Free Energy Calculations Research Articles

Optimal Dielectric Boundary for Binding Free Energy Estimates in the Implicit Solvent.

Accuracy of binding free energy calculations utilizing implicit solvent models is critically affected by parameters of the underlying dielectric boundary, specifically, the atomic and water probe radii. Here, a multidimensional optimization pipeline is used to find optimal atomic radii, specifically for binding calculations in the implicit solvent. To reduce overfitting, the optimization target includes separate, weighted contributions from both binding and hydration free energies. The resulting five-parameter radii set, OPT_BIND5D, is evaluated against experiment for binding free energies of 20 host-guest (H-G) systems, unrelated to the types of structures used in the training. The resulting accuracy for this H-G test set (root mean square error of 2.03 kcal/mol, mean signed error of -0.13 kcal/mol, mean absolute error of 1.68 kcal/mol, and Pearson's correlation of r = 0.79 with the experimental values) is on par with what can be expected from the fixed charge explicit solvent models. Best agreement with the experiment is achieved when the implicit salt concentration is set equal or close to the experimental conditions.

Directly Fused Porphyrin-Tetracyanopentacenequinone Conjugates: Role of the Cross-Conjugated, Powerful Electron Acceptor in Promoting Highly Efficient Charge Separation.

Tetracyanopentacenequinone, a powerful electron acceptor, is fused directly to the porphyrin π-system to create a new class of donor-acceptor conjugates. Owing to the direct fusion and electron-deficient property of tetracyanopentacenequinone, strong intramolecular charge transfer both in the ground and excited states was witnessed. As a control, porphyrin fused with pentacenequinone was also investigated. Upon complete spectral and electrochemical characterization, the excited state properties were initially probed by time-dependent DFT studies, and the occurrence of electron transfer from different excited states was established. Free-energy calculations revealed higher exothermic electron transfer (> 600 mV) than the control pentacenequinone-porphyrin systems. Pump-probe studies covering broad spatial and temporal regions revealed efficient excited state charge separation. This was unlike the control pentacenequinone-porphyrin system, where slow charge separation was witnessed only in the case of the zinc derivatives but not the free-base ones. The lifetimes of the charge-separated states ranged between 30-500 ps depending on the solvent and metal ion in the porphyrin cavity. The significance of cross-conjugated tetracyanopentacenequinone fused directly to the porphyrin π system in promoting highly exothermic and efficient charge separation, irrespective of its cross conjugation, is borne out from this study.

Leveraging a Separation of States Method for Relative Binding Free Energy Calculations in Systems with Trapped Waters.

Methods for calculating the relative binding free energy (RBFE) between ligands to a target protein are gaining importance in the structure-based drug discovery domain, especially as methodological advances and automation improve accuracy and ease of use. In an RBFE calculation, the difference between the binding affinities of two ligands to a protein is calculated by transforming one ligand into another, in the protein-ligand complex, and in solvent. Alchemical binding free energy calculations are often used for such ligand transformations. Such calculations are not without challenges, however; for example, it can be challenging to handle interfacial waters when these play a crucial role in mediating protein-ligand binding. In some cases, the exchange of the interfacial waters with solvent water might be very infrequent in the course of typical molecular simulations, and such interfacial waters can be considered trapped on the simulation time scale. In these cases, RBFE calculation between two ligands, where one ligand binds with a trapped water while the other ligand displaces it, can result in inaccuracies if the surrounding water structure is not sampled adequately for both ligands. So far, a popular choice for treating the trapped waters in RBFE calculations is to combine free energy calculations with enhanced sampling methods that insert/delete waters in the binding site. Despite recent developments in the enhanced sampling methods, they can result in hysteresis in the RBFE estimate, depending on whether the simulations were started with or without the trapped waters. In this study, we introduce an alternative method, separation of states, to calculate the RBFE between ligand pairs where the ligands bind to the protein with different numbers/positions of trapped waters. The separation of states approach treats the sampling of the trapped waters separately from the free energy calculation of the ligand transformation. In our method, a trapped water in protein's binding site is decoupled from the system first, and the cavity created by its decoupling is stabilized. We then grow a larger ligand into this cavity- a ligand that is known to displace the trapped water. In this study, we show that our method results in precise and accurate estimates of RBFEs for ligand pairs involving the rearrangement of trapped water via RBFE calculations for five such ligand pairs. We have optimized our simulation protocol to be suited for large distributed computational resources and have automated our RBFE calculation workflow.

