Design and characterization of electroactive gelatin methacrylate hydrogel incorporated with gold nanoparticles empowered with parahydroxybenzaldehyde and curcumin for advanced tissue engineering applications.

Electroconductive polymers are the materials of interest for the fabrication of electro-conductive tissues. Metal ions through the redox systems offer polymers with electrical conductivity. In this study, we processed a gelatin methacrylate (GelMA) network with gold nanoparticles (GNPs) through a redox system with parahydroxybenzaldehyde (PHB) or curcumin to enhance its electrical conductivity. Induction of the redox system with both PHB and curcumin into the GelMA, introduced some new functional groups into the polymeric network, as it has been confirmed by H-NMR and FTIR. These new bonds resulted in higher electro-conductivity when GNPs were added to the polymer. Higher electroactivity was achieved by PHB compared to the curcumin-induced redox system, and the addition of GNPs without redox system induction showed the lowest electroactivity. MTT was used to evaluate the biocompatibility of the resultant polymers, and the PHB-treated hydrogels showed higher proliferative effects on the cells. The findings of this study suggest that the introduction of a redox system by PHB in the GelMA network along with GNPs can contribute to the electrochemical properties of the material. This electroactivity can be advantageous for tissue engineering of electro-conductive tissues like cardiac and nervous tissues.

Investigating the role of peptides in effective therapies against cancer.

Early diagnosis and effective treatment of cancer are challenging. To diagnose and treat cancer effectively and to overcome these challenges, fundamental innovations in traditional diagnosis and therapy are necessary. Peptides can be very helpful in this regard due to their potential and diversity. To enhance the therapeutic potential of peptides, their limitations must be properly identified and their structures engineered and modified for higher efficiency. Promoting the bioavailability and stability of peptides is one of the main concerns. Peptides can also be effective in different areas of targeting, alone or with the help of other therapeutic agents. There has been a lot of research in this area, and the potential for variability of peptides will continue to improve this process. Another promising area in which peptides can help treat cancer is peptide vaccines, which are undergoing promising research, and high throughput technologies can lead to fundamental changes in this area. Peptides have been effective in almost all areas of cancer treatment, and some have even gone through clinical phases. However, many barriers need to be overcome to reach the desired point. The purpose of this review is to evaluate the mechanisms associated with peptides in the diagnosis and treatment of cancer. Therefore, related studies in this area will be discussed.

Synthetic strategies, SAR studies, and computer modeling of indole 2 and 3-carboxamides as the strong enzyme inhibitors: a review.

Indole derivatives have been the focus of many researchers in the study of pharmaceutical compounds for many years. Researchers have investigated the effect of carboxamide moiety at positions 2 and 3, giving unique inhibitory properties to these compounds. The presence of carboxamide moiety in indole derivatives causes hydrogen bonds with a variety of enzymes and proteins, which in many cases, inhibits their activity. In this review, synthetic strategies of indole 2 and 3-carboxamide derivatives, the type, and mode of interaction of these derivatives against HLGP, HIV-1, renin enzyme, and structure-activity studies of these compounds were investigated. It is hoped that indole scaffolds will be tested in the future for maximum activity in pharmacological compounds.

Introducing a pyrazolopyrimidine as a multi-tyrosine kinase inhibitor, using multi-QSAR and docking methods.

In cancer disease, which is one of the problems of today's human societies, the expression of some tyrosine kinase receptors that are effective in the growth and proliferation of cancerous cells rises. Therefore, it is essential to develop and propose new drugs to target the receptors. Performing modeling calculations such as QSAR and docking makes the drug discovery process more efficient. Thus, backpropagation artificial neural network was used for multidimensional quantitative structure-activity relationship (QSAR) to identify essential features of pyrazolopyrimidine moiety, responsible for anticancer activity. The statistical parameters of the model show that multi-QSAR has sufficient validity and accuracy. According to the QSAR modeling, among 26 compounds, the interaction of eight candidates with EGFR, FGFR4, PDGFRA, and VEGFR2 was analyzed by docking modeling. The results showed that 1u compound binds to proteins in a more appropriate area (except FGFR4) with acceptable energy. The results of docking for VEGFR2 binding showed that 1u binds to the active site and binding site of receptor, and it was in the interaction with ten residues in the sites. Although the binding site of 1u molecule in the FGFR4 was not suitable, the binding free energy was excellent (- 9.22 kcal mol-1), which was less than those two anticancer drugs of gefitinib and regorafenib. Furthermore, the values of binding free energy were - 8.69, - 9.64, and - 9.19 kcal mol-1 for EGFR, PDGFRA, and VEGFR2, respectively. Therefore, this study introduces 1u as an anticancer agent that can inhibit the tyrosine kinase receptors.

Synthesis, anticancer activity, and ß-lactoglobulin binding interactions of multitargeted kinase inhibitor sorafenib tosylate (SORt) using spectroscopic and molecular modelling approaches.

Sorafenib tosylate (SORt) is an oral multikinase inhibitor used for treatment of advanced renal cell, liver, and thyroid cancers. In this study, this drug was synthesized and its antiproliferative activities against HCT116 and CT26 cells were assessed. The interaction of SORt with ß-lactoglobulin (BLG) was studied using different fluorescence techniques, circular dichroism (CD), zeta potential measurements, and docking simulation. The results of infrared (IR), mass, H NMR, and C NMR spectra demonstrated that the drug was produced with high quality, purity, and efficiency. SORt showed potent cytotoxicity against HCT116 and CT26 cells with IC50 of 8.12 and 5.42 µM, respectively. For BLG binding of SORt, the results showed that static quenching was the cause of the high affinity drug-protein interaction. Three-dimensional fluorescence and synchronous spectra indicated that SORt conformation was changed at different levels. CD suggested that the α-helix content remained almost constant in the BLG-SORt complex, whereas random coil content decreased. Zeta potential values of BLG were more positive after binding with SORt, due to electrostatic interactions between BLG and SORt. Thermodynamic parameters confirmed van der Waals and hydrogen bond interactions in the complex formation. Molecular modelling predicted the presence of hydrogen bonds and electrostatic forces in the BLG-SORt system, which was consistent with the experimental results.

A Simple, Robust and Efficient Computational Method for n-Octanol/Water Partition Coefficients of Substituted Aromatic Drugs.

In this paper, multiple linear regression (MLR) was used to build quantitative structure property relationship (QSPR) of n-octanol-water partition coefficient (logPo/w) of 195 substituted aromatic drugs. The molecular descriptors were calculated for each compound by the VLifeMDS. By applying genetic algorithm/multiple linear regressions (GA/MLR) the most relevant descriptors were selected to build a QSPR model. The robustness of the model was characterized by the statistical validation and applicability domain (AD). The prediction results from MLR are in good agreement with the experimental values. The R2 and Q2LOO for MLR are 0.9433, 0.9341. The AD of the model was analyzed based on the Williams plot. The effects of different selected descriptors are described.