Enhancing Sulfidization and Flotation of Smithsonite Using Eco-Friendly Triethanolamine: Insights from Experimental and Simulation Studies.

Triethanolamine (TEA) is a promising eco-friendly alternative to inorganic ammonia for enhancing surface sulfidization and flotation recovery of smithsonite. Micro-flotation experiments revealed an enhancement in smithsonite recovery to 95.21% with TEA modification, comparable to the results obtained using ammonia. The mechanisms behind the ability of TEA to enhance the sulfidization process were investigated through surface analysis and molecular dynamics simulations. TEA modification increased the content of sulfidization products, the proportion of crucial S22- in adsorbed products, and the thickness and size of the sulfidization product layer. The complexation of TEA with Zn sites formed positively charged Zn-TEA complexes that adsorb onto the smithsonite surface. These complexes promoted negatively charged HS- adsorption, creating a multi-layered adsorption structure. Moreover, TEA modification reduced the total energy required for the sulfidization. These findings open up new possibilities for using eco-friendly reagents in mineral processing, highlighting the potential of TEA in green mineral processing practices.

Structure-Based Identification of Novel Histone Deacetylase 4 (HDAC4) Inhibitors.

Histone deacetylases (HDACs) are important cancer drug targets. Existing FDA-approved drugs target the catalytic pocket of HDACs, which is conserved across subfamilies (classes) of HDAC. However, engineering specificity is an important goal. Herein, we use molecular modeling approaches to identify and target potential novel pockets specific to Class IIA HDAC-HDAC4 at the interface between HDAC4 and the transcriptional corepressor component protein NCoR. These pockets were screened using an ensemble docking approach combined with consensus scoring to identify compounds with a different binding mechanism than the currently known HDAC modulators. Binding was compared in experimental assays between HDAC4 and HDAC3, which belong to a different family of HDACs. HDAC4 was significantly inhibited by compound 88402 but not HDAC3. Two other compounds (67436 and 134199) had IC50 values in the low micromolar range for both HDACs, which is comparable to the known inhibitor of HDAC4, SAHA (Vorinostat). However, both of these compounds were significantly weaker inhibitors of HDAC3 than SAHA and thus more selective, albeit to a limited extent. Five compounds exhibited activity on human breast carcinoma and/or urothelial carcinoma cell lines. The present result suggests potential mechanistic and chemical approaches for developing selective HDAC4 modulators.

Structure of epoxide hydrolase 2 from Mangifera indica throws light on the substrate specificity determinants of plant epoxide hydrolases.

Epoxide hydrolases (EHs) are a group of ubiquitous enzymes that catalyze hydrolysis of chemically reactive epoxides to yield corresponding dihydrodiols. Despite extensive studies on EHs from different clades, generic rules governing their substrate specificity determinants have remained elusive. Here, we present structural, biochemical and molecular dynamics simulation studies on MiEH2, a plant epoxide hydrolase from Mangifera indica. Comparative structure-function analysis of nine homologs of MiEH2, which include a few AlphaFold structural models, show that the two conserved tyrosines (MiEH2Y152 and MiEH2Y232) from the lid domain dissect substrate binding tunnel into two halves, forming substrate-binding-pocket one (BP1) and two (BP2). This compartmentalization offers diverse binding modes to their substrates, as exemplified by the binding of smaller aromatic substrates, such as styrene oxide (SO). Docking and molecular dynamics simulations reveal that the linear epoxy fatty acid substrates predominantly occupy BP1, while the aromatic substrates can bind to either BP1 or BP2. Furthermore, SO preferentially binds to BP2, by stacking against catalytically important histidine (MiEH2H297) with the conserved lid tyrosines engaging its epoxide oxygen. Residue (MiEH2L263) next to the catalytic aspartate (MiEH2D262) modulates substrate binding modes. Thus, the divergent binding modes correlate with the differential affinities of the EHs for their substrates. Furthermore, long-range dynamical coupling between the lid and core domains critically influences substrate enantioselectivity in plant EHs.

