Currently, the rise and dissemination of resistance to antimalarial drugs pose a significant global challenge. There is an ongoing effort to discover novel compounds for the development of new antimalarial therapies. This study aimed to evaluate harmicine derivatives known for their antimalarial activity and to explore their potential interactions with Plasmodium falciparum, specifically targeting the crucial falcipain-2 enzyme in the parasite's life cycle. Molecular docking and dynamics studies showed that compound 6f interacted with the binding site of the enzyme and stayed stable for 100 ns, the best of the derivatives. It had a binding affinity score of -8.4, higher than chloroquine (-5.5). This means that it might be better than chloroquine at inhibiting falcipain-2. Additionally, compound 6f successfully passed Lipinski's Rule of Five, suggesting its potential for oral use. Researchers found that the results of this study could help make new, stronger Harmicines with better antiplasmodial activities. This could lead to the creation of very effective medicines that fight malaria
Dental caries, caused primarily by Streptococcus mutans, is a major oral health issue worldwide. Sortase A (SrtA), a transpeptidase enzyme, plays a key role in bacterial adhesion and colonization, making it a potential target for caries prevention. This study aims to investigate the antibacterial potential of beluntas leaf (Pluchea indica) metabolites against S. mutans through in silico analysis. Using molecular docking and molecular dynamics (MD) simulations, we analyzed the binding interactions between beluntas leaf metabolites and SrtA. The results showed that beta-stigmasterol exhibited the strongest binding affinity to SrtA, with a binding energy of -8.73 kcal/mol. Molecular dynamics simulations further confirmed the stability of the beta-stigmasterol-SrtA complex. Furthermore, binding free energy analysis using MMPBSA showed that stigmasterol exhibited a significantly stronger binding affinity to Sortase A (−131.86 ± 12.57 kJ/mol) compared to astilbin (−54.38 ± 18.47 kJ/mol), supporting its potential as a potent anti-caries agent. This study suggests that beluntas leaf metabolites, particularly beta-stigmasterol, could be a promising natural agent for preventing dental caries by targeting the SortA receptor.
Diabetes Mellitus (DM) is a metabolic disorder marked by hyperglycemia, often necessitating alternatives to long-term medications due to side effects. This study evaluates the antioxidant and anti-diabetic potential of white frangipani (Plumeria acuminata L.) and red frangipani (Plumeria rubra L.) extracts. In alloxan-induced diabetic mice, a combination of white frangipani extract (WFE) 200 mg/kgBW and red frangipani extract (RFE) 400 mg/kgBW reduced blood glucose by 57.7%, while a dose of WFE 400 mg/kgBW and RFE 400 mg/kgBW in the OGTT method resulted in a 71.3% reduction. The extracts significantly reduced glucose levels compared to the Negative Control, with no significant difference from the Positive Control group (p>0.05). In silico_docking analysis revealed that Plumericin, a major metabolite, had high binding affinity to the SGLT-2 receptor (-9.36 kcal/mol), close to the native ligand (-11.46 kcal/mol). Molecular dynamics simulations confirmed the Plumericin-SGLT-2 complex's stability, supporting the therapeutic potential of these extracts for DM treatment. This dual In vivo and in silico approach provides a comprehensive understanding of their therapeutic potential and supports further exploration of these extracts as candidates for diabetes treatment
The global health crisis precipitated by COVID-19, caused by severe acute respiratory syndrome-Coronavirus 2 (SARS-CoV-2), has spurred an urgent quest for effective therapeutic interventions. Several repurposed drugs, including chloroquine, hydroxychloroquine, ivermectin, artemisinin, remdesivir, and azithromycin, have been explored for their antiviral potential. Amid this pharmacological landscape, curcumin—a natural polyphenolic compound renowned for its broad-spectrum bioactivity—has emerged as a promising candidate in the fight against COVID-19. Recent investigations into curcumin analogues and derivatives further underscore its therapeutic versatility. This study seeks to unravel the molecular interactions of hypothetical azo curcumins and hydroxychloroquine with the SARS-CoV-2 main protease, employing molecular docking and computational analysis to elucidate their binding affinities and mechanistic insights. By leveraging advanced computational techniques, this research endeavours to provide a deeper understanding of these molecules' antiviral potential, paving the way for future pharmacological developments in combating SARS-CoV-2.
