Targeting SARS-CoV-2 main protease: a comprehensive approach using advanced virtual screening, molecular dynamics, and in vitro validation.

The COVID-19 pandemic, driven by the SARS-CoV-2 virus, necessitates the development of effective therapeutics. The main protease of the virus, Mpro, is a key target due to its crucial role in viral replication. Our study presents a novel approach combining ligand-based pharmacophore modeling with structure-based advanced virtual screening to identify potential inhibitors of Mpro.

Inhibitory effects of nafcillin and diosmin on biofilm formation by Salmonella Typhimurium.

Objective: The foodborne pathogen Salmonella enterica serovar Typhimurium causes self-limiting gastroenteritis in humans and is difficult to eliminate due to its ability to adhere to surfaces and form biofilms that exhibit high resistance to antimicrobial agents. To explore alternative strategies for biofilm treatment, it is essential to investigate novel agents that inhibit Salmonella biofilms.

Method: In this study, we investigated the minimum biofilm inhibitory concentrations (MBICs) and minimum biofilm eradication concentrations (MBECs) of nafcillin and diosmin, both previously identified as Lon protease inhibitors, against biofilms formed by S.

DNA binding, and apoptosis-inducing activities of a β-ionone-derived ester in human myeloid leukemia cells: multispectral and molecular dynamic simulation analyses.

β-Ionone is the end-ring counterpart of β-carotenoids, which are widely found in fruits and vegetables. Recent studies have illustrated the antimetastatic, anti-proliferative, and apoptosis-inducing activities of β-ionone both in vitro and in vivo. We aimed to explore the anti-cancer potency of β-Ionone-derived ester, (E)-4-(2,6,6-trimethylcyclohex-1-enyl) but-3-en-2-ylpyrazine-2-carboxylate (4-TM.

Targeting lon protease to inhibit persister cell formation in Typhimurium: a drug repositioning approach.

Objective: Persister cells are a specific subset of bacteria capable of surviving exposure to lethal doses of antibiotics, leading to antibiotic therapy failures and infection relapses. This research explores the utilization of drug repositioning to target the Lon protease in Typhimurium.

Method: In this study, FDA-approved drugs sourced from the Drug Bank database were screened to identify existing pharmaceuticals with the potential to combat the Lon protease.

Docking-Based Virtual Screening Method for Selecting Natural Compounds with Synergistic Inhibitory Effects Against Cancer Signalling Pathways Using a Multi-Target Approach.

Objectives: This study aims to introduce a methodology for identifying medicinal plants that contain effective natural compounds with the most possible synergistic effects to inhibit cancer survival and proliferation in a multi-targeted manner.

Materials And Methods: To select targets, the signaling pathways involved in cancer development were defined from the KEGG database, and the protein-protein interactions (PPIs) of genes within these pathways were investigated using the STRING software. Then 14 proteins with the highest degree were identified as targets.

Insights on the conformation and appropriate drug-target sites on retinal IMPDH1 using the 604-aa isoform lacking the C-terminal extension.

Background And Purpose: Retinitis pigmentosa (RP) accounts for 2 percent of global cases of blindness. The RP10 form of the disease results from mutations in isoform 1 of inosine 5'-monophosphate dehydrogenase (IMPDH1), the rate-limiting enzyme in the purine nucleotide synthesis pathway. Retinal photoreceptors contain specific isoforms of IMPDH1 characterized by terminal extensions.

Computational evaluation and benchmark study of 342 crystallographic holo-structures of SARS-CoV-2 Mpro enzyme.

The coronavirus disease 19 pandemic, caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has led to a global health crisis with millions of confirmed cases and related deaths. The main protease (Mpro) of SARS-CoV-2 is crucial for viral replication and presents an attractive target for drug development. Despite the approval of some drugs, the search for effective treatments continues.

Evaluation of antibacterial, cytotoxicity, and apoptosis activity of novel chromene-sulfonamide hybrids synthesized under solvent-free conditions and 3D-QSAR modeling studies.

In this study, eleven novel chromene sulfonamide hybrids were synthesized by a convenient method in accordance with green chemistry. At first, chromene derivatives (1-9a) were prepared through the multi-component reaction between aryl aldehydes, malononitrile, and 3-aminophenol. Then, synthesized chromenes were reacted with appropriate sulfonyl chlorides by grinding method to give the corresponding chromene sulfonamide hybrids (1-11b).

A comparative analysis of computational drug repurposing approaches: proposing a novel tensor-matrix-tensor factorization method.

Efficient drug discovery relies on drug repurposing, an important and open research field. This work presents a novel factorization method and a practical comparison of different approaches for drug repurposing. First, we propose a novel tensor-matrix-tensor (TMT) formulation as a new data array method with a gradient-based factorization procedure.

CCL-DTI: contributing the contrastive loss in drug-target interaction prediction.

Background: The Drug-Target Interaction (DTI) prediction uses a drug molecule and a protein sequence as inputs to predict the binding affinity value. In recent years, deep learning-based models have gotten more attention. These methods have two modules: the feature extraction module and the task prediction module.

In silico studies of anti-oxidative and hot temperament-based phytochemicals as natural inhibitors of SARS-CoV-2 Mpro.

