The pH responding proteins

The changes in the environment acidity may lead to important protein conformational changes, even unfolding. Accounting for this effect in silico is a real challenge. A recent paper from the group of D. Baker shows how by modelling the distribution of histidine residues in the network of hydrogen bonds that stabilises the fold of a protein is possible to control the response of a protein to pH changes. The paper is out in the Science magazine here. The possibility to account in simulations for pH has inspired also several computational approaches along the years. Very recently titration method combined to coarse-grained MD simulations was demonstrated to be a cheap but effective strategy in both the simulation of RNA [see Pasquali et al, Interface Focus, 2019, here] and proteins [see Barroso et al, JCTC, 2019, here].

Coarse-graining can track protein thermal stability?

Molecular simulation based on coarse-grained (CG) models is commonly used to explore large scale molecular motion or folding/unfolding processes. However, it is questionable wether these simplified models are good enough to capture the different thermal-stabilities of proteins.

Here several problems come upfront. Not all CG models are apt to monitor protein unfolding and stability. In some cases external biases are glued on top of the model in order to ensure proteins stability during a simulation; without these biases the structures just do not hold. As consequence the effect of physical/chemical perturbations to the folded structure cannot be appreciated. In other models, the folded state is encoded in native-biases -as in the Go-like model- so one wonder wether the detected unfolding paths that are key to distinguish the stabilities of homologues are "real". Finally, one should always keep in mind that a CG hamiltonian is made up of effective interactions, and, if a rigorous bottom-up graining approach is used, this implies that the model is temperature and concentration and pressure dependent. That is, the thermodynamic reference state is embedded in the interactions. This makes troubles when simulations are performed at different temperatures as in the case of the Replica Exchange Method. Despite the limitations, the possibility to use a CG model to explore the kinetic and thermodynamic stabilities of mesophilic and thermophilic proteins is rather appealing. We have tackled the problem recently, and nice results have been obtained. The paper is out here.  If you have not access, just ask!