Relative Gibbs Free Energies Research Articles

Consecutive Trifluoromethylation of C88(7) Fullerene: A Theoretical Study

AbstractThe trifluoromethylation of C88(7) fullerene has been systematically studied using an energy‐controlled consecutive CF3 addition approach. The thermodynamically favored C88(7)(CF3)2n isomers with 2n = 2–20 were predicted at the DFT B3LYP‐D3BJ/6–311G* level of theory for the first time, in harmony with the two experimentally characterized isomers C88(7)(CF3)12/16. It was found that these stable isomers are formed mainly by 1,4‐additions of CF3 groups, and meanwhile, there are a few stable isomers with isolated CF3 groups for 2n ≤ 12, with ortho addition for 2n > 12, and with triple‐hexagon‐junction addition for the highest degree of trifluoromethylation (2n ≥ 18). The addition patterns of CF3 groups were discussed in terms of the local structural motif of the pristine cage and the formation of stabilizing substructures of local aromaticity. The possible trifluoromethylation pathways of C88(7) were proposed on the basis of the relative Gibbs free energies. The results show that almost all the intermediate isomers for the thermodynamically most stable isomers of C88(7)(CF3)2n possess low relative Gibbs free energies (below 14 kJ·mol−1). Moreover, the hardness, chemical potential, electrophilicity index, electron affinity, HOMO and LUMO energies, and HOMO–LUMO gaps of the thermodynamically most stable C88(7)(CF3)2n isomers were also calculated.

Contrasting Historical and Physical Perspectives in Asymmetric Catalysis: ΔΔG≠ versus Enantiomeric Excess

AbstractWith the rise of machine learning (ML), the modeling of chemical systems has reached a new era and has the potential to revolutionize how we understand and predict chemical reactions. Here, we probe the historic dependence on utilizing enantiomeric excess (ee) as a target variable and discuss the benefits of using relative Gibbs free activation energies (ΔΔG≠), grounded firmly in transition‐state theory, emphasizing practical benefits for chemists. This perspective is intended to discuss best practices that enhance modeling efforts especially for chemists with an experimental background in asymmetric catalysis that wish to explore modelling of their data. We outline the enhanced modeling performance using ΔΔG≠, escaping physical limitations, addressing temperature effects, managing non‐linear error propagation, adjusting for data distributions and how to deal with unphysical predictions,in order to streamline modeling for the practical chemist and provide simple guidelines to strong statistical tools. For this endeavor, we gathered ten datasets from the literature covering very different reaction types. We evaluated the datasets using fingerprint‐, descriptor‐, and graph neural network‐based models. Our results highlight the distinction in performance among varying model complexities with respect to the target representation, emphasizing practical benefits for chemists.

Contrasting Historical and Physical Perspectives in Asymmetric Catalysis: ▵▵G≠ versus Enantiomeric Excess.

With the rise of machine learning (ML), the modeling of chemical systems has reached a new era and has the potential to revolutionize how we understand and predict chemical reactions. Here, we probe the historic dependence on utilizing enantiomeric excess (ee) as a target variable and discuss the benefits of using relative Gibbs free activation energies (ΔΔG≠), grounded firmly in transition-state theory, emphasizing practical benefits for chemists. This perspective is intended to discuss best practices that enhance modeling efforts especially for chemists with an experimental background in asymmetric catalysis that wish to explore modelling of their data. We outline the enhanced modeling performance using ΔΔG≠, escaping physical limitations, addressing temperature effects, managing non-linear error propagation, adjusting for data distributions and how to deal with unphysical predictions,in order to streamline modeling for the practical chemist and provide simple guidelines to strong statistical tools. For this endeavor, we gathered ten datasets from the literature covering very different reaction types. We evaluated the datasets using fingerprint-, descriptor-, and graph neural network-based models. Our results highlight the distinction in performance among varying model complexities with respect to the target representation, emphasizing practical benefits for chemists.