The determination of redox potential (E°) was performed by computational study with correlation- function of B3LYP, for (Cu-L1), (Cu-L2), (Cu-L3) and (Cu-L4) were performed with the help of density functional theory (DFT). The basis set of def2-SVP def2/J D3BJ was used for geometry optimization and frequency calculation. The results showed that the calculation of redox potential of Cu-Ligand complexes were around E° of 0.82 to 0.970 V (vs NHE) and the calculated VOC values for the designed Cu-Ligand complexes range from 1.32 to 1.47 vs NHE (V). Increasing VOC can leads to higher JSC values, the largest VOC values were occupied by Cu-L1 which had the highest reduction potential (0.970 V vs. NHE). The complexes are promising to be used as a redox couple on DSSC’s application due to Voc and Regeneration value consideration.
Type 2 diabetes mellitus (T2DM) is a significant metabolic disorder affecting approximately 537 million people globally. Syzygium cumini (S. cumini) has been traditionally used in medicine due to its diverse pharmacological properties. Recognizing the multitarget and multipathway potential of herbal plants, this study employed network pharmacology to predict the target profiles and pharmacological mechanisms of S. cumini compounds. The methanolic leaf extract of S. cumini was analyzed using LC-HRMS, ADMET prediction, network pharmacology, and molecular docking. LC-HRMS analysis identified 42 compounds in the extract, 35 of which satisfied the Lipinski’s rule of 5. From the analysis, 150 common targets for S. cumini were identified, leading to the determination of 10 core targets: IL-6, TNF, ALB, AKT1, IL1B, STAT3, CTNNB1, PPARG, TLR4, and PTGS2. Molecular docking was then performed on the compounds targeting three best targets, i.e. IL-6, TNF, and ALB. Four compounds targeted IL-6, 4 compounds targeting TNF-α, and 1 compound targeting ALB. Notably, bergenin and FF-MAS had binding energy comparable to that of native ligands when bound to IL-6 and TNF-α, respectively. Interestingly, NP-012381 emerged as the only compound targeting the three targets (IL-6, TNF-α and ALB) simultaneously, and its binding energy was lower than that of native ligand of each target. The present study highlights the potential of Syzygium cumini in inhibiting T2DM.
One of the key parameters in designing DSSCs is the dye, which plays a crucial role in absorbing light. This study aims to modify the structure of D-π-A type dyes based on dithiophene with variations in the donor chain. The donor chains used were phenol, aniline, indoline, diphenylamine, coumarin, and toluene, symbolized as T1, T2, T3, T4, T5, and T6. The acceptor chain used was cyanoacetic acid. Calculations were performed using the Density Functional Theory (DFT) and Time-Dependent DFT (TD-DFT) methods with the B3LYP/6-31G basis set. The study results indicated that all modified dyes were potential sensitizers because they can absorb light in the visible to infrared (IR) regions. The T3 dye, with an indoline donor chain, was the best dye to be used as a sensitizer, with a bandgap value of 1.7149 eV, a maximum wavelength (λ) of 939.43 nm, excitation energy of 1.3198 eV, ΔGinj of -04250 eV, ΔGreg of 0.0948 eV, and a VOC value of 08201 eV
