Free Energy Values Research Articles

Exploring the Reactivity of Flavins with Nucleophiles Using a Theoretical and Experimental Approach.

Covalent adducts of flavin cofactors with nucleophiles play an important role in non-canonical function of flavoenzymes as well as in flavin-based catalysis. Herein, the interaction of flavin derivatives including substituted flavins (isoalloxazines), 1,10-ethylene-bridged flavinium salts, and non-substituted alloxazine and deazaflavin with selected nucleophiles was investigated using an experimental and computational approach. Triphenylphosphine or trimethylphosphine, 1-nitroethan-1-ide, and methoxide were selected as representatives of neutral soft, anionic soft, and hard nucleophiles, respectively. The interactions were investigated using UV/Vis and 1H NMR spectroscopy as well as by DFT calculations. The position of nucleophilic attack estimated using the calculated Gibbs free energy values was found to correspond with the experimental data, favouring the addition of phosphine and 1-nitroethan-1-ide into position N(5) and methoxide into position C(10a) of 1,10-ethylene-bridged flavinium salts. The calculated Gibbs free energy values were found to correlate with the experimental redox potentials of the flavin derivatives tested. These findings can be utilized as valuable tools for the design of artificial flavin-based catalytic systems or investigating the mechanism of flavoenzymes.

Machine Learning-Guided Discovery of AcrB and MexB Efflux Pump Inhibitors.

Multidrug efflux pump is one of the reasons behind the antimicrobial inactivity related to infection caused by Gram-negative pathogens. The inner membrane resistance-nodulation-cell division transporter proteins, AcrB and MexB, in association with outer membrane proteins, TolC and OprM, are responsible for the extrusion of a broad range of substrates, followed by recognizing them. Although various inhibitors were proposed to stop the efflux activity of the transporter protein, none of them had been approved clinically. Our study aims to identify potent inhibitor-like molecules employing supervised classification models trained upon the molecular descriptors of previously known inhibitors. Based on the intrinsic minimum inhibitory concentration (MIC) values of the reported inhibitors, they were classified into highly potent and less potent categories. A total of 10 different classification models were built using various molecular descriptors; among them, support vector machine, Random Forest, AdaBoost, and LightGBM models appeared to deliver promising results with >80% accuracy. These top four models were implemented on a library of 5043 to obtain 8 hit molecules after the multistep filtering process. To assess their activity toward AcrB and MexB, several molecular dynamics simulations of their ligand-bound structures were performed. We also calculated the binding free-energy values and analyzed other structural properties. Mol.3488 of the unknown molecules showed higher binding affinities for both AcrB and MexB. Also, the presence of "pyridopyrimidone" and "benzothiazole" moieties in the molecules and "V"-shaped orientation of ligands inside the deep binding pocket increase the binding affinity, thereby higher inhibitory properties.

Investigation of the effects of solvent on oxygen evolution reactions on the surface of magnesium oxide

In this research, due to the importance of oxygen evolution reactions (OER) in the production of hydrogen gas, the effects of the solvent on the OER steps on the magnesium oxide surface have been studied. For this purpose, the difference in free energy value in OER steps on the Magnesium oxide surface for two systems (in the presence and the absence of solvent) have been investigated using molecular dynamics (MD) simulation and thermodynamic integration (TI). These results are in perfect agreement with the results obtained from ab initio molecular dynamics simulations and quantum mechanics calculations. Our findings show that the presence of water solvent around the surface of magnesium oxide has a crucial role on OER and leads to an increase more than twofold in the free energy of all steps. Also, the presence of the solvent has the most effect on the third step of OER, and its ΔG increases by about 1.9 eV. This fact can be attributed to the approach of the water molecules to the substrate spontaneously, which increases the probability of forming hydrogen bonds and the number of contacts, leading to more favorable thermodynamic reactions. Close inspection of the calculated binding energies between the substrate and the intermediates confirms that the binding energy of OER's second step is significantly higher than the other steps and is the velocity determining step.

Illuminating a Solvent-Dependent Hierarchy for Aromatic CH/π Complexes with Dynamic Covalent Glyco-Balances.

