Physics-Based Design of Protein-Ligand Binding

F. Edward Boas
Harbury lab
Department of Biochemistry
Stanford University
May 2008

Research summary

Different potential energy functions have been used in protein dynamics simulations, protein design calculations, and protein structure prediction. Clearly, the same physics applies in all three cases, so the variation in potential energy functions reflects differences in how the calculations are performed. With improvements in computer power and algorithms, the same potential energy function should be applicable to all three problems.[1]

Molecular mechanics potential energy function Molecular mechanics potential energy function.

Here we show that a standard molecular-mechanics potential energy function without any modifications can be used to engineer protein-ligand binding. A molecular-mechanics potential is used to reconstruct the coordinates of various binding sites with an average root mean square error of 0.61 Å, and to reproduce known ligand-induced side-chain conformational shifts. Within a series of 34 mutants, the calculation can always distinguish weak (Kd > 1 mM) and tight (Kd < 10 μM) binding sequences. Starting from partial coordinates of the ribose binding protein lacking the ligand and the ten primary contact residues, the molecular-mechanics potential is used to redesign a ribose binding site. Out of a search space of 2×1012 sequences, the calculation selects a point mutant of the native protein as the top solution (experimental Kd = 17 μM), and the native protein as the second best solution (experimental Kd = 210 nM). The quality of the predictions depends on the accuracy of the generalized Born electrostatics model, treatment of protonation equilibria, high resolution rotamer sampling, a final local energy minimization step, and explicit modeling of the bound, unbound, and unfolded states.[2]

Binding constant predictions Predicting binding constants.

Structural prediction Predicting structure.

After this initial proof of principle experiment, we next used a standard molecular mechanics potential energy function to redesign ribose binding protein to bind a series of ligands: L-arabinose, D-xylose, indole-3-acetic acid, and estradiol. The resulting proteins have 5 - 10 mutations from the native, are stable, the predicted structures have good hydrogen bonds and shape complementarity, and they use motifs similar to natural binding proteins. All of the designed proteins bind to their target ligands with measurable but weak affinity. The affinity was improved by random mutagenesis and screening.[3]

Protein design Designing new binding sites.

The application of unmodified molecular-mechanics potentials to protein design links two fields in a mutually beneficial way. Design provides a new avenue to test molecular-mechanics energy functions, and future improvements in these energy functions will presumably lead to more accurate design results.

This is the first time a single model has been used to predict structures, binding constants, and to design new small-molecule binding sites. Using a standard model should improve the generality of protein design, which could enable the creation of custom proteins for a wide variety of applications, including sensors, enzymes, and protein therapeutics.

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Paper
Commentary

 1. Boas FE and Harbury PB. (2007) "Potential energy functions for protein design." Current Opinion in Structural Biology. 17: 199-204.

Different potential energy functions have predominated in protein dynamics simulations, protein design calculations, and protein structure prediction. Clearly, the same physics applies in all three cases. The differences in potential energy functions reflect differences in how the calculations are performed. With improvements in computer power and algorithms, the same potential energy function should be applicable to all three problems. In this review, we examine energy functions currently used for protein design, and look to the molecular mechanics field for advances that could be used in the next generation of design algorithms. In particular, we focus on improved models of the hydrophobic effect, polarization and hydrogen bonding.

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Published paper

Manuscript
Figures
Supplementary information

Rotamer library (6028 members)

2. Boas FE, Harbury PB. (2008) "Design of protein-ligand binding based on the molecular-mechanics energy model." Journal of Molecular Biology. 380: 415-24.

While the molecular-mechanics field has standardized on a few potential energy functions, computational protein design efforts are based on potentials that are unique to individual labs. Here we show that a standard molecular-mechanics potential energy function without any modifications can be used to engineer protein-ligand binding. A molecular-mechanics potential is used to reconstruct the coordinates of various binding sites with an average root mean square error of 0.61 Å, and to reproduce known ligand-induced side-chain conformational shifts. Within a series of 34 mutants, the calculation can always distinguish weak (Kd > 1 mM) and tight (Kd < 10 μM) binding sequences. Starting from partial coordinates of the ribose binding protein lacking the ligand and the ten primary contact residues, the molecular-mechanics potential is used to redesign a ribose binding site. Out of a search space of 2×1012 sequences, the calculation selects a point mutant of the native protein as the top solution (experimental Kd = 17 μM), and the native protein as the second best solution (experimental Kd = 210 nM). The quality of the predictions depends on the accuracy of the generalized Born electrostatics model, treatment of protonation equilibria, high resolution rotamer sampling, a final local energy minimization step, and explicit modeling of the bound, unbound, and unfolded states. The application of unmodified molecular-mechanics potentials to protein design links two fields in a mutually beneficial way. Design provides a new avenue to test molecular-mechanics energy functions, and future improvements in these energy functions will presumably lead to more accurate design results.
Key words: protein design, generalized Born, force field, dissociation constant, structure prediction.

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Thesis defense slides (12 MB)

Entire thesis (12 MB)

3. Boas FE. (2008) Physics-Based Design of Protein-Ligand Binding. PhD dissertation, Department of Biochemistry, Stanford University.

Front matter
Abstract | Acknowledgements | Table of contents | List of tables | List of figures

Chapter 1: Introduction
Relationship to the protein folding problem | Design goal | Innovative aspects of the research | Models for understanding molecular recognition | Finding a protein's low energy conformations | Probabilistic description of protein conformation | Evolving binding sites

Chapter 2: Potential energy functions for protein design
Summary | Introduction | Potential energy functions | Conclusions and future directions | Acknowledgements

Chapter 3: Physics-based design of protein-ligand Binding
Summary | Introduction | Results | Discussion | Materials and methods | Acknowledgments

Chapter 4: The protein design algorithm
Potential energy function | Overview | Water | Generalized Born energy | Pairwise approximation of solvent accessible surface area (SASA) | Deprotonation energy | Discrete sampling | Protein scaffold coordinates | Selection of design positions | Rotamer library | Ligand poses | Structural optimization | Unfolded state | Sequence optimization (genetic algorithm) | Appendix: Integrals

Chapter 5: Physics-based design of new binding proteins
Summary | Introduction | Results | Discussion | Materials and methods

Chapter 6: Conclusion
Designing for specificity | Energetic vs structural predictions | Comparison to more established branches of engineering | Application: Sensors | Application: Custom enzymes | Application: Therapeutic proteins | References

Related links:
Harbury lab web page
Predicting protein binding sites

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