COMPUTER-AIDED PREDICTION OF MULTITARGET PROFILES: CASE STUDIES FOR CLOZAPINE AND DASATINIB

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Cyclobutane-Containing Alkaloids: Origin, Synthesis, and Biological Activities

Present review describes research on novel natural cyclobutane-containing alkaloids isolated from terrestrial and marine species. More than 60 biological active compounds have been confirmed to have antimicrobial, antibacterial, antitumor, and other activities. The structures, synthesis, origins, and biological activities of a selection of cyclobutane-containing alkaloids are reviewed. With the computer program PASS some additional biological activities are also predicted, which point toward new possible applications of these compounds. This review emphasizes the role of cyclobutane-containing alkaloids as an important source of leads for drug discovery

Rationale for use mefloquine for COVID-19 treatment

Currently, the use of mefloquine in patients with COVID-19 does not have sufficient scientific justification and, given the unfavorable efficacy and safety profile, cannot be considered for routine use in clinical practice

HOW SHOULD ONE USE AVAILABLE DATA TO BE SUCCESSFUL IN COMPUTER-AIDED SEARCH FOR NOVEL KINASE INHIBITORS?

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PREDICTION OF THE METABOLIC NETWORK FOR XENOBIOTICS IN THE HUMAN ORGANISM

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Transcriptome-based analysis of human peripheral blood reveals regulators of immune response in different viral infections

IntroductionThere are difficulties in creating direct antiviral drugs for all viruses, including new, suddenly arising infections, such as COVID-19. Therefore, pathogenesis-directed therapy is often necessary to treat severe viral infections and comorbidities associated with them. Despite significant differences in the etiopathogenesis of viral diseases, in general, they are associated with significant dysfunction of the immune system. Study of common mechanisms of immune dysfunction caused by different viral infections can help develop novel therapeutic strategies to combat infections and associated comorbidities.MethodsTo identify common mechanisms of immune functions disruption during infection by nine different viruses (cytomegalovirus, Ebstein-Barr virus, human T-cell leukemia virus type 1, Hepatitis B and C viruses, human immunodeficiency virus, Dengue virus, SARS-CoV, and SARS-CoV-2), we analyzed the corresponding transcription profiles from peripheral blood mononuclear cells (PBMC) using the originally developed pipeline that include transcriptome data collection, processing, normalization, analysis and search for master regulators of several viral infections. The ten datasets containing transcription data from patients infected by nine viruses and healthy people were obtained from Gene Expression Omnibus. The analysis of the data was performed by Genome Enhancer pipeline.ResultsWe revealed common pathways, cellular processes, and master regulators for studied viral infections. We found that all nine viral infections cause immune activation, exhaustion, cell proliferation disruption, and increased susceptibility to apoptosis. Using network analysis, we identified PBMC receptors, representing proteins at the top of signaling pathways that may be responsible for the observed transcriptional changes and maintain the current functional state of cells.DiscussionThe identified relationships between some of them and virus-induced alteration of immune functions are new and have not been found earlier, e.g., receptors for autocrine motility factor, insulin, prolactin, angiotensin II, and immunoglobulin epsilon. Modulation of the identified receptors can be investigated as one of therapeutic strategies for the treatment of severe viral infections

WAY2DRUG CHEMINFORMATICS PLATFORM FOR DRUG REPURPOSING

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Current and future use of umifenovir in patients with COVID-19

At the time of print, the evidence for using umifenovir in COVID-19 is mainly theoretical. The published clinical trials have contradicting results. The decision to use umifenovir in COVID-19 should be individualized, considering the “experimental” nature of this treatment

A critical overview of computational approaches employed for COVID-19 drug discovery

COVID-19 has resulted in huge numbers of infections and deaths worldwide and brought the most severe disruptions to societies and economies since the Great Depression. Massive experimental and computational research effort to understand and characterize the disease and rapidly develop diagnostics, vaccines, and drugs has emerged in response to this devastating pandemic and more than 130 000 COVID-19-related research papers have been published in peer-reviewed journals or deposited in preprint servers. Much of the research effort has focused on the discovery of novel drug candidates or repurposing of existing drugs against COVID-19, and many such projects have been either exclusively computational or computer-aided experimental studies. Herein, we provide an expert overview of the key computational methods and their applications for the discovery of COVID-19 small-molecule therapeutics that have been reported in the research literature. We further outline that, after the first year the COVID-19 pandemic, it appears that drug repurposing has not produced rapid and global solutions. However, several known drugs have been used in the clinic to cure COVID-19 patients, and a few repurposed drugs continue to be considered in clinical trials, along with several novel clinical candidates. We posit that truly impactful computational tools must deliver actionable, experimentally testable hypotheses enabling the discovery of novel drugs and drug combinations, and that open science and rapid sharing of research results are critical to accelerate the development of novel, much needed therapeutics for COVID-19