Size-Dependent Relationships between Protein Stability and Thermal Unfolding Temperature Have Important Implications for Analysis of Protein Energetics and High-Throughput Assays of Protein–Ligand Interactions

Abstract

Changes in protein stability are commonly reported as changes in the melting temperature, Δ T, or as changes in unfolding free energy at a particular temperature, ΔΔ G°. Using data for 866 mutants from 16 proteins, we examine the relationship between ΔΔ G° and Δ T. A linear relationship is observed for each protein. The slopes of the plots of Δ T vs ΔΔ G° for different proteins scale as N, where N is the number of residues in the protein. Thus, a given change in Δ G° causes a much larger change in T for a small protein relative to the effect observed for a large protein. The analysis suggests that reasonable estimates of ΔΔ G° for a mutant can be obtained by interpolating measured values of T. The relationship between ΔΔ G° and Δ T has implications for the design and interpretation of high-throughput assays of protein-ligand binding. So-called thermal shift assays rely upon the increase in stability which results from ligand binding to the folded state. Quantitative relationships are derived which show that the observed thermal shift, Δ T, scales as N. Hence, thermal shift assays are considerably less sensitive for ligand binding to larger proteins.

DynaMut2: Assessing changes in stability and flexibility upon single and multiple point missense mutations

“…DynaMut2 achieved a Pearson's correlation of 0.52, comparable with the best‐performing methods (Table 2) and significantly better than MUpro 50 . Although not directly comparable, as there is a correlation between changes upon mutation in stability (Δ G ) and thermal stability ( T m ), 51 the performance of DynaMut2 on predicting changes in melting temperature was assessed using the blind test set S173. Results were stratified by protein structure and summarized in Table S11.…”

Quantification of biases in predictions of protein stability changes upon mutations

“…They are often defined either at room temperature T r ¼ 25 C or at the melting temperature T m of the wild-type protein. Sometimes, they are not directly measured but derived from DT m measures in differential scanning calorimetry (DSC) experiments, by utilizing the fact that these two quantities are correlated, even though this is only true in a first approximation [see Pucci et al (2016) and Watson and Raleigh (2017) for further details]. All these dependencies and approximations make the datasets of the experimentally annotated mutations quite noisy, which in turn impacts the accuracy of the predictors that are trained on them.…”

General method to stabilize mesophilic proteins in hyperthermal water

“…Most organisms only survive at low or moderate temperatures in aqueous environment, as these temperatures are the optimal working conditions for mesophilic proteins. High temperatures can induce denaturation and aggregation of mesophilic proteins ( Chang and Bowie, 2014 ; Leuenberger et al., 2017 ; Mahler et al., 2009 ; Watson et al., 2018 ), limiting the boundary of their functions. Stabilizing proteins out of their native physiological environments would generate extraordinary achievements.…”