ArticleJournal of the Royal Society, Interface2012
Hierarchical virtual screening for the discovery of new molecular scaffolds in antibacterial hit identification.
Article in Journal of the Royal Society, Interface, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 35 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
35 citing papers in PubMed, 83 citations in OpenAlex.
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- Artificial intelligence for antimicrobial resistance: advancing reproducibility, interpretability, and clinical deployment.Briefings in bioinformatics · 2026Review
- Inactive-enriched machine-learning models exploiting patent data improve structure-based virtual screening for PDL1 dimerizers.Journal of advanced research · 2025Article
- Comprehensive machine learning boosts structure-based virtual screening for PARP1 inhibitors.Journal of cheminformatics · 2024Article
- Identification of Potential Multitarget Compounds against Alzheimer's Disease through Pharmacophore-Based Virtual Screening.Pharmaceuticals (Basel, Switzerland) · 2023Article
- A practical guide to machine-learning scoring for structure-based virtual screening.Nature protocols · 2023Review
- Molecular Multi-Target Approach for Human Acetylcholinesterase, Butyrylcholinesterase andPharmaceuticals (Basel, Switzerland) · 2023Article
- Beware of Simple Methods for Structure-Based Virtual Screening: The Critical Importance of Broader Comparisons.Journal of chemical information and modeling · 2023Article
- The Chemical Property Position of Bedaquiline Construed by a Chemical Global Positioning System-Natural Product.Molecules (Basel, Switzerland) · 2022Article
- Drug Discovery forInternational journal of molecular sciences · 2021Review
- Regioselective Bromine/Magnesium Exchange for the Selective Functionalization of Polyhalogenated Arenes and Heterocycles.Angewandte Chemie (International ed. in English) · 2021Article
- Structure-basedComputational and structural biotechnology journal · 2021Review
- Machine learning classification can reduce false positives in structure-based virtual screening.Proceedings of the National Academy of Sciences of the United States of America · 2020Article
- OnionNet: a Multiple-Layer Intermolecular-Contact-Based Convolutional Neural Network for Protein-Ligand Binding Affinity Prediction.ACS omega · 2019Article
- Development and Testing of Druglike Screening Libraries.Journal of chemical information and modeling · 2019Article
- Advances in the Development of Shape Similarity Methods and Their Application in Drug Discovery.Frontiers in chemistry · 2018Review
- A Bayesian Target Predictor Method based on Molecular Pairing Energies estimation.Scientific reports · 2017Article
- Correcting the impact of docking pose generation error on binding affinity prediction.BMC bioinformatics · 2016Article
- USR-VS: a web server for large-scale prospective virtual screening using ultrafast shape recognition techniques.Nucleic acids research · 2016Article
- Neural-Network Scoring Functions Identify Structurally Novel Estrogen-Receptor Ligands.Journal of chemical information and modeling · 2015Article
Corrections and comments
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Authors and funding
7 authors at 4 institutions in 1 country.
Funding
Abstract
One of the initial steps of modern drug discovery is the identification of small organic molecules able to inhibit a target macromolecule of therapeutic interest. A small proportion of these hits are further developed into lead compounds, which in turn may ultimately lead to a marketed drug. A commonly used screening protocol used for this task is high-throughput screening (HTS). However, the performance of HTS against antibacterial targets has generally been unsatisfactory, with high costs and low rates of hit identification. Here, we present a novel computational methodology that is able to identify a high proportion of structurally diverse inhibitors by searching unusually large molecular databases in a time-, cost- and resource-efficient manner. This virtual screening methodology was tested prospectively on two versions of an antibacterial target (type II dehydroquinase from Mycobacterium tuberculosis and Streptomyces coelicolor), for which HTS has not provided satisfactory results and consequently practically all known inhibitors are derivatives of the same core scaffold. Overall, our protocols identified 100 new inhibitors, with calculated K(i) ranging from 4 to 250 μM (confirmed hit rates are 60% and 62% against each version of the target). Most importantly, over 50 new active molecular scaffolds were discovered that underscore the benefits that a wide application of prospectively validated in silico screening tools is likely to bring to antibacterial hit identification.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.