Hi,
I am looking to benchmark Rosetta ddg / single-point mutation stability calculations against some emerging machine learning methods. There doesn't seem to be a consensus on which methods are most broadly applicable; from the literature I have read, it seems that choices of applications and flags are almost arbitrary. Aside from the 'default' protocols posted on the documentation webpages for ddg_monomer and cartesian_ddg, has anyone established a reliable workflow that could be tested outside of ProTherm mutations? In particular, are there any obvious "higher-resolution" cartesian_ddg protocols expected to outperform the aforementioned default baselines?
Thanks!
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