This study uses computational approaches to predict and investigate the inhibition behavior of rosemary essential oil (REO) as a green corrosion inhibitor. These approaches are based on calculating quantum parameters and Mulliken atomic charges using Density Functional Theory (DFT) combined with a Monte Carlo simulation to explain the adsorption mechanism and a POM (Petra/Osiris/Molinspiration) analysis. The chemical composition analysis revealed eucalyptol (49.01%), alpha-pinene (17.31%), and beta-caryophyllene (6.42%) as the major constituents. Quantum chemical calculations identified alpha-thujene, beta-myrcene, and alpha-pinene as key inhibitors based on their electron-donating abilities, moderate energy gaps, and higher softness values, indicating a strong potential for adsorption onto metal surfaces. Mulliken charge analysis highlighted the significance of oxygenated compounds, especially alpha-terpineol, due to its highly negative oxygen charges, which suggest strong interactions with metal surfaces. Monte Carlo simulations showed that gamma-cadinene exhibited the highest adsorption energies in both gas (-53.259 kJ/mol) and aqueous (-631.011 kJ/mol) phases, indicating a robust interaction with the copper surface. Humulene and alpha-terpineol also showed significant adsorption characteristics. The OSIRIS and Molinspiration assessments confirmed the molecules' environmental safety and balanced lipophilicity, which enhanced their corrosion inhibition capabilities. The results indicate that the corrosion inhibition of the Rosemary essential oil is due to a combination of physical and chemical adsorption mechanisms, with possible synergistic effects among its constituents, making it an effective and sustainable corrosion inhibitor. These computational insights provide a foundation for understanding REO's behavior before progressing to experimental electrochemical evaluations.
In this study, we performed in-silico single guide RNA (sgRNA) construction as the first step of the genome editing process using CRISPR-Cas9 on Salmonella SSE-121 phage. The target gene used is a tail fiber protein that plays a role in recognizing and attaching to host bacteria. By carrying out in-silico sgRNA construction, it is expected to be able to determine the optimal sgRNA candidate in Salmonella phage and minimize failure. The genome sequence of Salmonella phage was taken from NCBI and Cas9 protein data was taken from RCSB Protein Data Bank (PDB). The results of sgRNA prediction from Salmonella phage using CHOPCHOP obtained 439 data. Based on the efficiency score, GC content and self complementarity for each candidate, 58 selected sgRNA data were obtained. Selected candidates were selected based on docking score using HNADOCK website and 33 selected candidates were re-docked with Cas9 protein using HDOCK website. The five best candidates were then validated to obtain the most optimal sgRNA candidate. Plasmid construction was performed by matching the plasmid structure with the candidate sgRNA to be inserted and used in in-vivo studies. Based on the data obtained, the docking score for sgRNA and target DNA binding was -553.09, while the docking score for sgRNA and Cas9 binding was -399.18. The plasmid construct pCMV-T7-ABE8 can be well bound by sgRNA 15 using the restriction enzyme SnaBI.
The mechanism of excited state proton transfer between guanine and cytosine in the Watson-Crick base pair was studied with experimental and theoretical methods. When irradiated with UV light the water solution of the equimolecular mixture of guanine and cytosine indicates a photoreaction with a rate constant 48.07×10-4 min-1. The backward dark reaction occurs with a rate constant 12.03×10-4 min-1. One of the identified processes is an excited-state proton transfer (ESPT). The mechanism of the photoreaction was followed at the B3LYP/aug-cc-pVDZ level of theory in water surroundings (according to PCM). We tested two mechanisms: intrinsic reaction coordinate (IRC) and Linear interpolation of internal coordinates (LIIC) between a base pair and a conical intersection S0/S1. They both showed that the ESPT occurs along 1pp* excited-state reaction paths.
