Journal of molecular graphics & modelling最新文献

Microsatellite instability (MSI) is a relatively common feature associated with multiple cancers, and Werner syndrome (WRN) ATP-dependent helicase has been recognized as a novel target for treating MSI cancers, such as colorectal cancer. A small-molecule inhibitor targeting WRN would be a promising strategy for treating colorectal cancer with high MSI expression. In this study, we employed a computer-assisted drug discovery strategy to screen over 30,000 natural product molecules. By using a combination of docking, ligand efficiency, Molecular Mechanics/Generalized Born Surface Area (MM/GBSA), and thermodynamic integration (TI) calculations, we identified MOL008980, MOL010740, MOL011832, T4743, TN1166, and TNP-002173 as potential WRN inhibitors. Subsequent molecular dynamics simulation revealed that these screened natural products possessed better binding dynamic characteristics than ATP substrate and were capable of inhibiting the dynamic process of WRN, making them potential strong ATP competitive inhibitors. In conclusion, our computational approach revealed potential WRN inhibitors from a natural product database, providing a theoretical basis for future research.

The leishmaniases are NDTs (neglected tropical diseases) that affect people all over the world. They are brought on by protozoans from the genus Leishmania and disseminated by phlebotomine flies that are afflicted with the disease. The best option to manage and lower the incidence of these diseases has been thought by the creation of a safe and effective vaccination. This research used an in silico based mining approach to look for high potential epitopes that might bind to MHC Class I and MHC Class II molecules (mainly; HLA-A*02:01 & HLA-DRB1*03:01) from human population in order to promote vaccine development. Based on the presence of signal peptides, GPI anchors, antigenicity predictions, and a subtractive proteomic technique, we have screened 17 putative antigenic proteins from the 8083 total proteins of L. major. After that thorough immunogenic epitope prediction were done using IEDB-AR tools. We isolated five immunogenic epitopes (three 9-mer & two 15-mer) from five antigenic proteins through docking and MD simulation analysis. Finally, these five anticipated epitopes, viz., TLPEIPVNV, ELMAPVFGL, TLAAAVALL, NSINIRLDGVTSAGF and NVPLVVDASSLFRVA have considerably stronger binding potential with their respective alleles and may trigger immunological responses. The goal of this work was to identify MHC restricted epitopes for CD8⁺ and CD4⁺ T cells activation using immunoinformatics in order to identify potential vaccine candidates against L. major parasites.

The determination of the critical micelle concentration (CMC) is a crucial factor when evaluating surfactants, making it an essential tool in studying the properties of surfactants in various industrial fields. In this present research, we assembled a comprehensive set of 593 different classes of surfactants including, anionic, cationic, nonionic, zwitterionic, and Gemini surfactants to establish a link between their molecular structure and the negative logarithmic value of critical micelle concentration (pCMC) utilizing quantitative structure-property relationship (QSPR) methodologies. Statistical analysis revealed that a set of 14 significant Mordred descriptors (SlogP, GATS6d, nAcid, GATS8dv, GATS4dv, PEOE_VSA11, GATS8d, ATS0p, GATS1d, MATS5p, GATS3d, NdssC, GATS6dv and EState_VSA4), along with temperature, served as appropriate inputs. Different machine learning methods, such as multiple linear regression (MLR), random forest regression (RFR), artificial neural network (ANN), and support vector regression (SVM), were employed in this study to build QSPR models. According to the statistical coefficients of QSPR models, SVR with Dragonfly hyperparameter optimization (SVR-DA) was the most accurate in predicting pCMC values, achieving ($R^2$ = 0.9740, $Q^2$ = 0.9739, ${\bar{r}}_m^2$ = 0.9627, and ${\Delta r}_m^2$ = 0.0244) for the entire dataset.

