⚛️ biophysics

Kinase inhibitors can change protonation or tautomeric state upon binding

Using Multi-Conformation Continuum Electrostatics (MCCE) simulations, this study demonstrates that kinase inhibitors frequently undergo dynamic shifts in protonation and tautomer states upon binding, revealing that minority species can become dominant in the bound complex and highlighting the critical need to consider full protonation and tautomer ensembles for accurate prediction of binding energetics.

Original authors: Ranepura, G. A., Chowdhury, S. I., Rosenzweig, E. A., Rustenburg, A. S., Lopez-Rios de Castro, R., Mao, J., Chodera, J. D., Singh, S., Gunner, M. R.

Published 2026-07-30

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CC BY 4.0

Original authors: Ranepura, G. A., Chowdhury, S. I., Rosenzweig, E. A., Rustenburg, A. S., Lopez-Rios de Castro, R., Mao, J., Chodera, J. D., Singh, S., Gunner, M. R.

Original paper licensed under CC BY 4.0 (https://creativecommons.org/licenses/by/4.0/). ⚕️ This is an AI-generated explanation of a preprint that has not been peer-reviewed. It is not medical advice. Do not make health decisions based on this content. Read full disclaimer

Imagine you are trying to fit a key into a very complex, high-tech lock. In the world of medicine, that lock is a protein inside your body, and the key is a drug molecule designed to stop a disease. For years, scientists have tried to predict exactly how well these keys fit by looking at their shapes. But there's a hidden twist: both the key and the lock are made of tiny building blocks that can change their electrical personality. Some parts can grab a proton (a tiny hydrogen nucleus) and become positively charged, while others can lose one and become negative. They can also rearrange their internal atoms into different "tautomeric" shapes, like a person changing their hairstyle.

These electrical changes are crucial because opposite charges attract, and like charges repel. If a drug molecule changes its charge or shape the moment it touches the protein, the whole fit changes. However, most computer programs used to design drugs are like rigid mannequins; they assume the drug and the protein stay in one fixed electrical state, usually the one they have when floating in water. This is a bit like trying to predict how a magnet will stick to a fridge without realizing the magnet might flip its poles the second it gets close. Understanding these dynamic shifts is vital for creating better, more effective medicines, but it's incredibly hard to calculate because there are so many possible combinations of charges and shapes to check.

This paper dives into that messy, dynamic world to see what really happens when kinase drugs (a major class of cancer and inflammation fighters) bind to their protein targets. The researchers used a sophisticated computer simulation tool called MCCE (Multi-Conformer Continuum Electrostatics) to act like a super-fast, super-accurate observer. Instead of guessing a single "best" shape for the drug or the protein, they let the computer explore thousands of different charge and shape possibilities at once, calculating which ones are most likely to happen. They looked at 18 different FDA-approved drugs binding to 9 different kinase proteins, simulating the environment both in the water of the cell and deep inside the protein's binding pocket.

The results revealed some surprising twists in the story of drug binding. First, the idea that a drug always becomes "calmer" or less charged when it leaves the water and enters the protein was proven wrong in many cases. While it makes sense that a charged object loses energy when it leaves the water (like a wet towel drying out), the protein's interior is often a charged party that actually wants to hold onto that electrical charge. In several instances, the drug actually became more charged or kept its high charge level once it was bound, defying the expectation that it would neutralize itself.

Furthermore, the study found that the drugs are chameleons. A drug might float in the water as one specific shape or charge, but the moment it locks into the protein, it often shifts to a completely different, sometimes rarer, shape or charge state. In fact, for some drugs, the "minority" version that barely exists in the water becomes the "majority" version once inside the protein. This means that if you only look at the drug in a test tube, you might be designing for a ghost that doesn't exist in the real target.

Interestingly, while the drugs were busy changing their electrical personalities, the proteins themselves were surprisingly chill. Even when a highly charged drug bound to them, the protein's overall electrical charge barely budged. It's as if the protein is a massive, well-buffered crowd; even if one person (the drug) enters shouting and waving a flag, the crowd doesn't panic or change its collective mood. The protein manages these changes by making tiny adjustments in just a few specific spots near the binding site, rather than shifting its entire electrical identity. The researchers also checked if the protein's "pose" (specifically a loop called the DFG, which can be "in" or "out") dictated these changes, but found that the charge shifts happened regardless of the protein's pose.

In short, this paper suggests that to accurately predict how well a drug will work, we can't just look at the drug in isolation or assume it stays the same once it enters the body. The drug and the protein are in a dynamic dance where they constantly adjust their electrical states to fit each other. Ignoring these shifts is like trying to predict a dance partner's moves without watching them move. By accounting for these fluid changes in charge and shape, scientists can build better models to design the next generation of life-saving medicines.