Experiment Meets Theory: Cope Rearrangements and Thermal E/Z Isomerisations of Terpenoid Hydrocarbons

AbstractSeveral terpenes are known that can undergo a Cope rearrangement. Prominent examples include germacrene A and hedycaryol that show a Cope rearrangement already slightly above room temperature. In the present study the Cope rearrangements of several terpenes and eventually co‐occurring thermal E/Z isomerisations were investigated experimentally for their minimum required temperatures and for their states of equilibrium. The experimental findings were supported by computational assessments of free activation energies (ΔG≠) as well as relative Gibbs free energies of the reactants (ΔG).

Simultaneous Native Mass Spectrometry Analysis of Single and Double Mutants To Probe Lipid Binding to Membrane Proteins.

Lipids are critical modulators of membrane protein structure and function. However, it is challenging to investigate the thermodynamics of protein-lipid interactions because lipids can simultaneously bind membrane proteins at different sites with different specificities. Here, we developed a native mass spectrometry (MS) approach using single and double mutants to measure the relative energetic contributions of specific residues on Aquaporin Z (AqpZ) toward cardiolipin (CL) binding. We first mutated potential lipid-binding residues on AqpZ, and mixed mutant and wild-type proteins together with CL. By using native MS to simultaneously resolve lipid binding to the mutant and wild-type proteins in a single spectrum, we directly determined the relative affinities of CL binding, thereby revealing the relative Gibbs free energy change for lipid binding caused by the mutation. Comparing different mutants revealed that W14 contributes to the tightest CL binding site, with R224 contributing to a lower affinity site. Using double mutant cycling, we investigated the synergy between W14 and R224 sites on CL binding. Overall, this novel native MS approach provides unique insights into the binding of lipids to specific sites on membrane proteins.

Measurements of Thermodynamic Data of Water in Ca-Bentonite by Relative Humidity Method

Buffer material (compacted bentonite), one of the engineered barrier elements in the geological disposal of a high-level radioactive waste, develops swelling stress due to groundwater penetration from the surrounding rock mass. Montmorillonite is the major clay mineral component of bentonite. Even previous studies provide few mechanical and thermodynamic data on Ca-montmorillonite. In this study, thermodynamic data on Ca-montmorillonite were obtained as a function of water content by measuring relative humidity (RH) and temperature. The activities of water and the relative partial molar Gibbs free energies of water were determined from the experimental results, and the swelling stress of Ca-bentonite was calculated using the thermodynamic model and compared with measured data. The activities of water and the relative partial molar Gibbs free energies obtained in the experiments decreased with decreasing water content in water contents lower than about 25%. This trend was similar to that of Na-montmorillonite. The swelling stress calculated based on the thermodynamic model was approximately 200 MPa at a montmorillonite partial density of 2.0 Mg/m3 and approximately 10 MPa at a montmorillonite partial density of 1.4 Mg/m3. The swelling stresses in the high-density region (around 2.0 Mg/m3) were higher than that of Na-montmorillonite and were similar levels in the low-density region (around 1.5 Mg/m3). Comparison with measured data showed the practicality of the thermodynamic model.

Swelling Stress of Bentonite: Thermodynamics of Interlayer Water in K-Montmorillonite in Consideration of Alteration

The buffer material that makes up the geological disposal system of high-level waste swells by contact with groundwater and seals space with rock mass and fractures in rock mass. The buffer material has a function of mechanical buffer with rock pressure, and swelling stress is important in this case. The alteration of bentonite may occur due to the initial replacement of cations (Na+ ions) in the interlayer with K+ ions upon contact with groundwater, but there are no studies on the swelling stress of K-bentonite. In this study, the author prepared K-montmorillonite samples and obtained thermodynamic data on interlayer water as a function of water content using a relative humidity method. The swelling stress was analyzed based on a thermodynamic model developed in earlier studies and compared with measured data. The activity and the relative partial molar Gibbs free energy of porewater decreased with decreasing water content in the region, below approximately 15%. This behavior significantly differs from that of other ions, such as Na. The swelling stress calculated based on the thermodynamic model and date occurred in the region of high density of 1.9 Mg/m3 with montmorillonite partial density. It was indicated for the first time that K-bentonite scarcely swells under realistic design conditions.

