The role of CNP-mediated PKG/PKA-PLCβ pathway in diabetes-induced gastric motility disorder

C-type natriuretic peptide facilitates autonomic Ca2+ entry in growth plate chondrocytes for stimulating bone growth

The growth plates are cartilage tissues found at both ends of developing bones, and vital proliferation and differentiation of growth plate chondrocytes are primarily responsible for bone growth. C-type natriuretic peptide (CNP) stimulates bone growth by activating natriuretic peptide receptor 2 (NPR2) which is equipped with guanylate cyclase on the cytoplasmic side, but its signaling pathway is unclear in growth plate chondrocytes. We previously reported that transient receptor potential melastatin-like 7 (TRPM7) channels mediate intermissive Ca²⁺ influx in growth plate chondrocytes, leading to activation of Ca²⁺/calmodulin-dependent protein kinase II (CaMKII) for promoting bone growth. In this report, we provide evidence from experiments using mutant mice, indicating a functional link between CNP and TRPM7 channels. Our pharmacological data suggest that CNP-evoked NPR2 activation elevates cellular cGMP content and stimulates big-conductance Ca²⁺-dependent K⁺ (BK) channels as a substrate for cGMP-dependent protein kinase (PKG). BK channel-induced hyperpolarization likely enhances the driving force of TRPM7-mediated Ca²⁺ entry and seems to accordingly activate CaMKII. Indeed, ex vivo organ culture analysis indicates that CNP-facilitated bone growth is abolished by chondrocyte-specific Trpm7 gene ablation. The defined CNP signaling pathway, the NPR2-PKG-BK channel–TRPM7 channel–CaMKII axis, likely pinpoints promising target proteins for developing new therapeutic treatments for divergent growth disorders.

In silico systems for predicting chemical-induced side effects using known and potential chemical protein interactions, enabling mechanism estimation

In silico models for predicting chemical-induced side effects have become increasingly important for the development of pharmaceuticals and functional food products. However, existing predictive models have difficulty in estimating the mechanisms of side effects in terms of molecular targets or they do not cover the wide range of pharmacological targets. In the present study, we constructed novel in silico models to predict chemical-induced side effects and estimate the underlying mechanisms with high general versatility by integrating the comprehensive prediction of potential chemical-protein interactions (CPIs) with machine learning. First, the potential CPIs were comprehensively estimated by chemometrics based on the known CPI data (1,179,848 interactions involving 3,905 proteins and 824,143 chemicals). Second, the predictive models for 61 side effects in the cardiovascular system (CVS), gastrointestinal system (GIS), and central nervous system (CNS) were constructed by sparsity-induced classifiers based on the known and potential CPI data. The cross validation experiments showed that the proposed CPI-based models had a higher or comparable performance than the traditional chemical structure-based models. Moreover, our enrichment analysis indicated that the highly weighted proteins derived from predictive models could be involved in the corresponding functions of the side effects. For example, in CVS, the carcinogenesis-related pathways (e.g., prostate cancer, PI3K-Akt signal pathway), which were recently reported to be involved in cardiovascular side effects, were enriched. Therefore, our predictive models are biologically valid and would be useful for predicting side effects and novel potential underlying mechanisms of chemical-induced side effects.

Mechanism of CNP-mediated DG-PKC and IP4 signaling pathway in diabetic rats with gastric motility disorder

In the precedent research conducted by the same team, it concluded that the activities in C-type natriuretic peptide (CNP)/cyclic guanosine monophosphate (cGMP)/cyclic adenosine monophosphate (cAMP)/β-type phospholipase C (PLCβ) pathways of rat antral smooth muscle were changed due to diabetes, which was the key pathogenetic mechanism for diabetic gastric dysmotility. As the follow-on step, this study was designed to probe into the downstream signaling pathway of CNP/PLCβ. The results showed that level of α-type protein kinase C (PKCα),cell membrane to cytoplasm ratio of PKCα, cell membrane to cytoplasmic ratio of βI-type protein kinase C (PKCβI) and level of Phosphor-PKCα (P-PKCα) were significantly reduced in diabetes rat antral smooth muscle samples. The content of tetraphosphate inositol (IP4) in gastric antral smooth muscle of diabetic rats reduced, and the content of diacyl-glycerol (DG) was unchanged. CNP significantly decreased the content of IP4 and DG, this effect was more obvious in diabetic rats. Subsequent to the addition of protein kinase A (PKA) blocker N-[2- (p-Bromocin-namylamino)ethyl]-5 -isoquinolinesulfonamide dihydrochloride (H-89) before CNP treatment, the inhibitory effect of CNP was reduced; subsequent to the addition of protein kinase G (PKG) blocker KT5823 before CNP treatment, the inhibitory effect of CNP was also reduced. With the addition of the combination of H-89 and KT5823 before CNP treatment, the inhibition by CNP could be offset. These results were concluded that CNP inhibited the activity of PKC family in rat smooth muscle and reduced the levels of IP4 and DG through the PKG/PKA-PLCβ pathways, causing inhibited muscular contractions, which may be a key pathogenetic factor for diabetic gastroparesis.