Computational investigation suggests that the cell adhesion sub-proteome is enriched for sites of pH-dependence and charge burial, whilst some key intracellular pathways may be shielded from pH fluctuations.

Prediction of protein pH-dependence is generally made for individual proteins or pathways, and is also increasingly being used to aid protein functional design. Combining high-throughput pKa prediction methods with AlphaFold models allows pH-dependence to be studied across a proteome. Here, two methods and a variety of features for detecting pH-dependence and charge burial that is physiologically relevant, have been applied to human proteins. Predictions are effective for a small benchmark subset of well-characterised proteins and, more broadly, identify an overlap between features associated with pH-dependence and enzymes and transporters. The most informative filters are those describing relatively buried ionisable groups, with pKas close to neutral pH and/or involvement in highly-coupled charge networks. The question is addressed of which human proteins not annotated as enzymes or transporters, are predicted to have these features of predicted pH-dependence and/or charge networking. A striking feature from gene ontology analysis of those proteins is a predicted enrichment at the cell periphery, in particular an association with cell adhesion, including protein families not currently known to exhibit pH-dependence. Gene ontology classifications that are depleted for proteins with buried charge networks and/or predicted functional pH-dependence, include some associated with ribosomal and nuclear structure. This overall result suggests a possible general resilience of some key processes to pH fluctuations, whilst not precluding specific instances where signalling pathways have evolved responses to pH changes. A drawback of the study is restriction to protomer models, thus omitting groups that mediate pH-dependence through burial at an interface. However predictions are already notable, with their details provided for experimental design.