Potassium tert‐Butoxide‐Catalyzed Selective Synthesis of 1,4‐Benzodioxepines via 7‐exo/7‐endo‐dig Cyclization of Alkynol: Experimental and DFT Study

AbstractA new method utilizing base catalysis is outlined for the synthesis of 1,4‐benzodioxepines, introducing a unique scaffold containing a seven‐membered ring heterocycle. The reaction proceeded under thermal conditions, with no waste was generated during the transformation, highlighting its remarkable atom efficiency and environmental friendliness. A straightforward metal‐free reaction condition utilizing 2‐propynyloxy benzyl alcohols as starting material and a catalytic amount of t‐BuOK in mesitylene at 100 °C for 1 hour was employed for this intramolecular cyclization transformation, resulting in the formation of 1,4‐Benzodioxepines in good to excellent yields and high regio‐ and diastereo‐selectivity. The density functional theory (DFT) calculations yielded the relative internal energy (U), enthalpy (H), and Gibbs free energy (G) values for all possible products, aligning closely with our experimental data.

Structural connectivity of 18‐Crown‐6/H+/L‐tryptophan noncovalent complexes in gas phase and in solution: Delineating host–guest–solvent interactions in solution from gas phase structures

AbstractWe investigate the structural correlation of noncovalent crown ether/H+/L‐tryptophan (CR/TrpH+) host–guest complexes in the solution phase with those in the gas phase generated through electrospray ionization/mass spectrometry (ESI/MS) techniques. We perform quantum chemical calculations to determine their structures, relative Gibbs free energies, and infrared spectra. We compare the calculated infrared (IR) spectra with the IR multiphoton dissociation (IRMPD) spectra observed for the 18‐Crown‐6/TrpH+ complex by Polfer and co‐workers [J. Phys. Chem. A 2013, 117, 1181–1188] for assigning the IR bands. We observe that the carboxyl group remains “naked,” lacking hydrogen bonding with the CR unit in the gas phase, and that this most stable conformer originates from the corresponding lowest Gibbs free energy structure in solution. Based on these findings, we propose that gas phase host–guest complexes directly correlate with those in solution, reinforcing the possibility of obtaining invaluable information about host–guest–solvent interactions in solution from the structure of the host–guest pair in the gas phase.

Structure prediction of physiological bis(amino acidato)copper(II) species in aqueous solution: The copper(II) compounds with l-glutamine and l-histidine

Neutral (l-histidinato)(l-glutaminato)copper(II) [Cu(His)(Gln)] has been established as the most abundant ternary copper(II) amino acid compound of the exchangeable copper(II) pool in blood plasma. The experimental studies of Cu(His)(Gln) and bis(glutaminato)copper(II) [Cu(Gln)2] in solutions did not specify their complete geometries. To determine the geometries, this paper investigates the conformers, energy landscapes, and a structure–magnetic parameters relation of Cu(Gln)2 and Cu(His)(Gln) by the density functional theory (DFT) calculations. We assume a glycine-like coordination of Gln (other coordination patterns are dismissed because of steric reasons), and three His in-plane copper(II) binding modes. The conformational analyses are performed in the gas phase and implicitly modeled aqueous solution. The reliability of the DFT relative electronic and Gibbs free energies of the Cu(His)(Gln) conformers is confirmed by benchmarking against the corresponding energies obtained by the domain-based local pair natural orbital coupled-cluster method with singles, doubles, and perturbative triples [DLPNO-CCSD(T)]. Several cis- and trans-Cu(His)(Gln) conformers with His in the histaminate-like and glycine-like modes have low Gibbs free energies, and the greatest estimated metal-binding affinities. The DFT-calculated magnetic parameters of the low-energy conformers reproduce best the experimental electron paramagnetic resonance parameters measured in aqueous solutions for trans- and cis-Cu(Gln)2 conformers having two oxygen atoms (either from Gln or water molecules) at the apical positions, and Cu(His)(Gln) conformers having His in the histaminate-like mode with an apically placed carboxylato oxygen atom. The predicted conformational flexibility of His‑copper(II)-amino acid compounds may be connected with their physiological abundance, and the role in copper(II) exchange reactions in blood plasma.

