计算分子生物学(英文)最新文献

Cancer is a public health crisis affecting approximately 19.3 million globally annually. Lung cancer has the highest percentage of incidence and is responsible for 27% of cancer-related deaths. The lung cancer of prevalence in smokers is small-cell lung carcinoma. Lung cancer cells often exhibit altered gene expression patterns, compared to their normal counterparts. Yet this differential gene expression is not well understood. Herein, we investigated the differential expression of genes in small cell cancer cell lines compared to a healthy lung cell line that can lead to further insights into the proliferation, metastasis, and drug resistance of these lung cancer cells. Whole transcriptomic and small non-coding RNA sequencing was done by Next-generation sequencing (NGS) method, coupled with the Ingenuity Pathway Analysis (IPA) to decipher the core canonical pathways involved in these lung cancer cell-signaling mechanisms in disease pathophysiology. The findings of this investigation identified multiple genes and small non-coding tRNA/tRNA fragments that were differentially expressed, which thereby showed the possibility of potential diagnostic/prognostic and therapeutic targets. This important transcriptomic analysis can be a valuable tool for developing more effective treatment strategies for smokers lung cancer.

Triple Negative Breast Cancer (TNBC) is a malignant form of cancer with very high mortality and morbidity. Epithelial to Mesenchymal Transition (EMT) is the most common pathophysiological change observed in cancer cells of epithelial origin that promotes metastasis, drug resistance and cancer stem cell formation. Since the information regarding differential gene expression in TNBC cells and cell signaling events leading to EMT is limited, this investigation was done by comparing transcriptomic data generated by RNA isolation and sequencing of a EMT model TNBC cell line in comparison to regular TNBC cells. RNA sequencing and Ingenuity Pathway Software Analysis (IPA) of the transcriptomic data revealed several upregulated and downregulated gene expressions along with novel core canonical pathways including Sirtuin signaling, Oxidative Phosphorylation and Mitochondrial dysfunction events involved in EMT changes of the TNBC cells.

The novel coronavirus (SARS-COV-2) is generally referred to as Covid-19 virus has spread to 213 countries with nearly 7 million confirmed cases and nearly 400,000 deaths. Such major outbreaks demand classification and origin of the virus genomic sequence, for planning, containment, and treatment. Motivated by the above need, we report two alignment-free methods combing with CGR to perform clustering analysis and create a phylogenetic tree based on it. To each DNA sequence we associate a matrix then define distance between two DNA sequences to be the distance between their associated matrix. These methods are being used for phylogenetic analysis of coronavirus sequences. Our approach provides a powerful tool for analyzing and annotating genomes and their phylogenetic relationships. We also compare our tool to ClustalX algorithm which is one of the most popular alignment methods. Our alignment-free methods are shown to be capable of finding closest genetic relatives of coronaviruses.

The current Chemistry at Harvard Molecular Mechanics (CHARMM) force field cannot accurately describe the properties of unsaturated phospholipid membranes. In this paper, a series of simulations was performed in which the Lennard-Jones (L-J) parameters of lipid acyl chains of dioleoylphosphatidylcholine (DOPC) were systematically adjusted. The results showed that adjustment of the L-J parameters in lipid acyl chains can significantly improve the current CHARMM force field. It was found that the L-J parameters have different influences on the order parameters of the top half and bottom half of the chain, separated by the cis double bond. The order parameters of the top half and the bottom half of the chain are related to the area/lipid and the length of the chain, respectively.

The results of computer simulations of the binding of etravirine (TMC125) and rilpivirine (TMC278) to HIV reverse transcriptase are reported. It is confirmed that consistent binding free energy estimates are obtained with or without the application of torsional restraints when the free energies of imposing the restraints are taken into account. The restraints have a smaller influence on the thermodynamics and apparent kinetics of binding of TMC125 compared to the more flexible TMC278 inhibitor. The concept of the reorganization free energy of binding is useful to understand and categorize these effects. Contrary to expectations, the use of conformational restraints did not consistently enhance convergence of binding free energy estimates due to suppression of binding/unbinding pathways and due to the influence of rotational degrees of freedom not directly controlled by the restraints. Physical insights concerning the thermodynamic driving forces for binding and the role of "jiggling" and "wiggling" motion of the ligands are discussed. Based on these insights we conclude that an ideal inhibitor, if chemically realizable, would possess the electrostatic charge distribution of TMC125, so as to form strong interactions with the receptor, and the larger and more flexible substituents of TMC278, so as to minimize reorganization free energy penalties and the effects of resistance mutations, suitably modified, as in TMC125, so as to disfavor the formation of non-binding competent extended conformations when free in solution.