Stable phosphorus ylids are usually synthesized as a mixture of two E- and Z- isomeric forms with different percentages. Experimental methods and techniques cannot find a reason for the presence of these products in different proportions. Therefore, in this project, we are trying to find evidence for the preference of one of the E- and Z-structural isomers. For this purpose, the mechanism of the reaction between triphenylphosphine R1 and dimethyl acetylenedicarboxylate R2 was investigated in the presence of 2-indolinone as NH-acid, based on quantum mechanical calculations. Theoretical studies were performed to evaluate the energy levels of all structures participating in the mechanism. All structures optimized at the B3LYP/6-311++g(d,p) levels. The first step of the reaction was recognized as a rate-determining step in the reaction mechanism. To investigate the solvent effect on the energy level of structures, condensed phase calculations in dichloromethane carried out with the polarizable continuum model (PCM). Finally, the natural bond orbital (NBO) method applied for a better understanding of molecular interaction.
Epidermal growth factor reseptör (EGFR) is an important protein in the cell cycle; mutations in the protein cause many problems. The vast majority of these diseases manifest themselves as tumours. One of the most common mutations in the EGFR protein is the L858R mutation in exon 21, which is a type of missense single nucleotide polymorphism (SNP). In this mutation, the leucine in the 858th amino acid of the protein changes to arginine, and the thymine nucleotide in the leucine structure changes to guanine nucleotide. This nucleotide change leads to a high rate of cancer. Lung cancers are the leading cause of cancer caused by L858R mutations. Especially the L858R mutation is the leading cause of non-small cell lung cancer (NSCLC), and this type of mutation has been detected in most patients with this type of cancer. In this study, a docking study was conducted to determine molecules that could be inhibitors for the mutant EGFR molecule, and lichen secondary metabolites were used for this purpose. While as known there are more than 400 lichen secondary metabolites, 155 molecules were selected as examples for this study. For this purpose, geometry optimizations were performed with the semi-empirical PM6 method on the most stable structure obtained after conformer analysis of the active molecules that have an effect from the selected lichen secondary metabolites, and a QSAR model was created to correlate the docking energies of the relevant molecules and their physicochemical properties. Optimizations and docking operations were performed in Spartan’14 and Autodock Vina programs, respectively. Calculations made for all studied molecule types, results of physicochemical parameters and linear regression analyses between binding energies were performed with the Excel program. BIOVIA Discovery Studio program was used for the docking images between protein and molecule.
Cancer remains to be among the major health issues in the global context, and safe and more efficient treatment is sought to be identified. EGFR, or Epidermal Growth Factor Receptor, is a promising target of one of the strategies aimed at the survival and growth of cancer cells. We have investigated, in this study, a set of more recently designed 2-(piperazin -1-yl)- 1H -benzo[d]imidazole derivatives through computer-based methods to determine their potential as EGFR inhibitors. The stability of the most promising complex was tested by the molecular dynamics simulation after molecular docking was used to predict the binding affinity of these compounds to EGFR. Other drug-like characteristics that were also looked at include absorption, bioavailability, and chemical suitability. Out of the tested compounds, one of them specifically the compound marked as A4 was interesting as it demonstrated high binding affinity, desirable pharmacokinetic properties, and a stable interaction with EGFR. The above findings indicate that compound A4 is a promising anti-cancer drug to be developed further. To establish its potential, additional laboratory tests are suggested.
Tuberculosis, caused by Mycobacterium tuberculosis (Mtb), remains one of the major global health problems requiring novel therapeutic approaches. The MtASADH (aspartate-semialdehyde dehydrogenase) enzyme in Mtb is a potential therapeutic target due to its role in bacterial essential amino acid biosynthesis. This study aims to explore the binding mechanism of compound IMB-XMA0038 on MtASADH receptor through in silico approach. The molecular docking method was used to predict the optimal binding position, affinity, and molecular interactions between IMB-XMA0038 and MtASADH. Results showed that IMB-XMA0038 strongly interacted with the active site of MtASADH through hydrogen bonding and significant hydrophobic interactions, exhibiting high binding affinity. In addition, molecular dynamics simulations were performed to evaluate the stability of the complex under physiological conditions, which showed that the IMB-XMA0038-MtASADH complex has good structural stability. This study provides mechanistic insights into the potential of IMB-XMA0038 as a MtASADH inhibitor and supports its development as a novel anti-TB agent. This in silico approach may facilitate further design of more efficient and selective compounds against Mtb.
