Ligand Drift Rate Descriptor in Receptor Pocket: Molecular Docking Sampling for Differentiating Partial Agonists in Nuclear Receptors

High Resolution Image Download MS PowerPoint Slide The recent discovery that inverse agonists bind to a secondary orthosteric site in PPARγ reveals unexpected structural complexity in this nuclear receptor. To differentiate between full and partial agonists, we hypothesize that partial agonists exhibit dynamic positional behavior, moving among alternative binding sites at equilibrium when saturated, while full agonists bind directly and consistently to the primary orthosteric site. Using a two-state model derived from the Boltzmann distribution and molecular docking (MODO) sampling, we developed a computational metric called the Ligand Drift Rate (LDR) Descriptor to differentiate full agonists (Emax ≥ 90%) from partial agonists (Emax ≤ 45%) of PPARγ by simulating ligand positional instability within the primary orthosteric binding pocket. We combined molecular docking and hydrogen bond fluctuation analysis across 28 PPARγ-ligand complexes (18 full agonists and 10 partial agonists). MODO sampling was performed with several algorithms, each tested on five carefully selected receptor-binding pockets from 356 crystal complexes. Hydrogen bonds between ligands and key residues (His323, His449, Tyr473) were analyzed at various hydrogen-bond displacement (HBD) thresholds (6–12 Å). The LDR was calculated as the percentage of the top 20-scoring poses that lacked hydrogen bonds. We found that adding constraints on pose diversity and allowing receptor flexibility can improve LDR’s ability to distinguish full from partial agonists. Finally, MODO-sampling-based LDR calculations were conducted on 1079 ChEMBL ligands (393 full agonists and 686 partial agonists). In this validation set, LDR successfully differentiated partial from full agonists ( t -test, p = 0.00043) using the genetic algorithm with the 3B1M-KRC binding pocket and a 10 Å hydrogen-bond threshold. In QSAR applications for drug discovery, we have developed a dynamics-aware molecular descriptor, LDR, that can be a key factor in quantifying partial agonism arising from small-molecule ligand drift away from the primary orthosteric site.

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Journal
Journal of Chemical Information and Modeling
Published
2026-07-23
DOI
https://doi.org/10.1021/acs.jcim.6c00669
Primary Topic
Receptor Mechanisms and Signaling
Type
article
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0.00

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article

Ligand Drift Rate Descriptor in Receptor Pocket: Molecular Docking Sampling for Differentiating Partial Agonists in Nuclear Receptors

Ying‐Ting Lin, Yung-Ting Shih
Journal of Chemical Information and Modeling
Receptor Mechanisms and Signaling
article

Ligand Drift Rate Descriptor in Receptor Pocket: Molecular Docking Sampling for Differentiating Partial Agonists in Nuclear Receptors

Ying‐Ting Lin, Yung-Ting Shih
article en

Abstract

High Resolution Image Download MS PowerPoint Slide The recent discovery that inverse agonists bind to a secondary orthosteric site in PPARγ reveals unexpected structural complexity in this nuclear receptor. To differentiate between full and partial agonists, we hypothesize that partial agonists exhibit dynamic positional behavior, moving among alternative binding sites at equilibrium when saturated, while full agonists bind directly and consistently to the primary orthosteric site. Using a two-state model derived from the Boltzmann distribution and molecular docking (MODO) sampling, we developed a computational metric called the Ligand Drift Rate (LDR) Descriptor to differentiate full agonists (Emax ≥ 90%) from partial agonists (Emax ≤ 45%) of PPARγ by simulating ligand positional instability within the primary orthosteric binding pocket. We combined molecular docking and hydrogen bond fluctuation analysis across 28 PPARγ-ligand complexes (18 full agonists and 10 partial agonists). MODO sampling was performed with several algorithms, each tested on five carefully selected receptor-binding pockets from 356 crystal complexes. Hydrogen bonds between ligands and key residues (His323, His449, Tyr473) were analyzed at various hydrogen-bond displacement (HBD) thresholds (6–12 Å). The LDR was calculated as the percentage of the top 20-scoring poses that lacked hydrogen bonds. We found that adding constraints on pose diversity and allowing receptor flexibility can improve LDR’s ability to distinguish full from partial agonists. Finally, MODO-sampling-based LDR calculations were conducted on 1079 ChEMBL ligands (393 full agonists and 686 partial agonists). In this validation set, LDR successfully differentiated partial from full agonists ( t -test, p = 0.00043) using the genetic algorithm with the 3B1M-KRC binding pocket and a 10 Å hydrogen-bond threshold. In QSAR applications for drug discovery, we have developed a dynamics-aware molecular descriptor, LDR, that can be a key factor in quantifying partial agonism arising from small-molecule ligand drift away from the primary orthosteric site.

Journal of Chemical Information and Modeling
Kaohsiung Medical University (TW), International Drug Development (FR)
Kaohsiung Medical University
Openalex Percentile: Top 15%
Receptor Mechanisms and Signaling
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