Quantum Mechanical Calculations Research Articles

Unprecedented carbonic anhydrase inhibition mechanism: Targeting histidine 64 side chain through a halogen bond.

2,2'-Thio-bis(4,6-dichlorophenol), namely bithionol, is a small molecule endowed with a multifaceted bioactivity. Its peculiar polychlorinated phenolic structure makes it a suitable candidate to explore its potentialities in establishing interaction patterns with enzymes of MedChem interest, such as the human carbonic anhydrase (hCA) metalloenzymes. Herein, bithionol was tested on a panel of specific hCAs through the stopped-flow technique, showing a promising micromolar inhibitory activity for the hCA II isoform. X-ray crystallographic studies revealed an unprecedented halogen-bond interaction between one chlorine of bithionol and the N3(ε) atom of the hCA II catalytically active histidine residue, His64. Then, quantum mechanics calculations based on the fragment molecular orbital method allowed us to estimate the strength of this bond (~2.9 kcal/mol) and highlighted the contribution of a rich hydrophobic interaction network within the isoenzyme. Interestingly, the compound inactivity against the hCA III isoform, characterized by His64Lys and Leu198Phe mutations, supported the key role played by halogen bonding in the enzyme affinity. This finding might pave the way for the development of a new class of hCA inhibitors characterized by such chemical features, with the halogen bond being a key ligand-receptor interaction.

Mechanism of ultrafast flavin photoreduction in the active site of flavoenzyme LSD1 histone demethylase.

Photoreduction of oxidized flavins has a functional role in photocatalytic and photoreceptor flavoproteins. In flavoproteins without light-dependent physiological functions, ultrafast, reversible flavin photoreduction is supposedly photoprotective by nature, and holds potential for nonnatural photocatalytic applications. In this work, we combine protein mutagenesis, ultrafast spectroscopy, molecular dynamics simulations and quantum mechanics calculations to investigate the nonfunctional flavin photoreduction in a flavoenzyme, lysine-specific demethylase 1 (LSD1) which is pivotal in DNA transcription. LSD1 harbors an oxidized flavin adenine dinucleotide (FAD) cofactor and multiple electron-donating residues in the active site. Upon photoexcitation, the FAD cofactor is photoreduced in <200 fs by electron transfer (ET) from nearby residue(s), and the charge pairs recombine in ca. 2 ps. Site-directed mutagenesis pinpoints a specific tryptophan residue, W751, as the primary electron donor, whereas a tyrosine residue, Y761, despite being located closer to the flavin ring, does not effectively contribute to the process. Based on a hybrid quantum-classical computational approach, we characterize the W751-FAD and Y761-FAD charge-transfer states (CTW751 and CTY761, respectively), as well as the FAD locally excited state (LEFAD), and demonstrate that the coupling between LEFAD and CTW751 is larger than those involving CTY761 by an order of magnitude, rationalizing the experimental observations. More generally, this work highlights the role of the intrinsic protein environment and details of donor-acceptor molecular configurations on the dynamics of short-range ET involving a flavin cofactor and amino acid residue(s).

Tunnel barriers for Fe-based spin valves providing high spin-polarized current.

Employing density functional theory for ground state quantum mechanical calculations and the non-equilibrium Green's function method for transport calculations, we investigate the potential of CdS, ZnS, Cd3ZnS4, and Zn3CdS4 as tunnel barriers in magnetic tunnel junctions for spintronics. Based on the finding that the valence band edges of these semiconductors are dominated by pz orbitals and the conduction band edges by s orbitals, we show that Δ1 symmetry filtering of the Bloch states in magnetic tunnel junctions with Fe electrodes results in high tunneling magnetoresistances and high spin-polarized current (up to two orders of magnitude higher than in the case of the Fe/MgO/Fe magnetic tunnel junction).

Identification of promising dipeptidyl peptidase-4 and protein tyrosine phosphatase 1B inhibitors from selected terpenoids through molecular modeling.

