Does the distribution of charged residues in a protein's sequence, acting through long-range electrostatic interactions, determine how cooperatively the protein folds? Desai, Cerminara, Sadqi and Muñoz (2010) showed on the downhill-folding protein BBL that ionic screening of net-repulsive electrostatics refolds the acid-denatured protein while making the unfolding transition roughly twice as broad and slowing the microsecond relaxation, implying that electrostatic repulsion preferentially destabilizes partially folded conformations and thereby enhances cooperativity. They proposed electrostatics as a general mechanism and engineering tool for tuning folding barriers and cooperativity. Fifteen years of follow-up work — an electrostatics-augmented statistical-mechanical folding model, electrostatic-potential sensing in disordered DNA-binding domains, and coarse-grained simulations of a highly charged homeodomain — has validated fragments of this picture while revealing protein-specific (even sign-opposite) salt effects, and no experimental survey across architectures, no a priori predictor from sequence and structure, and no validated charge-mutation engineering strategy exists. This statement formulates the surviving open problem: identify the molecular interactions by which electrostatics control ensemble coupling during folding, determine their generality across protein architectures, encode them minimally in coarse-grained and statistical-mechanical models, exploit them predictively to engineer folding barriers without creating non-native intermediates, and develop the measurement capability needed to quantify microscopic cooperativity in higher-barrier two-state proteins.

Background

Cooperativity is the property that makes a protein unfold as a sharp, all-or-none event: the stabilizing interactions (hydrogen bonds, hydrophobic packing, electrostatics) are coupled, so partially unfolded conformations are thermodynamically penalized. In the classical two-state picture a single large free-energy barrier, many times the thermal energy kBTk_B T, separates folded and unfolded ensembles, and that barrier — not the microscopic distribution of stabilizing energies — controls both the sharpness of the equilibrium unfolding curve and the unfolding and refolding rates. Energy-landscape theory also predicts a downhill regime in which the barrier nearly vanishes: ultrafast folders crossing marginal barriers of only a few kBTk_B T unfold through broad, non-two-state transitions in which different parts of the chain lose structure at different temperatures. Because microscopic coupling is then directly visible, such proteins are the main experimental window onto folding cooperativity.

BBL, a 40-residue helical peripheral subunit-binding domain of the Escherichia coli oxo-glutarate reductase complex, is the paradigmatic one-state downhill folder: atom-by-atom NMR showed its residues melt over a wide, graded temperature range (Sadqi, Fushman and Muñoz, 2006), and nanosecond laser temperature-jump experiments (in which a rapid heating pulse lets the relaxation kinetics of refolding/unfolding be followed on microsecond scales) resolved its one-state folding dynamics (Li, Oliva, Naganathan and Muñoz, 2009). Electrostatics is a distinctive contributor to folding energetics because charge–charge interactions act over much longer ranges — screened by ions in solution according to Debye–Hückel theory, with a screening length that shrinks as ionic strength grows — than hydrogen bonds or van der Waals contacts. Halskau et al. (2008) had shown for lysozyme and α-lactalbumin that solution electrostatics can shift thermodynamic folding barriers by large amounts.

Desai, Cerminara, Sadqi and Muñoz (2010) combined acid denaturation with salt addition on BBL. Salt refolds acid-denatured BBL through Debye–Hückel screening, showing that acid denaturation arises from generic net-charge repulsion rather than from burial of protonated groups. The pivotal observation is the converse: when electrostatics are fully screened (4 m salt), the thermal unfolding transition becomes roughly twice as broad — cooperativity decreases — and the microsecond relaxation slows about fourfold, at both neutral and acidic pH, with the melting temperature TmT_m saturating to the same value in both conditions. Since the net electrostatic interactions of BBL are repulsive (even at pH 7), the authors concluded that long-range repulsions enhance folding cooperativity by preferentially destabilizing partially folded conformations, and they proposed electrostatic modulation (pH–salt manipulation and mutagenesis of charged residues) as a general mechanism and a simple engineering tool for folding barriers and cooperativity in single-domain proteins. A parallel motivation comes from coarse-grained folding models: purely pairwise native-centric (Gō-type) models, which encode only native-contact interactions, fold without sharp transitions, and reproducing experimental cooperativity requires ad hoc many-body (for example solvation-like) terms (Kaya and Chan, 2003); how electrostatic contributions should enter such terms is unknown.

