Molecular docking of metal ion immobilized ligands to proteins in affinity chromatography

Hydroxytyrosol Counteracts Triple Negative Breast Cancer Cell Dissemination via Its Copper Complexing Properties

Polyphenols have gained increasing attention for their therapeutic potential, particularly in conditions like cancer, due to their established antioxidant and anti-inflammatory properties. Recent research highlights their ability to bind to transition metals, such as copper. This is particularly noteworthy given the key role of copper both in the initiation and progression of cancer. Copper can modulate the activity of kinases required for the epithelial-mesenchymal transition (EMT), a process fundamental to tumor cell dissemination. We have previously demonstrated the copper-binding capacity of oleuropein, a secoiridoid found in Olea europaea. In the present study, we investigated the effect of hydroxytyrosol, the primary oleuropein metabolite, on the metastatic potential of three triple-negative breast cancer cell lines (MDA-MB-231, MDA-MB-468, and SUM159). We found that hydroxytyrosol modulated the intracellular copper levels, influencing both the epithelial and mesenchymal markers, by downregulating copper-dependent AKT phosphorylation, a member of the EMT signaling cascade, through Western blot, RT-qPCR, and immunofluorescence. Indeed, by optical spectra, EPR, and in silico approaches, we found that hydroxytyrosol formed a complex with copper, acting as a chelating agent, thus regulating its homeostasis and affecting the copper-dependent signaling cascades. While our results bring to light the copper-chelating properties of hydroxytyrosol capable of countering tumor progression, they also provide further confirmation of the key role of copper in promoting the aggressiveness of triple-negative breast cancer cells.

Isolation and In silico Study of Curcumin from Curcuma longa and Its Anti-Diabetic Activity

Natural products have been widely used for the management of various diseases that affect human health. Natural products are chemical substances that can be extracted with solvents and isolated by column chromatography techniques from the plant source. The development of new drugs from natural products is still challenging, and the most extensively studied plant material is turmeric, Curcuma longa, which is the chief source of curcumin. Curcumin is a bright yellow solid. In our present study, we have taken Curcuma longa, which is defatted with hexane, followed by being extracted with methanol as a solvent. The turmeric methanolic extract is taken for the isolation of curcumin. This was carried out and confirmed by spectroscopy techniques including ¹H NMR, ¹³C NMR, ESI-HRMS, and FT-IR. The compound in silico ADME properties estimate falls within an acceptable range, and a molecular docking analysis shows that it has a higher binding affinity than reference standards. Based on the findings, it can be said that curcumin, a natural substance, has good therapeutic qualities when it is isolated.

Molecularly Designed Ion-Imprinted Nanoparticles for Real-Time Sensing of Cu(II) Ions Using Quartz Crystal Microbalance

A molecularly designed imprinting method was combined with a gravimetric nanosensor for the real-time detection Cu(II) ions in aqueous solutions without using expensive laboratory devices. Thus, 1:1 and 2:1 mol-ratio-dependent coordination modes between Cu(II), N-methacyloly-L histidine methyl ester (MAH) functional monomer complexes, and their four-fold and six-fold coordinations were calculated by means of density functional theory molecular modeling. Cu(II)-MIP1 and Cu(II)-MIP2 nanoparticles were synthesized in the size range of 80-100 nm and characterized by SEM, AFM and FTIR. Cu(II)-MIP nanoparticles were then conducted to a quartz crystal microbalance sensor for the real-time detection of Cu(II) ions in aqueous solutions. The effects of initial Cu(II) concentration, selectivity, and imprinting efficiency were investigated for the optimization of the nanosensor. Linearity of 99% was obtained in the Cu(II) ion linear concentration range of 0.15-1.57 µM with high sensitivity. The LOD was obtained as 40.7 nM for Cu(II)-MIP2 nanoparticles. The selectivity and the imprinting efficiency of the QCM nanosensor were obtained significantly in the presence of competitive ion samples (Co(II), Ni(II), Zn(II), and Fe(II)). The results are promising for sensing Cu(II) ions as environmental toxicants in water by combining molecularly designed ion-imprinted nanoparticles and a gravimetric sensor.

Affinity-Recognition-Based Gravimetric Nanosensor for Equilin Detection

The estrogenic hormones that are widely used in postmenopausal hormone supplements for women contaminate natural water resources. Equilin (Equ) is one of the estrogenic hormones that have a maximum contaminant level of 0.35 µg/L in the chemical pollutants list. In this study, estrogenic hormones were precisely detected in a short time by affinity-recognition-based interactions in Quartz Crystal Microbalance (QCM) sensors. The QCM sensors were modified with 11-mercaptoundecanoic acid forming a self-assembled monolayer and with amino acids, namely tyrosine, tryptophan and phenylalanine. The affinity interactions between Equ and amino acids were studied using docking tools and confirmed by QCM experiments. The LODs of Equ were obtained as 4.59, 5.05 and 6.30 ng/L for tyrosine-, tryptophan- and phenylalanine-modified QCM nanosensors, respectively, with linear dynamic detection in the range of 25–500 nM. In terms of the LOD, selectivity and sensitivity calculations, the tyrosine-modified QCM nanosensor was found to have the highest performance for Equ detection compared to the tryptophan- and phenylalanine-modified ones.

A Comprehensive Review of Computation-Based Metal-Binding Prediction Approaches at the Residue Level

Clear evidence has shown that metal ions strongly connect and delicately tune the dynamic homeostasis in living bodies. They have been proved to be associated with protein structure, stability, regulation, and function. Even small changes in the concentration of metal ions can shift their effects from natural beneficial functions to harmful. This leads to degenerative diseases, malignant tumors, and cancers. Accurate characterizations and predictions of metalloproteins at the residue level promise informative clues to the investigation of intrinsic mechanisms of protein-metal ion interactions. Compared to biophysical or biochemical wet-lab technologies, computational methods provide open web interfaces of high-resolution databases and high-throughput predictors for efficient investigation of metal-binding residues. This review surveys and details 18 public databases of metal-protein binding. We collect a comprehensive set of 44 computation-based methods and classify them into four categories, namely, learning-, docking-, template-, and meta-based methods. We analyze the benchmark datasets, assessment criteria, feature construction, and algorithms. We also compare several methods on two benchmark testing datasets and include a discussion about currently publicly available predictive tools. Finally, we summarize the challenges and underlying limitations of the current studies and propose several prospective directions concerning the future development of the related databases and methods.

Binding modes of cibacron blue with albumin in affinity chromatography using docking tools

Affinity chromatography is a standard method, which used for protein purification and separation studies due to its specificity and selectivity. There are several affinity chromatography methods, such as dye affinity, immobilized metal chelated affinity, and affinity electrophoresis. Cibacron Blue F3G-A (CBD), as a dye ligand, is one of the most used dyes among dye affinity chromatography. CBD is ideally suited for human serum albumin (HSA) separation and purification in affinity chromatography for several years. However, even though CBD has many purification applications, there is not much research focused on the interaction between CBD and HSA in molecular docking. The interactions between CBD and HSA were simulated via AutoDock molecular docking software in this study. Investigated possibilities resulted in six different conformations on different locations, which light the way to variable connectivity of CBD. Thus, it was determined that the most favorable binding is conformation 5, with its lowest binding energy, which is energetically favorable.