Systems biology is the inevitable outcome of long years of knowledge acquisition and data accumulation. The aim of systems biology is to integrate in a seamless way all existing knowledge in ...interconnected disciplines, stretching from modern biomedical research to physics, chemistry, and mathematics. The main integration tool of such complex biomedical systems is via computational and mathematical modeling. In this direction, a series of state-of-the-art computer science techniques are used, namely, data mining and fusion, machine learning, and deep learning all under the prism of big data. All in all, systems biology is at the arrowhead of modern and state-of-the-art biomedical research by attempting to address key biological questions describing holistically complex biological systems.
The contribution of modern-day genetics in designing efficient gene expression profiles for cancer is immense. The progress of technology and science in recent years provides the opportunity for ...discovery and application of new techniques for treating various diseases that affect humanity. Methods for finding and analyzing the profile of gene expression of infected cells give scientists the ability to develop more targeted and effective treatments, especially for diseases such as cancer. The development of gene expression profiling is one of the most important achievements in cancer genetics in our time. It is essentially the driving force behind personalized and precision medicine. This book highlights recent developments, applications, and breakthroughs in the field of gene expression profiling in cancer.
The novel coronavirus SARS-CoV-2 has emerged as a severe threat against public health and global economies. COVID-19, the disease caused by this virus, is highly contagious and has led to an ongoing ...pandemic. SARS-CoV-2 affects, mainly, the respiratory system, with most severe cases primarily showcasing acute respiratory distress syndrome. Currently, no targeted therapy exists, and since the number of infections and death toll keeps rising, it has become a necessity to study possible therapeutic targets. Antiviral drugs can target various stages of the viral infection, and in the case of SARS-CoV-2, both structural and non-structural proteins have been proposed as potential drug targets. This review focuses on the most researched SARS-CoV-2 proteins, their structure, function, and possible therapeutic approaches.
•Structural and non-structural proteins of SARS-CoV-2 are potential drug targets.•Spike glycoprotein and viral proteases may be promising targets against COVID-19.•Multi-stage viral entry/replication/viral vesicle formation are therapeutic targets.•Toxicity is a critical component in the development of safe and effective drugs.
Concerted alteration of immune and metabolic homeostasis underlies several inflammation-related pathologies, ranging from metabolic syndrome to infectious diseases. Here, we explored the coordination ...of nucleic acid-dependent inflammatory responses and metabolic homeostasis. We reveal that the STING (stimulator of interferon genes) protein regulates metabolic homeostasis through inhibition of the fatty acid desaturase 2 (FADS2) rate-limiting enzyme in polyunsaturated fatty acid (PUFA) desaturation. STING ablation and agonist-mediated degradation increased FADS2-associated desaturase activity and led to accumulation of PUFA derivatives that drive thermogenesis. STING agonists directly activated FADS2-dependent desaturation, promoting metabolic alterations. PUFAs in turn inhibited STING, thereby regulating antiviral responses and contributing to resolving STING-associated inflammation. Thus, we have unveiled a negative regulatory feedback loop between STING and FADS2 that fine-tunes inflammatory responses. Our results highlight the role of metabolic alterations in human pathologies associated with aberrant STING activation and STING-targeting therapies.
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•STING inhibits FADS2-dependent desaturation of PUFAs and LC-PUFAs•STING activation leads to upregulation of FADS2-associated desaturase activity•STING agonists activate FADS2-dependent PUFA and LC-PUFA desaturation•PUFAs inhibit STING-dependent inflammatory responses
The stimulator of interferon genes (STING) is a central regulator of nucleic acid-associated inflammatory responses. Here, Vila et al. discover that STING regulates polyunsaturated fatty acid (PUFA) metabolism, and in turn, PUFAs inhibit STING-dependent inflammation. This cross-regulation is central to the maintenance of metabolic homeostasis.
COVID19 is the most impactful pandemic of recent times worldwide. It is a highly infectious disease that is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2 virus), To date there ...is specific drug nor vaccination against COVID19. Therefor the need for novel and pioneering anti-COVID19 is of paramount importance. In this direction, computer-aided drug design constitutes a very promising antiviral approach for the discovery and analysis of drugs and molecules with biological activity against SARS-CoV2.
In silico
modelling takes advantage of the massive amounts of biological and chemical data available on the nature of the interactions between the targeted systems and molecules, as well as the rapid progress of computational tools and software. Herein, we describe the potential of the merging of mathematical modelling, artificial intelligence and learning techniques into seamless computational pipelines for the rapid and efficient discovery and design of potent anti- SARS-CoV-2 modulators.