Nilotinib: Disrupting the MYC-MAX Heterocomplex.

MYC is a transcription factor crucial for maintaining cellular homeostasis, and its dysregulation is associated with highly aggressive cancers. Despite being considered "undruggable" due to its unstable protein structure, MYC gains stability through its interaction with its partner protein, MAX. The MYC-MAX heterodimer orchestrates the expression of numerous genes that contribute to an oncogenic phenotype. Previous efforts to develop small molecules, disrupting the MYC-MAX interaction, have shown promise in vitro but none have gained clinical approval. Our current computer-aided study utilizes an approach to explore drug repurposing as a strategy for inhibiting the c-MYC-MAX interaction. We have focused on compounds from DrugBank library, including Food and Drug Administration-approved drugs or those under investigation for other medical conditions. First, we identified a potential druggable site on flat interface of the c-MYC protein, which served as the target for virtual screening. Using both activity-based and structure-based screening, we comprehensively assessed the entire DrugBank library. Structure-based virtual screening was performed on AutoDock Vina and Glide docking tools, while activity-based screening was performed on two independent quantitative structure-activity relationship models. We focused on the top 2% of hit molecules from all screening methods. Ultimately, we selected consensus molecules from these screenings-those that exhibited both a stable interaction with c-MYC and superior inhibitory activity against c-MYC-MAX interaction. Among the evaluated molecules, we identified a protein kinase inhibitor (tyrosine kinase inhibitor [TKI]) known as nilotinib as a promising candidate targeting c-MYC-MAX dimer. Molecular dynamic simulations demonstrated a stable interaction between MYC and nilotinib. The interaction with nilotinib led to the stabilization of a region of the MYC protein that is distorted in apo-MYC and is important for MAX binding. Further analysis of differentially expressed gene revealed that nilotinib, uniquely among the tested TKIs, induced a gene expression program in which half of the genes were known to be responsive to c-MYC. Our findings provide the foundation for subsequent in vitro and in vivo investigations aimed at evaluating the efficacy of nilotinib in managing MYC oncogenic activity.

Hydrodynamics and Aggregation of Nanoparticles with Protein Corona: Effects of Protein Concentration and Ionic Strength.

Multiple 10 nm-sized anionic nanoparticles complexed with plasma proteins (human serum albumin (SA) or immunoglobulin gamma-1 (IgG)) at different ratios are simulated using all-atom and coarse-grained models. Coarse-grained simulations show much larger hydrodynamic radii of individual particles at a low protein concentration (a protein-to-particle ratio of 1) than at high protein concentrations or without proteins, indicating particle aggregation only at such a low protein concentration, in agreement with experiments. This particle aggregation is attributed to both electrostatic and hydrophobic particle-protein interactions, to an extent dependent on different proteins. In all-atom simulations, IgG proteins induce particle aggregation with and without salt, while SA proteins promote particle aggregation only in the presence of salt that can weaken the electrostatic repulsion between anionic particles closely linked via SA that is smaller than IgG, which also agree well with experiments. Besides charge interactions, hydrophobic interactions between particles and proteins are also important especially at the high salt concentration, leading to the increased particle-protein contact area. These findings help explain experimental observations regarding that the effects of protein concentration and ionic strength on particle aggregation depend on different plasma proteins, which are interpreted by binding free energies, electrostatic, and hydrophobic interactions between particles and proteins.

Engineering of the Phytase YiAPPA to Improve Thermostability and Activity and Its Application Potential in Dephytinization of Food Ingredients.