Repurposed drugs as PCSK9-LDLR disruptors for lipid lowering and cardiovascular disease therapeutics.

The PCSK9 protein binds to LDL receptors (LDLR), leading to their degradation and reduced expression on cell surfaces. This decreased the clearance of LDL cholesterol from the bloodstream, thereby increasing the risk of coronary artery diseases. Targeting the PCSK9-LDL receptor interaction is crucial for regulating LDL cholesterol levels and preventing cardiovascular disease. This study aims to screen low molecular weight inhibitors to disrupt the PCSK9-LDLR interaction. We employed a comprehensive approach combining high-throughput virtual screening of DrugBank database, followed by molecular docking studies using CDOCKER and flexible docking methods. The top four lead compounds were further validated through molecular dynamics (MD) simulations and binding free energy calculations using MM-PBSA. Finally, the in vitro assay confirmed that Benazepril and Quinapril exhibited the highest potency as PCSK9-LDLR disruptors among the top candidates. These lead compounds have the potential to be repurposed as lipid-lowering agents for the treatment of cardiovascular diseases, offering a promising therapeutic strategy.

Structural transitions of calcium carbonate by molecular dynamics simulation.

Calcium carbonate (CaCO3) plays a crucial role in the global carbon cycle, and its phase diagram is of significant scientific interest. We used molecular dynamics to investigate selected structural phase transitions of calcium carbonate. Using the Raiteri potential, we explored the structural transitions occurring at the constant pressure of 1bar, with temperatures ranging from 300 to 2500K, and at the constant temperature of 1600K, with pressures ranging from 0 to 13GPa. With increasing temperature, the transitions between calcite, CaCO3-IV, and CaCO3-V were characterized. In the calcite structure, the carbonate ions are ordered in a planar triangular arrangement, alternating with layers of calcium ions. As the temperature increases, the transition from calcite to CaCO3-IV occurs, leading to partial disordering of the carbonate ions. At higher temperatures, CaCO3-IV transforms into CaCO3-V. Through free energy analysis, we classified the latter transition as a continuous phase transition. At a temperature of 2000K, a "disordered CaCO3" structure appears, characterized by low order within the calcium and carbonate sublattices and the free rotation of the carbonate ions. With increasing pressure, two calcium carbonate transformations were observed. At P = 2GPa, the CaCO3-V phase undergoes a phase transition into CaCO3-IV, demonstrating that the model can describe the transition between these two phases as pressure- and temperature-driven. At P = 4.25GPa, CaCO3-IV undergoes a phase transition into the CaCO3-Vb phase. This transition is classified as first-order based on free energy calculations.

Targeting serotonin receptors with phytochemicals – an in-silico study

The potential of natural phytochemicals in mitigating depression has been supported by substantial evidence. This study evaluated a total of 88 natural phytochemicals with potential antidepressant properties by targeting serotonin (5-HT) receptors (5-HT1A, 5-HT4, and 5-HT7) using molecular docking, ADMET (Absorption, Distribution, Metabolism, Excretion, and Toxicity) analysis, internal coordinates normal mode analysis (NMA), molecular dynamics simulation (MDS), and free energy calculation. Five evaluated compounds (Genistein, Kaempferol, Daidzein, Peonidin, and glycitein) exhibited favorable pharmacokinetic properties and improved binding scores, indicating their potential as effective antidepressants. Redocking and superimposition analysis of 5-HT with cocrystal structures validated these findings. Furthermore, NMA, MDS, and free energy calculations confirmed the stability and deformability of the ligand-receptor complexes, suggesting that these phytochemicals can effectively interact with 5-HT receptors to modulate depressive symptoms. These powerful phytochemicals, abundantly found in soybeans, fruits, vegetables, and herbs, represent a promising avenue for developing natural treatments for depression. Further in vitro and in vivo studies are warranted to explore their efficacy in alleviating stress and depression through their interactions with 5-HT receptors.

Protocols for Metallo- and Serine-β-Lactamase Free Energy Predictions: Insights from Cross-Class Inhibitors.