What the paper could not establish — and what remains open — is the mechanistic, general, and predictive status of this proposal, its embedding in quantitative folding models, and its deliberate use as an engineering tool.

Problem Statement

Under one overarching objective — making electrostatic control of folding cooperativity in single-domain proteins quantitative and predictive — the following linked questions, raised by Desai et al. (2010) on BBL, remain open:

(a) Mechanism. Which residue-level charge–charge and solvent-mediated interactions cause net repulsive electrostatics to preferentially destabilize partially folded conformations, sharpening the unfolding transition (and, conversely, broadening it and slowing the downhill relaxation when screened)? The mechanism has so far been inferred indirectly on one protein and explored only in isolated simulations.

(b) Generality. Do the quantitative relationships observed in BBL — ionic-strength-dependent stabilization with saturation of the melting temperature TmT_m, Debye–Hückel scaling of stability, broadening of the unfolding curve, and slowing of the microsecond relaxation upon screening — hold for single-domain proteins of different sizes, secondary-structure architectures, and distributions of charged residues, where the sign and magnitude of the effect may differ (as coarse-grained simulations of engrailed homeodomain already suggest)?

(c) Prediction and modeling. Can the effect of a protein's charge pattern and the solution ionic strength on its folding cooperativity be predicted a priori from sequence and structure; and what is the minimal, physically realistic electrostatic (and, where needed, many-body) term that coarse-grained and statistical-mechanical folding models must include to reproduce it, replacing the ad hoc many-body terms currently needed to make pairwise models cooperative?

(d) Engineering. Can pH–salt manipulation and mutagenesis of charged residues be used predictively to tune folding barriers and cooperativity of single-domain proteins without inducing non-native intermediates or ion-specific (Hofmeister) artifacts (salt effects that depend on the chemical identity of the ion rather than only on its charge-screening strength)?

(e) Enabling measurement. What experimental or theoretical advance would make intrinsic (microscopic) cooperativity measurable in higher-barrier, two-state proteins, where conventional thermodynamic observables cannot resolve ensemble coupling — a prerequisite for testing (b)–(d) beyond the downhill regime?

These components are jointly linked rather than independent: (a) supplies the mechanism that (c) must encode, (b) delimits the mechanism's domain of validity, (d) is its deliberate application, and (e) extends the testing of all components beyond the marginal-barrier folders where cooperativity is currently observable. Each of (a)–(e) is nevertheless posed as a separate question rather than a corollary of the others.