Formaldehyde is a VOC gas that plays a key role in air pollution. To limit emissions into the environment, the utilization of this waste as a raw material is a promising way. In this work, the M06-L functional calculation was used to investigate the structure, electronic properties, and catalytic activity of group IIA metals (Be, Mg, and Ca) partial substitution on Cu-BTC paddlewheels for formaldehyde encapsulation and carbonyl-ene reaction with propylene. Formaldehyde is absorbed by the metal center of the paddlewheel via its oxygen atom. The adsorption of formaldehyde on the substituted metal sites increased as compared to the parent Cu-BTC which can facilitate formaldehyde to react with propylene. The adsorption free energies are predicted to be −15.1 (Be–Cu-BTC), −14.7 (Mg–Cu-BTC), and −14.5 (Ca–Cu-BTC) kcal mol⁻¹, respectively. The substituted metal has a slight effect on the Lewis acidity of the Cu ion in the paddlewheel. The adsorption free energy of formaldehyde, similar to that found in the pristine Cu-BTC, is observed. For the carbonyl-ene reaction, the reaction is proposed via a single step involving the C–C bond formation between two reactants and one hydrogen of propylene methyl group moves to formaldehyde oxygen, simultaneously. It was found that the substituted metals do not affect the catalytic performance of the Cu center for this reaction. The activation energies for the reaction at the Cu center are in the range of 22.0–23.4 kcal mol⁻¹, which are slightly different from Cu-BTC (21.5 kcal mol⁻¹). Interestingly, the catalytic activity of this reaction on the substituted metal is greater than that on the Cu center. The catalytic activities are in the order Be–Cu-BTC (13.3 kcal mol⁻¹) > Mg–Cu-BTC (15.9 kcal mol⁻¹) > Ca–Cu-BTC (17.8 kcal mol⁻¹). Among them, the Be site of the bimetallic Be–Cu-BTC paddlewheel is predicted as a promising candidate catalyst.

On the basis of the atomic graph-theoretical index – aEAID (atomic Extended Adjacency matrix IDentification) and molecular adjacent topological index – ATID (Adjacent Topological IDentification) suggested by one of the authors (Zhang Q), a highly selective atomic topological index - aATID (atomic Adjacent Topological IDentification) index was suggested to identify the equivalent atoms in this study. The aATID index of an atom was derived from the number of the attached hydrogen atoms of the atom but omitting bond types. In this case, the suggested index can be used to identify equivalent atoms in chemistry but perhaps not equivalent in the molecular graph. To test the uniqueness of aATID indices, the virtual atomic data sets were derived from alkanes containing 15–20 carbon atoms and the isomers of Octogen, as well as a real data set was derived from the NCI database. Only four pairs of atoms from alkanes containing 20 carbons can't be discriminated by aATID, that is, four pairs of degenerates were found for this data set. To solve this problem, the aATID index was modified by introducing distance factors between atoms, and the 2-aATID index was suggested. Its uniqueness was examined by 5,939,902 atoms derived from alkanes containing 20 carbons and further 16,166,984 atoms from alkanes of 21 carbons, and no degenerates were found. In addition, another large real data set of 16,650,688 atoms derived from the PubChem database was also used to test the uniqueness of both aATID and 2-aATID. As a result, each atom was successfully discriminated by any of the two indices. Finally, the suggested aATID index was applied to the identification of duplicate atoms as data pretreatment for QSPR (Quantitative Structure–Property Relationships) studies.

Density functional theory was used to study the insertion reaction of stannylenoid H₂SnLiF with CH₃X, SiH₃X (X = F, Cl, Br). Comparing the reaction barrier of H₂SnLiF with CH₃X, SiH₃X, it can be found that the order of the difficulty of insertion reaction is F > Cl > Br. The insertion reaction potential barrier of SiH₃X is lower than that of CH₃X, which means that SiH₃X is easier to react. According to the calculation results, the reaction law in THF solvent is consistent with that in vacuum, while in THF solvent, the barrier is lower and therefore more prone to reactions. This work provides theoretical support for the reaction properties of stannylenoids.

Through a comprehensive computational analysis utilizing Density Functional Theory (DFT), we clarify the electronic structure and spectroscopic properties of modified iron(II)-terpyridine derivatives, with the aim of enhancing the efficiency of Dye-Sensitized Solar Cells (DSSCs). We optimized a series of nineteen iron(II)-terpyridine derivatives and related compounds in acetonitrile (MeCN) as the solvent using TDDFT, evaluating their potential as dyes for DSSCs. From the conducted computations on the optimized geometries of the nineteen [Fe(Lⁿ)₂]²⁺ complexes, containing substituted terpyridine and related ligands L¹-L¹⁹, we determined the wavelengths (λ in nm), transition energy (E in eV), oscillator strength (f), type of transitions, excited state lifetime (τ), light harvesting efficiency (LHE), frontier orbital character and their energies (E_LUMO/E_HOMO), natural transition orbitals (NTOs), injection driving force of a dye (ΔG_inject), and regeneration driving force of a dye (ΔG_regenerate). Results show that the theoretically calculated values for assessing dye efficiency in a DSSC correlate with available experimental values. The UV–visible spectra of [Fe(Lⁿ)₂]²⁺ exhibited a peak above 500 nm (λ_max) in the visible region, attributed to the ligand-to-metal charge transfer band (LMCT) in literature, and a significant absorbance peak at approximately 300 nm (λ_A,max) in the UV region. The M06-D3/CEP-121G method replicated all reported λ_max and λ_A,max values with a mean absolute deviation (MAD) of 21 and 18 nm, respectively. Our findings underscore the connections between electronic modifications and absorption spectra, emphasizing their impact on the light-harvesting capabilities and overall performance of DSSCs. This research contributes to the advancement of fundamental principles governing the design and optimization of novel photovoltaic materials, facilitating the development of more efficient and sustainable solar energy technologies.

