Thiol-Reactive or Redox-Active: Revising a Repurposing Screen Led to a New Invalidation Pipeline and Identified a True Noncovalent Inhibitor Against Papain-like Protease from SARS-CoV-2.

The SARS-CoV-2 papain-like protease PLpro has multiple roles in the viral replication cycle, related to both its polypeptide cleavage function and its ability to antagonize the host immune response. Targeting the PLpro function is recognized as a promising mechanism to modulate viral replication, while supporting host immune responses. However, the development of PLpro-specific inhibitors remains challenging.

Approaching Pharmacological Space: Events and Components.

The pharmacological space comprises all the dynamic events that determine the bioactivity (and/or the metabolism and toxicity) of a given ligand. The pharmacological space accounts for the structural flexibility and property variability of the two interacting molecules as well as for the mutual adaptability characterizing their molecular recognition process. The dynamic behavior of all these events can be described by a set of possible states (e.

Corrigendum to "Addressing docking pose selection with structure-based deep learning: Recent advances, challenges and opportunities" [Comput Struct Biotechnol J vol. 23 (2024) 2141-2151].

[This corrects the article DOI: 10.1016/j.csbj.

Addressing docking pose selection with structure-based deep learning: Recent advances, challenges and opportunities.

Molecular docking is a widely used technique in drug discovery to predict the binding mode of a given ligand to its target. However, the identification of the near-native binding pose in docking experiments still represents a challenging task as the scoring functions currently employed by docking programs are parametrized to predict the binding affinity, and, therefore, they often fail to correctly identify the ligand native binding conformation. Selecting the correct binding mode is crucial to obtaining meaningful results and to conveniently optimizing new hit compounds.

Identification and characterization of a new potent inhibitor targeting CtBP1/BARS in melanoma cells.

Background: The C-terminal-binding protein 1/brefeldin A ADP-ribosylation substrate (CtBP1/BARS) acts both as an oncogenic transcriptional co-repressor and as a fission inducing protein required for membrane trafficking and Golgi complex partitioning during mitosis, hence for mitotic entry. CtBP1/BARS overexpression, in multiple cancers, has pro-tumorigenic functions regulating gene networks associated with "cancer hallmarks" and malignant behavior including: increased cell survival, proliferation, migration/invasion, epithelial-mesenchymal transition (EMT). Structurally, CtBP1/BARS belongs to the hydroxyacid-dehydrogenase family and possesses a NAD(H)-binding Rossmann fold, which, depending on ligands bound, controls the oligomerization of CtBP1/BARS and, in turn, its cellular functions.

Drug repurposing screen to identify inhibitors of the RNA polymerase (nsp12) and helicase (nsp13) from SARS-CoV-2 replication and transcription complex.

Coronaviruses contain one of the largest genomes among the RNA viruses, coding for 14-16 non-structural proteins (nsp) that are involved in proteolytic processing, genome replication and transcription, and four structural proteins that build the core of the mature virion. Due to conservation across coronaviruses, nsps form a group of promising drug targets as their inhibition directly affects viral replication and, therefore, progression of infection. A minimal but fully functional replication and transcription complex was shown to be formed by one RNA-dependent RNA polymerase (nsp12), one nsp7, two nsp8 accessory subunits, and two helicase (nsp13) enzymes.

Ultrahigh-quality-factor micro- and nanomechanical resonators using dissipation dilution.

Mechanical resonators are widely used in sensors, transducers and optomechanical systems, where mechanical dissipation sets the ultimate limit to performance. Over the past 15 years, the quality factors in strained mechanical resonators have increased by four orders of magnitude, surpassing the previous state of the art achieved in bulk crystalline resonators at room temperature and liquid helium temperatures. In this Review, we describe how these advances were made by leveraging 'dissipation dilution'-where dissipation is reduced through a combination of static tensile strain and geometric nonlinearity in dynamic strain.

"DompeKeys": a set of novel substructure-based descriptors for efficient chemical space mapping, development and structural interpretation of machine learning models, and indexing of large databases.

The conversion of chemical structures into computer-readable descriptors, able to capture key structural aspects, is of pivotal importance in the field of cheminformatics and computer-aided drug design. Molecular fingerprints represent a widely employed class of descriptors; however, their generation process is time-consuming for large databases and is susceptible to bias. Therefore, descriptors able to accurately detect predefined structural fragments and devoid of lengthy generation procedures would be highly desirable.

Target Prediction by Multiple Virtual Screenings: Analyzing the SARS-CoV-2 Phenotypic Screening by the Docking Simulations Submitted to the MEDIATE Initiative.

Phenotypic screenings are usually combined with deconvolution techniques to characterize the mechanism of action for the retrieved hits. These studies can be supported by various computational analyses, although docking simulations are rarely employed. The present study aims to assess if multiple docking calculations can prove successful in target prediction.

Structure of human TRPM8 channel.

TRPM8 is a non-selective cation channel permeable to both monovalent and divalent cations that is activated by multiple factors, such as temperature, voltage, pressure, and changes in osmolality. It is a therapeutic target for anticancer drug development, and its modulators can be utilized for several pathological conditions. Here, we present a cryo-electron microscopy structure of a human TRPM8 channel in the closed state that was solved at 2.

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.

