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April 12, 2026SAR and QSAR in environmental research

Systematic evaluation of data preprocessing and model selection strategies for reliable pIC 50 prediction of acetylcholinesterase inhibitors

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Authors

EDEmre DelibaşHGH.İ. Güler

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Overview

Evaluation of machine learning strategies predicts AChE activity, indicating challenges in dataset correlation.

Key Points

  • The aim is to evaluate different data preprocessing and model selection strategies for predicting AChE inhibitory activity.
  • Utilized machine learning models including CatBoost, XGBoost, and Support Vector Regression.
  • Applied data preprocessing strategies such as logarithmic transformation and winsorization of IC50 values.
  • Implemented a 70-15-15 train-validation-test split and 10-fold cross validation for performance assessment.
  • Explored stacking based ensemble learning strategies to enhance model generalization.
  • Optimized tree-based models achieved the highest accuracy for predicting AChE activity.
  • Predictive performance was influenced more by intrinsic dataset characteristics than by model selection.
  • Stacking models provided marginal improvements over the best individual learners.
  • SHAP analysis revealed important contributions from molecular descriptors, aiding interpretability.

Cite This Study

Delibaş et al. (2026) studied this question.

synapsesocial.com/papers/69db36c24fe01fead37c4cbbhttps://doi.org/10.1080/1062936x.2026.2647204
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Also Consider

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  1. 1Prediction of acetylcholinesterase inhibition associated with Alzheimer’s disease using hybrid descriptor and graph-based machine learning models2026
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  3. 3Integrating multi-structure covalent docking with machine-learning consensus scoring enhances potency ranking of human acetylcholinesterase inhibitors2026
  4. 4Machine learning framework for predicting DPP-4 inhibitory activity: a preliminary study on candidate screening and structural determinants2026
  5. 5Machine learning-based virtual screening and molecular modelling studies for identification of butyrylcholinesterase inhibitors as anti-Alzheimer’s agent2024