CH/π interactions are prevalent among aromatic complexes and represent invaluable tools for stabilizing well-defined molecular architectures. Their energy contributions are exceptionally sensitive to various structural and environmental factors, resulting in a context-dependent nature that has led to conflicting findings in the scientific literature. Consequently, a universally accepted hierarchy for aromatic CH/π interactions has remained elusive. Herein, we present a comprehensive experimental investigation of aromatic CH/π complexes, employing a novel approach that involves isotopically labeled glyco-balances generated in situ. This innovative strategy not only allows us to uncover thermodynamic insights but also delves into the often less-accessible domain of kinetic information. Our analyses have yielded more than 180 new free energy values while considering key factors such as solvent properties, the interaction geometry, and the presence and nature of accompanying counterions. Remarkably, the obtained results challenge conventional wisdom regarding the stability order of common aromatic complexes. While it was believed that cationic CH/π interactions held the highest strength, followed by polarized CH/π, nonpolarized CH/π, and finally anionic CH/π interactions, our study reveals that this hierarchy can be subverted depending on the environment. Indeed, the performance of polarized CH/π interactions can match or even outcompete that of cationic CH/π interactions making them a more reliable stabilization strategy across the entire spectrum of solvent polarity. Overall, our results provide valuable guidelines for the selection of optimal interacting partners in every chemical environment, allowing the design of tailored aromatic complexes with applications in supramolecular chemistry, organocatalysis, and/or material sciences.

Molecular Docking Study of Pramipexole Derivatives as Radiopharmaceutical Candidates for Brain Imaging

Neurodegenerative diseases are a global priority disease. According to the World Health Organization (WHO), it is estimated that by 2050, there will be 152 million people with neurodegenerative diseases. Currently, the method used for brain imaging is PET/CT, with the most widely used radiopharmaceutical being 18F-FDG [7,8]. 18F-FDG is used to determine brain glucose metabolism, however the 18F-FDG does not have a specific receptor. Pramipexole compounds can cross the blood-brain barrier and have high specificity for dopamine receptors. By modifying and labelling the structure of pramipexole derivatives, it is expected to obtain pramipexole derivatives with a good affinity to the dopamine receptor. In order to reduce the risk of failure, radiation hazard, and research funds, in this research, a molecular docking study was carried out using the targeted docking method between dopamine receptor proteins and 22 pramipexole derivatives using AutoDock 4, GaussView software for structure preparation, Gaussian software for energy calculation, and Biovia Discovery Studio for structure visualization. The experimental results showed that the free binding energy of pramipexole derivatives for the dopamine receptor was obtained in the range of -2.81 to -5.84 kcal/mol. The best free binding energy value was obtained for compound PD-7, with a free binding energy value of -5.84 kcal/mol, while the RMSD value obtained was 0.6 A°, and amino acid residues that interacted with compound PD-7 among others: Leu347, Leu343, Tyr198, Leu199, Glu202, Phe201, and Val203 with hydrophobic and hydrogen bond interactions. The PD-7 compound was labeled using the radioisotope iodine-131 based on the free binding energy value. From the experimental results, compound 131I-PD-7 showed a free binding energy value of -4.66 kcal/mol and interacts with the similar amino acid residues as compound PD-7. These results indicate that the compound 131I-PD-7 is a potential candidate to be studied further as a radiopharmaceutical candidate for brain imaging.

The potentiality of isoflavones from Derris robusta (DC.) Benth. against α-glucosidase.

The four recently described isoflavones, derrisrobustones A-D, and eight known isoflavones extracted from Derris robusta (DC.) Benth. (Leguminosae) were identified as potential isoflavones for α-glucosidase inhibitory activity. However, the inhibitory ability of each isoflavone was quite different and the structural and dynamical properties of the isoflavones in the binding with α-glucosidase have not been studied. In this study, the molecular dynamics (MD) simulation and the molecular mechanics generalized Born surface area (MM/GBSA) methods were applied to gain insight into isoflavones bound with the α-glucosidase active site. The results found that the isoflavones with a hydroxy substituent could be stabilized in the α-glucosidase active site with low values of the binding free energy, especially derrisrobustone D and derrubone. The isoflavones, except for derrubone, were bound with α-glucosidase by means of electrostatic force effectively.