MetaSpot: A General Approach for Recognizing the Reactive Atoms Undergoing Metabolic Reactions Based on the MetaQSAR Database.

The prediction of drug metabolism is attracting great interest for the possibility of discarding molecules with unfavorable ADME/Tox profile at the early stage of the drug discovery process. In this context, artificial intelligence methods can generate highly performing predictive models if they are trained by accurate metabolic data. MetaQSAR-based datasets were collected to predict the sites of metabolism for most metabolic reactions.

MEDIATE - Molecular DockIng at homE: Turning collaborative simulations into therapeutic solutions.

Introduction: Collaborative computing has attracted great interest in the possibility of joining the efforts of researchers worldwide. Its relevance has further increased during the pandemic crisis since it allows for the strengthening of scientific collaborations while avoiding physical interactions. Thus, the E4C consortium presents the MEDIATE initiative which invited researchers to contribute via their virtual screening simulations that will be combined with AI-based consensus approaches to provide robust and method-independent predictions.

ProfhEX: AI-based platform for small molecules liability profiling.

Off-target drug interactions are a major reason for candidate failure in the drug discovery process. Anticipating potential drug's adverse effects in the early stages is necessary to minimize health risks to patients, animal testing, and economical costs. With the constantly increasing size of virtual screening libraries, AI-driven methods can be exploited as first-tier screening tools to provide liability estimation for drug candidates.

Ensemble of structure and ligand-based classification models for hERG liability profiling.

Drug-induced cardiotoxicity represents one of the most critical safety concerns in the early stages of drug development. The blockade of the human ether-à-go-go-related potassium channel (hERG) is the most frequent cause of cardiotoxicity, as it is associated to long QT syndrome which can lead to fatal arrhythmias. Therefore, assessing hERG liability of new drugs candidates is crucial to avoid undesired cardiotoxic effects.

The SARS-CoV-2 spike protein binds and modulates estrogen receptors.

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spike (S) protein binds angiotensin-converting enzyme 2 as its primary infection mechanism. Interactions between S and endogenous proteins occur after infection but are not well understood. We profiled binding of S against >9000 human proteins and found an interaction between S and human estrogen receptor α (ERα).

The Spike Mutants Website: A Worldwide Used Resource against SARS-CoV-2.

A large number of SARS-CoV-2 mutations in a short period of time has driven scientific research related to vaccines, new drugs, and antibodies to combat the new variants of the virus. Herein, we present a web portal containing the structural information, the tridimensional coordinates, and the molecular dynamics trajectories of the SARS-CoV-2 spike protein and its main variants. The Spike Mutants website can serve as a rapid online tool for investigating the impact of novel mutations on virus fitness.

Exscalate4CoV: Innovative High Performing Computing (HPC) Strategies to Tackle Pandemic Crisis.

This Special Issue was intended as a dissemination forum where the major results pursued by the EXSCALATE4CoV project (E4C, https://www [...

Computational Insights into the Sequence-Activity Relationships of the NGF(1-14) Peptide by Molecular Dynamics Simulations.

The Nerve Growth Factor (NGF) belongs to the neurothrophins protein family involved in the survival of neurons in the nervous system. The interaction of NGF with its high-affinity receptor TrkA mediates different cellular pathways related to Alzheimer's disease, pain, ocular dysfunction, and cancer. Therefore, targeting NGF-TrkA interaction represents a valuable strategy for the development of new therapeutic agents.

Structural Evolution of Delta (B.1.617.2) and Omicron (BA.1) Spike Glycoproteins.

The vast amount of epidemiologic and genomic data that were gathered as a global response to the COVID-19 pandemic that was caused by SARS-CoV-2 offer a unique opportunity to shed light on the structural evolution of coronaviruses and in particular on the spike (S) glycoprotein, which mediates virus entry into the host cell by binding to the human ACE2 receptor. Herein, we carry out an investigation into the dynamic properties of the S glycoprotein, focusing on the much more transmissible Delta and Omicron variants. Notwithstanding the great number of mutations that have accumulated, particularly in the Omicron S glycoprotein, our data clearly showed the conservation of some structural and dynamic elements, such as the global motion of the receptor binding domain (RBD).

Extensive Sampling of Molecular Dynamics Simulations to Identify Reliable Protein Structures for Optimized Virtual Screening Studies: The Case of the hTRPM8 Channel.

(1) Background: Virtual screening campaigns require target structures in which the pockets are properly arranged for binding. Without these, MD simulations can be used to relax the available target structures, optimizing the fine architecture of their binding sites. Among the generated frames, the best structures can be selected based on available experimental data.

Cytopathic SARS-CoV-2 screening on VERO-E6 cells in a large-scale repurposing effort.

Worldwide, there are intensive efforts to identify repurposed drugs as potential therapies against SARS-CoV-2 infection and the associated COVID-19 disease. To date, the anti-inflammatory drug dexamethasone and (to a lesser extent) the RNA-polymerase inhibitor remdesivir have been shown to be effective in reducing mortality and patient time to recovery, respectively, in patients. Here, we report the results of a phenotypic screening campaign within an EU-funded project (H2020-EXSCALATE4COV) aimed at extending the repertoire of anti-COVID therapeutics through repurposing of available compounds and highlighting compounds with new mechanisms of action against viral infection.