Physical Chemistry Research
Volume:12 Issue: 3, Summer 2024

In this study, the solubility of clonazepam (CZP) in binary solvent mixtures of (1-propanol + water) and (2-propanol + water) at five different temperatures was investigated. The solubility of CZP was assessed using the shake-flask technique, while the concentrations of CZP in the solutions were measured utilizing a UV-Vis spectrophotometer. The obtained solubility data were analyzed using the main mathematical models available in this context. The experimental data obtained for CZP dissolution encompassed various thermodynamic properties, including ΔG°, ΔH°, TΔS°, and ΔS°. These properties offer valuable insights into the energetic aspects of the dissolution process. The results revealed that the solubility of CZP in both binary solvent mixtures increased with increasing alcohol concentration and temperature. The mathematical models provided accurate predictions of the solubility of CZP in these binary solvent systems (MRDs% were less than 14.3). Based on the thermodynamic analysis, it was determined that the dissolution of CZP in the examined mixtures is endothermic. Furthermore, the inverse Kirkwood-Buff integrals revealed the presence of preferential hydration of CZP in mixtures that were rich in water as well as those rich in cosolvent.

In their earlier research, the authors explored the correlation of solid-liquid solubility using an updated semi-theoretical equation (Eur. J. Pharm. Sci. 2019, 143, 1-13). This current study applies an Artificial Neural Network (ANN) and a refined Apelblat model to predict the solubility of nine pharmaceutical compounds in pure organic solvents over an extensive temperature range. By training the optimized network using the back-propagation method of the Levenberg-Marquardt algorithm, optimal parameters —such as neurons, hidden layers, and transfer function — were established in the ANN through the utilization of training, testing, and validation data. This network was trained with 764 data points and subsequently tested and validated with 164 data points. A satisfactory correlation of 1.33% was obtained from the enhanced Apelblat model across 1092 data points. The findings from thermodynamic analysis and solubility parameters can optimize the purification process in the synthesis of pharmaceutical compounds.

The present study has been conducted to discover a new inhibitor against lung cancer. A large database comprising more than 500,000 molecules was explored. ADME-Tox study was performed to narrow down the selection to 20,000 molecules. Initially, docking SP was employed due to its faster and less computationally expensive nature. This enabled the identification of numerous molecules with high docking scores. To refine the search, docking XP was then applied to the top 250 molecules with the highest docking scores. Through this process, a single molecule with a significant docking score was identified. A comparison between this molecule and the reference molecule revealed that their docking scores were very close. To gain further insights, a molecular dynamics study was performed. The results indicated that the molecule effectively bound to the target protein and inhibited its activity, suggesting its potential as a therapeutic agent for lung cancer. The newly discovered inhibitor demonstrates several advantages over existing inhibitors, including high potency, selectivity, and favorable ADME-Tox properties.

The ALK tyrosine kinase receptor is a promising target in lung cancer. To estimate ALK-TK inhibitory activity, we used QSAR modeling on heterocyclic compounds with varied structures and a large dataset of 1329 chemicals experimentally reported for anticancer activity against ALK-TK. The developed QSAR model meets various validation criteria, such as R2 = 0.79, Q2LOO = 0.78, Q2LMO = 0.78, R2ex = 0.77, and CCCex = 0.87. In addition, we have used QSAR-based virtual screening found 12 FDA compounds as in-silico hits, some of which could be used in clinical settings as ALK-TK inhibitors with a docking score ranging from -7.10 to -10.57 kcal/mol. For both wild-type and mutant ALK-TK, QSAR-based virtual screening predicted a PIC50 of 9.18 M for the new compound ZINC000150338819 with a docking score of -10.57 kcal/mol (RMSD 1.54Å). MD simulation and MMGBSA investigations confirm that the ZINC000150338819-ALK TK complex is stable for 200 ns for both wild-type and mutant ALK TK. To confirm the in-silico findings, MTT assay reveals that the Ledipasvir showed more inhibition as compared to ceritinib. This study suggests that the hit compound ZINC000150338819 may be a repurposed ALK TK inhibitor in drug discovery.