While relative binding free energy (RBFE) calculations using alchemical methods are routinely carried out for many pharmaceutically relevant protein targets, challenges remain. For example, open-source tools do not support the easy setup and simulation of metalloproteins, particularly when ligands directly coordinate to the metal site. Here, we evaluate the performance of RBFE methods for KPC-2, a serine-β-lactamase (SBL), and two nonbonded metal parameter setups for VIM-2, a metallo-β-lactamase (MBL) with two active site zinc ions. We tested two different ways of modeling the ligand-zinc interactions. First, a restraint-based approach, in which FF14SB zinc parameters are combined with harmonic restraints between the zincs and their coordinating residues. The second approach uses an upgraded Amber force field (UAFF) for zinc-metalloproteins with adjusted partial charges and nonbonded terms of zinc-coordinating residues. Molecular mechanics (MM) and quantum mechanics/molecular mechanics (QM/MM) simulations show that the crystallographically observed zinc coordination is not retained in MM simulations with either zinc parameter set for a series of known phosphonic acid-based inhibitors bound to VIM-2. These phosphonic acid-based inhibitors exhibit known cross-class affinity for SBLs and MBLs and serve as a benchmark for RBFE calculations for VIM-2, after validation with KPC-2. The KPC-2 free energy of binding estimates are within expected literature accuracies for the ligand series with a mean absolute error of kcal/mol and a Pearson's correlation coefficient of . For VIM-2, the UAFF approach has improved correlation from to , compared to the restraint approach. The presented strategies for handling ligands coordinating to metal sites highlight that simple metal parameter models can provide some predictive free energy estimates for metalloprotein-ligand systems, but leave room for improvement in their ease of use, modeling of coordination sites and as a result, their accuracy.

Discovery of novel VEGFR2 inhibitors against non-small cell lung cancer based on fingerprint-enhanced graph attention convolutional network

Despite the proven inhibitory effects of drugs targeting vascular endothelial growth factor receptor 2 (VEGFR2) on solid tumors, including non-small cell lung cancer (NSCLC), the development of anti-NSCLC drugs solely targeting VEGFR2 still faces risks such as off-target effects and limited efficacy. This study aims to develop a novel fingerprint-enhanced graph attention convolutional network (FnGATGCN) model for predicting the activity of anti-NSCLC drugs. Employing a multimodal fusion strategy, the model integrates a feature extraction layer that comprises molecular graph feature extraction and molecular fingerprint feature extraction. The performance evaluation results indicate that the model exhibits high accuracy and stability in predicting activity. Moreover, we explored the relationship between molecular features and biological activity through visualization analysis, thus improving the interpretability of the approach. Utilizing this model, we screened the ZINC database and conducted high-precision molecular docking, leading to the identification of 11 potential active molecules. Subsequently, molecular dynamics simulations and free energy calculations were performed. The results demonstrate that all 11 aforementioned molecules can stably bind to VEGFR2 under dynamic conditions. Among the short-listed compounds, the top six exhibited satisfactory inhibitory activity against VEGFR2 and A549 cells. Especially, compound Z-3 displayed VEGFR2 inhibitory with IC50 values of 0.88 μM, and anti-proliferative activity against A549 cells with IC50 values of 4.23 ± 0.45 μM. This approach combines the advantages of target-based and phenotype-based screening, facilitating the rapid and efficient identification of candidate compounds with dual activity against VEGFR2 and A549 cell lines. It provides new insights and methods for the development of anti-NSCLC drugs. Furthermore, further biological activity tests revealed that Z1-Z3 and Z6 manifested relatively strong antiproliferative activities against NCI-H23 and NCI-H460, and relatively low toxicity towards GES-1. The hit compounds were promising candidates for the further development of novel VEGFR2 inhibitors against NSCLC.

Immunoinformatics design of a multi-epitope vaccine for Chlamydia trachomatis major outer membrane proteins