CONFORMATIONAL STUDY OF MOLECULES IN A BIOLOGICAL ENVIRONMENT, DESIGN OF INHIBITORS OF HUMAN AMINOPEPTIDASE M1 IMPLICATED IN CANCER THERAPY

Objective: A novel subnanomolar anticancer hydroxamic acid containing drug candidates, inhibitors of human M1 aminopeptidase (APN) a recent validated target and has reached the predicted subnanomolar range of inhibitory potency. Methods: A quantitative structure activity relationships (QSAR) complexation model has been developed from a compounds of 37 hydroxamic acid derivatives (AHD1-37 as training set, TS) to establish a linear correlation between the calculated relative Gibbs free energies (GFE: ΔΔGcom) of APN-AHDx complex formation and the experimental inhibition potency (Kiexp). The predictive power of the QSAR model was then validated first with 9 other AHDs not included in the TS and thereafter with the generation of a 3D-QSAR-PH4 pharmacophore (PH4) model to screen the AHD chemical subspace built as a virtual combinatorial library of more than 58,644 AHD analogs). Finally the best PH4 hits were evaluated with the initial QSAR model for predicted potency (Kipre) and pharmacokinetic profile. Results: The QSAR model linear correlation equation: pKiexp=-0.1901×∆∆Gcom + 8.2886 , R2=0.94, the subsequent PH4 model linear correlation between experiment and PH4-estimated Ki: pKiexp=1.0006× pKipre + 0.0028, R2=0.79 documents the high predictive power of this approach. Finally the screening of the virtual library of AHD analogs yielded 95 orally bioavailable candidates the best reaching a predicted potency (Kipre) of 50 pM and displaying favorable pharmacokinetic profile. Conclusion: The combined use of molecular modeling (QSAR) and in silico PH4-based screening of the hypothetical combinatorial library has resulted in proposed and predicted potent anticancer candidates with a suitable pharmacokinetic profile. Peer Review History: Received: 3 August 2023; Revised: 12 September; Accepted: 25 October, Available online: 15 November 2023 Academic Editor: Dr. Nuray Arı, Ankara University, Turkiye, ari@ankara.edu.tr Received file: Reviewer's Comments: Average Peer review marks at initial stage: 7.0/10 Average Peer review marks at publication stage: 9.0/10 Reviewers: Prof. Hassan A.H. Al-Shamahy, Sana'a University, Yemen, shmahe@yemen.net.ye Prof. Dr. A. Hakan AKTAŞ, Süleyman Demirel University, Faculty of Science and Art, Department of Chemistry, Isparta-Turkey, hakanaktas@sdu.edu.tr

Stereoselective Synthesis of a Novel Series of Dispiro-oxindolopyrrolizidines Embodying Thiazolo[3,2-a]benzimidazole Motif: A Molecular Electron Density Theory Study of the Mechanism of the [3 + 2] Cycloaddition Reaction