Advancing imine metal chelates for corrosion inhibition across diverse environments: A novel perspective

Using a suite of techniques, including potentiodynamic polarization, electrochemical impedance spectroscopy (EIS), and open circuit potential measurements, we investigated the corrosion resistance of transition metal chelates derived from Schiff base ligands against mild steel, copper oxide, aluminum, stainless steel, and high-carbon steel in acidic environments containing varying concentrations of hydrochloric acid, hydroxide ions, and sulfate ions at 25 °C. Spectral, quantitative, and physico-chemical analyses were employed to characterize the compounds under investigation. Our findings reveal a significant inhibition of corrosion across various steel substrates in the tested media by the studied compounds. Moreover, we observed an enhancement in corrosion inhibition efficacy with increasing concentrations of the investigated complexes. Notably, the negative values of Gibb's free adsorption energy (ΔG°ads) challenge the applicability of the Langmuir adsorption isotherm, suggesting a novel perspective on corrosion control mechanisms. Our study underscores the potential of Schiff bases and related transition metal chelates as effective corrosion inhibitors, providing insights into their utilization and factors influencing their application in corrosion mitigation strategies.

Физико-химические трансформации сапонитсодержащего материала при его активации измельчением

Structural-phase transformations on the surface of powder systems of saponite-containing material after mechanical dispersion have been studied. The degree of crystallinity, adsorption capacity and specific surface energy depending on the time mode of grinding were used as compared information characteristics. It has been established that, despite the fact of the constancy of the degree of crystallinity, mechanical grinding of saponite-containing raw materials leads to its activation, which is expressed by a proportional increase in the sorption capacity of the obtained powders, an increase in the concentration of active adsorption centers and the value of the specific free surface energy. An increase in the time of mechanical grinding of a saponite-containing material leads to the production of samples with an increased (compared to the initial material) surface hydrophilicity.

Insights from in silico study of receptor energetics of SARS-CoV-2 variants.

The emergence of new variants of the novel coronavirus SARS-CoV-2 with increased infectivity, superior virulence, high transmissibility, and unmatched immune escape has demonstrated the adaptability and evolutionary fitness of the virus. The subject of relative order of the binding affinity of SARS-CoV-2 variants with the human ACE2 (hACE2) receptor is hotly debated and its resolution has implications for drug design and development. In this work, we have investigated the energetics of the binding of receptor binding domain (RBD) of SARS-CoV-2 variants of concern (VOCs): Beta (B.1.351), Delta (B.1.617.2), Omicron (B.1.1.529), variant of interest (VOI): Kappa (B.1.617.1), and Delta Plus (B.1.617.2.1) variant with the human ACE2 receptor by using the umbrella sampling (US) method. Our work indicates that Delta and Delta Plus variants have greater values of the US binding free energy than Wild-type (WT), whereas Beta, Kappa, and Omicron variants have lower values. Further analysis of hydrogen bonding, salt bridges, non-bonded interaction energy, and contact surface area at the RBD-hACE2 interface establish Delta as the variant with the highest binding affinity among these variants.

Sulphur-atom positional engineering in perylenimide: structure-property relationships and H-aggregation directed type-I photodynamic therapy.