Investigating novel drug-target interactions is crucial for expanding the chemical space of emerging therapeutic targets in human diseases. Herein, we explored the interactions of dipeptidyl peptidase-4 and protein tyrosine phosphatase 1B with selected terpenoids from African antidiabetic plants. Using molecular docking, molecular dynamics simulations, molecular mechanics with generalized Born and surface area solvation-free energy, and density functional theory analyses, the study revealed dipeptidyl peptidase-4 as a promising target. Cucurbitacin B, 6-oxoisoiguesterin, and 20-epi-isoiguesterinol were identified as potential dipeptidyl peptidase-4 inhibitors with strong binding affinities. These triterpenoids interacted with key catalytic and hydrophobic pockets of dipeptidyl peptidase-4, demonstrating structural stability and flexibility under dynamic conditions, as indicated by dynamics simulation parameters. The free energy analysis further supported the binding affinities in dynamic environments. Quantum mechanical calculations revealed favorable highest occupied molecular orbital and lowest unoccupied molecular orbital energy profiles, indicating the suitability of the hits as proton donors and acceptors, which likely enhance their molecular interactions with the targets. Moreover, the terpenoids showed desirable drug-like properties, suggesting their potential as safe and effective dipeptidyl peptidase-4 inhibitors. These findings may pave the way for the development of novel antidiabetic agents and nutraceuticals based on these promising in silico hits. Not applicable.

Decoherence, entanglement, and information in the electron double-slit experiment with monitoring

This paper considers a theoretical model of the double-slit experiment with electrons whose paths are monitored. This monitoring, inspired by a recent text by Maudlin, is performed by the Coulomb scattering of the electron by a proton. A simple quantum mechanical calculation is presented, inspired in part by a recent experimental demonstration of this famous thought experiment. The results illustrate the relationship between entanglement and the loss of coherence in the interference pattern. The tradeoff between the visibility of interference and the information gained by measurement is also explored. This calculation can provide advanced undergraduates insight into decoherence, entanglement, and quantum information.

A General Nonbonded Force Field Based on Accurate Quantum Mechanics Calculations for Elements H-La and Hf-Rn.

Noncovalent interactions (NCI) play a central role in numerous physical, chemical, and biological phenomena. An accurate description of NCI is the key to success for any theoretical study in such areas. Although quantum mechanics (QM) methods such as dispersion-corrected density functional theory are sufficiently accurate, their applications are practical only for <300 atoms and <100 ps of simulation time. Thus, empirical force fields (FF) have generally been the only choice for systems with thousands to millions of atoms and for nanoseconds and longer. We want to develop a FF that can be applied to applications of thousands to millions of atoms with an accuracy comparable to QM methods. As the first step, we develop here a new general nonbonded potential (GNB) based on a novel functional form with four adjustable parameters for each element. We report here parameters for elements H-La, Hf-Rn (excluding lanthanides and actinides) by fitting the interaction energy of molecular complexes to QM calculations using the accurate Head-Gordon ωB97M-V density functional. We performed extensive testing of GNB for organic molecules, organometallic molecules, and metal organic-framework (MOF) systems. The mean absolute errors of GNB are 0.37 kcal/mol for the dispersion and mixed groups of the S66 × 8 benchmark set, 0.35 kcal/mol for CO2 adsorption on MOF materials, and 4.53 kcal/mol for the XTMC43 benchmark. GNB outperforms existing FF and in many cases has accuracy comparable to that of QM methods such as PBE-D3. GNB can potentially replace the nonbonded part of existing FFs in a wide range of applications.

Fullerene-Doped Poly(ionic liquids) as Small Molecular Gas Sensors-Control of Intermolecular Interactions.