References

  1. Desai, T. M., Cerminara, M., Sadqi, M., & Muñoz, V. (2010). The effect of electrostatics on the marginal cooperativity of an ultrafast folding protein. Journal of Biological Chemistry, 285(45), 34549–34556. DOI: 10.1074/jbc.M110.154021. https://doi.org/10.1074/jbc.M110.154021 (source paper)
  2. Sadqi, M., Fushman, D., & Muñoz, V. (2006). Atom-by-atom analysis of global downhill protein folding. Nature, 442(7100), 317–321. DOI: 10.1038/nature04859. https://doi.org/10.1038/nature04859
  3. Li, P., Oliva, F. Y., Naganathan, A. N., & Muñoz, V. (2009). Dynamics of one-state downhill protein folding. Proceedings of the National Academy of Sciences USA, 106(1), 103–108. DOI: 10.1073/pnas.0802986106. https://doi.org/10.1073/pnas.0802986106
  4. Halskau, Ø., Pérez-Jiménez, R., Ibarra-Molero, B., Underhaug, J., Muñoz, V., Martínez, A., & Sánchez-Ruiz, J. M. (2008). Large-scale modulation of thermodynamic protein folding barriers linked to electrostatics. Proceedings of the National Academy of Sciences USA, 105(25), 8625–8630. DOI: 10.1073/pnas.0709881105. https://doi.org/10.1073/pnas.0709881105
  5. Kaya, H., & Chan, H. S. (2003). Solvation effects and driving forces for protein thermodynamic and kinetic cooperativity: how adequate is native-centric topological modeling? Journal of Molecular Biology, 326(3), 911–931. DOI: 10.1016/S0022-2836(02)01434-1. https://doi.org/10.1016/S0022-2836(02)01434-1
  6. Naganathan, A. N. (2012). Predictions from an Ising-like statistical mechanical model on the dynamic and thermodynamic effects of protein surface electrostatics. Journal of Chemical Theory and Computation, 8(11), 4646–4656. DOI: 10.1021/ct300676w. https://doi.org/10.1021/ct300676w
  7. Dasgupta, A., & Udgaonkar, J. B. (2012). Four-state folding of an SH3 domain: salt-induced modulation of the stabilities of the intermediates and native state. Biochemistry, 51(23), 4723–4734. DOI: 10.1021/bi300223b. https://doi.org/10.1021/bi300223b
  8. Munshi, S., Gopi, S., Asampille, G., Subramanian, S., Campos, L. A., Atreya, H. S., & Naganathan, A. N. (2018). Tunable order–disorder continuum in protein–DNA interactions. Nucleic Acids Research, 46(17), 8700–8709. DOI: 10.1093/nar/gky732. https://doi.org/10.1093/nar/gky732
  9. Munshi, S., Subramanian, S., Ramesh, S., Golla, H., Kalivarathan, D., Kulkarni, M., Campos, L. A., Sekhar, A., & Naganathan, A. N. (2019). Engineering order and cooperativity in a disordered protein. Biochemistry, 58(19), 2389–2397. DOI: 10.1021/acs.biochem.9b00182. https://doi.org/10.1021/acs.biochem.9b00182
  10. Sanchez-Medina, C., Sekhar, A., Vallurupalli, P., Cerminara, M., Muñoz, V., & Kay, L. E. (2014). Probing the free energy landscape of the fast-folding gpW protein by relaxation dispersion NMR. Journal of the American Chemical Society, 136(20), 7444–7451. DOI: 10.1021/ja502705y. https://doi.org/10.1021/ja502705y
  11. Szczepaniak, M., Iglesias-Bexiga, M., Cerminara, M., Sadqi, M., Sánchez de Medina, C., Martínez, J. C., Luque, I., & Muñoz, V. (2019). Ultrafast folding kinetics of WW domains reveal how the amino acid sequence determines the speed limit to protein folding. Proceedings of the National Academy of Sciences USA, 116(17), 8137–8142. DOI: 10.1073/pnas.1900203116. https://doi.org/10.1073/pnas.1900203116
  12. Zhou, H.-X., & Pang, X. (2018). Electrostatic interactions in protein structure, folding, binding, and condensation. Chemical Reviews, 118(4), 1691–1741. DOI: 10.1021/acs.chemrev.7b00305. https://doi.org/10.1021/acs.chemrev.7b00305
  13. Rajendran, D., Goyal, S., Chaurasiya, D. K., & Naganathan, A. N. (2024). Determinants of unfolding cooperativity and binding are decoupled in a DNA binding domain. Journal of Physical Chemistry B, 128(39), 9341–9352. DOI: 10.1021/acs.jpcb.4c03895. https://doi.org/10.1021/acs.jpcb.4c03895
  14. Xu, C., & Chu, X. (2024). Dissecting the roles of electrostatic interactions in modulating the folding stability and cooperativity of engrailed homeodomain. Biochemistry, 63(24), 3261–3272. DOI: 10.1021/acs.biochem.4c00645. https://doi.org/10.1021/acs.biochem.4c00645