An innovative design strategy of placing sulfur (S)-atoms within the pendant functional groups and at carbonyl positions in conventional perylenimide (PNI-O) has been demonstrated to investigate the condensed state structure-property relationship and potential photodynamic therapy (PDT) application. Incorporation of simply S-atoms at the peri-functionalized perylenimide (RPNI-O) leads to an aggregation-induced enhanced emission luminogen (AIEEgen), 2-hexyl-8-(thianthren-1-yl)-1H-benzo[5,10]anthra[2,1,9-def]isoquinoline-1,3(2H)-dione (API), which achieves a remarkable photoluminescence quantum yield (Φ PL) of 0.85 in aqueous environments and established novel AIE mechanisms. Additionally, substitution of the S-atom at the carbonyl position in RPNI-O leads to thioperylenimides (RPNI-S): 2-hexyl-8-phenyl-1H-benzo[5,10]anthra[2,1,9-def]isoquinoline-1,3(2H)-dithione (PPIS), 8-([2,2'-bithiophen]-5-yl)-2-hexyl-1H-benzo[5,10]anthra[2,1,9-def]isoquinoline-1,3(2H)-dithione (THPIS), and 2-hexyl-8-(thianthren-1-yl)-1H-benzo[5,10]anthra[2,1,9-def]isoquinoline-1,3(2H)-dithion (APIS), with distinct photophysical properties (enlarged spin-orbit coupling (SOC) and Φ PL ≈ 0.00), and developed diverse potent photosensitizers (PSs). The present work provides a novel SOC enhancement mechanism via pronounced H-aggregation. Surprisingly, the lowest singlet oxygen quantum yield (Φ Δ) and theoretical calculation suggest the specific type-I PDT for RPNI-S. Interestingly, RPNI-S efficiently produces superoxide (O2˙-) due to its remarkably lower Gibbs free energy (ΔG) values (THPIS: -40.83 kcal mol-1). The non-toxic and heavy-atom free very specific thio-based PPIS and THPIS PSs showed selective and efficient PDT under normoxia, as a rare example.

Enhanced adsorption of carbon sphere by doping with titania nanotubes for crystal violet removal: isotherm, kinetics, and thermodynamic studies.

In this study, the carbon sphere (Cs) has been prepared and modified by titania nanotubes (TNTs) to be utilized as an adsorbent toward crystal violet (CV) dye as a model for cationic dyes from aqueous solution. The prepared TNTs@Cs composites has been characterized by various techniques such as XRD, SEM, and TEM analysis. The adsorption analysis displayed that the adsorption capacity of CV dye onto the modified Cs with TNTs is 92.5 mg g-1, which is much higher than that achieved by pristine Cs (12.5 mg g-1). Various factors that influence the overall adsorption processes, such as pH, contact time, initial CV dye concentration, adsorbent weight, and temperature, were studied. The TNTs@Cs76.7 composite showed the highest removal percentage of 99.00% at optimum conditions. The adsorption isotherm analysis showed that the experimental data of adsorption CV dye fitted better with the Langmuir isotherm model with R 2 of 0.999, and the estimated maximum adsorption capacity was 84.7 mg g-1. On the other hand, the adsorption kinetic study showed that the adsorption of CV follows the pseudo-second order kinetic model with an equilibrium adsorption capacity (q e) of 10.66, 18.622, 47.61, and 48.31 mg g-1 for Cs, TNTs@Cs93, TNTs@Cs86.8, and TNTs@Cs76.7 composites, respectively. The thermodynamic analysis showed negative free energy (ΔG) values, this indicates that the adsorption of CV is a spontaneous and feasible process. Furthermore, the ΔH and ΔS are positive values that indicate an endothermic adsorption process. Furthermore, the prepared TNTs@Cs76.7 composite displayed remarkable adsorption stability and the removal efficiency of CV remains at 96.3% after five cycles.

Transition metal single-atoms supported on hexagonal ZnIn2S4 monolayers for the hydrogen evolution reaction.

Herein, we report a series of 5d transition metal (TM) single atoms supported on ZIS as promising catalysts for the hydrogen evolution reaction using first-principles calculations. The binding behaviors of TMs with the ZIS surface in single-atom catalyst formation are analysed using the adsorption energy (Eads), partial density of states (PDOS), charge density difference (CDD), and crystal orbital Hamilton population (COHP). The TM@ZIS (TM = Ta, W, Re, Os, Ir, and Pt) shows excellent hydrogen evolution performance with the Gibbs free energy (ΔGH*) values from -0.120 to 0.128 eV. The Tafel and Heyrovsky reaction mechanisms to drive H2 formation are also identified.

Cyclodextrin-enhanced photo-induced fluorescence of tau-fluvalinate, molecular modelling of inclusion complexes and determination in natural waters.

