Papers by Keyword: Molecular Modeling

Abstract: This study examines the adsorption behavior of textile dyes Crystal Violet (CV), Methylene Blue (MB), and Congo Red (CR) within cyclodextrin-based metal-organic frameworks (CD-MOFs) using simulated annealing and molecular dynamics simulations. The lowest-energy configurations revealed that CV is predominantly trapped within the central cavity of CD-MOF, stabilized by strong hydrogen bonding between cyclodextrin moieties and the amine group of CV. The adsorption energy of -74.84 kJ mol^-1 suggests strong interaction, indicative of chemisorption-like behavior. MB and CR, in contrast, were primarily adsorbed within the side cavities of CD-MOF, exhibiting adsorption energies of -47.55 kJ mol^-1 and -718.17 kJ mol^-1, respectively. The stability of these dye-CD-MOF complexes was confirmed by molecular dynamics, with low root-mean-square deviations (RMSD) and consistent radii of gyration over 10 ns simulations. Electrostatic and van der Waals interactions played a critical role in maintaining dye entrapment, ensuring prolonged retention within the MOF structure. These results highlight the potential of CD-MOFs as effective adsorbents for dye removal in wastewater treatment, with strong and stable dye-MOF interactions preventing desorption and ensuring efficient pollutant capture.

Abstract: Globally, manufacturing industries are generating a large volume of solid waste during their processes. These wastes, when spread through soil/water affect public health. This work focuses on the use of solid industrial waste from herbal medicine and TiO₂ manufacturing industries to produce iron oxide incorporated biochar, which can be served as adsorbent and low cost catalyst for many reactions. Biochar was produced by the slow pyrolysis of waste collected from herbal manufacturing units using tubular furnace at 550°C at a heating rate of 5°C/min. The iron oxide waste collected from Kerala Minerals and Metals Limited, Kerala, India (KMML), was incorporated into the produced biochar by using planetary ball mill apparatus. Structural and elemental analysis of produced biochar and Fe₂O₃ incorporated biochar was conducted using XRD, SEM and SEM-EDS, BET surface area analysis, ICP-OES, and CHNS analysis. The H/C ratio of prepared biochar shows it has a rectangular layered structure of 50*50 aromatic cluster size. The changes in bonds and groups before and after metal incorporation were studied using FTIR spectroscopic analysis and temperature stability of prepared samples were analyzed using TGA. The molecular structure of produced biochar and changes in their bond length was studied and optimized employing Avogadro and Chemcraft software. The BET analysis shows the surface area of biochar become increased after the metallic incorporation. The same results were concluded from the molecular modelling data obtained from Chemcraft software. These results proved that the biochar surface area and pore volume can be increased by incorporation of iron oxide from industrial waste.

Abstract: Molecular modelling method has been extensively used by process simulators to forecast the expected outcome of certain processes. The objective of this study is to predict the behavior of standard and modified epoxy resins with water using molecular dynamic technique. An arbitrary cell containing adhesive and water molecules was built using the Amorphous Cell Module and dynamic simulation was conducted using Forcite module at two different temperatures; 20 and 50°C for both standard and modified adhesive. From the analysis, the mean square displacement (MSD) for water molecules in a standard adhesive system was higher than Albipox which leads to a higher value of diffusion coefficient. Higher MSD for water in the system with standard adhesive means that it is easier for water molecules to move in the system. It moves to a wider or larger area compared to the water with Albipox in the system. This also shows that the usage of Albipox was successful to control the moisture uptake of water. The predicted diffusion coefficient of water also follows the trend of the experimental data where it increased when the temperature increased for both systems. Based on the result presented in this paper, it has been concluded that molecular modelling was able to predict the interaction of standard and modified adhesive with water.

Abstract: In this paper, we have reported a theoretical study of the geometric and electronic structures of EDOT:SS oligomers based on semi-empirical Austin model1 (AM1) method and density functional theory at B3LYP/3-21G* level. The effects of polymer chain length of both EDOT and SS on structural and electronic properties including bond length, bond angle, binding distance, charge, the highest occupied orbital (HOMO), the lowest unoccupied molecular orbital (LUMO), and energy gap have been studied from the optimized oligomers which were built by varying repeating unit of monomer as n = 1, 2, 3 and 4. The results show that AM1 is not appropriate for geometry optimization of EDOT:SS system comparing to B3LYP/3-21G* level. The binding distance between H atom on EDOT and O atom on SS tends to close together with the average distance of 2.21 Å. The most positive charges locate at sulfur atoms on EDOT and EDOT:SS. The electrical conductivity of EDOT, SS and EDOT:SS increases when polymer chain is extended.

Abstract: Crystal morphology remains an important aspect in pharmaceutical industries and thus lengthy experimentally determined morphology becomes a routine. This leads to advancement of molecular modeling to assist in crystal morphology determination. Morphology of racemic ibuprofen can be grown in PEG 300 solvent and simulated via molecular modeling, the computational technique. The resulting morphology dictates its feasibility and prepares for further necessary control to produce desired morphology. Tuning up the morphology can be done by rationalizing out via molecular modeling the effect of the solvent and crystallization method. Solvent effect persists to influence crystal morphology mainly via interaction of hydrogen bond specific at different facets. However, the influence of solvent-surface interaction in enhancing or inhibiting crystal growth is still not completely resolved. To date, racemic ibuprofen grown in PEG 300 solvent is the first ever reported. The objective of this study is to compare experimental and predicted morphology of racemic ibuprofen using selected potential functions and charge set in vacuum condition. Racemic ibuprofen crystal morphology was grown in PEG 300 solvent via cooling at ambient temperature and predicted via attachment energy (AE) method using molecular modeling. It was found that the experimental morphology is tabular hexagonal while the predicted one is tabular octagonal. The facets were cleaved and its surface chemistry was explained. The predicted lattice energy with lowest percentage error of 0.02% is dominated by van der Waals force rather than electrostatic force.