Here, we investigate the interactions between five representative gaseous analytes and two poly(ionic liquids) (PILs) based on the sulfopropyl acrylate polyanion in combination with the alkylphosphonium cations, P4,4,4,4 and P4,4,4,8, and their nanocomposites with fullerenes (C60, C70) to reveal the potential of PILs as sensitive layers for gas sensors. The gaseous analytes were chosen based on their molecular size (all of them containing two carbon atoms) and variation of functional groups: alcohol (ethanol), nitrile (acetonitrile), aldehyde (acetaldehyde), halogenated alkane (bromoethane), and carboxylic acid (acetic acid). The six variations of PILs-P4,4,4,4SPA (1), P4,4,4,4SPA + C60 (1 + C60), P4,4,4,4SPA + C70 (1 + C70), and P4,4,4,8SPA (2), P4,4,4,8SPA + C60 (2 + C60), P4,4,4,8SPA + C70 (2 + C70)-were characterized by UV-vis and Raman spectroscopy, and their interactions with each gaseous analyte were studied using electrochemical impedance spectroscopy. Exposure of all PIL samples to acetaldehyde, bromoethane, and ethanol leads to a decrease in the diffusion coefficient, while exposure to acetic acid reveals an increase. Fullerene-doping significantly enhances the response to the analyte. Semiempirical quantum mechanical xTB-GFN2 calculations revealed that hydrogen bonding and proton transfer events play an important role during the detection process.

Enhancing the structural and optoelectronic properties of carboxymethyl cellulose sodium filled with ZnO/GO and CuO/GO nanocomposites for antimicrobial packaging applications.

One of the biggest challenges in food packaging is the creation of sustainable and eco-friendly packaging materials to shield foods from ultraviolet (UV) photochemical damage and to preserve the distinctive physical, chemical, and biological characteristics of foods throughout the supply chain. Accordingly, this study focuses on enhancing the UV shielding properties and biological activity of carboxylmethyl cellulose sodium (CMC) through modifications using zinc oxide (ZnO), copper oxide (CuO), and graphene oxide (GO) using the solution casting technique. The hybrid nanocomposites were characterized by fourier-transform infrared (FTIR) spectrophotometer, ultraviolet-visible (UV-Vis) spectrophotometer, scanning electron microscopy (SEM), energy-dispersive X-ray spectroscopy (EDX), and x-ray diffraction (XRD). Significant interactions between CMC and the metal oxide/GO nanocomposites were revealed by FTIR analysis, which reflects the formation of hydrogen bonding between CMC and the nanocomposites. XRD confirmed the functionalization of CMC with ZnO/GO and CuO/GO nanocomposites. Additionally, the CMC film showed a decrease in the optical bandgap from 5.53 to 3.43eV with improved UV shielding capacity. Moreover, the composite films had excellent refractive index and optical conductivity values of 1.97 and 1.56 × 1010Ωcm- 1, respectively. SEM and EDX analysis confirmed the formation of ZnO/GO and CuO/GO within the CMC matrix. Thus, dedicates that the CMC nanocomposites have promising applications in packaging materials. These results were confirmed by the quantum mechanical calculations utilizing density functional theory (DFT). Total dipole moment (TDM), frontier molecular orbitals (FMOs), chemical reactivity descriptors, and molecular electrostatic potential (MESP) maps were all studied using the B3LYP/LanL2DZ model. The TDM and FMO investigations revealed that the CMC/CuO/GO model has the highest TDM (84.031 Debye) and the smallest band gap energy (0.118eV). Moreover, CMC's reactivity increased after CuO/GO nanocomposites integration, as demonstrated by MESP mapping. Finally, the antibacterial activity of pure CMC, CMC/ZnO/GO, and CMC/CuO/GO nanocomposite films was evaluated against Staphylococcus aureus and Escherichia coli. The zones of inhibition data showed that both CMC/ZnO/GO and CMC/CuO/GO exhibited higher antibacterial activity than CMC alone, particularly against S. aureus. The inhibition zones for CMC/ZnO/GO and CMC/CuO/GO against S. aureus were 16mm and 14mm, respectively, suggesting enhanced susceptibility of S. aureus compared to E. coli. These results highlight the significant potential of ZnO and CuO NPs in improving the antimicrobial efficacy of CMC nanocomposites.

Impact of Intracellular Proteins on μ-Opioid Receptor Structure and Ligand Binding.