Photostabilizing polymeric materials is vital in safeguarding against aging and ultraviolet (UV) irradiation. Consequently, the modification of polymers to enhance their resilience to photodegradation and photooxidation during prolonged exposure to UV light in challenging settings becomes imperative. Notably, recent advancements have led to the design and synthesis of various polymeric additives, with their potential utility as photostabilizers being extensively investigated. In this context, thin films of Polylactic acid (PLA) were developed, incorporating diverse concentrations of naringin alongside the commercial stabilizer TINUVIN 622. The study focused on assessing the role of naringin and TINUVIN 622 as effective UV blockers against PLA photodegradation. Detailed examination encompassing weight loss analysis, surface morphology observations, determination of the photodecomposition rate constant Kd, and analysis of changes in infrared spectra of irradiated polymeric blends, revealed the efficacy of 0.075% naringin concentration in significantly mitigating UV-induced degradation, thereby providing PLA with robust protection. Overall, the study demonstrated that 0.075% naringin emerged as the most efficient additive in stabilizing PLA against UV-induced degradation.

Cancer has become a global health concern, with escalating mortality rates in the 21st century, leading the World Health Organization to recognize it as one of the deadliest diseases. In their search for new anticancer therapeutic agents, researchers have identified the 3,5-disubstituted Indole derivatives as potential therapeutic agents capable of targeting the Proviral integration of moloney (Pim) kinases that correlate to hematological cancers. This study aims to investigate a series of 3,5-disubstituted indole derivatives as potent inhibitors of Pim1 kinase. Different computational chemistry techniques were utilized, including 2D-QSAR and molecular docking, to design novel inhibitors for targeting Pim1. The analysis of 2D-QSAR results showed that the inhibitory activity might be predicted with high accuracy (R²test = 0.96) using a classical statistical modeling technique, namely partial least squares regression.The six inhibitors that were identified as highly bio-active, were subjected to the docking study, and the results highlighted the important Pi-Alkyl interactions rising between the ligands and the Pim-1 kinase receptor (PDBcode:5DWR),which may enhance the binding of the ligand to a hydrophobic pocket on the target receptor. Overall, the combination of 2D-QSAR, moleculardocking, and ADMETanalysis has provided valuable insights and potential avenues for further exploration in the development of effective hematologicalanticancer agents.

Coccinia Indica (L.) fruit (CIFs) is a mounting, herbaceous, branching latitude vascular domestic plant in Asia, including India. It is a popular medicine for reducing high levels of blood glucose. This work aimed to appraise the photochemical, liquid, gaseous, and solid substances using Gas chromatography and Mass spectroscopy and find the aldose reductase inhibitor (ARI) activity through in-vitro assay using CIFs extracts. CIFs were extracted using polar and non-polar solvents. The results indicated that the ethanolic had a high yield of 33.9% when compared to 18.6% aqueous, 11.3% chloroform, 9.2% petroleum, and also the ethanolic extracts showing maximum phenolic (12.5±0.84mg GAE/g) and flavonoids (78.4±3.6mg QE/gm) dry extract content. GC-MS analysis of the ethanolic extract shows a total of 23 peaked compounds. The in-vitro aldose reductase inhibitor activity was performed with a partly purified bovine lens and revealed that ethanolic extract of CIFs established a 78.46% ARI activity at IC50 value 2.34µg/mL followed by aqueous 76.88% by IC50 value 3.88 µg/mL. Furthermore, the in-silico molecular docking and Density Functional Theory for peak compound was carried out. The CIFs are, therefore, a possible efficient agent with ARI and can be used to manage diabetic mellitus and its accompanying complications.

To enhance the electrical and optical properties of zirconium dioxide for industrial applications, we conducted a study investigating the influence of two transition metals on the characteristics of monoclinic ZrO2. The investigation involved the use of the plane-wave ultrasoft pseudopotential technique, which relies on first-principles density-functional theory (DFT). Our comprehensive analysis covered various aspects, including the assessment of structural parameters, elastic behavior, electronic structure, bonding properties, and optical characteristics of monoclinic ZrO2, along with its (V-Y)-doped and V, Y-codoped variations. Our estimations of the structural properties and independent elastic constants of ZrO2 aligned well with previous research findings. To examine the electronic structure and bonding characteristics, we utilized densities of states and charge densities. Notably, the analysis of optoelectronic properties revealed that the addition of V and Y dopants led to a significant reduction in the band gap of ZrO2. This phenomenon is attributed to the appearance of impurity states linked to V and Y in the valence band's up spin. Moreover, the incorporation of V and Y separately or together into ZrO2 resulted in a remarkable increase in the refractive index and the generation of distinct absorption peaks within the visible range.

