ArticleScientific reports2016
Constructing and Validating High-Performance MIEC-SVM Models in Virtual Screening for Kinases: A Better Way for Actives Discovery.
Article in Scientific reports, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.
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Who cites it
22 citing papers in PubMed.
- Bridging predictive reliability and explainability: a multi-representation deep learning framework for chemical space analysis of immune bioassays.Journal of cheminformatics · 2026Article
- Inactive-enriched machine-learning models exploiting patent data improve structure-based virtual screening for PDL1 dimerizers.Journal of advanced research · 2025Article
- Deep learning pipeline for accelerating virtual screening in drug discovery.Scientific reports · 2024Article
- A potent new-scaffold androgen receptor antagonist discovered on the basis of a MIEC-SVM model.Acta pharmacologica Sinica · 2024Article
- Comprehensive machine learning boosts structure-based virtual screening for PARP1 inhibitors.Journal of cheminformatics · 2024Article
- A practical guide to machine-learning scoring for structure-based virtual screening.Nature protocols · 2023Review
- Beware of Simple Methods for Structure-Based Virtual Screening: The Critical Importance of Broader Comparisons.Journal of chemical information and modeling · 2023Article
- Deciphering the Shared and Specific Drug Resistance Mechanisms of Anaplastic Lymphoma Kinase via Binding Free Energy Computation.Research (Washington, D.C.) · 2023Article
- Identification of Novel Arachidonic Acid 15-Lipoxygenase Inhibitors Based on the Bayesian Classifier Model and Computer-Aided High-Throughput Virtual Screening.Pharmaceuticals (Basel, Switzerland) · 2022Article
- The impact of cross-docked poses on performance of machine learning classifier for protein-ligand binding pose prediction.Journal of cheminformatics · 2021Article
- Machine learning on ligand-residue interaction profiles to significantly improve binding affinity prediction.Briefings in bioinformatics · 2021Article
- Artificial intelligence and machine learning-aided drug discovery in central nervous system diseases: State-of-the-arts and future directions.Medicinal research reviews · 2021Review
- Property-Unmatched Decoys in Docking Benchmarks.Journal of chemical information and modeling · 2021Article
- Comparative Study of Interactions between Human cGAS and Inhibitors: Insights from Molecular Dynamics and MM/PBSA Studies.International journal of molecular sciences · 2021Article
- Structure-based protein-ligand interaction fingerprints for binding affinity prediction.Computational and structural biotechnology journal · 2021Review
- Merging Ligand-Based and Structure-Based Methods in Drug Discovery: An Overview of Combined Virtual Screening Approaches.Molecules (Basel, Switzerland) · 2020Review
- Discovery of novel natural compound inhibitors targeting estrogen receptor α by an integrated virtual screening strategy.Journal of molecular modeling · 2019Article
- Glucose-6-Phosphate Upregulates Txnip Expression by Interacting With MondoA.Frontiers in molecular biosciences · 2019Article
- Exploring the binding mechanisms of PDE5 with chromeno[2,3-RSC advances · 2018Article
- The Impact of Protein Structure and Sequence Similarity on the Accuracy of Machine-Learning Scoring Functions for Binding Affinity Prediction.Biomolecules · 2018Article
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Authors and funding
8 authors.
Funding
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Abstract
The MIEC-SVM approach, which combines molecular interaction energy components (MIEC) derived from free energy decomposition and support vector machine (SVM), has been found effective in capturing the energetic patterns of protein-peptide recognition. However, the performance of this approach in identifying small molecule inhibitors of drug targets has not been well assessed and validated by experiments. Thereafter, by combining different model construction protocols, the issues related to developing best MIEC-SVM models were firstly discussed upon three kinase targets (ABL, ALK, and BRAF). As for the investigated targets, the optimized MIEC-SVM models performed much better than the models based on the default SVM parameters and Autodock for the tested datasets. Then, the proposed strategy was utilized to screen the Specs database for discovering potential inhibitors of the ALK kinase. The experimental results showed that the optimized MIEC-SVM model, which identified 7 actives with IC50 < 10 μM from 50 purchased compounds (namely hit rate of 14%, and 4 in nM level) and performed much better than Autodock (3 actives with IC50 < 10 μM from 50 purchased compounds, namely hit rate of 6%, and 2 in nM level), suggesting that the proposed strategy is a powerful tool in structure-based virtual screening.
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