NMR biomolecular structure calculations exploit simulated annealing methods for conformational sampling and require a relatively high level of redundancy in the experimental restraints to determine quality three-dimensional structures. Recent advances in generalized Born (GB) implicit solvent models should make it possible to combine information from both experimental measurements and accurate empirical force fields to improve the quality of NMR-derived structures. In this paper, we study the influence of implicit solvent on the refinement of protein NMR structures and identify an optimal protocol of utilizing these improved force fields. To do so, we carry out structure refinement experiments for model proteins with published NMR structures using full NMR restraints and subsets of them. We also investigate the application of advanced sampling techniques to NMR structure refinement. Similar to the observations of Xia et al. (J.Biomol. NMR 2002, 22, 317-331), we find that the impact of implicit solvent is rather small when there is a sufficient number of experimental restraints (such as in the final stage of NMR structure determination), whether implicit solvent is used throughout the calculation or only in the final refinement step. The application of advanced sampling techniques also seems to have minimal impact in this case. However, when the experimental data are limited, we demonstrate that refinement with implicit solvent can substantially improve the quality of the structures. In particular, when combined with an advanced sampling technique, the replica exchange (REX) method, near-native structures can be rapidly moved toward the native basin. The REX method provides both enhanced sampling and automatic selection of the most native-like (lowest energy) structures. An optimal protocol based on our studies first generates an ensemble of initial structures that maximally satisfy the available experimental data with conventional NMR software using a simplified force field and then refines these structures with implicit solvent using the REX method. We systematically examine the reliability and efficacy of this protocol using four proteins of various sizes ranging from the 56-residue B1 domain of Streptococcal protein G to the 370-residue Maltose-binding protein. Significant improvement in the structures was observed in all cases when refinement was based on low-redundancy restraint data. The proposed protocol is anticipated to be particularly useful in early stages of NMR structure determination where a reliable estimate of the native fold from limited data can significantly expedite the overall process. This refinement procedure is also expected to be useful when redundant experimental data are not readily available, such as for large multidomain biomolecules and in solid-state NMR structure determination.
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http://dx.doi.org/10.1021/ja047624f | DOI Listing |
J Comput Chem
January 2025
Scuola Superiore Meridionale, Napoli, Italy.
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Dipartimento di Scienze Matematiche, Informatiche e Fisiche (DMIF), University of Udine, 33100 Udine, Italy.
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Department of Chemistry and Biochemistry, Brigham Young University, Provo, Utah 84602, United States.
Macrocyclization or stapling is an important strategy for increasing the conformational stability and target-binding affinity of peptides and proteins, especially in therapeutic contexts. Atomistic simulations of such stapled peptides and proteins could help rationalize existing experimental data and provide predictive tools for the design of new stapled peptides and proteins. Standard approaches exist for incorporating nonstandard amino acids and functional groups into the force fields required for MD simulations and have been used in the context of stapling for more than a decade.
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IBM Research, Hursley, SO21 2JN, UK.
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Dipartimento di Biotecnologie, Chimica e Farmacia, Università degli Studi di Siena, Via A. Moro 2, Siena 53100, Italy.
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