A one-pot multi-component reaction was employed for the stereoselective synthesis of a novel set of dispiro-oxindolopyrrolizidines analogs incorporating a thiazolo[3,2-a]benzimidazole scaffold based on the [3 + 2] cycloaddition (32CA) reaction approach. The desired novel dispiro-oxindolopyrrolizidines 9a–d were achieved using the 32CA reaction of new ethylene derivatives based on thiazolo[3,2-a]benzimidazole moiety seven with thiazolidine derivatives eight and different substituted isatin compounds 5a–d (R = H, Cl, NO2, and Br). The final dispiro-oxindolopyrrolizidines cycloadducts were separated, purified, and fully characterized by means of a set of spectroscopic tools including IR, HNMR, CNMR, and MS. The Molecular Electron Density Theory (MEDT) was applied to explain the mechanism and stereoselectivity in the of the key 32CA reaction step. The reactive pseudo(mono)radical electronic structure of the in situ generated azomethine ylides and the high polar character of the corresponding 32CA reactions account for the low computed activation Gibbs free energies and total endo stereoselectivity of this kinetically controlled exergonic reaction. The computed relative Gibbs free activation energies of competitive reaction paths and regioisomers ratio distribution of 80:20 justify the major formation of 9a via the most favorable ortho/endo reaction path.

Design of Cr-PNP catalysts for ethylene tri-/tetramerization assisted by a data-driven approach

The implementation of data-driven methods in the domain of transition metal catalyst design has emerged as an undeniable trend. With the Curtin-Hammett principle, the selectivity of ethylene tri-/tetramerization showed a strong correlation with the relative Gibbs free energy (ΔΔG) of the key transition states. By leveraging the machine learning method, the prediction of ethylene tri-/tetramerization can be accomplished through a database training model, thereby expediting the process of new catalysts design. Herein, we constructed a group of practical descriptors that exhibit a close relationship with the Gibbs free energy, proving to be more valuable in the design of new ligands when compared to extracting elusive descriptors from the sophisticated molecular structure. Through high-throughput screening feature selection, we established an XGBoost machine learning model for Cr bisphosphine (Cr-PNP) catalysts, enabling the power of the prediction of selectivity for ethylene tri-/tetramerization. In this work, the descriptors extracted from precatalysts only take into account the influence of the metal center and the ligands, avoiding the complicated and laborious conformational search required for predicting the selectivity of the new ligands, which effectively reduces the computational costs. Descriptor analysis, guided by the feedback from the model, allows us to identify the most influential factors governing the selectivity, which can be regulated to effectively advance the design of new catalysts. The validation performed with new ligands confirms the well-predictive performance of the model, as evidenced by the relatively low mean absolute error (MAE).

Synthesis, characterization, crystal structure, and DFT study of 3,4-Diphenyl -1H-pyrrolo[2,3-b]pyridine

3,4-Diphenyl-1H-pyrrolo[2,3-b]pyridine, a useful organic building block, was obtained via a four-step reaction and the structure was determined using FT-IR, 1H NMR, 13C NMR, and mass spectrometry, and the single crystals were characterized using X-ray diffraction analysis. The optimal molecular structure, 1-2 (49.95%), was calculated using density functional theory, and was consistent with the structure determined based on single-crystal diffraction; the relative Gibbs free energy of conformer 1-2 was 0.001255 kcal mol−1. In addition, the molecular electrostatic potentials and frontier molecular orbitals of the title compound were investigated, and surface analysis was performed to further reveal its physicochemical properties.

Fragment Linker Prediction Using the Deep Encoder-Decoder Network for PROTACs Drug Design.

A drug discovery and development pipeline is a prolonged and complex process that remains challenging for both computational methods and medicinal chemists and has not been able to be resolved using computational methods. Deep learning has been utilized in various fields and achieved tremendous success in designing novel molecules in the pharmaceutical industry. Herein, we use state-of-the-art techniques to propose a deep neural network, AIMLinker, to rapidly design and generate meaningful drug-like proteolysis targeting chimeras (PROTACs) analogs. The model extracts the structural information from the input fragments and generates linkers to incorporate them. We integrate filters in the model to exclude nondruggable structures guided via protein-protein complexes while retaining molecules with potent chemical properties. The novel PROTACs subsequently pass through molecular docking, taking root-mean-square deviation (RMSD), relative Gibbs free energy (ΔΔGbinding), molecular dynamics (MD) simulation, and free energy perturbation (FEP) calculations as the measurement criteria for testing the robustness and feasibility of the model. The generated novel PROTACs molecules possess similar structural information with superior binding affinity to the binding pockets compared to the existing CRBN-dBET6-BRD4 ternary complexes. We demonstrate the effectiveness of the methodology of leveraging AIMLinker to design novel compounds for PROTACs molecules exhibiting better chemical properties compared to the dBET6 crystal pose.

