Abstract: Medications used for supportive care or prophylaxis constitute a significant portion of drug utilization in the intensive care unit. Evidence-based guidelines are available for many aspects of supportive care but drug doses listed are typically for patients with normal body habitus and not morbid obesity. Failure to account for the pharmacokinetic changes that occur with obesity can lead to an incorrect dose and treatment failure or toxicity. This paper is intended to help clinicians design initial dosing regimens in critically ill obese patients for medications commonly used for hemodynamic support or prophylaxis. A detailed literature search of medications used for supportive care or prophylaxis listed in practice guidelines was conducted with an emphasis on obesity, pharmacokinetics and dosing. Relevant manuscripts were reviewed and strategies for dosing are provided. For medications used for hemodynamic support, a similar strategy can be used as in non-obese patients. Similarly, medications for stress ulcer prophylaxis do not need to be adjusted. Anticoagulants for venous thromboembolism prophylaxis, on the other hand, require an individualized approach where higher doses are necessary.

Abstract: The recent outbreak of SARS-CoV-2 is responsible for high morbidity and mortality rate across the globe. This requires an urgent identification of drugs and other interventions to overcome this pandemic. Computational drug repurposing represents an alternative approach to provide a more effective approach in search for COVID-19 drugs. Selected natural product known to have antiviral activities were screened, and based on their hits; a similarity search with FDA approved drugs was performed using computational methods. Obtained drugs from similarity search were assessed for their stability and inhibition against SARS-CoV-2 targets. Diosmin (DB08995) was found to be a promising drug that works with two distinct mechanisms, preventing viral replication and viral fusion into the host cell. Isoquercetin (DB12665) and rutin (DB01698) work by inhibiting viral replication and preventing cell entry, respectively. Our analysis based on molecular dynamics simulation and MM-PBSA binding free energy calculation suggests that diosmin, isoquercetin, rutin and other similar flavone glycosides could serve as SARS-CoV-2 inhibitor, hence an alternative solution to treat COVID-19 upon further clinical validation.

Abstract: Although several pharmacological agents are under investigation to be repurposed as therapeutic against COVID-19, not much success has been achieved yet. So, the search for an effective and active option for the treatment of COVID-19 is still a big challenge. The Spike protein (S), RNA-dependent RNA polymerase (RdRp), and Main protease (Mpro) are considered to be the primary therapeutic drug target for COVID-19. In this study we have screened the drugbank compound library against the Main Protease. But our search was not limited to just Mpro. Like other viruses, SARS-CoV-2, have also acquired unique mutations. These mutations within the active site of these target proteins may be an important factor hindering effective drug candidate development. In the present study we identified important active site mutations within the SARS-CoV-2 Mpro (Y54C, N142S, T190I and A191V). Further the drugbank database was computationally screened against Mpro and the selected mutants. Finally, we came up with the common molecules effective against the wild type (WT) and all the selected Mpro. The study found Imiglitazar, was found to be the most active compound against the wild type of Mpro. While PF-03715455 (Y54C), Salvianolic acid A (N142S and T190I), and Montelukast (A191V) were found to be most active against the other selected mutants. It was also found that some other compounds such as Acteoside, 4-Amino-N- {4-[2-(2,6-Dimethyl-Phenoxy)-Acetylamino]-3-Hydroxy-1-Isobutyl-5-Phenyl-Pentyl}-B enzamide, PF-00610355, 4-Amino-N-4-[2-(2,6-Dimethyl-Phenoxy)-Acetylamino]-3-Hydroxy-1-Isobutyl-5-Phenyl- Pentyl}-Benzamide and Atorvastatin were showing high efficacy against the WT as well as other selected mutants. We believe that these molecules will provide a better and effective option for the treatment of COVID-19 clinical manifestations.

Abstract: The core goal of cheminformatics is to efficiently store robust and accurate chemical information and make it accessible for drug discovery, environmental analysis, and the development of prediction models including quantitative structure-activity relationships (QSAR). The U.S. Environmental Protection Agency (EPA) has developed a web-based application, the CompTox Chemicals Dashboard, which provides access to a compilation of data generated within the agency and sourced from public databases and literature and to utilities for real-time QSAR prediction and chemical read-across. While the vast majority of online tools only allow interrogation of chemicals one at a time, the Dashboard provides a batch search feature that allows for the sourcing of data based on thousands of chemical inputs at one time, by chemical identifier (e.g., names, Chemical Abstract Service registry numbers, or InChIKeys), or by mass or molecular formulas. Chemical information that can then be sourced via the batch search includes chemical identifiers and structures; intrinsic, physicochemical and fate and transport properties; in vitro and in vivo toxicity data; and the presence in environmentally relevant lists. We outline how to use the batch search feature and provide an overview regarding the type of information that can be sourced by considering a series of typical-use questions.

Abstract: Data integration plays a vital role in scientific research. In biomedical research, the OMICS fields have shown the need for larger datasets, like proteomics, pharmacogenomics, and newer fields like foodomics. As research projects require multiple data sources, mapping between these sources becomes necessary. Utilized workflow systems and integration tools therefore need to process large amounts of heterogeneous data formats, check for data source updates, and find suitable mapping methods to cross-reference entities from different databases. This article presents BioDWH2, an open-source, graph-based data warehouse and mapping tool, capable of helping researchers with these issues. A workspace centered approach allows project-specific data source selections and Neo4j or GraphQL server tools enable quick access to the database for analysis. The BioDWH2 tools are available to the scientific community at https://github.com/BioDWH2.