Chronic pain is a prevalent problem affecting approximately one out of every five adults in the U.S. The most effective way to treat chronic pain is with opioids, but they cause dangerous side effects such as tolerance, addiction, and respiratory depression, which makes them quite deadly. Opioids, such as fentanyl, target the μ-opioid receptor (MOR), which can then bind to the intracellular Gi protein or the β-arrestin protein. The Gi pathway is primarily responsible for pain relief and potential side effects, but the β-arrestin pathway is chiefly responsible for the unwanted side effects. Ideally, an effective pain medication without side effects would bind to MOR, which would bias signaling solely through the Gi pathway. We used the Bio3D library to conduct principal component analysis to compare the cryo-electron microscopy MOR structures in complex with the Gi versus an X-ray crystallography MOR structure with a nanobody acting as a Gi mimic. Our results agree with a previous study by Munro, which concluded that nanobody-bound MOR is structurally different than Gi-bound MOR. Furthermore, we investigated the structural diversity of opioids that can bind to MOR. Quantum mechanical calculations show that the low energy solution structures of fentanyl differ from the one bound to MOR in the experimental structure, and pKa calculations reveal that fentanyl is protonated in aqueous solution. Glide docking studies show that higher energy structures of fentanyl in solution form favorable docking complexes with MOR. Our calculations show the relative abundance of each fentanyl conformation in solution as well as the energetic barriers that need to be overcome to bind to MOR. Docking studies confirm that multiple fentanyl conformations can bind to the receptor. Perhaps a variety of conformations of fentanyl can stabilize multiple conformations of the MOR, which can explain why fentanyl can induce different intracellular signaling and multiple physiological effects.

QM40, Realistic Quantum Mechanical Dataset for Machine Learning in Molecular Science

The growing popularity of machine learning (ML) and deep learning (DL) in scientific fields is hindered by the scarcity of high-quality datasets. While quantum mechanical (QM) predictions using DL techniques such as graph neural networks (GNNs) and generative models are gaining traction, insufficient training data remains a bottleneck. The QM40 dataset addresses this challenge by representing 88% of the FDA-approved drug chemical space. It includes molecules containing 10 to 40 atoms and composed of elements commonly found in drug molecular structures (C, O, N, S, F, Cl). QM40 offers valuable resources for researchers which include the core QM40 main dataset, containing 16 key quantum mechanical parameters for 162,954 molecules calculated using the B3LYP/6-31G(2df,p) level of theory in Gaussian16, ensuring consistency with established datasets like QM9 and Alchemy. This compatibility allows for future concatenation of QM40 with these datasets. In addition to other valuable information, the QM40 dataset offers the initial and optimized Cartesian coordinates, Mulliken charges, and detailed bond information, including local vibrational mode force constants, which serve as indicators of bond strength. QM40 can be used to benchmark both existing and new methods for predicting QM calculations using ML and DL techniques.

Pseudo‐silapnictene and Bis(pseudo‐silapnictene) – Hyperconjugatively Stabilized Heavier Analogues of Imine and Ethane‐1,2‐diimine

The equilibrium geometry, bonding, and proton affinity of the pseudo‐silapnictenes and the bis(pseudo‐silapnictenes) are explored using computational quantum mechanical calculations carried out at M06/def2‐TZVPP//BP86‐D3(BJ)/def2‐SVP level of theory. The pseudo‐silapnictene 1E features a dicoordinated, monovalent group‐15 center having two lone pairs of σ‐ and π‐local symmetry. Both the lone pairs are stabilized by hyperconjugative donation to the silylene fragment. The extent of hyperconjugative stabilization of π‐type lone pair is higher than that of σ‐type lone pair and is comparable to classical Si‐E π‐bonds. Accordingly, the former interactions can be considered as pseudo‐π‐bonding interactions. The strength of the pseudo‐π‐bond reduces as the group‐15 element changes from nitrogen to bismuth. Hence, 1E can be considered as heavier analogues of imine. Even though these lone pairs are stabilized by hyperconjugative interactions, they are very reactive as indicated by the very high values of first and second proton affinities. In the bis(pseudo‐silapnictene) 2E, two Si‐E pseudo‐π‐bonds formed by hyperconjugative interactions are delocalized over the E‐Si‐Si‐E skeleton. Since the π‐bonds are majorly localized on the group‐15 element, the extent of delocalization is quite less than that of the classical π‐delocalized system. Nevertheless, the bis(pseudo‐silapnictene) can be considered as the heavier analogue of ethane‐1,2‐diimine.