The effect of adding organized supramolecular systems such as β-cyclodextrin (β-CD) and hydroxypropyl-β-cyclodextrin (HP-β-CD) on the photochemically-induced fluorescence (PIF) spectral properties of tau-fluvalinate (TFV) in aqueous solutions was examined. The influence of pH, UV irradiation time and photoproduct stability on the cyclodextrin-enhanced photochemically-induced fluorescence intensity was also investigated. The spectral changes associated with the inclusion process yielded values for the formation constants of TFV inclusion complexes between 450 and 640 M-1, which were calculated using the nonlinear iterative regression approach least squares. In addition, host-guest interaction was clearly determined by PIF enhancement and a 1 : 1 stoichiometry was found for the β-CD and HP-β-CD complexes formed with TFV. The negative free energy (ΔG°) value indicated that the reaction of TFV with cyclodextrins was thermodynamically favorable. Furthermore, the structures of inclusion complexes of TFV with cyclodextrins were elucidated by 3-21G ab initio calculations. The limits of detection and quantification obtained ranged between 1.3 and 4.0 ng mL-1 and from 4.4 to 13.0 ng mL-1 in β-CD and HP-β-CD media, respectively. The analytical application in tap and river water samples yielded satisfactory mean recoveries ranging from 98.12 to 102.97%. Due to its sensitivity and ease of use, this method can be reliably applied to routine analysis.

Application of central composite design to optimization of Yellow Tartarazine and Methylene Blue environmentally clean adsorption by untreated walnut shells

Climate change poses a real threat to the water security by altering the precipitation patterns and other weather variables, desirability function (df) was used to determine the interactive effects and optimize with the Central Composite Design (CCD) of important variables such as initial dyes concentration (Co : 20–100 mg L–1), solution pH (1.5–11), temperature (20–60 °C) and adsorbent dosage (0.1–1.3 g L–1) for the removal of toxic Yellow Tartarazine (YT) and Methylene Blue (MB) onto Untreated Walnut Shells (UWS). The analysis of variance (ANOVA) was applied for the treatment of experimental data, fitted by a second-order polynomial equation and multiple regression analysis. The ideal conditions optimized according to the response surfaces are initial concentration (COyt = 60 mg L–1, pHYT = 1.5, DYT = 0.7 g L–1 and TYT = 40 °C for YT and (Co MB = 60 mL–1, pHMB = 8.5, DMB= 0.7 g L–1 and TMB = 40 °C for MB). Experimental confirmation allowed to accurately determine the maximum eliminations (76.15) for YT and (76.81%) for MB under optimal conditions. Several error analysis equations were used to measure the goodness of fit. Kinetic studies showed that the adsorption kinetic data are well modeled by a pseudo-second-order model. Among the different models used to fit the experimental isotherms, the Langmuir model gave the best correlation with capacities qmax of 55.55 and 50.00 mg/g, for YT and MB respectively at 40 oC. The effect of temperature on the adsorption isotherms allowed to arrive at the thermodynamic functions, the negative values of free energy ( ΔG°), enthalpy ( ΔH°) and entropy ( ΔS°) indicate a spontaneous and exothermic adsorption of physical nature, confirmed by the activation energy ( Ea) for both dyes. The elimination of pollutants by new-generation adsorbents has proven to be very effective by application of statistical methodology, Central composite design and the desirability function.

INTEGRATIVE BIOINFORMATICS APPROACHES TO THE UNDERSTANDING OF CHRISTININ MOLECULAR MECHANISM AS JANUS KINASE (JAK) INHIBITORS FOR SUPPRESSING HYPERINFLAMMATION IN COVID-19

COVID-19 is a significant worldwide health concern. The exaggerated immune response known as the "cytokine storm" is a key factor in this illness, and there are potential ways to address it. Janus kinase (JAK) inhibitors are a type of medication that might reduce inflammation and improve the body's production of antibodies. Pharmacokinetic profiles, toxicity characteristics, biological activities prediction, and molecular docking simulation will be conducted to discover, assess, and investigate the molecular interactions of Christinin compounds, including Christinin-A, Christinin-B, Christinin-C, and Christinin-D derived from Ziziphus spina-christi leaves as Janus kinase (JAK) inhibitors using bioinformatics approaches. Based on the molecular docking simulation, it can be concluded that the Christinin compound has a molecular interaction with Janus Kinase (JAK). However, Christinin-A and Christinin-C compounds have better affinity than Christinin-B and Christinin-D compounds, with binding free energy values of −7.59 kcal/mol and −5.37 kcal/mol, respectively. Therefore, these two compounds can be used as candidates for Janus Kinase (JAK) inhibitors in preventing hyperinflammation in the COVID-19 infectious disease

Sequence determinants of protein phase separation and recognition by protein phase-separated condensates through molecular dynamics and active learning.