Chlamydia trachomatis (CT) remains a significant infectious cause of blindness and sexually transmitted infections worldwide. The objective and novelty of this study lie in using different serovars of CT to design a broad-spectrum multi-epitope vaccine that might confer immunity against different CT infections. As the major outer membrane protein in CT has good immunodominance properties and high conservation and also determines the several serotypes of CT, it is selected as an antibody target in this study. T-cell and B-cell epitopes from serovars A, B, D, E, L1, and L2 were predicted and combined into a single construct by incorporating adjuvants and linkers to enhance immunogenicity and stability. Physicochemical characterization confirmed the constructed vaccine’s anti-allergic, immunogenicity, and thermostable characteristics, followed by structural modeling to refine its 3D configuration. The 3D model structure of the vaccine was validated through the Ramachandran plot and ProSA z-score. Molecular docking studies of the vaccine demonstrated stable binding with toll-like receptor 3, along with molecular dynamics simulations and binding free energy calculations supporting the complex’s stability. In silico cloning has indicated a high potential for expression in Escherichia coli. Lastly, immune simulations revealed robust activation of B cells, cytotoxic T cells, and antigen-presenting cells, alongside significant production of IgM, IgG antibodies, and balanced Th1/Th2 cytokine response, which is crucial for effective immunity. These results suggest the multi-epitope vaccine could effectively induce comprehensive immune responses against CT, highlighting the need for further in vivo validation to advance this promising candidate toward clinical use.

Martignac: Computational Workflows for Reproducible, Traceable, and Composable Coarse-Grained Martini Simulations.

Despite their wide use and far-reaching implications, molecular dynamics (MD) simulations suffer from a lack of both traceability and reproducibility. We introduce Martignac: computational workflows for the coarse-grained (CG) Martini force field. Martignac describes Martini CG MD simulations as an acyclic directed graph, providing the entire history of a simulation─from system preparation to property calculations. Martignac connects to NOMAD, such that all simulation data generated are automatically normalized and stored according to the FAIR principles. We present several prototypical Martini workflows, including system generation of simple liquids and bilayers, as well as free-energy calculations for solute solvation in homogeneous liquids and drug permeation in lipid bilayers. By connecting to the NOMAD database to automatically pull existing simulations and push any new simulation generated, Martignac contributes to improving the sustainability and reproducibility of molecular simulations.

The Solvation of Na+ Ions by Ethoxylate Moieties Enhances Adsorption of Sulfonate Surfactants at the Air-Water Interface

HypothesisExperiments show pronounced synergy in the reduction of surface tension when the nonionic surfactant Poly(oxy-1,2-ethanediyl), .alpha.-tris(1-phenylethyl)phenyl-.omega.-hydroxy- (Ethoxylated tristyrylphenol, EOT) is mixed with the anionic surfactant Sodium 4-dodecylbenzenesulfonate (NaDDBS). We hypothesize that the synergism is due to counterion (cation) effects. This would be unusual as one of the surfactants is nonionic. To test this hypothesis, the molecular mechanisms responsible need to be probed using experiments and simulations. ApproachThe interfacial properties of mixtures comprising EOT and NaDDBS are investigated using equilibrium molecular dynamics (MD) simulations. Free energy calculation using thermodynamic integration and umbrella sampling methods are employed to analyze the molecular interactions at surface and reveal the role of counterion solvation on the results observed. Simulation snapshots and trajectories are interrogated to confirm the findings. FindingsSimulation results indicate that the ethoxylate moieties solvate Na+ ions, forming long-lasting cation-EOT complexes. Free energy calculations suggest that these complexes are more stable at the interface than in the bulk, likely because of changes in the dielectric properties of water. The cation-EOT complexes, in turn, cause a stronger affinity between the interface and NaDDBS when EOT is present. Similar studies conducted for mixtures of EOT and cationic surfactant Dodecylammonium chloride (DAC) do not show evidence of Cl− ions solvation via the ethoxylate moieties, while the DAC headgroup was found to form hydrogen bonds with the EOT headgroup. This suggests that the mechanisms observed are somewhat ion specific.

Enhanced photocatalytic hydrogen and oxygen evolution activity by two-dimensional van der Waals AlSb/ZnO heterostructure: A first-principles study

Photocatalytic water splitting facilitates the generation of green hydrogen energy by transforming renewable solar energy into chemical energy. This paper investigated the electronic, optical, and photocatalytic properties of AlSb/ZnO van der Waals (vDW) heterostructure using density functional theory. AlSb/ZnO, a semiconductor heterostructure with an indirect bandgap, was energetically stable with a formation energy of −0.4 eV as well as dynamically and thermally stable. The band edges of the 2D heterostructure maintained the essential redox energy levels for complete water splitting, allowing hydrogen and oxygen generation. Moreover, the heterostructure exhibited a high absorption coefficient in the visible region of the solar spectrum compared to the individual AlSb and ZnO monolayers. We revealed low barrier potential at neutral pH conditions for oxygen and hydrogen evolution reactions from the Gibbs free energy calculation without any external potential. Our study additionally showed the solar-to-hydrogen efficiency of 27.93% and a carrier utilization efficiency of 42.83%, indicating the AlSb/ZnO heterostructure as an excellent water splitting photocatalyst with remarkable potential for fuel cells and energy storage applications.