A combined approach, including the use of homodesmotic reference reaction (HDR) and G4 calculation of absolute enthalpies of its participants, was applied for theoretical evaluation of the gas-phase standard enthalpies of formation fH for the set of cis- and trans-isomers of ortho- and meta-substituted aromatic nitroso oxides R C6H4NOO. Compared with isomeric nitroaromatic compounds, nitroso oxides have a higher energy by 252 – 280 kJmol 1, which explains their high reactivity. A satisfactory correlation was established between the enthalpy of the HDR and the Hammett constants of meta-substituents R, which made it possible to derive a simple expression for fH evaluation of meta-substituted aryl nitroso oxides. A detailed analysis of the obtained results for the ortho-R C6H4NOO set (Hammett correlation, QTAIM and distortion/interaction analyses) allowed us to identify three main factors of R influencing on the enthalpy of formation of aryl nitroso oxide: the inductive-resonance effect, which is most strongly manifested in dimethylamino-substituted phenyl nitroso oxide, steric repulsion of the NOO and R fragments, and close-shell stabilization of the cis-isomers of syn-ortho-R C6H4NOO due to the interaction of terminal oxygen atom of nitroso oxide group with an appropriate atom of substituent.
Mangostin is a bioactive compound derived from mangosteen with significant therapeutic potential. However, mangostin has limitations in biomedical applications due to its low solubility in water. This study aims to increase the solubility of mangostin derivatives through encapsulation in cucurbituril crystalline architecture using in silico methods. The results showed that cucurbituril significantly enhanced the solubility of mangostin derivatives through supramolecular encapsulation, which stabilized the bioactive compound within the hydrophobic cavity of cucurbituril. This encapsulation not only improved the solubility but also maintained the bioactivity of mangostin derivatives, offering potential for the development of advanced delivery systems for hydrophobic bioactive compounds in the pharmaceutical and nutraceutical fields. This study utilized molecular dynamics simulations, docking studies, and computational chemistry techniques to reveal the host-guest interaction between cucurbituril and mangostin derivatives. Molecular dynamics simulations were performed using GROMACS software with CHARMM force field to evaluate the stability of the host-guest complex. Docking studies were performed with AutoDock Vina to predict the binding affinity and interaction position. In addition, computational chemistry calculations were performed using density function theory (DFT) with B3LYP calculation level and 6-31G(d,p) basis set to optimize the geometry and describe the electron distribution. This technique comprehensively describes the supramolecular interaction mechanism underlying the enhanced solubility of mangostin derivatives.
A comparative theoretical and experimental study was carried out using three reliable spectroscopic techniques (Fourier-transform infrared, ultra-violet–visible, and nuclear magnetic resonance) to characterize the organic crystal (Z)-3-N-(methyl)-2-N’-(4-methoxyphenylimino) thiazolidin-4-one. An in-depth analysis of the reactivity of this compound constitutes one of the objectives of this study by analyzing the local and global descriptors of the reactivity as well as the molecular electrostatic potential by using density functional theory as method calculation. Furthermore, optoelectronic properties in the static regime are calculated and discussed to investigate the nonlinear optical aspect of this compound. The analysis of the obtained results reveals that the time-dependent density functional theory calculations and the obtained conclusions from density functional theory agree well with the experimental data. Regarding the chemical reactivity spectrum, this compound presents more stability less reactivity when solvent dielectric constant increases with higher electrophilic behavior in polar medium such as DMSO. According to local descriptor values, the most common locations for nucleophilic assaults are O2, C10, S, and C8 atoms, whereas C11 and C4 present favorable sites for electrophilic attacks. The investigation of the nonlinear optical aspect show that the moderate values of optoelectronic properties are due to the absence of the strong donor-acceptor character in the compound.