Synthesis, XRD and DFT studies on Pb[ChCN]2 (Ch = O, S, Se) and Pb[SeCN][OH

We report on the synthesis of Pb[ChCN]2 (Ch = O, S, Se) and Pb[SeCN][OH] and their hitherto unknown crystal structures. All products were fully characterized by single-crystal and powder X-ray diffraction. Bulk analysis was performed by Rietveld refinement, elemental analysis, differential scanning calorimetry-thermogravimetric analysis (DSC-TGA), and solid-state Raman spectroscopy. Quantum-mechanical calculations based on the density functional theory allowed optimization of the structural parameters of these lead-based compounds, as well as assessment of their electronic structures and detailed assignment and interpretation of the vibrational spectra. In addition, the origin of bands related to difficulties in assigning the exact position of H atoms in the structures was resolved.

Bipyridine-Containing Optically Active π-Conjugated Polymers Derived from Amino Alcohols: Examination of the Higher-Order Structures, Chiral Recognition, and Metal Coordination Based on Quantum Mechanical and Molecular Dynamics Calculations.

Helical π-conjugated polymers are promising as optically active functional materials. The present paper reports the synthesis of novel bipyridine-containing π-conjugated polymers with optically active amino-alcohol-derived side chains, examination of their higher-order structures, chiral recognition, and metal coordination properties. The polymers adopt a folded helical conformation and aggregate in CHCl3/MeOH depending on the solvent composition, as supported by density functional theory calculations and molecular dynamics simulations. The polymer films showed differences in contact angles with aqueous solutions of (R)- and (S)-alcohols. Addition of some metal chlorides and perchlorates changed the intensity and color of the photoluminescence of the polymers.

Self-Assembly of Supramolecular Double Helix from a Tetrapeptide and Direct Visualization by Scanning Tunneling Microscopy.

This work reports single-crystal X-ray diffraction (XRD), Scanning Tunneling Microscopy (STM), and quantum mechanics calculations of the 310-helical peptide Z-(Aib)2-L-Dap(Boc)-Aib-NHiPr (Aib, α-aminoisobutyric acid; Dap, 2,3-diaminopropionic acid; Z, benzyloxycarbonyl; Boc, t-butoxycarbonyl). The peptide forms a double-helical superstructure, studied by XRD and STM. Such architecture is rare in short peptides. Here, we show, by combining XRD and STM that this intriguing conformational feature is not driven by crystal packing; rather, it is an intrinsic property of this peptide. Indeed, the double helix is clearly detected also by STM, where crystal packing cannot be invoked. XRD reveals that intermolecular H-bonds stabilize two left-handed supra-helices (tertiary structure) that develop around a 6-fold screw axis. Then, two supra-helices are intertwined in a quaternary structure as a left-handed, double supra-helix, where C-H⋯π interactions play a crucial role. STM images show the formation of long, isolated "necklaces" (>110 nm). They are of left and right helical handedness. Their size agrees with the XRD finding. DFT calculations allowed us to weigh the contribution of the different intermolecular interactions in the two single supra-helices and the supramolecular double-helix. Interestingly, we were able to conclude that the contribution of the C-H⋯π interactions to the binding energies is close to 50 %.

