Computational Study of the Binding Mechanism of Actin-Depolymerizing Factor 1 with Actin in Arabidopsis thaliana

Genome-Wide Identification and Low Temperature Responsive Pattern of Actin Depolymerizing Factor (ADF) Gene Family in Wheat (Triticum aestivum L.)

The actin depolymerizing factor (ADF) gene family, which is conserved in eukaryotes, is important for plant development, growth, and stress responses. Cold stress restricts wheat growth, development, and distribution. However, genome-wide identification and functional analysis of the ADF family in wheat is limited. Further, because of the promising role of ADF genes in cold response, there is need for an understanding of the function of this family on wheat under cold stress. In this study, 25 ADF genes (TaADFs) were identified in the wheat genome and they are distributed on 15 chromosomes. The TaADF gene structures, duplication events, encoded conversed motifs, and cis-acting elements were investigated. Expression profiles derived from RNA-seq data and real-time quantitative PCR analysis revealed the tissue- and temporal-specific TaADF expression patterns. In addition, the expression levels of TaADF13/16/17/18/20/21/22 were significantly affected by cold acclimation or freezing conditions. Overexpression of TaADF16 increased the freezing tolerance of transgenic Arabidopsis, possibly because of enhanced ROS scavenging and changes to the osmotic regulation in cells. The expression levels of seven cold-responsive genes were up-regulated in the transgenic Arabidopsis plants, regardless of whether the plants were exposed to low temperature. These findings provide fundamental information about the wheat ADF genes and may help to elucidate the regulatory effects of the encoded proteins on plant development and responses to low-temperature stress.

Dynamics Insights Into the Gain of Flexibility by Helix-12 in ESR1 as a Mechanism of Resistance to Drugs in Breast Cancer Cell Lines

Incidents of breast cancer (BC) are on the rise on a daily basis and have proven to be the most prevelant cause of death for women in both developed and developing countries. Among total BC cases diagnosed after menopause, 70% of cases are Estrogen Receptor (ER) positive (ER-positive or ER+). Mutations in the LBD (ligand-binding domain) of the ER have recently been reported to be the major cause of resistance to potent antagonists. In this study, the experimentally reported mutations K303R, E380Q, V392I, S463P, V524E, P535H, P536H, Y537C, Y537N, Y537S, and D538G were analyzed, and the most significant mutations were shortlisted based on multiple analyses. Initial analyses, such as mCSM stability, occluded depth analysis, mCSM-binding affinity, and FoldX energy changes shortlisted only six mutations as being highly resistant. Finally, simulations of force field-based molecular dynamics (MD on wild type (WT) ERα) on six mERα variants (E380Q, S463P, Y537S, Y537C, Y537N, and D538G) were carried out to justify mechanism of the resistance. It was observed that these mutations increased the flexibility of the H12. A bonding analysis suggested that previously reported important residue His524 lost bonding upon mutation. Other parameters, such as PCA (principal component analysis), DCCM (dynamics cross-correlation), and FEL (free energy landscape), verified that the shortlisted mutations affect the H12 helix, which opens up the co-activator binding conformation. These results provide deep insight into the mechanism of relative resistance posed to fulvestrant due to mutations in breast cancer. This study will facilitate further understanding of the important aspects of designing specific and more effective drugs.

Recent Developments and Applications of the MMPBSA Method

The Molecular Mechanics Poisson-Boltzmann Surface Area (MMPBSA) approach has been widely applied as an efficient and reliable free energy simulation method to model molecular recognition, such as for protein-ligand binding interactions. In this review, we focus on recent developments and applications of the MMPBSA method. The methodology review covers solvation terms, the entropy term, extensions to membrane proteins and high-speed screening, and new automation toolkits. Recent applications in various important biomedical and chemical fields are also reviewed. We conclude with a few future directions aimed at making MMPBSA a more robust and efficient method.