You are here

Benchmarking Rosetta DDG Methods

1 post / 0 new
Benchmarking Rosetta DDG Methods


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?


Post Situation: 
Fri, 2022-07-29 09:55