Technical Summary: Kinase Inhibitors Can Change Protonation or Tautomeric State Upon Binding

Problem Statement
Accurate prediction of protein-ligand binding affinity ( $\Delta G$ ) is a cornerstone of computer-aided drug design (CADD). However, standard workflows often fail to account for the dynamic distribution of protonation and tautomeric states of both the ligand and the protein target. At physiological pH, residues such as Histidine, Aspartate, Glutamate, Arginine, and Lysine exist in ensembles of ionization states, and ligands possess multiple accessible protonation and tautomeric forms. Current methods frequently rely on heuristic assignment of fixed protonation states or require computationally prohibitive sampling (e.g., constant-pH MD) that is incompatible with high-throughput pipelines. Consequently, misassignment of these states can lead to significant errors in binding energy predictions, particularly for kinase inhibitors where pH dependence and ionization states are critical for function and drug design.

Methodology
The authors employed the Multi-Conformer Continuum Electrostatics (MCCE) method, a Grand Canonical Monte Carlo (GCMC) approach based on Continuum Electrostatics (CE), to investigate the protonation and tautomeric distributions of kinase-inhibitor complexes.

System Selection: The study analyzed 37 experimental crystal structures comprising 9 unique kinase domains (ABL1, ALK, CDK6, DDR1, EGFR, JAK3, MEK, MET, VEGFR) bound to 18 FDA-approved inhibitors.
Workflow: Three independent MCCE calculations were performed for each system: (1) the apo-protein (ligand removed), (2) the holo-protein complex, and (3) the isolated ligand in solution.
Sampling: The method samples side-chain rotamers, ligand conformers, and protonation/tautomer states. Self-energies and pairwise interactions were calculated using the Poisson-Boltzmann equation (solved via Delphi) with a protein dielectric constant of 4 and solvent of 80.
Analysis: The Boltzmann-weighted probabilities of microstates were computed to determine the average net charge and dominant protonation/tautomer states for both the protein and ligand in solution versus the bound state. The study specifically examined shifts in charge ( $\Delta q$ ) and tautomeric populations upon binding.

Key Contributions and Results

Dynamic Ligand Charge: Contrary to the assumption that ligands lose charge upon entering the hydrophobic binding pocket (due to desolvation penalties), the study found that individual inhibitor charges are highly dynamic. While some inhibitors become less charged upon binding, others maintain or even increase their net charge. For instance, Crizotinib shifts from a dominant +2 state in solution to a +1 state when bound to ALK, whereas Lapatinib shifts from a predominantly +1 state in solution to a neutral state when bound to EGFR.
Protein Charge Stability: Despite binding charged ligands, the net charge of the kinase domains remained largely stable. The protein's net charge is effectively "buffered" by a large ensemble of microstates with similar energies, allowing redistribution of protonation states without significant changes in the total net charge.
Localized Protonation Shifts: Significant protonation changes ( $\Delta q > 0.2$ ) were restricted to a small fraction of residues, predominantly Lysine and Cysteine, often located near the binding site but occasionally up to 10 Å away (e.g., LYS1205 in ALK). The vast majority of residues showed no change in protonation state between apo and holo forms.
Tautomeric Shifts: The study identified cases where the lowest-energy tautomer in solution is not the dominant species in the bound state. In some cases, minority species in solution become the dominant component in the bound complex, with free energy differentials between tautomers reaching 3–6 kcal/mol.
Conformational Independence: The magnitude of charge changes upon binding showed no strong dependence on the kinase's DFG-loop conformation (DFG-in vs. DFG-out). Neither the protein nor the ligand exhibited a predictable charge shift pattern based solely on the DFG state.

Significance and Claims
The paper asserts that accurate prediction of protein-ligand binding energetics requires considering the full ensemble of protonation and tautomeric states for both partners, rather than relying on solution-state properties or fixed assignments.

Ensemble Necessity: The findings emphasize that "minority species" in solution can become dominant in the bound state, necessitating ensemble-wide consideration to avoid large errors in affinity prediction.
Target-Specific Assignment: Protonation and tautomeric states should be treated as binding-site-specific properties. They cannot be extrapolated from the ligand's solution state, the global kinase conformation, or a single fixed model.
Methodological Efficiency: The study demonstrates that MCCE provides a scalable, efficient alternative to constant-pH MD for capturing these effects in pharmacologically relevant systems, enabling the identification of significant free energy differentials (3–6 kcal/mol) associated with specific tautomeric states.

The authors conclude that while the protein's net charge is robust to ligand binding, the specific protonation state of the ligand is highly context-dependent and must be determined within the complex to ensure reliable downstream physics-based modeling.

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