Proteomic Analysis Identifies Multiple Mechanisms of 5-Fluorouracil-Induced Gut Mucositis in Mice.

Damage of the gastrointestinal mucosa is a major side effect of the anticancer drug 5-fluorouracil (5-FU). Insight into the molecular pathogenesis of 5-FU-induced gut mucositis is expected to justify the strategies of prophylaxis. We analyzed intestinal specimens obtained from Balb/c mice treated with 70 mg/kg 5-FU daily for up to 6 days.

Viral Factors in Modulation of Host Immune Response: A Route to Novel Antiviral Agents and New Therapeutic Approaches.

Viruses utilize host cells at all stages of their life cycle, from the transcription of genes and translation of viral proteins to the release of viral copies. The human immune system counteracts viruses through a variety of complex mechanisms, including both innate and adaptive components. Viruses have an ability to evade different components of the immune system and affect them, leading to disruption.

Quantitative Prediction of Human Immunodeficiency Virus Drug Resistance.

Drug resistance of pathogens, including viruses, is one of the reasons for decreased efficacy of therapy. Considering the impact of HIV type 1 (HIV-1) on the development of progressive immune dysfunction and the rapid development of drug resistance, the analysis of HIV-1 resistance is of high significance. Currently, a substantial amount of data has been accumulated on HIV-1 drug resistance that can be used to build both qualitative and quantitative models of HIV-1 drug resistance.

DIGEP-Pred 2.0: A web application for predicting drug-induced cell signaling and gene expression changes.

The analysis of drug-induced gene expression profiles (DIGEP) is widely used to estimate the potential therapeutic and adverse drug effects as well as the molecular mechanisms of drug action. However, the corresponding experimental data is absent for many existing drugs and drug-like compounds. To solve this problem, we created the DIGEP-Pred 2.

SAnDReS 2.0: Development of machine-learning models to explore the scoring function space.

Classical scoring functions may exhibit low accuracy in determining ligand binding affinity for proteins. The availability of both protein-ligand structures and affinity data make it possible to develop machine-learning models focused on specific protein systems with superior predictive performance. Here, we report a new methodology named SAnDReS that combines AutoDock Vina 1.

Chronic Behavioral and Neurochemical Effects of Four Novel -Benzyl-2-phenylethylamine Derivatives Recently Identified as "Psychoactive" in Adult Zebrafish Screens.

Potently affecting human and animal brain and behavior, hallucinogenic drugs have recently emerged as potentially promising agents in psychopharmacotherapy. Complementing laboratory rodents, the zebrafish () is a powerful model organism for screening neuroactive drugs, including hallucinogens. Here, we tested four novel -benzyl-2-phenylethylamine (NBPEA) derivatives with 2,4- and 3,4-dimethoxy substitutions in the phenethylamine moiety and the -F, -Cl, and -OCF substitutions in the position of the phenyl ring of the -benzyl moiety (34H-NBF, 34H-NBCl, 24H-NBOMe(F), and 34H-NBOMe(F)), assessing their behavioral and neurochemical effects following chronic 14 day treatment in adult zebrafish.

MetaTox 2.0: Estimating the Biological Activity Spectra of Drug-like Compounds Taking into Account Probable Biotransformations.

After the biotransformation of xenobiotics in the human body, the biological activity of the metabolites may differ from the activity of parent compounds. Therefore, to assess the overall biological activity of a drug-like compound, it is important to take into account its metabolites and their biological activity. We developed MetaTox 2.

Web Service for HIV Drug Resistance Prediction Based on Analysis of Amino Acid Substitutions in Main Drug Targets.

Predicting viral drug resistance is a significant medical concern. The importance of this problem stimulates the continuous development of experimental and new computational approaches. The use of computational approaches allows researchers to increase therapy effectiveness and reduce the time and expenses involved when the prescribed antiretroviral therapy is ineffective in the treatment of infection caused by the human immunodeficiency virus type 1 (HIV-1).

HGMMX: Host Gut Microbiota Metabolism Xenobiotics Database.

The metagenome of bacteria colonizing the human intestine is a set of genes that is almost 150 times greater than the set of host genes. Some of these genes encode enzymes whose functioning significantly expands the number of potential pathways for xenobiotic metabolism. The resulting metabolites can exhibit activity different from that of the parent compound.

A community effort in SARS-CoV-2 drug discovery.

The COVID-19 pandemic continues to pose a substantial threat to human lives and is likely to do so for years to come. Despite the availability of vaccines, searching for efficient small-molecule drugs that are widely available, including in low- and middle-income countries, is an ongoing challenge. In this work, we report the results of an open science community effort, the "Billion molecules against COVID-19 challenge", to identify small-molecule inhibitors against SARS-CoV-2 or relevant human receptors.

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

Introduction: There 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.

Towards Novel Potential Molecular Targets for Antidepressant and Antipsychotic Pharmacotherapies.

Depression and schizophrenia are two highly prevalent and severely debilitating neuropsychiatric disorders. Both conventional antidepressant and antipsychotic pharmacotherapies are often inefficient clinically, causing multiple side effects and serious patient compliance problems. Collectively, this calls for the development of novel drug targets for treating depressed and schizophrenic patients.

Phyto4Health: Database of Phytocomponents from Russian Pharmacopoeia Plants.

Medicinal plants growing in Russia are a rich source of biologically active compounds. However, the evaluation of the hidden pharmacological potential of these compounds by methods is complicated by the lack of specialized databases. We have created a database of 3128 phytocomponents from 268 medical plants included in the Russian Pharmacopoeia.

Exploring Scoring Function Space: Developing Computational Models for Drug Discovery.