Abstract: . In this paper, L-alanine crystal was crystallized in the presence and absence of glycine additive using slow evaporation method, in association with a simulation technique using ab-initio quantum mechanical method used to predict the crystal morphology of L-alanine. Comparison between the experimental and simulated lattice energies have shown a good agreement with the 8% error, thus validating the set of force field and the partial atomic charges used. Attachment energy method used by the simulation to predict the morphology of L-alanine crystal, revealed a prismatic crystal morphology bounded with 10 dominant faces: (110), ( 0), ( 10), (1 0), (020), (0 0) (011), (0 ), (0 1) and (01 ), which is in good agreement with the experimental morphology. Crystallization of L-alanine in the presence of glycine in the solution also resulted in prismatic crystal morphology, but elongated in the z-axis direction. This result was further explained by intermolecular bonding analysis of glycine on the morphological faces of L-alanine crystal, which suggested that glycine was preferentially adsorbed on the (0 ) and (1 0) faces of L-alanine crystal morphology.

Abstract: Molecular conformation and binding modeling were built by Hyperchem 8.0 computational chemistry package and the optimum molecular conformation was obtained by molecular mechanics optimizer. It was found that there were two types of binding sites for norfloxacin on the molecular imprinted particles (MIPs).One was the hydrogen bonds between oxygen atom of MIPs with the carbonyl group of norfloxacin and the other one was the hydrogen bonds between oxygen atom of MIPs with the hydroxyl group of norfloxacin. Moreover, the energies change of the molecules were1.69 x10⁶ J/mol, 1.80x10⁶ J/mol and 5.37x10⁶ J/mol and 2.54 x10⁶ J/mol during the binding process of the norfloxacin (NOR), ciprofloxacin (CIP), bisphenol A (BPA) and tonalide (TON) onto the MIPs, respectively. The result indicated that the MIPs had a good selectivity for NOR and CIP than BPA and TON.

Abstract: Many gas-condensate reservoirs experience a sharp drop in gas production owing to condensation near the wellbore as pressure drops lower than the dew point. It has been a challenge for a long time to develop cheaper chemical to stop the dramatic decline in gas production. In this study several molecule formulas are designed, properties of two chemicals for wettability alteration are predicted using molecular modeling method and then synthesized. Analysis result shows high conformity between the prediction and experimental properties.

Abstract: Human α-enolase (ENO1), an evolutionarily conserved and multifunctional protein, is a target self-antigen of rheumatoid arthritis (RA). Rheumatoid arthritis (RA) is genetically associated with MHC class II molecules, such as DRB1*0101, DRB1*0401 and DRB1*0404 allele. Among these DRB1 alleles, DRB1*0401 show the most correlation with RA. However, strong binding ability polypeptide of ENO1 with HLA-DRB1*0401 is still largely unknown. In this study, we used NetMHCII prediction method to predict the strong binding ability polypeptide with HLA-DRB1*0401. Among the 434 predicted fragment peptide, ENO1_129-141: PLYRHIADLAGNS showed strong binding with HLA-DR4 and peptide ENO1_281-293 KSFIKDYPVVSIE is the second candidate peptide. Based on these result, we choosed EON1_129-141 and EON1_281-293 polypeptides to do the molecular modeling, and used the molecular dynamics to optimize the three-dimensional structural model. The molecular dynamics results showed that ENO1_129-141: PLYRHIADLAGNS and ENO1_281-293: KSFIKDYPVVSIE have strong binding ability with HLA-DR4* 0401. In the shared epitope, both ENO1_129-141and ENO1_281-293 have the very near distance 3.15Å and 3.10Å with K71 of the β1 chain. The main-chain conformations of ENO1_129-141 sit more deeply with β1 chain. All together, results indicated that ENO1_129-141 and ENO1_281-293 bind strong with HLA-DR4 and would be potential T cell epitopes of human α-enolase that induced RA.

Abstract: Tumor necrosis factor-alpha converting enzyme (TACE) is a very important membrane-bound proteinase, and it can cut a lot of membrane proteins to their released form. Many of the substrates of TACE are critical protein factors, such as IL-6, TNF-alpha, EGF receptor. Therefore, TACE has been a hopeful drug targets in many diseases. However, selective inhibitors against TACE with high specificity has yet been developed successfully, partly due to the lack of the understanding of the TACE substrate interaction details. To solve this problem, here we build a computational complex model of the TACE catalytic domain and its substrate peptide using the protein design software Rosetta. To further optimize the complex model, molecular dynamics analysis was performed in NAMD with explicit water molecules. The result showed that our complex model is a pretty reliable intermediate model for TACE and its peptide substrate. This complex model could be very useful for further study of the substrate specificity and selectivity of TACE.