kinase to facilitate nucleotide diffusion. Tuning of creatine kinase-dependent amplification of the nucleotide response was provided by adenylate kinase capable of adjusting the ATP/ADP ratio in the submembrane compartment securing adequate KATP channel response in accord with cellular metabolic demand. Thus, complementation between creatine kinase and adenylate kinase systems, here predicted by modeling and further supported experimentally, provides a mechanistic basis for metabolic sensor function governed by alterations in intracellular phosphotransfer fluxes.     

Dual-action hypoglycemic and hypocholesterolemic agents that inhibit glycogen phosphorylase and lanosterol demethylase

Diabetic dyslipidemia requires simultaneous treatment with hypoglycemic agents and lipid-modulating drugs. We recently described glycogen phosphorylase inhibitors that reduce glycogenolysis in cells and lower plasma glucose in ob/ob mice (J. Med. Chem., 41: 2934, 1998). In evaluating the series prototype, CP-320626, in dogs, up to 90% reduction in plasma cholesterol was noted after 2 week treatment. Cholesterol reductions were also noted in ob/ob mice and in rats. In HepG2 cells, CP-320626 acutely and dose-dependently inhibited cholesterolgenesis without affecting fatty acid synthesis. Inhibition occurred together with a dose-dependent increase in the cholesterol precursor, lanosterol, suggesting that cholesterolgenesis inhibition was due to lanosterol 14alpha-demethylase (CYP51) inhibition. In ob/ob mice, acute treatment with CP-320626 resulted in a decrease in hepatic cholesterolgenesis with concomitant lanosterol accumulation, further implicating CYP51 inhibition as the mechanism of cholesterol lowering in these animals. CP-320626 and analogs directly inhibited rhCYP51, and this inhibition was highly correlated with HepG2 cell cholesterolgenesis inhibition (R2 = 0.77). These observations indicate that CP-320626 inhibits cholesterolgenesis via direct inhibition of CYP51, and that this is the mechanism whereby CP-320626 lowers plasma cholesterol in experimental animals. Dual-action glycogenolysis and cholesterolgenesis inhibitors therefore have the potential to favorably affect both the hyperglycemia and the dyslipidemia of type 2 diabetes.