Recent Advances in Machine Learning‐Assisted Multiscale Design of Energy Materials

AbstractThis review highlights recent advances in machine learning (ML)‐assisted design of energy materials. Initially, ML algorithms were successfully applied to screen materials databases by establishing complex relationships between atomic structures and their resulting properties, thus accelerating the identification of candidates with desirable properties. Recently, the development of highly accurate ML interatomic potentials and generative models has not only improved the robust prediction of physical properties, but also significantly accelerated the discovery of materials. In the past couple of years, ML methods have enabled high‐precision first‐principles predictions of electronic and optical properties for large systems, providing unprecedented opportunities in materials science. Furthermore, ML‐assisted microstructure reconstruction and physics‐informed solutions for partial differential equations have facilitated the understanding of microstructure–property relationships. Most recently, the seamless integration of various ML platforms has led to the emergence of autonomous laboratories that combine quantum mechanical calculations, large language models, and experimental validations, fundamentally transforming the traditional approach to novel materials synthesis. While highlighting the aforementioned recent advances, existing challenges are also discussed. Ultimately, ML is expected to fully integrate atomic‐scale simulations, reverse engineering, process optimization, and device fabrication, empowering autonomous and generative energy system design. This will drive transformative innovations in energy conversion, storage, and harvesting technologies.

Deep Eutectic Solvents Meet Non-Aqueous Cosolvents: A Modeling and Simulation Perspective-A Tutorial Review.

Deep eutectic solvents (DESs) have recently gained attention due to their tailorable properties and versatile applications in several fields, including green chemistry, pharmaceuticals, and energy storage. Their tunable properties can be enhanced by mixing DESs with cosolvents such as ethanol, acetonitrile, and water. DESs are structurally complex, and molecular modeling techniques, including quantum mechanical calculations and molecular dynamics simulations, play a crucial role in understanding their intricate behavior when mixed with cosolvents. While the most studied cosolvent is water, in some applications, even a small content of water is considered a contaminant, for example, when the processes of interest require dry conditions. Only quite recently have modeling studies begun to focus on DES mixed with cosolvents other than water. This tutorial provides the first comprehensive overview of these studies. It highlights how modern molecular modeling increases our understanding of their structural organization, transport properties, phase behavior, and thermodynamic properties. Additionally, case studies and recent developments in the field are discussed along with the challenges and future directions in molecular modeling of DES in cosolvent mixtures. Overall, this review offers valuable insights into the molecular-level understanding of DES-cosolvent systems and their implications for designing novel solvent mixtures with tailored properties for various applications.

Structural and mechanism-based engineering of sulfotransferase CHST15 for the efficient synthesis of chondroitin sulfate E.

Natural chondroitin sulfate (CS), extracted from animal cartilage, is widely used in the pharmaceuticals and foods. However, contamination with animal-derived heteropolysaccharides presents significant challenges, including potential immune responses. To address this, we developed a green and efficient method for synthesizing chondroitin sulfate E (CSE) via enzymatic synthesis, identifying EcCHST15, a sulfotransferase that catalyzes the conversion of chondroitin sulfate A (CSA) to CSE. We investigated the novel catalytic mechanism of CHST15 through quantum mechanical (QM) calculations and experimental validation, confirming its alignment with the SN2 reaction mechanism. Subsequently, we enhanced the catalytic efficiency of CHST15 using protein engineering, improving the catalytic efficiency from 18.1% in the wild type (WT) to 62.5% in the M7 mutant-a 3.5-fold increase. Finally, we constructed a six-enzyme cascade whole-cell catalyst, achieving a 72.2% conversion of 15 g/L CSA to produce CSE within 24 h. These findings offer a promising strategy for the industrial production of CSE.IMPORTANCECurrent methods for obtaining chondroitin sulfate (CS) primarily rely on tissue extraction and chemical synthesis. However, these approaches are hindered by contamination risks from animal-derived heteropolysaccharides and the technical challenges inherent in complex chemical synthesis, limiting the scalability of industrial CS production. To address this, we developed a green and efficient enzymatic biosynthesis method for chondroitin sulfate E (CSE). By identifying and engineering the sulfotransferase CHST15 from Erpetoichthys calabaricus, we created a mutant (EcCHST15M7) with a 3.5-fold increase in catalytic efficiency toward chondroitin sulfate A (CSA) compared to the wild-type enzyme. Additionally, we constructed a six-enzyme cascade whole-cell biocatalyst, achieving a 72.2% conversion rate from CSA to CSE. This study opens new avenues for the industrial-scale production of CSE through sustainable enzymatic processes.