The aim of this study was to modify phytase YiAPPA via protein surficial residue mutation to obtain phytase mutants with improved thermostability and activity, enhancing its application potential in the food industry. First, homology modeling of YiAPPA was performed. By adopting the strategy of protein surficial residue mutation, the lysine (Lys) and glycine (Gly) residues on the protein surface were selected for site-directed mutagenesis to construct single-site mutants. Thermostability screening was performed to obtain mutants (K189R and K216R) with significantly elevated thermostability. The combined mutant K189R/K216R was constructed via beneficial mutation site stacking and characterized. Compared with those of YiAPPA, the half-life of K189R/K216R at 80°C was extended from 14.81 min to 23.35 min, half-inactivation temperature (T50 30) was increased from 55.12°C to 62.44°C, and Tm value was increased from 48.36°C to 53.18°C. Meanwhile, the specific activity of K189R/K216R at 37°C and pH 4.5 increased from 3960.81 to 4469.13 U/mg. Molecular structure modeling analysis and molecular dynamics simulation showed that new hydrogen bonds were introduced into K189R/K216R, improving the stability of certain structural units of the phytase and its thermostability. The enhanced activity was primarily attributed to reduced enzymesubstrate binding energy and shorter nucleophilic attack distance between the catalytic residue His28 and the phytate substrate. Additionally, the K189R/K216R mutant increased the hydrolysis efficiency of phytate in food ingredients by 1.73-2.36 times. This study established an effective method for the molecular modification of phytase thermostability and activity, providing the food industry with an efficient phytase for hydrolyzing phytate in food ingredients.

Molecular dynamics study on the physical compatibility of SEBS/plasticizer blend systems.

CONTEXT: Thermoplastic elastomer styrene-ethylene-butylene-styrene block copolymer (SEBS) has excellent mechanical properties and aging resistance, so it has good application prospects in thermoplastic solid propellants. The selection of plasticizer is one of the keys to the formulation design of thermoplastic solid propellant. The compatibility of the plasticizer with the polymer determines the plasticizer's ability to plasticize the polymer's molecular chain segments. Herein, the compatibility of four plasticizers with SEBS was investigated, and the results declared that the order of compatibility between SEBS and the four plasticizers is SEBS/WO > SEBS/DOS > SEBS/DEP > SEBS/TA. METHODS: Physical compatibility of SEBS binder with plasticizer triacetin (TA), diethyl phthalate (DEP), dioctyl sebacate (DOS), and 26# industrial white oil (WO) was simulated using molecular dynamics (MD) method via Materials Studio 8.0, and the simulation results were verified experimentally. The results showed that the compatibility of SEBS with these plasticizers can be comprehensively evaluated by analyzing solubility parameters, radial distribution functions, and blend miscibility simulations.

In silico discovery of potential PPI inhibitors for anti-lung cancer activity by targeting the CCND1-CDK4 complex via the P21 inhibition mechanism.

Non-Small Cell Lung Cancer (NSCLC) is a prevalent and deadly form of lung cancer worldwide with a low 5-year survival rate. Current treatments have limitations, particularly for advanced-stage patients. P21, a protein that inhibits the CCND1-CDK4 complex, plays a crucial role in cell proliferation. Computer-Aided Drug Design (CADD) based on pharmacophores can screen and design PPI inhibitors targeting the CCND1-CDK4 complex. By analyzing known inhibitors, key pharmacophores are identified, and computational methods are used to screen potential PPI inhibitors. Molecular docking, pharmacophore matching, and structure-activity relationship studies optimize the inhibitors. This approach accelerates the discovery of CCND1-CDK4 PPI inhibitors for NSCLC treatment. Molecular dynamics simulations of CCND1-CDK4-P21 and CCND1-CDK4 complexes showed stable behavior, comprehensive sampling, and P21's impact on complex stability and hydrogen bond formation. A pharmacophore model facilitated virtual screening, identifying compounds with favorable binding affinities. Further simulations confirmed the stability and interactions of selected compounds, including 513457. This study demonstrates the potential of CADD in optimizing PPI inhibitors targeting the CCND1-CDK4 complex for NSCLC treatment. Extended simulations and experimental validations are necessary to assess their efficacy and safety.

Electric Field-Enhanced Ion Rejection Rate in Freeze Desalination.