This comprehensive study delves into the inhibitory properties of various natural flavonoids against cyclooxygenase-2 (COX-2), a crucial enzyme in the inflammatory pathway. Non-steroidal anti-inflammatory drugs (NSAIDs) are commonly employed to alleviate pain by targeting the COX enzyme. Employing molecular docking techniques, with established drugs like celecoxib, rofecoxib, and valdecoxib as benchmarks, the investigation assessed the interaction patterns of natural flavonoids. Notably, flavanone demonstrated a robust interaction with key residues TYR 385 and SER 530. Additionally, Density Functional Theory (DFT) and ADME calculations were employed to analyze structures with optimal affinities. These insights significantly contribute to discerning the potential therapeutic applications of natural compounds in COX-2 inhibition, offering promising avenues for future research and drug development.

This study presents experimental measurements of tie-line and solubility points for the ternary mixtures (water + lactic acid + propylene carbonate) at temperatures of 298.2 and 308.2 K and 101.7 kPa. HPLC measurements were employed to determine the mass fractions of solvent and water layers. The cloud point method was utilized to verify the Type-1 liquid-liquid equilibrium (LLE) behavior of the studied system. To ascertain the reliability of the tie-line points, Othmer-Tobias and Hand plots were analyzed. The thermodynamic correlation of tie-line data was achieved using the NRTL model, and the resulting binary interaction parameters were rigorously validated. Excellent agreement was observed between experimental and correlated data, with a root-mean-square deviation (rmsd) of only 0.3%. The study further explored activity coefficients calculated via the NRTL equation, revealing significant negative deviations for lactic acid and positive deviations for water and propylene carbonate from Raul's law. Extraction quality of propylene carbonate was investigated through the figuring of distribution coefficients and separation factors across the non-miscible region. Interestingly, separation factors increased from 1.07 to 1.11 when lactic acid mass fraction in aqueous layer increased from 0.036 to 0.105. However, distribution coefficients increased from 0.12 to 0.18 in the same investigated area.

Flavonoids have a broad area of anatomical interest and as such, it is vital to understand their association behaviour with proteins. Here, under biological conditions, the interaction of 2ʹ-hydroxyflavanone (2HF) with cattle protein (BSA) was investigated using steady-state UV-Visible and fluorescence spectroscopy, FT-Infra Red spectroscopy, circular dichroism, and docking investigations. Analysis showed static quenching of BSA in presence of 2HF. FRET analysis showed possibilities of energy transfer between 2HF and BSA. Experiments and molecular docking results indicate 2HF binds to subdomain IIA of BSA. The thermodynamic parameters like ∆H, ∆S, and ∆G indicate that the association with 2HF is spontaneous, exothermic, and involves van der Waals force and H-bonding. By using FTIR and CD investigations demonstrate structural changes in BSA following a drug interaction. The conformational and functionality change of serum albumin (BSA) after association with the drug is further depicted by esterase-like activity study of serum albumin in presence of 2HF. The binding of the BSA-2HF complex decreased in presence of selected metallic ions.

Tuberculosis (TB) is one of the top ten causes of mortality worldwide, necessitating the discovery of new molecules with potential anti-tuberculosis activity. In this study, Pretomanid derivatives as potent anti-TB agents were collected from the literature to generate a 3D-QSAR model and conduct molecular docking. The 3D-QSAR model was successfully generated with a high regression coefficient R²= 0.98 and an excellent cross-validated determination coefficient Q2cv= 0.51 for the training set. Furthermore, the model developed showed good predictive ability, with a high predictive value Q2= 0.75 for the test set. The generated 3D contour cubes were applied to find the structural properties necessary to inhibit Deazaflavin-dependent nitroreductase. Then, the results were used to discover novel molecules with a potential anti-tuberculosis activity using the structure-based virtual screening. Based on successful results obtained by virtual screening, twelve compounds were selected as potential inhibitors of the Ddn with highly predicted activities, binding interactions, and acceptable ADME properties.