Structure-Based Design and Pharmacophore-Based Virtual Screening of Combinatorial Library of Triclosan Analogues Active against Enoyl-Acyl Carrier Protein Reductase of Plasmodium falciparum with Favourable ADME Profiles.

Cost-effective therapy of neglected and tropical diseases such as malaria requires everlasting drug discovery efforts due to the rapidly emerging drug resistance of the plasmodium parasite. We have carried out computational design of new inhibitors of the enoyl-acyl carrier protein reductase (ENR) of Plasmodium falciparum (PfENR) using computer-aided combinatorial and pharmacophore-based molecular design. The Molecular Mechanics Poisson-Boltzmann Surface Area (MM-PBSA) complexation QSAR model was developed for triclosan-based inhibitors (TCL) and a significant correlation was established between the calculated relative Gibbs free energies of complex formation (∆∆Gcom) between PfENR and TCL and the observed inhibitory potencies of the enzyme (IC50exp) for a training set of 20 known TCL analogues. Validation of the predictive power of the MM-PBSA QSAR model was carried out with the generation of 3D QSAR pharmacophore (PH4). We obtained a reasonable correlation between the relative Gibbs free energy of complex formation ∆∆Gcom and IC50exp values, which explained approximately 95% of the PfENR inhibition data: pIC50exp=-0.0544×∆∆Gcom+6.9336,R2=0.95. A similar agreement was established for the PH4 pharmacophore model of the PfENR inhibition (pIC50exp=0.9754×pIC50pre+0.1596, R2=0.98). Analysis of enzyme-inhibitor binding site interactions suggested suitable building blocks to be used in a virtual combinatorial library of 33,480 TCL analogues. Structural information derived from the complexation model and the PH4 pharmacophore guided us through in silico screening of the virtual combinatorial library of TCL analogues to finally identify potential new TCL inhibitors effective at low nanomolar concentrations. Virtual screening of the library by PfENR-PH4 led to a predicted IC50pre value for the best inhibitor candidate as low as 1.9 nM. Finally, the stability of PfENR-TCLx complexes and the flexibility of the active conformation of the inhibitor for selected top-ranking TCL analogues were checked with the help of molecular dynamics. This computational study resulted in a set of proposed new potent inhibitors with predicted antimalarial effects and favourable pharmacokinetic profiles that act on a novel pharmacological target, PfENR.

Elastic Electron scattering by thermal mixture of glycine conformers in gas phase

A theoretical study of electron scattering by a thermal mixture of glycine molecules in the energy range from 1 to 10 eV is performed using the UK-RMol codes which are based on the R-Matrix method. The six lowest relative Gibbs free energies glycine conformers considered, Ip, IIp, IIn, IIIp, IIIn and IVn, are significantly populated in thermal mixtures. All these conformers present similar resonance structures in the eigenphase sums: a lower-energy resonance state near 1.8 eV and another at higher-energy above 7 eV. For the six conformers the lowest resonance lies between 1.75 eV and 2.21 eV. The very large dipole moments of 6.32 D and 5.67 D for IIp and IIn, respectively, makes the magnitude of their cross sections significantly larger than other conformers, which increases the average cross sections in thermal mixtures compared with the cross sections of the lowest energy Ip conformer. Three conformer population sets are used to calculate the averaged differential and integral cross sections: two theoretical sets based on the relative Gibbs free energies and another set that aims to mimic experiment based on the observed populations. The averaged cross sections are similar for all population sets, but differ from the Ip conformer cross section. This suggests that, for large and flexible molecules, the computed average cross sections should be used when comparing with experimental data.