The Quantum Mechanics/Molecular Mechanics (QM/MM) hybrid approach combines the accuracy of quantum mechanics with the computational efficiency of molecular mechanics, making it a powerful tool in drug design. This review discusses the QM/MM methodology, which applies quantum mechanics to active sites in biomolecules while using molecular mechanics to model their surrounding environment. This method has proven effective for studying enzyme reactions, ligand-protein interactions, and other critical processes in drug discovery. Key components such as QM and MM region partitioning, link atom schemes, and boundary treatments are reviewed, alongside recent advancements like polarizable force fields, enhanced sampling techniques, and integration with machine learning. Real-world applications, including virtual screening, lead optimization, and biochemical mechanism analysis, illustrate QM/MM's impact on designing effective therapeutics. As QM/MM technology continues to advance, its role in accelerating and refining drug discovery is expected to grow, bringing new possibilities to the field.
Understanding uracil solvation is crucial for refining hydrogen bonding (H-bonding) models in aqueous systems, with implications for enzyme activity and drug design. In this study, we investigate novel uracil-5water (U5W) complexes, revealing an unusual H-bond arrangement that significantly influences vibrational properties. Density functional theory (DFT) calculations using ωB97XD and CAM-B3LYP-D3 functionals with various basis sets identified the most stable isomers (U11333, U11133, U12223), characterized by clustered water molecules and optimal H-bond lengths. New isomers (U11134, U11144, U11124) exhibited enhanced stability compared to previously reported configurations. Vibrational mode analysis confirmed hydration effects, notably influencing ν(N-H) and ν(C2=O) shifts. The U12223 complex displayed a distinct N3H···Ow bond, altering vibrational behavior. These findings provide insights into H-bonding interactions and molecular stability, paving the way for future theoretical and experimental studies.
The study investigates the promising role of new 1,3,4-oxadiazole and 1,3,4-thiadiazole derivatives (A1–A6) as potent epidermal growth factor receptor (EGFR) inhibitors, which is a crucial therapeutic target in non-small cell lung cancer (NSCLC). Using extensive in silico approaches, by combined molecular docking, molecular dynamics (MD) simulations, and ADMET profiling to assess the pharmacological potential of these compounds. Because EGFR is crucial in NSCLC, mutations in this receptor promote tumor growth and resistance to current tyrosine kinase inhibitors (TKIs) including Erlotinib. Although initially very effective, first-generation TKIs are often eventually rendered ineffective by resistance mechanisms such as T790M mutations, therefore innovative inhibitors with improved efficacy and stability are warranted. The process began with ligand preparation, which was performed through ChemDraw and Chem3D to minimize energy, and the computational evaluations were conducted using Schrödinger Suites. All compounds showed good adherence to Lipinski’s Rule of Five, indicating their drug-likeness, as shown by ADMET statistically analyzed data. The molecular docking showed that the derivatives have better binding affinities than Erlotinib and the compound A1 and A2 which have PLPfitness 90.61 and 83.77, respectively. Robust hydrogen bonding and hydrophobic interaction with the essential EGFR residues such as THR830 and THR766 was credited for these results. Molecular dynamics (MD) simulations further supported the stability of the complex, showing a 100-nanosecond trajectory with root mean square deviation (RMSD) and root mean square fluctuation (RMSF) analyses confirming structural stability and stability of ligand binding in the A1-EGFR complex. Pharmacokinetic assessments highlighted the compounds' favorable absorption, distribution, and low cardiotoxicity risks. Candidate A1 (Caco-2, 2636.59 nm/sec, LogP, 4.19) showed the highest internal permeability as well as optimal lipophilicity and binding interactions, respectively. Specifically, Specifically, A1 shows a stable interaction with key residues in the EGFR active site during 100nm of simulation, thereby supporting its role as a selective inhibitor. Consequently, A1 emerges as a promising candidate for experimental validation and further drug development to treat EGFR-driven NSCLC. This study highlights the power of computational methods in the early stage of drug discovery.