The chemical and biological pathways for acetic acid production involve the separation of acetic acid from water. Azeotropic distillation and liquid-liquid extraction are used to separate acetic acid from water with conventional solvents, as simple distillation is impractical due to pinch point near the water edge and requires more energy to separate these two components. Methyl tert-butyl ether (MTBE) is a more viable solvent due to its low energy consumption during recovery. To compute isobaric vapor-liquid equilibrium (VLE) data for a binary mixture of methyl tert-butyl ether (MTBE) + acetic acid (AA) system, the group contribution method, UNIFAC was used. The thermodynamic consistency tests such as Redlich and Kister's and Wisniak's L-W were used to check the validity of these data. Wilson, UNIQUAC, and NRTL excess Gibbs energy models were used to determine the binary interaction parameters of these models. VLE data obtained in this work can be used to design the distillation and extraction system to recover and purify MTBE.

Drug delivery based on nanocages is helpful in nanomedicine with the minimum side effects and targeting drugs in the cancer cell. Bendamustine, an anti-cancer drug, inhibits the activity of cancer cells in humans and is broadly used in the therapy of breast cancer. The interaction of single Bendamustine and Bendamustine @Al/B-N/P nanocages with P53 protein was studied. In this study, molecular docking and molecular dynamics simulations(MD) were conducted to investigate the interaction of some of the Bendamustine, Al/B-N/P nanocages with the P53 protein. The best pose of the configuration of Bendamustine and Bendamustine @Al/B-N/P nanocages in the active sites of the P53 protein results in negative binding energies. Complexes of Bendamustine@B12N12 and Bendamustine@B12P12 with P53 protein have the most binding energy. In addition, MD simulation was done on the stable complexes with high binding energy to recognize the structural changes in the complexes of Bendamustine, Bendamustine@B12N12, and bendamustine@B12P12 nanocages with P53 protein. Studies illustrated that B12N12 and B12P12 could serve as drug carriers for delivering the Bendamustine drug in a targeted procedure for inhibiting the P53 protein. In-silico studies are important parts of the structure-based drug design process that displayed that nanocages are suitable sensors of Bendamustine drug.

Nowadays photocatalysts are widely used to degrade industrial and waste by-products. Among different catalysts, anatase is the most applied one due to its abundance and low cost. However, its large band gap (3.2 eV) limits its efficiency. Many metal and non-metal atoms have been used experimentally to reduce the band gap of anatase. In this paper, we tried to use a hybrid periodic density functional theory (DFT) method to model the solid-state phase of anatase photocatalyst and investigate nitrogen and cobalt substitutional doping on the band gap reduction. In addition to the band gap value, the magnetic properties of defected anatases are also studied. Results show that Co-doping by itself reduces the band gap from 3.56 (for pristine anatase) to 2.4 eV. The band gap reduction for (N, Co) dual-doping depends on the relative positions of N and Co to each other. If Co and N are located far from each other, the band gap reduces from 3.56 to 2.5 and 2.0 eV for spin-up and spin-down, respectively. If they are nearest neighbors, the band gap reduces from 3.56 to 3.2 and 2.6 eV for spin-up and spin-down, respectively.

VO2+ doped SrSn(PO4)2 nanopowder was prepared by solid state reaction method. The obtained nanopowder was studied using XRD, SEM, HR-TEM, FT-IR, optical absorption, EPR and PL measurements. The X-ray diffraction analysis revealed a monoclinic structure of VO2+ doped SrSn(PO4)2 nanopowder and exhibited an average crystallite size of 26 nm. The size is in the nano scale and W-H plot approach was also in agreement with this value. SEM and HR-TEM images are showing the non-uniform stone-like particle morphology of the prepared sample and confirms information about the average particle size of nanopowder, while EDS analysis confirms elemental composition. The selected area electron diffraction pattern revealed the sample crystalline by means of rings corresponding to XRD planes. Vibration modes related to phosphate functional groups were observed in FT-IR studies. Optical absorption spectrum shows characteristic VO2+ peaks at 520, 668 and 824 nm, and the crystal field and tetragonal parameters were evaluated: Dq = 1497, Ds = -2331 and Dt = 1028 cm-1. From the EPR spectrum, Hamiltonian parameters and hyperfine coupling constant values were calculated. The associated CIE chromaticity coordinates and CCT parameters were computed from the PL spectrum, and they indicate possible applications in LEDs and lighting devices.