Elucidating how protein sequence determines the properties of disordered proteins and their phase-separated condensates is a great challenge in computational chemistry, biology, and biophysics. Quantitative molecular dynamics simulations and derived free energy values can in principle capture how a sequence encodes the chemical and biological properties of a protein. These calculations are, however, computationally demanding, even after reducing the representation by coarse-graining; exploring the large spaces of potentially relevant sequences remains a formidable task. We employ an "active learning" scheme introduced by Yang et al. (bioRxiv, 2022, https://doi.org/10.1101/2022.08.05.502972) to reduce the number of labelled examples needed from simulations, where a neural network-based model suggests the most useful examples for the next training cycle. Applying this Bayesian optimisation framework, we determine properties of protein sequences with coarse-grained molecular dynamics, which enables the network to establish sequence-property relationships for disordered proteins and their self-interactions and their interactions in phase-separated condensates. We show how iterative training with second virial coefficients derived from the simulations of disordered protein sequences leads to a rapid improvement in predicting peptide self-interactions. We employ this Bayesian approach to efficiently search for new sequences that bind to condensates of the disordered C-terminal domain (CTD) of RNA Polymerase II, by simulating molecular recognition of peptides to phase-separated condensates in coarse-grained molecular dynamics. By searching for protein sequences which prefer to self-interact rather than interact with another protein sequence we are able to shape the morphology of protein condensates and design multiphasic protein condensates.

Computer-aided drug discovery of natural antiviral metabolites as potential SARS-CoV-2 helicase inhibitors

In our quest to discover effective inhibitors against severe acute respiratory syndrome coronavirus 2 helicase, a diverse set of more than 300 naturally occurring antiviral metabolites was investigated. Employing advanced computational techniques, we initiated the selection process by analyzing and comparing the co-crystallized ligand (VXG) of the severe acute respiratory syndrome coronavirus 2 helicase protein (PDB ID: 5RMM) to identify compounds with structurally similar features and potential for comparable binding. Through structural similarity and pharmacophore research, 13 compounds that shared important characteristics with VXG were pinpointed. Subsequently, these candidates were subjected to molecular docking to identify seven compounds that demonstrated favorable energy profiles and accurate binding to the severe acute respiratory syndrome coronavirus 2 helicase. Among these, mycophenolic acid emerged as the most promising candidate. To ensure the safety and viability of the selected compounds, we conducted ADMET tests, which confirmed the favorable characteristics of mycophenolic acid, and the safety of atropine and plumbagin. Building on these results, we performed additional analyses on mycophenolic acid, including various molecular dynamics simulations. These investigations demonstrated that mycophenolic acid exhibited optimal binding to the severe acute respiratory syndrome coronavirus 2 helicase, maintaining flawless dynamics throughout the simulations. Furthermore, the Molecular Mechanics Poisson–Boltzmann Surface Area tests provided strong evidence that mycophenolic acid successfully formed a stable connection with the severe acute respiratory syndrome coronavirus 2 helicase, with a calculated free energy value of −294 kJ mol−1. These encouraging findings provide a solid foundation for further research, including in vitro and in vivo studies, on the three identified compounds. The potential efficacy of these compounds as treatment options for coronavirus-19 warrants further exploration and may hold significant promise in the ongoing fight against the pandemic.

Modulation of the conformational landscape of the PDZ3 domain by perturbation on a distal non-canonical α3 helix: decoding the microscopic mechanism of allostery in the PDZ3 domain.