Activating HfX2 (X = S, Se and Te) for the hydrogen evolution reaction by introducing defects: a first-principles study.

An ideal catalyst should have a relative hydrogen adsorption Gibbs free energy (ΔGH) close to zero [J. K. Nørskov, et al., J. Electrochem. Soc., 2005, 152, J23]. However, most of the known catalysts cannot reach this standard. Based on first-principles calculations, we studied the hydrogen evolution reaction (HER) catalytic performance of pristine and defect (including vacancy and heteroatom doping) structures in terms of its ΔGH. We found that the ΔGH values of Co-doped HfS2 and P-doped HfSe2 are extremely close to zero, even closer than that of Pt (111), indicating that they are excellent catalysts. Moreover, we found that the source of the HER catalytic performance of Co-doped HfS2 is the reduction of electron accumulation of the active site S atom. Our work provides two potential ideal catalysts and provides guidance for the experimental group to search for suitable catalysts.

Design and In silico Screening of Combinatorial Library of New Herbicidal Analogs of Cycloalka[d]quinazoline-2,4dione−Benzoxazinones Inhibiting Protoporphyrinogen IX Oxidase

We virtually design here an important new weedkiller Cycloalka[d]quinazoline-2,4dione−Benzoxazinones (CQB), inhibitors of Protoporphyrinogen IX Oxidase (PPO). Based on computer-assisted combinatorial chemistry techniques, docking, 3D-QSAR and pharmacophore models we first enumerate, focus and in silico screen a virtual library of CQB analogs substituted at positions R1, R2 and R3. By docking inhibitors into the target active site from the crystal structure (PDB ID: 1SEZ) of PPO in complex with a CQB ligand, 3D models of 29 PPO:CQBx complexes with known observed activity (Kiexp) were prepared to establish a quantitative structure–activity (QSAR) model and linear correlation between relative Gibbs free energy (GFE) of receptor-ligand complex formation (ΔΔGcom) and Kiexp: pKiexp = -0.1664 ×ΔΔGcom + 8.306 (1); R2 = 0.94. A 3D QSAR pharmacophore model (PH4) derived from the QSAR directed our effort to design novel CQB analogs. During the design, an initial virtual library of 118 CQB was focused down and PH4 screened to identify 28 promising novel analogs. Their Ki (Kipre) values were predicted by means of equation (1). The most active analog namely CQB22 display Kipre 22 times superior to that of the reported most active training set ligand 17i. Our survey proposes this compounds to the synthesis and to the assessment on herbicidal.

Boron-doping on the surface mediated low-valence Co centers in cobalt phosphide for improved electrocatalytic hydrogen evolution

Rationally engineering the surface structure of transition metal phosphides (TMPs) could regulate valence state of metal centers (Mδ+) with optimized binding strength of H2O and H* and relative Gibbs free energy (ΔGH*) in alkaline hydrogen evolution reaction (HER). However, the precise location of such metal centers is still challenging due to the limited synthetic methodology. Herein we report the surface-layer-confined doping of boron on cobalt phosphide nanowire arrays (B-CoP) via a controllable surface redox reaction. Nanowire CoP decorated with B-doped surface layer structure has proved to be an outstanding HER electrocatalyst, with an overpotential of 112 mV at 100 mA cm−2. X-ray absorption near edge structure (XANES) and X-ray photoelectron spectroscopy (XPS) analysis, and theoretical results demonstrate that B-doping induced electron redistribution of Co with electron-rich features. Such low-valence Co centers coordinated with B can achieve strong affinity toward H2O molecules and optimized ΔGH* to accelerating reaction kinetics.