Freeze desalination is an appealing method for seawater desalination through freezing seawater. The percentage of ions in the liquid phase, which is termed ion rejection rate, is a critical factor affecting the performance of freeze desalination. Improving the ion rejection rate is an important topic for freeze desalination. In this work, we investigate the effects of electric fields on the ion rejection rate during the freezing of seawater through molecular dynamics simulations.  It is found that the ion rejection rate increases with increasing electric field strength.  The enhanced ion rejection rate is due to the reduction of the energy barrier at the ice-water interface caused by the electric field, which affects the orientation of water molecules and ion-water interactions. However, the electric field hinders the ice growth rate, which affects the productivity of freeze desalination. Nevertheless, the finding in this work offers a new idea to improve the ion rejection rate. Practically, a trade-off needs to be found to optimize the overall performance of freeze desalination.

Identification of Inhibitors for Flagellar Assembly Protein FliN of Uropathogenic Escherichia coli using Virtual Screening and Molecular Dynamics Simulation Study.

Escherichia coli (E. coli) is a gram-negative bacterial pathogen that poses a significant clinical and epidemiologic challenge. The selection pressure brought by the insufficient use of antibiotics has resulted in the emergence of multi-drug-resistant E. coli in the past ten years. Computational and bioinformatics methods for screening inhibitors have significantly contributed to discovering novel antibacterial agents. One possible target for novel anti-virulence drugs is motility. Motility inhibitors are generally effective at concentrations lower than those required for the antibacterial properties of traditional antibiotics, and they are likely to exert less selective pressure than current medicines. Motility may be essential for bacteria to survive, find nutrients, and escape unfavorable environments and biofilm formation. The FliN is a protein forming the bulk of the C ring of the flagella and is present in multiple copies (more than 100) in bacteria. Its absence in mammals makes it an attractive drug target for drug discovery. Two-thousand seven hundred seventy-eight natural compounds from the ZINC library were screened against FliN (PDB ID: 4YXB) using PyRx AutoDock Vina, and the top compounds were selected for secondary screening after sorting the results based on their binding energy. Based on interactional analysis, binding energy (- 7.78 kcal/mol), and inhibition constant (1.98 µM), ZINC000000619481 was the best inhibitor. This compound binds exactly as per the defined active site residues of the receptor protein. Also, molecular dynamics was performed. The eigenvalue of the selected complex was 1.241657e-05. There were no ADME properties outside of the specified range for the identified hit; it fitted exactly to the binding site of the FliN receptor well and was found to be stable in MD simulation studies. Further in vitro and in vivo studies are needed to confirm its anti-bacterial activity and use as a potential antimicrobial drug against urinary tract infections caused by E. coli.

Evaluation of suppressor behavior of guanidine-derived metformin and galegine as novel potential drugs for cancer treatment: an in silico study.

There are some natural products from plants that can prevent and treat disease. Metformin, a derivative of galegine, is the basic drug to treat diabetes. Moreover, this molecule has anticancer properties that inhibit cancer cell growth and proliferation. In this study, the main interactions of galegine and metformin with various cancer-involved proteins, including mitochondrial alpha-glycerophosphate dehydrogenase, yeast NADH dehydrogenase, and transforming growth factor-ß1, were surveyed by molecular docking and molecular dynamics simulations. The results showed that each of the proteins makes complexes with the ligands via favorable non-bonded interactions, especially hydrogen bond interactions. There is greater stability for complexes containing galegine based on the root mean square deviation results. The higher structure compactness is also found in galegine receptors than in metformin receptors. Calculation of ΔGbinding, using the MM/PBSA methodology, shows that the binding energy values for metformin and galegine in interaction with each of the receptors are almost the same, and galegine has similar binding properties with metformin in interaction with the studied protein receptors. Therefore, galegine, a natural ingredient with better binding properties to cancer-involved proteins than metformin (with various side effects), can be applied as a new drug for cancer treatment.

