A Self Consistent Approach to Rotamer and Protonation State Assignments (RAPA): Moving Beyond Single Protein Configurations

There are currently over 160,000 protein crystal structures obtained by X-ray diffraction with resolutions of 1.5Å or greater in the Protein Data Bank. At these resolutions hydrogen atoms do not resolve and heavy atoms such as oxygen, carbon, and nitrogen are indistinguishable. This leads to ambiguity in the rotamer and protonation states of multiple amino acids, notably asparagine, glutamine, histidine, serine, tyrosine, and threonine. When the rotamer and protonation states of these residues changes, so too does the electrochemical surface of a binding site. A variety of computational tools have been developed to assign these states for these residues based on a crystal protein structure by evaluating the possible states and typically deciding on one single state for each residue. We posit that multiple rotamer and protonation states of residues are consistent with the resolved structure of the proteins and introduce a protonation and rotamer assignment tool that identifies an ensemble of rotamer and protonation states that are consistent with the X-ray scattering data of the protein. Here, we present a Rotamer and Protonation state Assignment (RAPA) tool that analyzes local hydrogen bonding environments in the resolved structures of proteins and identifies a set of unique rotamer and protonation states that are energetically consistent with the crystal structure. We evaluate all RAPA predicted states in unrestrained molecular dynamics simulations and find that there are multiple configurations for each protein which match the X-ray results with RMSDs of less than 1.0Å for the atoms with the lowest 90% B-factors. We find that for most protein systems (62 of 77) there are 8 or fewer possible states suggesting that there is no combinatorial explosion of accessible configurations for a majority of proteins. This suggests that investigating all energetically accessible rotamer and protonation states for most proteins is computationally feasible and that the selection of single states is arbitrary.