ArticleJournal of cheminformatics2018
Life beyond the Tanimoto coefficient: similarity measures for interaction fingerprints.
Article in Journal of cheminformatics, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 61 papers.
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Who cites it
61 citing papers in PubMed.
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- Machine Learning-Guided Discovery of Bacterial-Selective Membrane-Active Compounds Reveals Mechanistic Bias in Antibiotic Training Datasets.bioRxiv : the preprint server for biology · 2026Article
- Machine learning-based design, screening, and activity validation of topoisomerase I inhibitors.Molecular diversity · 2026Article
- Machine Learning Exploration of Food-Derived Chemical Space for Potential Nutritional Metabolic Regulators Targeting Dipeptidyl Peptidase-4.Pharmaceuticals (Basel, Switzerland) · 2026Article
- Computational Analysis of Balanites aegyptiaca Phytochemicals as Inhibitors of Human Pancreatic α-Amylase.Chemistry & biodiversity · 2026Article
- DeepTargetClass: a web-based platform for predicting protein target classes of small molecules.Journal of computer-aided molecular design · 2025Article
- Molecular Motif Learning as a pretraining objective for molecular property prediction.Nature communications · 2025Article
- Systematic Exploration of Small-Molecule Binding via a Large Language Model Trained on Textualized Protein-Ligand Interactions.Molecules (Basel, Switzerland) · 2025Article
- Evaluation of single-template ligand-based methods for the discovery of small-molecule nucleic acid binders.Briefings in bioinformatics · 2025Article
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- SHINE: Deterministic Many-to-Many Clustering of Molecular Pathways.Journal of chemical information and modeling · 2025Article
- Identification of druggable binding sites and small molecules as modulators of TMC1.Communications biology · 2025Article
- DynHeter-DTA: Dynamic Heterogeneous Graph Representation for Drug-Target Binding Affinity Prediction.International journal of molecular sciences · 2025Article
- Identify potential drug candidates within a high-quality compound search space.Briefings in bioinformatics · 2024Article
- Alternative weighting schemes for fine-tuned extended similarity indices.Journal of chemometrics · 2024Article
- Neglected Tropical Diseases: A Chemoinformatics Approach for the Use of Biodiversity in Anti-Trypanosomatid Drug Discovery.Biomolecules · 2024Review
- Protein Retrieval via Integrative Molecular Ensembles (PRIME) through Extended Similarity Indices.Journal of chemical theory and computation · 2024Article
1 more citing papers are in PubMed but not listed here.
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Authors and funding
3 authors.
Funding
Abstract
backgroundInteraction fingerprints (IFP) have been repeatedly shown to be valuable tools in virtual screening to identify novel hit compounds that can subsequently be optimized to drug candidates. As a complementary method to ligand docking, IFPs can be applied to quantify the similarity of predicted binding poses to a reference binding pose. For this purpose, a large number of similarity metrics can be applied, and various parameters of the IFPs themselves can be customized. In a large-scale comparison, we have assessed the effect of similarity metrics and IFP configurations to a number of virtual screening scenarios with ten different protein targets and thousands of molecules. Particularly, the effect of considering general interaction definitions (such as Any Contact, Backbone Interaction and Sidechain Interaction), the effect of filtering methods and the different groups of similarity metrics were studied.
resultsThe performances were primarily compared based on AUC values, but we have also used the original similarity data for the comparison of similarity metrics with several statistical tests and the novel, robust sum of ranking differences (SRD) algorithm. With SRD, we can evaluate the consistency (or concordance) of the various similarity metrics to an ideal reference metric, which is provided by data fusion from the existing metrics. Different aspects of IFP configurations and similarity metrics were examined based on SRD values with analysis of variance (ANOVA) tests.
conclusionA general approach is provided that can be applied for the reliable interpretation and usage of similarity measures with interaction fingerprints. Metrics that are viable alternatives to the commonly used Tanimoto coefficient were identified based on a comparison with an ideal reference metric (consensus). A careful selection of the applied bits (interaction definitions) and IFP filtering rules can improve the results of virtual screening (in terms of their agreement with the consensus metric). The open-source Python package FPKit was introduced for the similarity calculations and IFP filtering; it is available at: https://github.com/davidbajusz/fpkit .
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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.