Through virtual saturation mutagenesis and rational design for superior substrate conversion in engineered d-amino acid oxidase.

The d-amino acid oxidase (DAAO) is pivotal in obtaining optically pure l-glufosinate (l-PPT) by converting d-glufosinate (d-PPT) to its deamination product. We screened and designed a Rasamsonia emersonii DAAO (ReDAAO), making it more suitable for oxidizing d-PPT. Using Caver 3.0, we delineated three substrate binding pockets and, via alanine scanning, identified nearby key residues. Pinpointing key residues influencing activity, we applied virtual saturation mutagenesis (VSM), and experimentally validated mutants which reduced substrate binding energy. Analysis of positive mutants revealed elongated side-chain prevalence in substrate binding pocket periphery. Although computer-aided approaches can rapidly identify advantageous mutants and guide further design, the mutations obtained in the first round may not be suitable for combination with other advantageous mutations. Therefore, each round of combination requires reasonable iteration. Employing VSM-assisted screening multiple times and after four rounds of combining mutations, we ultimately obtained a mutant, N53V/F57Q/V94R/V242R, resulting in a mutant with a 5097% increase in enzyme activity compared to the wild type. It provides valuable insights into the structural determinants of enzyme activity and introduces a novel rational design procedure.

Repurposing of FDA-approved drugs against oligomerization domain of dengue virus NS1 protein: a computational approach.

Dengue fever is a serious health hazard on a global scale and its primary causative agent is the dengue virus (DENV). The non-structural protein 1 (NS1) of DENV plays a pivotal role in pathogenesis. It is associated with several autoimmune events, endothelial cell apoptosis, and vascular leakage, which increase mainly during the critical phase of infection. In this study, important residues of the oligomerization domain of NS1 protein were identified by literature searches. Virtual screening has been conducted using the entire dataset of the DrugBank database and the potential small-molecule inhibitors against the NS1 protein have been chosen on the basis of binding energy values. This is succeeded by molecular dynamics (MD) simulations of the shortlisted compounds, ultimately giving rise to five compounds. These five compounds were further subjected to RAMD simulations by applying a random direction force of specific magnitude on the ligand center of mass in order to push the ligand out of the protein-binding pocket, for the quantitative estimation of their binding energy values to determine the interaction strength between protein and ligand which prevents ligand unbinding from its binding site, ultimately leading to the selection of three major compounds, DB00826 (Natamycin), DB11274 (Dihydro-alphaergocryptine), and DB11275 (Epicriptine), with the DB11274 having a role against idiopathic Parkinson's disease, and thus may have possible important roles in the prevention of dengue-associated Parkinsonism. These compounds may act as prospective drugs against dengue, by preventing the oligomerization of the NS1 protein, thereby preventing disease progression and pathogenesis.

Quantifying Membrane Alterations with Tailored Fluorescent Dyes: A Rapid Antibiotic Resistance Profiling Methodology.

Accurate detection of bacterial antibiotic sensitivity is crucial for theranostics and the containment of antibiotic-resistant infections. However, the intricate task of detecting and quantifying the antibiotic-induced changes in the bacterial cytoplasmic membrane, and their correlation with other metabolic pathways leading to antibiotic resistance, poses significant challenges. Using a novel class of 4-aminophthalimide (4AP)-based fluorescent dyes with precisely tailored alkyl chains, namely 4AP-C9 and 4AP-C13, we quantify stress-mediated alterations in E. coli membranes. Leveraging the unique depth-dependent positioning and environment-sensitive fluorescence properties of these dyes, we detect antibiotic-induced membrane damage through single-cell imaging and monitoring the fluorescence peak maxima difference ratio (PMDR) of the dyes within the bacterial membrane, complemented by other methods. The correlation between the ROS-induced cytoplasmic membrane damage and the PMDR of dyes quantifies sensitivity against bactericidal antibiotics, which correlates to antibiotic-induced lipid peroxidation. Significantly, our findings largely extend to clinical isolates of E. coli and other ESKAPE pathogens like K. pneumoniae and Enterobacter subspecies. Our data reveal that 4AP-Cn probes can potentially act as precise scales to detect antibiotic-induced membrane damage ("thinning") occurring at a subnanometer scale through the quantification of dyes' PMDR, making them promising membrane dyes for rapid detection of bacterial antibiotic resistance, distinguishing sensitive and resistant infections with high specificity in a clinical setup.

