We propose a coarse-grained modeling strategy for peptides where the effect of changes of the pH can be efficiently described. The idea is based on modeling the effects of the pH value on the main driving interactions using reference data from atomistic simulations and experimental databases and transferring its main physical features to the coarse-grained resolution according the principle of  consistency across the scales . After refining the coarse-grained model appropriately this was achieved by finding a unique set of parameters for the coarse-grained model that, when applied to peptides with different sequences and experimental properties, reproduces the experimental and atomistic data of reference. We used the such parametrized model for performing several numerical tests to check  the universality of the model . We have tried systems with rather different response to pH variations, showing a highly satisfactory performance of the model.
We propose the first, to our knowledge, coarse-grained modeling strategy for peptides where the effect of changes of the pH can be efficiently described. The idea is based on modeling the effects of the pH value on the main driving interactions . We use reference data from atomistic simulations and experimental databases and transfer its main physical features to the coarse-grained resolution according the principle of " consistency across the scales ". The coarse-grained model is refined by finding a set of parameters that, when applied to peptides with different sequences and experimental properties, reproduces the experimental and atomistic data of reference. We use the such parameterized model for performing several numerical tests to check its transferability to other systems and to prove the universality of the related modeling strategy . We have tried systems with rather different response to pH variations, showing a highly satisfactory performance of the model.
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