In this work, the influence of dipeptide composition on protein thermostability was studied. After comparing the normalized dipeptide composition between mesophilic proteins and (hyper)thermophilic proteins, we concluded that when organism optimal growth temperature increased, for archaeal proteins, the compositions of VK, KI, YK, IK, KV, KY, and EV increased significantly and the compositions of DA, AD, TD, DD, DT, HD, DH, DR, and DG decreased significantly; and for bacterial proteins, the compositions of KE, EE, EK, YE, VK, KV, KK, LK, EI, EV, RK, EF, KY, VE, KI, KG, EY, FK, KF, FE, KR, VY, MK, WK, and WE increased significantly and the compositions of WQ, AA, QA, MQ, AW, QW, QQ, RQ, QH, HQ, AD, AQ, WL, QL, HA, and DA decreased significantly. So these characteristic dipeptides are correlative to protein thermostability. At the same time, the influence of single amino acid composition on protein thermostability was also studied for comparison. We found that the influence of single amino acid composition could be deduced from the influence of dipeptide composition. So we thought that the influence of dipeptide composition on protein thermostability is larger than the influence of amino acid composition. The characteristic dipeptides not only describe the dipeptides that influence protein thermostability significantly but also show the relationship among significant single amino acids that influence protein thermostability.
The iterative method in functional analysis is applied to looking for a solution of the Poisson-Boltzmann equation in order to describe the problems of the distribution of the potentials in the electric double layer (EDL) inside the water pool for a cylindrical inverse micelle. Potentials as a function of the position of a particular point in EDL are computed, which display a quantitative agreement with those from earlier calculation of Debye and Hückel in the case of low potentials. But it is also shown that in the higher-potential range the iterative calculations can give more accurate results. These results indicate the utility of this functional analysis technique in the description of the properties of EDL for a cylindrical inverse micelle.
Density functional theory (DFT) of quantum chemistry was used to optimize the configuration of the anionic surfactant complexes CH 3 (CH 2 ) 7 OSO− 3 (H 2 O) n (n=0-6) and calculate their molecular frequencies at the B3LYP/6-311+G * level. The interaction of CH 3 (CH 2 ) 7 OSO − 3 with 1 to 6 water molecules was investigated at the air-water interface with DFT. The results revealed that the hydration shell was formed in the form of H-bond between the hydrophilic group of CH 3 (CH 2 ) 7 OSO − 3 and 6 waters. The strength of H-bonds belongs to medium. Binding free energy revealed that the hydration shell was stable. The increase of the number of water molecules will cause increases of the total charge of hydrophilic group and S10-O9-C8 bond angle, but decreases of the alkyl chain length and the bond lengths of S10-O11, S10-O12 as well as S10-O13, respectively. anionic surfactant, quantum chemistry method, density functional theory A surfactant molecule has an amphiphilic structure and a tendency to escape from solution. Therefore, surfactants can concentrate from the solution and adsorb each other together to form a parallel single molecular layer easily at the interface when dissolved in water. This is a speculation from molecule structure of surfactant [1] . By measuring the interfacial tension and using the Gibbs adsorption equation, we can conduct experiment analysis of the status of adsorption of surfactants at the air-water interface [1,2] . And by using molecular dynamics simulation, the adsorption of surfactants at the interface also can be predicted [3][4][5] . But neither of the above described the changes of molecular structure of surfactants adsorbed at the interface and the essential of interaction between surfactant and solvent at the molecular level. Because of the complicated molecular structure of the surfactant, which generally consists of from dozens of atoms to hundreds of atoms and possesses the amphiphilic structure, and very little work has been reported on the adsorption of the surfactant at the interface with quantum chemistry method so far. Ryszard and his co-workers [6] investigated the interaction of an alkyl ammonium surfactant with only three water molecules. Yan et al. [7] investigated the characteristics of electronic structure for surfactants in solution by using Onsager model. But neither of them described the mechanism of interaction between surfactant and solvent at the molecular level. Hence, if the interaction of surfactant with solvent at the air/water interface can be investigated with quantum chemistry method, it will not only provide theoretical reference for explaining the adsorption of surfactant at the interface, but also enlarge the application of the quantum chemistry method in surfactant area.In the present work, with the help of quantum chemistry, the interactions of a widely used anionic surfactant,
Molecular dynamics simulation of the interaction between the Tenebrio molitor alpha-amylase and its inhibitor at different proportion of crystal water was carried out with OPLS force field by hyperchem 7.5 software. In the correlative study, the optimal temperature of wheat monomeric and dimeric protein inhibitors was from 273 K to 318 K. The the average temperature of experimentation is 289 K. (1) The optimal temperature of interaction between alpha-amylase and its inhibitors was 280 K without crystal water that was close to the results of experimentation. The forming of enzyme-water and inhibitor-water was easy, but incorporating third monomer was impossible. (2) Having analyzed the potential energy data, the optimal temperature of interaction energy between alpha-amylase and its inhibitors covering 9 : 1, 5 : 5, 4 : 6, and 1 : 9 proportion crystal water was 290 K. (3) We compared the correlative QSAR properties. The proportion of crystal water was close to the data of polarizability (12.4%) in the QSAR properties. The optimal temperature was 280 K. This result was close to 289 K. These findings have theoretical and practical implications.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.