Simulation of rapid sand filters to understand and design sequential iron and manganese removal using reactive transport modelling

Iron (Fe2+), manganese (Mn2+), and ammonium (NH4+) oxidation processes were studied in three single media and three dual media full-scale rapid sand filters (RSFs) using reactive transport modelling (RTM) in PHREEQC and parameter estimation using PEST. Here, we present the insights gained into the spatial distribution of Fe and Mn mineral coatings in RSFs and its influence on the oxidation sequence and rates. Fe2+ and Mn2+ oxidation predominantly occurred simultaneously in the RSFs, contrary to the expected sequential oxidation based on Gibbs free energy calculations. During backwashing, RSF grains become fully mixed, which initiates heterogeneous Mn2+ oxidation on Mn-coated grains that end up in the top layer. The resulting grains have a mixed Fe/Mn mineral coating, which is limiting heterogeneous Mn2+ oxidation due to the limited Mn mineral surface available. Mixed coatings did not seem to affect Fe2+ oxidation rates, instead oxidation rates were increasing at lower pH. We found that RSFs can be designed to spatially separate Fe2+ and Mn2+ oxidation, which results in optimal conditions for Mn2+ oxidation. The RSF needs to consist of two layers with varying density to inhibit mixing and complete Fe2+ oxidation should occur in the top layer. The developed RTM can be used to estimate the depth at which Fe2+ oxidation is complete, and thus the ideal intersection depth of the two layers. A novel perspective is provided on how mineral coating distribution in single and dual media filters influence removal rates and the sequence of oxidation, which contributes to the design of more efficient groundwater filters.

Expression of PPAR-γ TF by newly synthesized thiazolidine-2,4-diones to manage glycemic control: Insights from in silico, in vitro and experimental pharmacology in wistar rats.

In pursuit of novel antidiabetic agents to combat type II diabetes mellitus, our study focused on identifying pharmacophoric features responsible for PPAR-γ expression, a key regulator of glucose homeostasis and lipid metabolism. This goal was achieved through pharmacophore model generation and screening of rationally designed library of thiazolidine-2,4-dione hybrids (7a-7f). The top hits were synthesized, characterized, and evaluated for their in vitro and in vivo antidiabetic activities. Among these, compounds 7b and 7c emerged as promising candidates, exhibiting significant in vitro inhibitory activity against human pancreatic α-amylase (HPA) and human liver α-glucosidase (HLAG) enzymes, along with enhanced glucose uptake in L6 myotube cell lines. Specifically, compound 7b showed 29.04±1.13µM HPA inhibition, 34.21±1.16µg/mL HLAG inhibition, and 77.12±1.02% glucose uptake, while compound 7c displayed 28.35±1.01µM HPA inhibition, 26.21±1.17µM HLAG inhibition, and 78.54±0.54% glucose uptake. Mechanistic studies revealed a dose-dependent increase in PPAR-γ transcription factor expression, supported by molecular docking that showed favorable interactions with key residues TYR473, SER289, and HIE323. Molecular dynamics simulations confirmed the stability of these interactions, and MM/GBSA binding free energy calculations indicated potential for further optimization. In vivo studies in STZ-induced diabetic Wistar rats demonstrated significant improvements in glucose homeostasis, insulin sensitivity, and lipid metabolism, with a notable decrease in triglycerides and VLDL levels. Compound 7c also showed an improved pharmacokinetic profile with a half-life of 4.01h and an elimination rate constant of 0.325, compared to compound 7b. Both compounds enhanced glycogen content and antioxidant biomarkers, with a high safety profile (LD50 of 500mg/kg). Overall, compound 7c stands out as a promising lead for further development, with compound 7b also showing strong potential, providing valuable insights for future antidiabetic drug development efforts.

