Journal of Theoretical and Computational Chemistry

Riboswitch can bind small molecules to regulate gene expression. Unlike other RNAs, riboswitch relies on its conformational switching for regulation. However, the understanding of the switching mechanism is still limited. Here, we focussed on the add A-riboswitch to illustrate the dynamical switching mechanism as an example. We performed molecular dynamics simulation, conservation and co-evolution calculations to infer the dynamical motions and evolutionary base pairings. The results suggest that the binding domain is stable for molecule recognition and binding, whereas the switching base pairings are co-evolutionary for translation. The understanding of the add A-riboswitch switching mechanism provides a potential solution for riboswitch drug design.

One quarter of the world’s population are infected by Mycobacterium tuberculosis (Mtb), which is a leading death-causing bacterial pathogen. Recent evidence has demonstrated that two virulence factors, ESAT-6 and CFP-10, play crucial roles in Mtb’s cytosolic translocation. Many efforts have been made to study the ESAT-6 and CFP-10 proteins. Some studies have shown that ESAT-6 has an essential role in rupturing phagosome. However, the mechanisms of how ESAT-6 interacts with the membrane have not yet been fully understood. Recent studies indicate that the ESAT-6 disassociates with CFP-10 upon their interaction with phagosome membrane, forming a membrane-spanning pore. Based on these observations, as well as the available structure of ESAT-6, ESAT-6 is hypothesized to form an oligomer for membrane insertion as well as rupturing. Such an ESAT-6 oligomer may play a significant role in the tuberculosis infection. Therefore, deeper understanding of the oligomerization of ESAT-6 will establish new directions for tuberculosis treatment. However, the structure of the oligomer of ESAT-6 is not known. Here, we proposed a comprehensive approach to model the complex structures of ESAT-6 oligomer inside a membrane. Several computational tools, including MD simulation, symmetrical docking, MM/PBSA, are used to obtain and characterize such a complex structure. Results from our studies lead to a well-supported hypothesis of the ESAT-6 oligomerization as well as the identification of essential residues in stabilizing the ESAT-6 oligomer which provide useful insights for future drug design targeting tuberculosis. The approach in this research can also be used to model and study other cross-membrane complex structures.

Mucin-type O-glycosylation is one of the most common post-translational modifications of proteins. This glycosylation is initiated in the Golgi by the addition of the sugar N-acetylgalactosamine (GalNAc) onto protein Ser and Thr residues by a family of polypeptide GalNAc transferases. In humans, there are 20 isoforms that are differentially expressed across tissues that serve multiple important biological roles. Using random peptide substrates, isoform specific amino acid preferences have been obtained in the form of enhancement values (EV). These EVs alone have previously been used to predict O-glycosylation sites via the web based ISOGlyP (Isoform Specific O-Glycosylation Prediction) tool. Here, we explore additional protein features to determine whether these can complement the random peptide derived enhancement values and increase the predictive power of ISOGlyP. The inclusion of additional protein substrate features (such as secondary structure and surface accessibility) was found to increase sensitivity with minimal loss of specificity, when tested with three different published in vivo O-glycoproteomics data sets, thus increasing the overall accuracy of the ISOGlyP predictions.

To investigate the thermal behavior of complex model with amorphous region and crystallization region of cellulose II, the structures and properties of cellulose II, amorphous chain and their combined models were studied by molecular dynamics simulation. The results showed that the amorphous chain is more susceptible to temperature than the cellulose II. It can form anti-parallel structure similar to cellulose II at high temperature. In the complex model, one end of the amorphous chain is fixed to form hydrogen bonds with the cellulose II, and the other end is not. At 300K, the free part of amorphous chain is approximately perpendicular to the axial direction of the cellulose II. When the temperature increases, the free part of amorphous chain adheres to the surface of cellulose II. The free part of amorphous chain did not form hydrogen bond with the cellulose II. The formation of amorphous chain and surface of the cellulose II is a zipper process at 450K. Furthermore, water molecules penetrate into the inter-space of the amorphous and crystalline regions. The probability of hydrogen bonds between water molecules and the complex model was less than 8.21% which explains why cellulose is insoluble in water. These conclusions provide a guiding significance for the dissolution mechanism of cellulose.

This paper deals with the entropy optimization and heat transport of magneto-nanomaterial flow of non-Newtonian (Jeffrey fluid) towards a curved stretched surface. MHD fluid is accounted. The modeling of energy expression is developed subject to Brownian diffusion, Joule (Ohmic) heating, thermophoresis and viscous dissipation. Total entropy rate is discussed with the help of fluid friction irreversibility, mass transfer irreversibility, Joule heating irreversibility and heat transfer irreversibility. Binary chemical reaction with the smallest amount of activation energy is further considered. The governing equations of Jeffrey fluid with effects of hydrodynamic, thermal radiation, heat and mass transfer were solved through built-in-shooting method. The flow variables on the entropy rate, velocity field, concentration, Bejan number, skin friction coefficient and temperature are physically discussed through various graphs. The outcomes reveal that the entropy rate increases with an enhancement in curvature parameter. Such obtained outcomes help in mechanical and industrial engineering sciences. Moreover, the velocity and temperature decays versus ratio of relaxation to retardation times are also noticed.

The high-throughput correlated DNA methylation (DNAmeth) dataset generated from Illumina Infinium Human Methylation 27 (IIHM 27K) BeadChip assay. In the DNAmeth data, there are several CpG sites for every gene, and these grouped CpG sites are highly correlated. Most of the current filtering-based ranking (FBR) methods do not consider the group correlation structures. Obtaining the significant features with the FBR methods and applying these features to the classifiers to attain the best classification accuracy in highly correlated DNAmeth data is a challenging task. In this research, we introduce a resampling of group least absolute shrinkage and selection operator (glasso) FBR method capable of ignoring the unrelated features in the data considering the group correlation among the features. The various classifiers, such as random forests (RF), Naive Bayes (NB), and support vector machines (SVM) with the significant CpGs obtained from the proposed resampling of group lasso-based ranking (RGLR) method helped to boost the classification accuracy. Through simulated and experimental prostate DNAmeth data, we showed that higher performance of accuracy, sensitivity, specificity, and geometric mean is achieved by ignoring the unimportant CpG sites through the RGLR method.