Search results for " virtual screening"
showing 10 items of 15 documents
An Integrated Pharmacophore/Docking/3D-QSAR Approach to Screening a Large Library of Products in Search of Future Botulinum Neurotoxin A Inhibitors
2020
Botulinum toxins are neurotoxins produced by Clostridium botulinum. This toxin can be lethal for humans as a cause of botulism
The dimer-monomer equilibrium of SARS-CoV-2 main protease is affected by small molecule inhibitors
2021
AbstractThe maturation of coronavirus SARS-CoV-2, which is the etiological agent at the origin of the COVID-19 pandemic, requires a main protease Mpro to cleave the virus-encoded polyproteins. Despite a wealth of experimental information already available, there is wide disagreement about the Mpro monomer-dimer equilibrium dissociation constant. Since the functional unit of Mpro is a homodimer, the detailed knowledge of the thermodynamics of this equilibrium is a key piece of information for possible therapeutic intervention, with small molecules interfering with dimerization being potential broad-spectrum antiviral drug leads. In the present study, we exploit Small Angle X-ray Scattering (…
Identification of noncovalent proteasome inhibitors with high selectivity for chymotrypsin-like activity by a multistep structure-based virtual scree…
2016
Noncovalent proteasome inhibitors introduce an alternative mechanism of inhibition to that of covalent inhibitors, e.g. carfilzomib, used in cancer therapy. A multistep hierarchical structure-based virtual screening (SBVS) of the 65,375 NCI lead-like compound library led to the identification of two compounds (9 and 28) which noncovalently inhibited the chymotrypsin-like (ChT-L) activity (Ki = 2.18 and 2.12 μM, respectively) with little or no effects on the other two major proteasome proteolytic activities, trypsin-like (T-L) and post-glutamyl peptide hydrolase (PGPH) activities. A subsequent hierarchical similarity search over the full NCI database with the most active tripeptide-based inh…
Repurposing old drugs to fight multidrug resistant cancers.
2020
Overcoming multidrug resistance represents a major challenge for cancer treatment. In the search for new chemotherapeutics to treat malignant diseases, drug repurposing gained a tremendous interest during the past years. Repositioning candidates have often emerged through several stages of clinical drug development, and may even be marketed, thus attracting the attention and interest of pharmaceutical companies as well as regulatory agencies. Typically, drug repositioning has been serendipitous, using undesired side effects of small molecule drugs to exploit new disease indications. As bioinformatics gain increasing popularity as an integral component of drug discovery, more rational approa…
Synthesis and biological activities of a new class of heat shock protein 90 inhibitors, designed by energy-based pharmacophore virtual screening
2013
The design through energy-based pharmacophore virtual screening has led to aminocyanopyridine derivatives as efficacious new inhibitors of Hsp90. The synthesized compounds showed a good affinity for the Hsp90 ATP binding site in the competitive binding assay. Moreover, they showed an excellent antiproliferative activity against a large number of human tumor cell lines. Further biological studies on the derivative with the higher EC50 confirmed its specific influence on the cellular pathways involving Hsp90.
Recent advances in computational design of potent aromatase inhibitors: open-eye on endocrine-resistant breast cancers.
2019
Introduction: The vast majority of breast cancers (BC) are estrogen receptor positive (ER+). The most effective treatments to fight this BC type rely on estrogen deprivation therapy, by inhibiting the aromatase enzyme, which performs estrogen biosynthesis, or on blocking the estrogens signaling path via modulating/degrading the estrogen's specific nuclear receptor (estrogen receptor-?, ER?). While being effective at early disease stage, patients treated with aromatase inhibitors (AIs) may acquire resistance and often relapse after prolonged therapies. Areas covered: In this compendium, after an overview of the historical development of the AIs currently in clinical use, and of the computati…
Similarity-Based Virtual Screening to Find Antituberculosis Agents Based on Novel Scaffolds: Design, Syntheses and Pharmacological Assays
2022
A method to identify molecular scaffolds potentially active against the Mycobacterium tuberculosis complex (MTBC) is developed. A set of structurally heterogeneous agents against MTBC was used to obtain a mathematical model based on topological descriptors. This model was statistically validated through a Leave-n-Out test. It successfully discriminated between active or inactive compounds over 86% in database sets. It was also useful to select new potential antituberculosis compounds in external databases. The selection of new substituted pyrimidines, pyrimidones and triazolo[1,5-a]pyrimidines was particularly interesting because these structures could provide new scaffolds in this field. T…
Targeting the Class A Carbapenemase GES-5 via Virtual Screening
2020
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Modeling Natural Anti-Inflammatory Compounds by Molecular Topology
2011
One of the main pharmacological problems today in the treatment of chronic inflammation diseases consists of the fact that anti-inflammatory drugs usually exhibit side effects. The natural products offer a great hope in the identification of bioactive lead compounds and their development into drugs for treating inflammatory diseases. Computer-aided drug design has proved to be a very useful tool for discovering new drugs and, specifically, Molecular Topology has become a good technique for such a goal. A topological-mathematical model, obtained by linear discriminant analysis, has been developed for the search of new anti-inflammatory natural compounds. An external validation obtained with …
EMBER—Embedding Multiple Molecular Fingerprints for Virtual Screening
2022
In recent years, the debate in the field of applications of Deep Learning to Virtual Screening has focused on the use of neural embeddings with respect to classical descriptors in order to encode both structural and physical properties of ligands and/or targets. The attention on embeddings with the increasing use of Graph Neural Networks aimed at overcoming molecular fingerprints that are short range embeddings for atomic neighborhoods. Here, we present EMBER, a novel molecular embedding made by seven molecular fingerprints arranged as different “spectra” to describe the same molecule, and we prove its effectiveness by using deep convolutional architecture that assesses ligands&…