ArticleJournal of chemical information and modeling2017
Comprehensive and Automated Linear Interaction Energy Based Binding-Affinity Prediction for Multifarious Cytochrome P450 Aromatase Inhibitors.
Article in Journal of chemical information and modeling, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
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Who cites it
15 citing papers in PubMed, 25 citations in OpenAlex.
- Computation of Protein-Ligand Binding Free Energies with a Quantum Mechanics-Based Mining Minima Algorithm.Journal of chemical theory and computation · 2025Article
- Integrated Virtual Screening Approach Identifies New CYP19A1 Inhibitors.Journal of chemical information and modeling · 2025Article
- The Interaction Mechanism Between C14-Polyacetylene Compounds and the Rat TRPA1 Receptor: An In Silico Study.International journal of molecular sciences · 2024Article
- Mechanistic Insights of Polyphenolic Compounds from Rosemary Bound to Their Protein Targets Obtained by Molecular Dynamics Simulations and Free-Energy Calculations.Foods (Basel, Switzerland) · 2023Article
- Tailored Parameterization of the LIE Method for Calculating the Binding Free Energy of Vps34-Inhibitor Complexes.ACS omega · 2021Article
- Network pharmacology-based analysis for unraveling potential cancer-related molecular targets of Egyptian propolis phytoconstituents accompanied with molecular docking andRSC advances · 2021Article
- Recent Developments in Free Energy Calculations for Drug Discovery.Frontiers in molecular biosciences · 2021Review
- Structure-based peptide design targeting intrinsically disordered proteins: Novel histone H4 and H2A peptidic inhibitors.Computational and structural biotechnology journal · 2021Article
- Docking Studies and Molecular Dynamics Simulation ofJournal of pharmacy & bioallied sciences · 2020Article
- How Good is Jarzynski's Equality for Computer-Aided Drug Design?The journal of physical chemistry. B · 2020Article
- Effective estimation of the inhibitor affinity of HIV-1 proteaseRSC advances · 2020Article
- Recent Developments in Linear Interaction Energy Based Binding Free Energy Calculations.Frontiers in molecular biosciences · 2020Article
- A Comparative Linear Interaction Energy and MM/PBSA Study on SIRT1-Ligand Binding Free Energy Calculation.Journal of chemical information and modeling · 2019Article
- Adequate prediction for inhibitor affinity of AβRSC advances · 2019Article
- Binding free energy predictions of farnesoid X receptor (FXR) agonists using a linear interaction energy (LIE) approach with reliability estimation: application to the D3R Grand Challenge 2.Journal of computer-aided molecular design · 2018Article
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Authors and funding
6 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Cytochrome P450 aromatase (CYP19A1) plays a key role in the development of estrogen dependent breast cancer, and aromatase inhibitors have been at the front line of treatment for the past three decades. The development of potent, selective and safer inhibitors is ongoing with in silico screening methods playing a more prominent role in the search for promising lead compounds in bioactivity-relevant chemical space. Here we present a set of comprehensive binding affinity prediction models for CYP19A1 using our automated Linear Interaction Energy (LIE) based workflow on a set of 132 putative and structurally diverse aromatase inhibitors obtained from a typical industrial screening study. We extended the workflow with machine learning methods to automatically cluster training and test compounds in order to maximize the number of explained compounds in one or more predictive LIE models. The method uses protein-ligand interaction profiles obtained from Molecular Dynamics (MD) trajectories to help model search and define the applicability domain of the resolved models. Our method was successful in accounting for 86% of the data set in 3 robust models that show high correlation between calculated and observed values for ligand-binding free energies (RMSE < 2.5 kJ mol
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