In this work, molecular docking was performed to evaluate the anticancer activities of cannabidiol on various targeted proteins. Interactions and significant binding energy prove that cannabidiol can be synthesized and tested as a potent drug that treats all types of human cancer safely. The data obtained highlight the key amino acids involved in the ligand/protein interactions and show that the designed cannabidiol-bound complexes exhibited the best confirmation in the binding site. In addition, a DFT optimization of the geometry and orbital frontier analysis was performed to describe the chemical reactivity of the studied molecule. A pharmacokinetic and bioavailability study in the body was performed by ADMET proprietes. The results of the molecular docking indicate that cannabinol can tested as a potent drug to treat human cancer, given its interactions and significant binding energy up to -8,6 kcal/mol with FAAH protein.

This study employed advanced computational methods, including semi-empirical parametric method 3 (PM3) and density functional theory (DFT), to investigate the host/guest inclusion complexes of β-cyclodextrin (β-CD) with homovanilic acid (HVA). Utilizing B3LYP, M08HX, and PW6B95 approaches, global minima were optimized in both vacuum and aqueous phases. The focus spanned complexation, interaction, and deformation energies, as well as the geometry, electronic structure, and chemical reactivity of HVA during encapsulation. Natural-bonding orbital (NBO) simulations highlighted the significant role of intermolecular hydrogen interactions in the stability of HVA/β-CD complexes. The study, employing the Global-hybrid meta-GGA functional methodology (PW6B95/6-31G(d)), shed light on energetically favored molecules, emphasizing superior results in orientation A. The Gauge-Including Atomic Orbital (GIAO) method has been used to study 1H nuclear magnetic resonance (NMR) complexes. .These insights contribute to advancing host-guest systems and drug delivery applications.

In the current landscape of drug discovery, various docking programs for virtual database screening significantly reduce costs and time. This study re-docked twenty-three inhibitors of glycogen phosphorylase (GP), a key target for type 2 diabetes (T2D) therapy, using seven methods including Autodock 4 (AD4), AutoDockVina (Vina), modified Vina (mVina), Standard Precision mode (SP) and Extra Precision mode (XP) of Glide methods, Molecular Operating Environment (MOE) and Genetic Optimization for Ligand Docking (GOLD). Results showed that GOLD showed the worst computational precision with the highest RMSE of 20.98 kcal.mol-1. Conversely, MOE was the most precise with the lowest RMSE of 1.99 kcal.mol-1, closely followed by AD4. However, MOE failed to generate the correct ligand-binding pose, showing a 0% success rate in docking for all RMSD resolutions (<0.2, 0.15, and 0.1 nm). Among the top-performing methods, GOLD surpassed others in docking success rates for GP ligands, achieving 96% at RMSD <0.2 nm, compared to 74%, 70%, and 74% for AD4, Vina, and mVina, respectively. These four packages can produce a ligand-binding posture that closely resembles the crystal structure discovered through experimental studies. The findings serve as the foundation for selecting an appropriate tool for screening candidate drugs for the T2D therapeutic target.

Gout is a prevalent rheumatic disorder arising from elevated uric acid levels in the bloodstream, a condition known as hyperuricemia. Uricase serves the purpose of reducing uric acid levels nevertheless, it is absent in humans as a result of evolutionary modifications. The present investigation focused on the computational analysis of uricase enzymes derived from eighty-eight fungal species and the analysis includes their structural, functional, physicochemical properties, motif search and domain architecture analysis were done. In addition to this we have performed the phylogenetic analysis of these protein sequences to study their phylogenetic relationship. Physicochemical analysis revealed that uricase spans amino acid residues 296-330, with a molecular weight of 33.03-35.05 kDa and theoretical pI values of 5.71 to 9.03. Valine was the most prevalent amino acid, averaging 8.40% across all species. These uricase were thermally stable and active in acidic and alkaline conditions. The secondary structure analysis indicated a predominance of alpha-helices and beta-sheets in uricase. Aspergillus niger (ABI79319.1) was chosen as the representative species, with its three-dimensional structure accurately predicted and validated. The comprehensive computational analysis conducted on the uricase protein offers the potential to identify a suitable microorganism capable of producing uricase with desirable characteristics for industrial applications.