Cyclooxygenases 1 and 2 (COX-1/2) are enzymes renowned for inducing inflammatory responses through the production of prostaglandins. Thus, the development of COX inhibitors has been a promising approach for identifying compounds with anti-inflammatory potential. In this study, we designed 27 new compounds (1–27) based on the structure of a previously known COX inhibitor, using the Ligand Designer tool. Our aim was to improve the affinity of the compounds with COX enzymes by inducing interactions with residue Arg120 while retaining the good π-π stacking interactions of the chromene-phenyl scaffold. Through screening based on ligand-binding free energy defined by molecular docking simulations and MM/GBSA technique, compounds 9 and 10 were identified as having the highest ability to inhibit COX proteins. The binding affinities of the two compounds with COX-1/2 were superior to those of the original NAI10 compound and the reference drug indomethacin. Our virtual screening suggests that compounds 9 and 10 have a strong ability to inhibit COX-1/2 and thus could be promising candidates for further anti-inflammatory drug studies. In essence, our study underscores the pivotal role of the N-aryl iminocoumarin scaffold in shaping the future landscape of novel anti-inflammatory drug development.

Nanolubricant viscosity plays a crucial role in various industries due to its impact on pressure drop, pumping power, and heat transfer. The purpose of this research is to measure the viscosity of a (base oil) C₃₀H₆₂–CuO nano-lubricant experimentally using a viscometer and determine its viscosity using the equilibrium molecular dynamics (MD) simulation. In addition, the impacts of nano CuO particle volume fraction and temperature on the viscosity were investigated within different concentrations of nano CuO particles (0%, 0.25%, 0.5%, and 0.75%) and variable temperatures (300 K, 313 K, 323 K, and 373 K). The simulation results agreed with experimental results and depicted that the viscosity of base oil and nano lubricant of CuO-base oil decreased with increasing temperature. Additionally, increasing the concentration of nanoparticles increased the viscosity of the nano lubricant, but the effect of increasing the concentration of nanoparticles at high temperatures was not significant. For instance, the viscosity of the base oil increased by 1.2% and 1.5% after adding 0.5% and 0.75% copper oxide nanoparticles at 373 K. Based on our research; no study has been done to calculate the viscosity of nanolubricant (C₃₀H₆₂ (base oil) - CuO) and its influencing factors by molecular dynamics simulation and compare its results with experimental methods. The research findings have practical implications for using nano lubricants in various industries, such as the internal combustion engine industry or other industries that use lubricants, and it is a critical parameter in heat transfer.

In the present work, the electronic structure and stability of acyclic nitronic acids were studied. Depending on the different substituents, the analyzed compounds can be classified as pseudo(mono)radical or zwitterionic nitronic acids. ELF topological analysis of the electron density of nitronic acids containing in their structure EWG substituent (-NO₂ (1); –COOCH₃ (2); –NO₂, –CH₃ (5); –COOCH₃, –OCH₃ (6); –NO₂, –H (7); –COOH₃, –H (8)) permits establishing a pseudo(mono)radical electronic structure with a pseudoradical centers at the C1 carbon atom. In turn, ELF analysis of the compounds 3, 4, 9 and 10 containing substituent belonging to the EGD group (-CH₃ (3); –OCH₃ (4); –CH₃, –H (9); –COH₃, –H (10)) and based on the presence of C1–N2 double bond and absence of pseudoradical centre allows for the classification of these compounds as a zwitterionic nitronic acids. Nitronic acids containing EDG substituents in their structure are the most stable among the analyzed nitronic acids. In turn, nitronic acids containing EWG groups are characterized by higher reactivity in chemical reactions compared to other analyzed nitronic acids.