Polymers in Physics, Chemistry and Biology: Behavior of Linear Polymers in Fractal Structures.

We start presenting an overview on recent applications of linear polymers and networks in condensed matter physics, chemistry and biology by briefly discussing selected papers (published within 2022-2024) in some detail. They are organized into three main subsections: polymers in physics (further subdivided into simulations of coarse-grained models and structural properties of materials), chemistry (quantum mechanical calculations, environmental issues and rheological properties of viscoelastic composites) and biology (macromolecules, proteins and biomedical applications). The core of the work is devoted to a review of theoretical aspects of linear polymers, with emphasis on self-avoiding walk (SAW) chains, in regular lattices and in both deterministic and random fractal structures. Values of critical exponents describing the structure of SAWs in different environments are updated whenever available. The case of random fractal structures is modeled by percolation clusters at criticality, and the issue of multifractality, which is typical of these complex systems, is illustrated. Applications of these models are suggested, and references to known results in the literature are provided. A detailed discussion of the reptation method and its many interesting applications are provided. The problem of protein folding and protein evolution are also considered, and the key issues and open questions are highlighted. We include an experimental section on polymers which introduces the most relevant aspects of linear polymers relevant to this work. The last two sections are dedicated to applications, one in materials science, such as fractal features of plasma-treated polymeric materials surfaces and the growth of polymer thin films, and a second one in biology, by considering among others long linear polymers, such as DNA, confined within a finite domain.

Desing and In Silico Validation of Vitamin B5 and Its Derivatives As A Potential Target Against Cyclophilin A (CyPA)

The title molecule (N-(2,4-dihydroxy-3,3-dimethylbutyryl)b-alanine), DDBBA and its derivatives were selected for theoretical investigations viz geometry optimization, ADME profiling, binding affinity using quantum-mechanical calculations and modelling simulation tools. Geometry optimization by Gaussian 09 program revealed the stability and electrophilic nature of the investigated molecules. In order to depict the charge density distributions that may be related to biological activity, the contour maps of HOMO-LUMO as well as the associated chemical descriptors such as chemical potential (µ), electronegativity (χ), electrophilicity (ω), hardness (η) and softness (σ) were explored. Utilizing molecular docking, the antiviral, antibacterial, and anticancer activities was examined. The docked molecules showed strong propensity for binding to 2HQ6 cancer protein active sites. Vit B5-CH=CF2 and VitB5-CCl3 showed lowest binding energies (-5.861 and -5.478 kcal/mol) and low inhibition constant values (1.43 M). Studies on the (NBO) natural bond orbital, the Mulliken population, and the Fukui function were all analyzed. Further, the interactions between the derivatives and other molecules were studied using Hirshfeld surface analysis.

Catalytic effect of the in-situ rhodium(III) complexes in surfactant medium on the auto-oxidation of 1,2-hydroxyphenylthiourea: A theoretical and experimental study for rhodium(III) sensing

1,2-hydroxyphenylthiourea(HPTU) undergoes auto-oxidation to form an yellow colored dimer. The process of auto-oxidation is enhanced by the presence of trace quantities of transition metal ions and transition metal complexes that act as catalysts. In the current study, catalytic potential of rhodium(III) complexes on the auto-oxidation of 1,2-hydroxyphenylthiourea(HPTU) was studied theoretically using quantum mechanical calculations and experiments were carried out using photometry and fluorometry. DFT studies inferred that [Rh(Py)6]Cl3 showed a better catalytic activity in the dimerization of HPTU. Theoretical studies were subsequently validated through experiments using photometric methods and the range of detection was determined to be 6 ng/mL–100 ng/mL. The detection limit was observed to be 2 ng/mL. Analytical parameters such as pH, reagent concentration, metal ion concentration, appropriate activators and surfactants were established.