Improved physicochemical properties of bigels produced with ethyl cellulose-based oleogel and moderately deacetylated konjac glucomannan hydrogel.

The ideal physicochemical properties of bigels are important for food applications. Therefore, a new bigel was prepared based on mixed beef tallow and soybean oil oleogel and deacetylated konjac glucomannan (KGM) hydrogel. The effect of the deacetylation degree of KGM on the physicochemical properties and microstructure of bigels was studied. The bigel containing moderate deacetylation degree of KGM had better rheological properties and hardness (319.84 g) than that with low and high deacetylation degrees of KGM. The interactions among the bigel components were analyzed by Fourier transform infrared spectroscopy and molecular dynamics simulation, indicating that the formation of the bigels was dominated by electrostatic interactions. Overall, the bigels containing moderate deacetylation degree of KGM had better physical properties, which may provide a theoretical foundation to develop bigels with low cholesterol, trans and saturated fats levels to replace traditional solid fats in food industry.

Simulating asymmetric membranes using P21 periodic boundary conditions.

Molecular dynamics (MD) simulations of symmetric lipid bilayers are now well established, while those of asymmetric ones are considerably less developed. This disjunction arises in part because the surface tensions of leaflets in asymmetric bilayers can differ (unlike those of symmetric ones), and there is no simple way to determine them without assumptions. This chapter describes the use of P21 periodic boundary conditions (PBC), which allow lipids to switch leaflets, to generate asymmetric bilayers under the assumption of equal chemical potentials of lipids in opposing leaflets. A series of examples, ranging from bilayers with one lipid type to those with peptides and proteins, provides a guide for the use of P21 PBC. Critical properties of asymmetric membranes, such as spontaneous curvature, are highly sensitive to differences in the leaflet surface tensions (or differential stress), and equilibration with P21 PBC substantially reduces differential stress of asymmetric bilayers assembled with surface area-based methods. Limitations of the method are discussed. Technically, the nonstandard unit cell is difficult to parallelize and to incorporate restraints. Inherently, the assumption of equal chemical potentials, and therefore the method itself, is not applicable to all target systems. Despite these limitations, it is argued that P21 simulations should be considered when designing equilibration protocols for MD studies of most asymmetric membranes.

Analyzing lipid distributions and curvature in molecular dynamics simulations of complex membranes.

We describe methods to analyze lipid distributions and curvature in membranes with complex lipid mixtures and embedded membrane proteins. We discuss issues involved in these analyses, available tools to calculate curvature preferences of lipids and proteins, and focus on tools developed in our group for visual analysis of lipid-protein interactions and the analysis of membrane curvature.

Genomic and computational-aided integrative drug repositioning strategy for EGFR and ROS1 mutated NSCLC.