Gene expression is a complex process that is essential to living organisms. Gene expression plays the important role of converting information that is encoded in a gene into a functional product. The ...primary regulators of gene expression are transcription factors (TFs). TFs are proteins that can bind specific DNA sequences and regulate gene expression. Their evolution is influenced by a large number of factors, including epigenetic mechanisms, gene regulatory elements and molecular cofactors. These molecular mediators, along with transcription factors, form a network that governs gene expression. Elucidating the mechanisms through which TFs have evolved and how they influence the evolution of other regulatory molecules can provide information on organism evolution and on the development of phenotypic variations. The aim of this review article was to provide a summary of the current literature on transcription factor evolution, function and how such evolution has played an important role in the emergence of complex organisms. Key words: transcription regulation, transcription factors, evolution, development, evo-devo, cis-regulatory elements, epigenetics
Monocarboxylate transporters (MCTs) are of great research interest for their role in cancer cell metabolism and their potential ability to transport pharmacologically relevant compounds across the ...membrane. Each member of the MCT family could potentially provide novel therapeutic approaches to various diseases. The major differences among MCTs are related to each of their specific metabolic roles, their relative substrate and inhibitor affinities, the regulation of their expression, their intracellular localization, and their tissue distribution. MCT4 is the main mediator for the efflux of L-lactate produced in the cell. Thus, MCT4 maintains the glycolytic phenotype of the cancer cell by supplying the molecular resources for tumor cell proliferation and promotes the acidification of the extracellular microenvironment from the co-transport of protons. A promising therapeutic strategy in anti-cancer drug design is the selective inhibition of MCT4 for the glycolytic suppression of solid tumors. A small number of studies indicate molecules for dual inhibition of MCT1 and MCT4; however, no selective inhibitor with high-affinity for MCT4 has been identified. In this study, we attempt to approach the structural characteristics of MCT4 through an in silico pipeline for molecular modelling and pharmacophore elucidation towards the identification of specific inhibitors as a novel anti-cancer strategy.
Understanding the structure and function of intermediate filaments (IFs) is necessary in order to explain why more than 70 related IF genes have evolved in vertebrates while maintaining such ...dramatically tissue-specific expression. Desmin is a member of the large multigene family of IF proteins and is specifically expressed in myocytes. In an effort to elucidate its muscle-specific behavior, we have used a yeast two-hybrid system in order to identify desmin's head binding partners. We described a mitochondrial and a lysosomal protein, NADH ubiquinone oxidoreductase core subunit S2 (NDUFS2), and saposin D, respectively, as direct desmin binding partners. In silico analysis indicated that both interactions at the atomic level occur in a very similar way, by the formation of a three-helix bundle with hydrophobic interactions in the interdomain space and hydrogen bonds at R16 and S32 of the desmin head domain. The interactions, confirmed also by GST pull-down assays, indicating the necessity of the desmin head domain and, furthermore, point out its role in function of mitochondria and lysosomes, organelles which are disrupted in myopathies due to desmin head domain mutations.
The human microbiome has emerged as a central research topic in human biology and biomedicine. Current microbiome studies generate high-throughput omics data across different body sites, populations, ...and life stages. Many of the challenges in microbiome research are similar to other high-throughput studies, the quantitative analyses need to address the heterogeneity of data, specific statistical properties, and the remarkable variation in microbiome composition across individuals and body sites. This has led to a broad spectrum of statistical and machine learning challenges that range from study design, data processing, and standardization to analysis, modeling, cross-study comparison, prediction, data science ecosystems, and reproducible reporting. Nevertheless, although many statistics and machine learning approaches and tools have been developed, new techniques are needed to deal with emerging applications and the vast heterogeneity of microbiome data. We review and discuss emerging applications of statistical and machine learning techniques in human microbiome studies and introduce the COST Action CA18131 "ML4Microbiome" that brings together microbiome researchers and machine learning experts to address current challenges such as standardization of analysis pipelines for reproducibility of data analysis results, benchmarking, improvement, or development of existing and new tools and ontologies.
Molecular docking has always been and will be on the forefront of developments in the eminent field of drug design and medicinal chemistry. At the early days, drug discovery was based on blackboard ...drawings and expert intuition. However, as times move on, the amount of available information and overall knowledge base that needs to be analyzed cannot be processed manually. This, coupled by the rapid growth in computational infrastructure and processing power, has allowed for the efficient use of molecular docking tools and algorithms to be considered in the greater field of drug discovery. In the postgenomic era, molecular docking has become the key player for the screening of hundreds of thousands of compounds against a repertoire of pharmacological targets.
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