On the development of protein pKa calculation algorithms
Protein pKa calculation algorithms are typically developed to reproduce experimental pKa values and provide us with a better understanding of the fundamental importance of electrostatics for protein structure and function. However, the approximations and adjustable parameters employed in almost all pKa calculation methods means that there is the risk that pKa calculation algorithms are 'over-fitted' to the available datasets, and that these methods therefore do not model protein physics realistically. We employ simulations of the protein pKa calculation algorithm development process to show that careful optimization procedures and non-biased experimental datasets must be applied to ensure a realistic description of the underlying physical terms. We furthermore investigate the effect of experimental noise and find a significant effect on the pKa calculation algorithm optimization landscape. Finally, we comment on strategies for ensuring the physical realism of protein pKa calculation algorithms and we assess the overall state of the field with a view to predicting future directions of development.
- Research Organization:
- Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
- Sponsoring Organization:
- USDOE
- DOE Contract Number:
- AC05-76RL01830
- OSTI ID:
- 1037531
- Report Number(s):
- PNNL-SA-77764; 400412000; TRN: US201207%%337
- Journal Information:
- Proteins. Structure, Function, and Bioinformatics, Vol. 79, Issue 12
- Country of Publication:
- United States
- Language:
- English
Similar Records
Progresses in Ab Initio QM/MM Free Energy Simulations of Electrostatic Energies in Proteins: Accelerated QM/MM Studies of pKa, Redox Reactions and Solvation Free Energies
Bayesian model aggregation for ensemble-based estimates of protein pKa values