AI Article Synopsis
- The letter discusses a ligand-based virtual screening campaign targeting M5 NAMs, specifically ML375 and VU6000181, using SAR data.
- A library of 98,000 compounds was virtually screened using both QSAR and shape scores, but only a combined consensus score identified a promising new compound, VU0549108, which is a weak inhibitor of M5 mAChR.
- Binding studies indicate that VU0549108 interacts with the orthosteric site, though its effectiveness is limited and analogs show poor results, suggesting that further exploration for new chemotypes is needed.
Article Abstract
This Letter describes a ligand-based virtual screening campaign utilizing SAR data around the M5 NAMs, ML375 and VU6000181. Both QSAR and shape scores were employed to virtually screen a 98,000-member compound library. Neither approach alone proved productive, but a consensus score of the two models identified a novel scaffold which proved to be a modestly selective, but weak inhibitor (VU0549108) of the M5 mAChR (M5 IC50=6.2μM, M1-4 IC50s>10μM) based on an unusual 8-((1,3,5-trimethyl-1H-pyrazol-4-yl)sulfonyl)-1-oxa-4-thia-8-azaspiro[4,5]decane scaffold. [(3)H]-NMS binding studies showed that VU0549108 interacts with the orthosteric site (Ki of 2.7μM), but it is not clear if this is negative cooperativity or orthosteric binding. Interestingly, analogs synthesized around VU0549108 proved weak, and SAR was very steep. However, this campaign validated the approach and warranted further expansion to identify additional novel chemotypes.
Download full-text PDF |
Source |
|---|---|
| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4996684 | PMC |
| http://dx.doi.org/10.1016/j.bmcl.2016.07.071 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
Virtual Screening Identifies Inhibitors of SARS-CoV-2 Main Protease through Pharmacophore and Similarity Approaches.
Curr Pharm Des
January 2025
Department of Pharmaceutical Sciences, Faculty of Pharmacy, The University of Jordan, P.O Box 13140, Amman 11942, Jordan.
Introduction: The emergence of SARS-CoV-2 and the COVID-19 pandemic highlighted the urgent need for novel antiviral therapies. The main protease (Mpro) of SARS-CoV-2 is a key enzyme in viral replication and a promising therapeutic target.
Methods: This study employed virtual screening approaches to identify potential Mpro inhibitors, leveraging both structure- and ligand-based methods.
Evaluation of the Alkaloids as Inhibitors of Human Acetylcholinesterase by Molecular Docking and ADME Prediction.
In Vivo
December 2024
Doctoral School of Biomedical Sciences, University of Oradea, Oradea, Romania.
Background/aim: Alzheimer's disease is a complex, incurable to date, multifactorial disease, which suggests the need for continued development of pharmacotherapy.
Materials And Methods: A comprehensive literature search was conducted to identify known ligands with anticholinesterase activity, resulting in the discovery of over 100 alkaloids that are also available in the PubChem database. Subsequently, the ligands underwent molecular docking to evaluate their affinity for the target enzyme.
Machine learning-enabled virtual screening indicates the anti-tuberculosis activity of aldoxorubicin and quarfloxin with verification by molecular docking, molecular dynamics simulations, and biological evaluations.
Brief Bioinform
November 2024
Institute of Medical Information, Chinese Academy of Medical Sciences and Peking Union Medical College, Chaoyang District, Beijing 100020, China.
Drug resistance in Mycobacterium tuberculosis (Mtb) is a significant challenge in the control and treatment of tuberculosis, making efforts to combat the spread of this global health burden more difficult. To accelerate anti-tuberculosis drug discovery, repurposing clinically approved or investigational drugs for the treatment of tuberculosis by computational methods has become an attractive strategy. In this study, we developed a virtual screening workflow that combines multiple machine learning and deep learning models, and 11 576 compounds extracted from the DrugBank database were screened against Mtb.
View Article and Find Full Text PDFIdentification and structural characterization of CB1 receptor antagonists: A comprehensive virtual screening and molecular dynamics study of arachidin-2.
Biophys Chem
December 2024
Tecnologico de Monterrey, The Institute for Obesity Research, Unit of Experimental Medicine, Monterrey, NL 64849, Mexico. Electronic address:
The cannabinoid receptor 1 (CB1) is an essential component of the endocannabinoid system, responsible for regulating various physiological processes such as pain, mood, and appetite. Despite increasing interest in the therapeutic potential of CB1 modulators, the precise mechanisms by which small molecules modulate receptor activity-particularly without fully transitioning between active and inactive states-remain partially understood. In this study, the complexity of CB1-ligand interactions was evaluated for the inactive CB1 state.
View Article and Find Full Text PDFLarge-scale prediction of biological activities with Active-IT system.
Biomed Khim
December 2024
Chemoinformatics Group - NEQUIM, Departamento de Quimica, Instituto de Ciências Exatas, Universidade Federal de Minas Gerais (UFMG), Belo Horizonte, Brazil.
Traditional testing methods in pharmaceutical development can be time-consuming and costly, but in silico evaluation tools can offer a solution. Our in-house Active-IT system, a Ligand-Based Virtual Screening (LBVS) tool, was developed to predict the biological and pharmacological activities of small organic molecules. It includes four independent modules for generating molecular descriptors (3D-Pharma), machine learning modeling (ExCVBA), a database of bioactivity models, and a prediction module.
View Article and Find Full Text PDFWant AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!