Molecular dynamics exploration of cacophony protein interactions with brood volatiles in honey bee colonies

The cacophony protein is a key component of honey bee biology that has been investigated concerning hygienic behavior. The voltage-gated calcium channel subunit α1 appears to play a significant role in modulating neuronal activity associated with the detection and response to compromised brood within honey bee colonies. Despite its essential role, the molecular mechanisms underpinning hygienic behavior remain incompletely understood. Recent research suggests that the expression of the cacophony protein is linked to the efficiency of hygienic behavior, where colonies with enhanced hygienic behavior exhibit distinct patterns of cacophony expression. Understanding the role of cacophony in honey bee behavior provides insights into the molecular mechanisms underlying social interactions within bee colonies, with implications for enhancing pollination services and mitigating threats to honey bee populations. Therefore, the present study focused on unraveling and characterizing its structure and function, a bioinformatics approach involving sequence and phylogenetic analysis. Homology modeling developed three-dimensional models of cacophony protein for Apis cerana and A. mellifera. Molecular docking studies were performed for various brood pheromones and volatiles, triggering hygienic behavior in honey bees, against cacophony providing computational insights into their molecular interactions. Binding free energy calculations using MM/PBSA and MM/GBSA consistently demonstrate a higher affinity of γ-octalactone for AcerCAC protein (−21.77 ± 3.01 kcal/mol and −24.81 ± 4.07 kcal/mol respectively) compared to AmelCAC protein (−20.03 ± 3.01 kcal/mol and −21.47 ± 3.19 kcal/mol respectively). This study lays a theoretical foundation for further studies regarding the mechanism of interaction ofcacophony with hygienic behavior.

A Comprehensive Genetic Analysis of Mycotoxin-Producing Penicillium expansum Isolated from River Water Using Molecular Profiling, DNA Barcoding, and Secondary Structure Prediction

This study marks the first report on the genetic characterization of Penicillium expansum strain capable of mycotoxin production isolated from river water. Situated in Ganagalawanipeta village, Srikakulam, Andhra Pradesh, India, where river water serves as a vital resource, our investigation probed the presence of pathogenic opportunistic fungi adept at mycotoxin synthesis. Over six months, 30 samples were collected to assess their occurrence. This article revolves around the use of morphological traits for Penicillium genus identification. Precise species determination involved PCR analysis using universal primers ITS1 and ITS4, followed by sequence analysis through NCBI-BLASTn and the ITS2 database. The analysis indicated a striking 99.49% genetic similarity to Penicillium expansum isolate MW559596 from CSIR-National Institute of Oceanography, Goa, an Indian isolate, with a resultant 600-base pair fragment. This sequence was officially cataloged as OR536221 in the NCBI GenBank database. Sequence and phylogenetic assessments were conducted to pinpoint the strain and geographical origin. Notably, the ribosomal nuclear ITS region displayed significant inter- and intra-specific divergence, manifested in DNA barcodes and secondary structures established via minimum free energy calculations. These findings provide crucial insights into the genetic diversity and potential mycotoxin production of P. expansum isolates, shedding light on the environmental repercussions and health risks associated with river water contamination from agricultural and aquaculture effluents. This pioneering research advances our understanding of mycotoxin-producing fungi in aquatic environments and underscores the imperative need for water quality monitoring in regions reliant on such water sources for their sustenance and livelihoods.

In silico screening and identifying phytoconstituents of Withania somnifera as potent inhibitors of BRCA1 mutants: A therapeutic against breast cancer

Breast CAncer gene 1 (BRCA1) is an anti-oncogene that helps the cell repair damaged DNA and preserve genetic material. BRCA1 also acts as a cell growth suppressor and produces tumor suppressor gene (TSG) proteins, i.e., BRCA1 protein. Remarkably, BRCA1 mutations account for 90 % of hereditary breast cancer and a majority of hereditary ovarian cancer. Hence, we have considered three mutants of BRCA1 (R1699W, R1699Q, T1700A) in this study and adopted an in-silico approach to find the best possible phytochemical to inhibit these mutated proteins, enabling early breast cancer diagnosis. Perceiving the importance, many natural molecules from ancient medicinal plants are considered for molecular docking. Our findings suggest that though many molecules bind actively with the receptor's active site, the top three phytoconstituents (27-Deoxy-14-hydroxywithaferin A, Withacoagulin, Somniferanolide) of Withania somnifera, commonly known as Ashwagandha, have high binding affinities and suitable pharmacokinetic properties, making these natural compounds potential drug candidates. Further, molecular dynamics (MD) simulation and the binding free energy calculation show stability and thermodynamically favourable. We can, therefore, draw the conclusion that these lead compounds act as potential inhibitors against BRCA1. However, wet lab experiments and clinical trials are recommended to ascertain its efficacy, hence the development of novel BRCA1 inhibitors.