Abstract: Aging is a physiological process whose underlying mechanisms are still largely unknown. The study of the biochemical transformations associated with aging is crucial for understanding this process and could translate into an improvement of the quality of life of the aging population. Red blood cells (RBCs) are the most abundant cells in humans and are involved in essential functions that could undergo different alterations with age. The present study analyzed the metabolic alterations experienced by RBCs during aging, as well as the influence of obesity and gender in this process. To this end, the metabolic profile of 83 samples from healthy and obese patients was obtained by Nuclear Magnetic Resonance spectroscopy. Multivariate statistical analysis revealed differences between Age-1 (=45) and Age-2 (>45) subgroups, as well as between BMI-1 (<30) and BMI-2 (>/=30) subgroups, while no differences were associated with gender. A general decrease in the levels of amino acids was detected with age, in addition to metabolic alterations of glycolysis, the pentose phosphate pathway, nucleotide metabolism, glutathione metabolism and the Luebering-Rapoport shunt. Obesity also had an impact on the metabolomics profile of RBCs; sometimes mimicking the alterations induced by aging, while, in other cases, its influence was the opposite, suggesting these changes could counteract the adaptation of the organism to senescence.

Abstract: Mitochondrial (mt) dysfunction is linked to rare diseases (RDs) such as respiratory chain complex (RCC) deficiency, MELAS, and ARSACS. Yet, how altered mt protein networks contribute to these ailments remains understudied. In this perspective article, we identified 21 mt proteins from public repositories that associate with RCC deficiency, MELAS, or ARSACS, engaging in a relatively small number of protein-protein interactions (PPIs), underscoring the need for advanced proteomic and interactomic platforms to uncover the complete scope of mt connectivity to RDs. Accordingly, we discuss innovative untargeted label-free proteomics in identifying RD-specific mt or other macromolecular assemblies and mapping of protein networks in complex tissue, organoid, and stem cell-differentiated neurons. Furthermore, tag- and label-based proteomics, genealogical proteomics, and combinatorial affinity purification-mass spectrometry, along with advancements in detecting and integrating transient PPIs with single-cell proteomics and transcriptomics, collectively offer seminal follow-ups to enrich for RD-relevant networks, with implications in RD precision medicine.

Abstract: Coronavirus desease 2019 (COVID-19) is responsible for more than 1.80 M deaths worldwide. A Quantitative Structure-Activity Relationships (QSAR) model is developed based on experimental pIC50 values reported for a structurally diverse dataset. A robust model with only five descriptors is found, with values of R(2) = 0.897, Q(2)LOO = 0.854, and Q(2)ext = 0.876 and complying with all the parameters established in the validation Tropsha's test. The analysis of the applicability domain (AD) reveals coverage of about 90% for the external test set. Docking and molecular dynamic analysis are performed on the three most relevant biological targets for SARS-CoV-2: main protease, papain-like protease, and RNA-dependent RNA polymerase. A screening of the DrugBank database is executed, predicting the pIC50 value of 6664 drugs, which are IN the AD of the model (coverage = 79%). Fifty-seven possible potent anti-COVID-19 candidates with pIC50 values > 6.6 are identified, and based on a pharmacophore modelling analysis, four compounds of this set can be suggested as potent candidates to be potential inhibitors of SARS-CoV-2. Finally, the biological activity of the compounds was related to the frontier molecular orbitals shapes.

Abstract: Obstructive sleep apnea (OSA) results from episodes of airway collapse and intermittent hypoxia (IH) and is associated with a host of health complications. Although the lung is the first organ to sense changes in oxygen levels, little is known about the consequences of IH to the lung hypoxia-inducible factor-responsive pathways. We hypothesized that exposure to IH would lead to cell-specific up- and downregulation of diverse expression pathways. We identified changes in circadian and immune pathways in lungs from mice exposed to IH. Among all cell types, endothelial cells showed the most prominent transcriptional changes. Upregulated genes in myofibroblast cells were enriched for genes associated with pulmonary hypertension and included targets of several drugs currently used to treat chronic pulmonary diseases. A better understanding of the pathophysiologic mechanisms underlying diseases associated with OSA could improve our therapeutic approaches, directing therapies to the most relevant cells and molecular pathways.

Abstract: Programed cell death or apoptosis fails to induce cell death in many recalcitrant cancers. Thus, there is an emerging need to activate the alternate cell death pathways in such cancers. In this study, we analyzed the apoptosis-resistant colon adenocarcinoma, glioblastoma multiforme, and small cell lung cancers transcriptome profiles. We extracted clusters of non-apoptotic cell death genes from each cancer to understand functional networks affected by these genes and their role in the induction of cell death when apoptosis fails. We identified transcription factors regulating cell death genes and protein-protein interaction networks to understand their role in regulating cell death mechanisms. Topological analysis of networks yielded FANCD2 (ferroptosis, negative regulator, down), NCOA4 (ferroptosis, up), IKBKB (alkaliptosis, down), and RHOA (entotic cell death, down) as potential drug targets in colon adenocarcinoma, glioblastoma multiforme, small cell lung cancer phenotypes respectively. We also assessed the miRNA association with the drug targets. We identified tumor growth-related interacting partners based on the pathway information of drug-target interaction networks. The protein-protein interaction binding site between the drug targets and their interacting proteins provided an opportunity to identify small molecules that can modulate the activity of functional cell death interactions in each cancer. Overall, our systematic screening of non-apoptotic cell death-related genes uncovered targets helpful for cancer therapy.