Non-small cell lung cancer (NSCLC) has been marked as the major cause of death in lung cancer patients. Due to tumor heterogeneity, mutation burden, and emerging resistance against the available therapies in NSCLC, it has been posing potential challenges in the therapy development. Hence, identification of cancer-driving mutations and their effective inhibition have been advocated as a potential approach in NSCLC treatment. Thereof, this study aims to employ the genomic and computational-aided integrative drug repositioning strategy to identify the potential mutations in the selected molecular targets and repurpose FDA-approved drugs against them. Accordingly, molecular targets and their mutations, i.e., EGFR (V843L, L858R, L861Q, and P1019L) and ROS1 (G1969E, F2046Y, Y2092C, and V2144I), were identified based on TCGA dataset analysis. Following, virtual screening and redocking analysis, Elbasvir, Ledipasvir, and Lomitapide drugs for EGFR mutants (>-10.8 kcal/mol) while Indinavir, Ledipasvir, Lomitapide, Monteleukast, and Isavuconazonium for ROS1 mutants (>-8.8 kcal/mol) were found as putative inhibitors. Furthermore, classical molecular dynamics simulation and endpoint binding energy calculation support the considerable stability of the selected docked complexes aided by substantial hydrogen bonding and hydrophobic interactions in comparison to the respective control complexes. Conclusively, the repositioned FDA-approved drugs might be beneficial alone or in synergy to overcome acquired resistance to EGFR and ROS1-positive lung cancers.

Reporting multitargeted potency of Tiaprofenic acid against lung cancer: Molecular fingerprinting, MD simulation, and MTT-based cell viability assay studies.

Lung Cancer (LC) is among the most death-causing cancers, has caused the most destruction and is a gender-neutral cancer, and WHO has kept this cancer on its priority list to find the cure. We have used high-throughput virtual screening, standard precision docking, and extra precise docking for extensive screening of Drug Bank compounds, and the uniqueness of this study is that it considers multiple protein targets of prognosis and metastasis of LC. The docking and MM\GBSA calculation scores for the Tiaprofenic acid (DB01600) against all ten proteins range from -8.422 to -5.727 kcal/mol and - 47.43 to -25.72 kcal/mol, respectively. Also, molecular fingerprinting helped us to understand the interaction pattern of Tiaprofenic acid among all the proteins. Further, we extended our analysis to the molecular dynamic simulation in a neutralised SPC water medium for 100 ns. We analysed the root mean square deviation, fluctuations, and simulative interactions among the protein, ligand, water molecules, and protein-ligand complexes. Most complexes have shown a deviation of <2 Å as cumulative understanding. Also, the fluctuations were lesser, and only a few residues showed the fluctuation with a huge web of interaction between the protein and ligand, providing an edge that supports that the protein and ligand complexes were stable. In the MTT-based Cell Viability Assay, Tiaprofenic Acid exhibited concentration-dependent anti-cancer efficacy against A549 lung cancer cells, significantly reducing viability at 100 µg/mL. These findings highlight its potential as a therapeutic candidate, urging further exploration into the underlying molecular mechanisms for lung cancer treatment.

Discovering novel targets of abscisic acid using computational approaches.

Abscisic acid (ABA) is a crucial plant hormone that is naturally produced in various mammalian tissues and holds significant potential as a therapeutic molecule in humans. ABA is selected for this study due to its known roles in essential human metabolic processes, such as glucose homeostasis, immune responses, cardiovascular system, and inflammation regulation. Despite its known importance, the molecular mechanism underlying ABA's action remain largely unexplored. This study employed computational techniques to identify potential human ABA receptors. We screened 64 candidate molecules using online servers and performed molecular docking to assess binding affinity and interaction types with ABA. The stability and dynamics of the best complexes were investigated using molecular dynamics simulation over a 100 ns time period. Root mean square fluctuations (RMSF), root mean square deviation (RMSD), solvent-accessible surface area (SASA), radius of gyration (Rg), free energy landscape (FEL), and principal component analysis (PCA) were analyzed. Next, the molecular mechanics Poisson-Boltzmann surface area (MM-PBSA) method was employed to calculate the binding energies of the complexes based on the simulated data. Our study successfully pinpointed four key receptors responsible for ABA signaling (androgen receptor, glucocorticoid receptor, mineralocorticoid receptor, and retinoic acid receptor beta) that have a strong affinity for binding with ABA and remained structurally stable throughout the simulations. The simulations with Hydralazine as an unrelated ligand were conducted to validate the specificity of the identified receptors for ABA. The findings of this study can contribute to further experimental validation and a better understanding of how ABA functions in humans.