Force-Field Benchmarking by Alternatives: A Systematic Study of Ten Small α- and β-Proteins

Predicting protein structure from sequence is a central challenge of biochemistry, yet different force fields feature distinct structural biases that are hard to quantify, preventing clear assessment of results. Since structural transitions occur on milliseconds to seconds, sampling is out of reach in almost all routine studies, we inherently rely on local sampled structures, and benchmarks have emphasized the ability to reproduce these local structures. Here we approach the force field bias problem in a different way, via alternatives, by revisiting the old question: How unique is the sequence-structure relationship when studied computationally? To circumvent the sampling problem, the system-bias (specific structure choices affect apparent force field structural preference) and the complexity of tertiary structure, we studied ten small - and {beta}-proteins (20-35 amino acids) with one helix or sheet. For each of the ten sequences, we then designed alternative {beta}- or -structures and subjected all 20 proteins to molecular dynamics simulations. We apply this "alternative structure" benchmark to five of the best modern force fields: Amber ff99SB-ILDN, Amber ff99SB*-ILDN, CHARMM22*, CHARMM36, and GROMOS54A8. Surprisingly, we find that all sequences with reported {beta}-structures also feature stable native-like -structures with all five force fields. In contrast, only the alternative {beta}-1T5Q and to some extent {beta}-1CQ0 and {beta}-1V1D resembled native {beta}-proteins. With full phase space sampling being impossible in almost all cases, our benchmark by alternatives, which samples another local part of phase space in direct comparison, is a useful complement to millisecond benchmarks when these become more common.