Background: The idea of scoring function space established a systems-level approach to address the development of models to predict the affinity of drug molecules by those interested in drug discovery.

Objective: Our goal here is to review the concept of scoring function space and how to explore it to develop machine learning models to address protein-ligand binding affinity.

Methods: We searched the articles available in PubMed related to the scoring function space.

CLC-Pred 2.0: A Freely Available Web Application for In Silico Prediction of Human Cell Line Cytotoxicity and Molecular Mechanisms of Action for Druglike Compounds.

In vitro cell-line cytotoxicity is widely used in the experimental studies of potential antineoplastic agents and evaluation of safety in drug discovery. In silico estimation of cytotoxicity against hundreds of tumor cell lines and dozens of normal cell lines considerably reduces the time and costs of drug development and the assessment of new pharmaceutical agent perspectives. In 2018, we developed the first freely available web application (CLC-Pred) for the qualitative prediction of cytotoxicity against 278 tumor and 27 normal cell lines based on structural formulas of 59,882 compounds.

Identification of Molecular Mechanisms Involved in Viral Infection Progression Based on Text Mining: Case Study for HIV Infection.

Viruses cause various infections that may affect human lifestyle for durations ranging from several days to for many years. Although preventative and therapeutic remedies are available for many viruses, they may still have a profound impact on human life. The human immunodeficiency virus type 1 is the most common cause of HIV infection, which represents one of the most dangerous and complex diseases since it affects the immune system and causes its disruption, leading to secondary complications and negatively influencing health-related quality of life.

Blood Plasma Proteome: A Meta-Analysis of the Results of Protein Quantification in Human Blood by Targeted Mass Spectrometry.

A meta-analysis of the results of targeted quantitative screening of human blood plasma was performed to generate a reference standard kit that can be used for health analytics. The panel included 53 of the 296 proteins that form a “stable” part of the proteome of a healthy individual; these proteins were found in at least 70% of samples and were characterized by an interindividual coefficient of variation <40%. The concentration range of the selected proteins was 10−10−10−3 M and enrichment analysis revealed their association with rare familial diseases.

New Positive TRPC6 Modulator Penetrates Blood-Brain Barrier, Eliminates Synaptic Deficiency and Restores Memory Deficit in 5xFAD Mice.

Synapse loss in the brain of Alzheimer's disease patients correlates with cognitive dysfunctions. Drugs that limit synaptic loss are promising pharmacological agents. The transient receptor potential cation channel, subfamily C, member 6 (TRPC6) regulates the formation of an excitatory synapse.

Inhibitory Effects of 7-Methylguanine and Its Metabolite 8-Hydroxy-7-Methylguanine on Human Poly(ADP-Ribose) Polymerase 1.

Previously, we have found that a nucleic acid metabolite, 7-methylguanine (7mGua), produced in the body can have an inhibitory effect on the poly(ADP-ribose) polymerase 1 (PARP1) enzyme, an important pharmacological target in anticancer therapy. In this work, using an original method of analysis of PARP1 activity based on monitoring fluorescence anisotropy, we studied inhibitory properties of 7mGua and its metabolite, 8-hydroxy-7-methylguanine (8h7mGua). Both compounds inhibited PARP1 enzymatic activity in a dose-dependent manner, however, 8h7mGua was shown to be a stronger inhibitor.

Computational Prediction of Inhibitors and Inducers of the Major Isoforms of Cytochrome P450.

Human cytochrome P450 enzymes (CYPs) are heme-containing monooxygenases. This superfamily of drug-metabolizing enzymes is responsible for the metabolism of most drugs and other xenobiotics. The inhibition of CYPs may lead to drug-drug interactions and impair the biotransformation of drugs.

Novel mitochondria-targeting compounds selectively kill human leukemia cells.

Acute myeloid leukemia (AML) is a heterogeneous group of aggressive hematological malignancies commonly associated with treatment resistance, high risk of relapse, and mitochondrial dysregulation. We identified six mitochondria-affecting compounds (PS compounds) that exhibit selective cytotoxicity against AML cells in vitro. Structure-activity relationship studies identified six analogs from two original scaffolds that had over an order of magnitude difference between LD50 in AML and healthy peripheral blood mononuclear cells.

The method predicting interaction between protein targets and small-molecular ligands with the wide applicability domain.

Prediction of protein-ligand interaction is necessary for drug design, gene regulatory networks investigation, and chemical probes detection. The existing methods commonly demonstrate high prediction accuracy for the particular groups of protein and their ligands. We developed an approach suited for the wider applicability and tested it on three dataset types significantly differing by protein homology.

Relationships between the Structure and Severe Drug-Induced Liver Injury for Low, Medium, and High Doses of Drugs.

Assessment of structure-activity relationships (SARs) for predicting severe drug-induced liver injury (DILI) is essential since and preclinical methods cannot detect many druglike compounds disrupting liver functions. To date, plenty of SAR models for the prediction of DILI have been developed; however, none of them considered the route of drug administration and daily dose, which may introduce significant bias into prediction results. We have created a dataset of 617 drugs with parenteral and oral administration routes and consistent information on DILI severity.

Synthesis, Biological Evaluation and Molecular Docking Studies of 5-Indolylmethylen-4-oxo-2-thioxothiazolidine Derivatives.

Background: Infectious diseases represent a significant global strain on public health security and impact on socio-economic stability all over the world. The increasing resistance to the current antimicrobial treatment has resulted in the crucial need for the discovery and development of novel entities for the infectious treatment with different modes of action that could target both sensitive and resistant strains.

Methods: Compounds were synthesized using the classical organic chemistry methods.