Evaluation of atomic level mean force potentials via inverse folding and inverse refinement of protein structures:...

Two atomic level knowledge-based mean force interaction potentials (KBPs), a centrosymmetric burial position term and a long-range pairwise term, were developed. These were tested by comparing multiple configurations of three structurally unrelated proteins and were found successfully to (i) discriminate native state proteins from grossly misfolded structures in inverse folding tests, (ii) rank identify, using the KBP energy/r.m.s.d. correlation, native from progressively less native-like (compact and dilated) structures generated via molecular dynamics sampling, providing an energy gradient sloping from partially unfolded structures towards near-native states in inverse refinement tests (iii) smooth the overall potential energy surface in the region of dilated non-native structures by countering local minima of the in vacuo molecular mechanical potential and (iv) serve as a local minimum detector during simulated temperature quenching studies. These atomic KBPs discriminated native from non-native structures with greater overall sensitivity than did either a residue-based pairwise interaction potential or an effective solvation potential based on atomic contact volume occupancy. The KBPs presented here are immediately useful as a tool for selecting "good refinement candidates' from an arbitrary collection of protein configurations and may play a role in dynamic computational protein refinement.