DFT insights into the role of penta-SiC₂ in enhancing Li-S battery performance through polysulfide anchoring

The interactions between soluble Li2Sn species (S8, Li2S8, Li2S6, Li2S4, Li2S2, and Li2S) and the penta-SiC2 (p-SiC2) surface were examined to assess its suitability as an anchoring material for Li-S batteries using Density Functional Theory (DFT) calculations. Our analysis of the structural and electronic properties of these species revealed their most stable configurations and associated binding energies. The findings indicate that p-SiC2 has moderate binding energies with Li2Sn species, which implies that it can serve as a moderate anchoring material, helping to prevent the dissolution of polysulfides into the electrolyte. Bader charge analysis confirmed the transfer of charge from Li atoms to S atoms and highlighted the role of p-SiC2 as a charge acceptor, thereby enhancing its anchoring effect. Furthermore, Gibbs free energy calculations showed that the reduction of Li2S2 to Li2S is the rate-limiting step in the sulfur redox reaction, underscoring the catalytic role of p-SiC2. This study offers valuable insights into the potential application of p-SiC2 as a functional material in Li-S batteries, effectively balancing the interaction between Li2Sn species and the anchoring surface to enhance battery performance.

Enhancement of Mo-Pb flotation separation using gallic acid as a molybdenite depressant: Investigating flotation behavior and mechanism

In the flotation separation of Mo-Pb bulk concentrate and the purification process of Pb-containing molybdenite concentrate, depressants are typically added to depress galena or molybdenite, aiming to obtain high-quality flotation products. Previous studies have focused on the depression of galena. In this study, gallic acid (GA) was utilized as a molybdenite depressant during Mo-Pb flotation separation. Single mineral flotation experiments showed that pH notably influenced galena and molybdenite flotation with GA, particularly at pH 10, displaying the most substantial recovery difference. Mixed mineral flotation experiments revealed GA’s selective depression on molybdenite. At the optimal dosage of GA, the Mo recovery was reduced by 76.62 percentage points, while the Pb recovery remained unaffected. The depression and separation mechanisms of GA were investigated using contact angle, infrared spectroscopy, Zeta potential, inductively coupled plasma optical emission spectrometer (ICP-OES), X-ray photoelectron spectroscopy (XPS) analysis, first-principles calculations analysis, and interface interaction free energy calculations. The results indicate that GA treatment significantly reduces the hydrophobicity of molybdenite surfaces; however, it slightly enhances the hydrophobicity of galena surfaces. At pH 10, the primary species in GA solution is HGA3-. It adsorbs on PbO species of the galena surface as Pb-GA complexes and tends to detach from the surface at high adsorption capacity, resulting in galena not being depressed by GA. Differently, GA adsorbs on the molybdenite surface through hydrophobic attraction force, rendering it hydrophilic. Additionally, after treatment with potassium butyl xanthate (PBX), the hydrophobicity of GA-treated galena is significantly enhanced, while the hydrophobicity of GA-treated molybdenite is not restored. This is because PBX can adsorb stably on GA-treated galena, but its adsorption on GA-treated molybdenite is hindered by the pre-adsorbed GA.

Hypothermia Exposes Hidden Epitopes in Influenza A Hemagglutinin and Potentiates the Binding of Neutralizing Antibodies

AbstractInfluenza viruses are an important cause of human morbidity and mortality. Influenza uses hemagglutinin, a trimeric surface protein whose monomers are composed of a head and a stalk domain, for immune evasion and cell entry. As the head domain is under constant antigenic drift, eliciting neutralizing antibodies through vaccination against its evolutionarily more conserved stalk domain is a key goal in the treatment of this infection. It is unknown how temperature affects the formation of hemagglutinin‐antibody complexes, particularly with respect to temperatures relevant for the human respiratory tract. Using molecular dynamics simulations and free energy calculations, we determined that bending of hemagglutinin's head domains, an initial step in the process of cell attachment, is present at hypothermia (36 °C), but not at higher temperatures. These conformational changes lead not only to exposure of new epitopes in its stalk domains, but also to enhanced binding of a neutralizing antibody.