Main protease (Mpro) of SARS-CoV-2 is considered one of the key targets due to its role in viral replication. The use of traditional phytochemicals is an important part of complementary/alternative medicine, which also accompany the concept of temperament, where it has been shown that hot medicines cure cold and cold medicines cure hot, with cold and hot pattern being associated with oxidative and anti-oxidative properties in medicine, respectively. Molecular docking in this study has demonstrated that a number of anti-oxidative and hot temperament-based phytochemicals have high binding affinities to SARS-CoV-2 Mpro, both in the monomeric and dimeric deposited states of the protein.

DEDTI versus IEDTI: efficient and predictive models of drug-target interactions.

Drug repurposing is an active area of research that aims to decrease the cost and time of drug development. Most of those efforts are primarily concerned with the prediction of drug-target interactions. Many evaluation models, from matrix factorization to more cutting-edge deep neural networks, have come to the scene to identify such relations.

Virtual screening reveals aprepitant to be a potent inhibitor of neutral sphingomyelinase 2: implications in blockade of exosome release in cancer therapy.

Purpose: Exosomes are membrane-derived nano-vesicles upregulated in pathological conditions like cancer. Therefore, inhibiting their release is a potential strategy for the development of more efficient combination therapies. Neutral sphingomyelinase 2 (nSMase2) is a key component in exosome release; however, a clinically safe yet efficient nSMase2 inhibitor remains to be used discovered.

New insights into the inhibitory effect of phenol carboxylic acid antioxidants on mushroom tyrosinase by molecular dynamic studies and experimental assessment.

The inhibitory effects of ferulic and chlorogenic acids on tyrosinase activity were investigated through multi-spectroscopic and molecular docking techniques. Ferulic and chlorogenic acids, flavonoid compounds, demonstrated inhibitory monophenolase activities of tyrosinase. The inhibitor effects against monophenolase activity were in a reversible and competitive manner with ki value equal to 6.

DRaW: prediction of COVID-19 antivirals by deep learning-an objection on using matrix factorization.

Background: Due to the high resource consumption of introducing a new drug, drug repurposing plays an essential role in drug discovery. To do this, researchers examine the current drug-target interaction (DTI) to predict new interactions for the approved drugs. Matrix factorization methods have much attention and utilization in DTIs.

Rational approaches to discover SARS-CoV-2/ACE2 interaction inhibitors: Pharmacophore-based virtual screening, molecular docking, molecular dynamics and binding free energy studies.

The lack of effective treatment remains a bottleneck in combating the current coronavirus family pandemic, particularly coronavirus 2019 (COVID-19), which is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The infection of host cells by SARS-CoV-2 is mediated by the binding of its receptor-binding domain (RBD) on the spike (S) glycoprotein to the host angiotensin-converting enzyme (ACE2) receptor. As all developed and available vaccines against COVID-19 do not provide long-term immunity, the creation of an effective drug for the treatment of COVID-19 is necessary and cannot be ignored.

Identification of new potent agonists for toll-like receptor 8 by virtual screening methods, molecular dynamics simulation, and MM-GBSA.

Toll-like receptor 8 (TLR8), as an endosomal transmembrane receptor, plays a crucial role in the innate immune response to neoplasia and viruses. Previous studies have shown that TLR8 agonists e.g.

Identification of repurposed drugs targeting significant long non-coding RNAs in the cross-talk between diabetes mellitus and Alzheimer's disease.

The relationship between diabetes mellitus (DM) and Alzheimer's disease (AD) is so strong that scientists called it "brain diabetes". According to several studies, the critical factor in this relationship is brain insulin resistance. Due to the rapid global spread of both diseases, overcoming this cross-talk has a significant impact on societies.

Exploring the role of non-coding RNAs as potential candidate biomarkers in the cross-talk between diabetes mellitus and Alzheimer's disease.

Background: Recent research has investigated the connection between Diabetes Mellitus (DM) and Alzheimer's Disease (AD). Insulin resistance plays a crucial role in this interaction. Studies have focused on dysregulated proteins to disrupt this connection.

Matrix factorization with denoising autoencoders for prediction of drug-target interactions.

Drug-target interaction is crucial in the discovery of new drugs. Computational methods can be used to identify new drug-target interactions at low costs and with reasonable accuracy. Recent studies pay more attention to machine-learning methods, ranging from matrix factorization to deep learning, in the DTI prediction.

Drug-target interaction prediction using reliable negative samples and effective feature selection methods.

Machine learning-based approaches in the field of drug discovery have dramatically reduced the time and cost of the laboratory process of detecting potential drug-target interactions (DTIs). Standard binary classifiers require both positive and negative samples in the training and validation phases. One of the major challenges in the DTI context is the lack of access to non-interacting pairs as negative samples in the learning process.

Proteochemometrics modeling for prediction of the interactions between caspase isoforms and their inhibitors.

Caspases (cysteine-aspartic proteases) play critical roles in inflammation and the programming of cell death in the form of necroptosis, apoptosis, and pyroptosis. The name of these enzymes has been chosen in accordance with their cysteine protease activity. They act as cysteines in nucleophilically active sites to attack and cleave target proteins in the aspartic acid and amino acid C-terminal.

Biomolecular interactions and binding dynamics of inhibitor arachidonic acid, with tyrosinase enzyme.

Hyperpigmentation is a disorder caused by increased melanin deposition and changes in skin pigmentation. Inhibition of tyrosinase activity contributes to the control of food browning and skin pigmentation diseases. The effects of arachidonic acid (AA) on tyrosinase activity were examined using different spectroscopy methods including UV-VIS spectrophotometry, fluorescence spectroscopy, circular dichroism (CD) differential scanning calorimetry, and molecular dynamics (MD) simulations.