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Updated: Jul 8, 2026

Incorporating Target Protein Structure Flexibility and Dynamics in Computational Drug Discovery Using Ensemble-Based Docking Analysis

Incorporating Target Protein Structure Flexibility and Dynamics in Computational Drug Discovery Using Ensemble-Based Docking Analysis

Published on: June 20, 2025

Can we use docking and scoring for hit-to-lead optimization?

Istvan J Enyedy¹, William J Egan

¹Global Discovery Chemistry, Computer-Aided Drug Discovery, Novartis Institutes for BioMedical Research, 250 Massachusetts Avenue, Cambridge, MA 02139, USA. istvan.enyedy@novartis.com

Journal of Computer-Aided Molecular Design

|January 10, 2008

Summary

Computational docking and scoring show limitations in hit-to-lead optimization. Expert interpretation remains crucial for reliably differentiating active from inactive compounds in drug discovery.

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Area of Science:

Computational chemistry
Drug discovery
Medicinal chemistry

Background:

Molecular docking and scoring are vital for identifying and optimizing drug candidates when target structures are known.
These methods aid in refining ligand binding and predicting experimental binding modes.

Purpose of the Study:

To evaluate the reliability of docking and scoring functions for hit-to-lead optimization.
To assess the correlation between docking scores and experimental IC50 values.
To analyze the impact of target, crystal structure, and scoring function precision on compound differentiation.

Main Methods:

Tested the relationship between in-house docking scores and experimentally determined IC50 values.
Analyzed the performance of scoring functions using receiver operating characteristic (ROC) curves.
Evaluated the influence of molecular weight (MW) and ClogP as alternative predictors.

Main Results:

Docking scores showed limited reliability for hit-to-lead optimization across the tested datasets.
Molecular weight (MW) and ClogP were found to be as effective as GlideScores in differentiating active from inactive compounds.
No significant performance difference was observed between SP and XP scoring methods.

Conclusions:

Docking and scoring alone are insufficient for reliable hit-to-lead optimization.
Simple physicochemical properties can be competitive with complex scoring functions.
Expert interpretation is essential for successful application of docking and scoring in drug discovery pipelines.