Kv2.1 channel currents in pancreatic beta-cells are thought to contribute to action potential repolarization and thereby modulate insulin secretion. Because of its central role in this important physiological process, Kv2.1 channel is a promising target for the treatment of type 2 diabetes. Jingzhaotoxin-XI (JZTX-XI) is a novel peptide neurotoxin isolated from the venom of the spider Chilobrachys jingzhao. Two-microelectrode voltage clamp experiments had showed that the toxin inhibited Kv2.1 potassium currents expressed in Xenopus Laevis oocytes. In order to investigate the structure-function relationship of JZTX-XI, the natural toxin and a mutant of JZTX-XI in which Arg3 was replaced by Ala, were synthesized by solid-phase chemistry method with Fmoc-protected amino acids on the PS3 automated peptide synthesizer. Reverse-phase high performance liquid chromatography (RP-HPLC) and matrix assisted laser desorption/ ionization time-of-flight mass spectrometry (MALDI-TOF/TOF MS) were used to monitor the oxidative refolding process of synthetic linear peptides to find the optimal renaturation conditions of these toxins. The experiments also proved that the relative molecular masses of refolded peptides were in accordance with their theoretical molecular masses. RP-HPLC chromatogram of co-injected native and refolded JZTX-XI was a single peak. Under the whole-cell patch-clamp mode, JZTX-XI could completely inhibit hKv2.1 and hNav1.5 channels currents expressed in HEK293T cells with IC50 values of 95.8 nmol/L and 437.1 nmol/L respectively. The mutant R3A-JZTX-XI could also inhibit hKv2.1 and hNav1.5 channel currents expressed in HEK293T cells with IC50 values of 1.22 micromol/L and 1.96 micromol/L respectively. However, the prohibitive levels of R3A-JZTX-XI on hKv2.1 and hNav1.5 channels were reduced by about 12.7 times and 4.5 times respectively, indicating that Arg3 was a key amino acid residue relative to the hKv2.1 channel activity of JZTX-XI, but it is also an amino acid residue correlated with the binding activity of JZTX-XI to hNav1.5 channel. Our findings should be helpful to develop JZTX-XI into a molecular probe and drug candidate targeting to Kv2.1 potassium channel in the pancreas.
Animals ; HEK293 Cells ; Humans ; Insulin-Secreting Cells ; metabolism ; Mutant Proteins ; genetics ; pharmacology ; NAV1.5 Voltage-Gated Sodium Channel ; metabolism ; Neurotoxins ; chemical synthesis ; genetics ; pharmacology ; Protein Refolding ; Shab Potassium Channels ; antagonists & inhibitors ; metabolism ; Sodium Channel Blockers ; pharmacology ; Spider Venoms ; genetics ; pharmacology ; Transfection

Objective:We aimed to develop a novel visualized model based on nomogram to predict postoperative overall survival.Methods:This was a multicenter, retrospective, observational cohort study, including participants with histologically confirmed gastric and colorectal cancer who underwent radical surgery from 11 medical centers in China from August 1, 2015 to June 30, 2018. Baseline characteristics, histopathological data and nutritional status, as assessed using Nutrition Risk Screening 2002 (NRS 2002) score and the scored Patient-Generated Subjective Global Assessment, were collected. The least absolute shrinkage and selection operator regression and Cox regression were used to identify variables to be included in the predictive model. Internal and external validations were performed.Results:There were 681 and 127 patients in the training and validation cohorts, respectively. A total of 188 deaths were observed over a median follow-up period of 59 (range: 58 to 60) months. Two independent predictors of NRS 2002 and Tumor-Node-Metastasis (TNM) stage were identified and incorporated into the prediction nomogram model together with the factor of age. The model's concordance index for 1-, 3- and 5-year overall survival was 0.696, 0.724, and 0.738 in the training cohort and 0.801, 0.812, and 0.793 in the validation cohort, respectively.Conclusions:In this study, a new nomogram prediction model based on NRS 2002 score was developed and validated for predicting the overall postoperative survival of patients with gastric colorectal cancer. This model has good differentiation, calibration and clinical practicability in predicting the long-term survival rate of patients with gastrointestinal cancer after radical surgery.