While allosteric signal transduction is crucial for protein signaling and regulation, the dynamic process of allosteric communication remains poorly understood. The third PDZ domain (PDZ stands for the common structural domain shared by the postsynaptic density protein (PSD95), Drosophila disc large tumor suppressor (DlgA), and zonula occludens-1 protein (ZO-1)) serves as a classic example of a single-domain allosteric protein, demonstrating a long-range coupling between the C-terminal α helix (known as the α3 helix) and ligand binding. A molecular level understanding of how the α3 helix modulates the ligand binding affinity of the PDZ3 domain is still lacking. In this study, extensive molecular dynamics simulations corroborated with principal component analysis (PCA), ligand binding free energy calculations, energetic frustration analysis and Markov state model analysis are employed to uncover such molecular details. We demonstrate the definite presence of a binding competent closed-like state in the conformational landscape of wild-type PDZ3. The population modulations of this closed state and other binding incompetent states in the landscape due to α3-truncation/mutation of PDZ3 are explored. A correlation between the closed state population and calculated binding free energy is established, which supports the conformation selection mechanism. Covariance analysis identified the presence of correlated motion between two distant loops (β1-β2 and β2-β3) in the wild-type PDZ3 system, which weakened due to truncation/mutation in the distant α3 helix. It has also been observed that whenever the α3 helix was perturbed, the β2-β3 loop got further away from the binding groove and it is found to be correlated with the binding free energy values. Energetic frustration analysis of the PDZ3 domain also showed that the β2-β3 loop is highly frustrated. Finally, MSM analysis revealed a relevant timescale (closed to open state transition), which is similar to the observed experimental signal transduction timescale for the system. These observations led to the conclusion that the distantly located α3 helix plays a pivotal role in regulating the conformational landscape of the PDZ3 domain, determining the ligand binding affinity and resulting in allosteric behavior of the domain.

Tuning the product selectivity of single-atom catalysts for CO2 reduction beyond CO formation by orbital engineering.

Electrochemical CO2 reduction (CO2R) is one of the promising strategies for developing sustainable energy resources. Single-atom catalysts (SACs) have emerged as efficient catalysts for CO2R. However, the efficiency of SACs for the formation of reduction products beyond two-step CO formation is low due to the lower binding strength of the CO intermediate. In this study, we present an orbital engineering strategy based on density functional theory calculations and the fragment molecular orbital approach to tune product selectivity for the CO2R reaction on macrocycle based molecular catalysts (porphyrin and phthalocyanine) and extended SACs (graphene and covalent organic frameworks) with Fe, Co, and Ni dopants. The introduction of neutral axial ligands such as imidazole, pyridine, and trimethyl phosphine to the metal dopants enhances the binding affinity of the CO intermediate. The stability of the catalysts is investigated through the thermodynamic binding energy of the axial ligands and ab initio molecular dynamics simulations (AIMD). The grand canonical potential method is used to determine the reaction free energy values. Using a unified activity volcano plot based on the reaction free energy values, we investigated the catalytic activity and product selectivity at an applied potential of -0.8 V vs. SHE and a pH of 6.8. We found that with the imidazole and pyridine axial ligands, the selectivity of Fe-doped SACs towards the formation of the methanol product is improved. The activity volcano plot for these SACs shows a similar activity to that of the Cu (211) surface. The catalytic activity is found to be directly proportional to the sigma-donating ability of the axial ligands.

Assessing the catalytic potential of novel halogen substituted carbene NHC (F, Cl, Br, I) catalysts in [3 + 2] cycloaddition reactions: A computational investigation.

This study investigated the catalytic behavior of NHC-X ligands (X = F, Cl, Br, I) in cycloaddition reactions, focusing on both mononuclear and binuclear pathways. Using NCI (noncovalent interaction), RDG (reduced density gradient), ELF (electron localization function), and LOL (localized orbital locus) computational analyses, the electronic interactions and stability of the ligands were examined. The results showed that NHC-Cl exhibited the least steric hindrance and strongest transition state stabilization, making it the most efficient catalyst. NHC-F also demonstrated strong stabilization, particularly in the binuclear pathway. In contrast, NHC-Br showed moderate efficiency, whereas NHC-I was the least effective owing to higher Gibbs free energy values and greater steric hindrance, especially in polar solvents such as water and acetonitrile. This study emphasizes the crucial role of solvent effects and thermodynamic factors in influencing the catalytic efficiency. These findings provide a framework for optimizing NHC-based catalysts for chemical transformations.