A generic program for multistate protein design

Abstract

Some protein design tasks cannot be modeled by the traditional single state design strategy of finding a sequence that is optimal for a single fixed backbone. Such cases require multistate design, where a single sequence is threaded onto multiple backbones (states) and evaluated for its strengths and weaknesses on each backbone. For example, to design a protein that can switch between two specific conformations, it is necessary to to find a sequence that is compatible with both backbone conformations. We present in this paper a generic implementation of multistate design that is suited for a wide range of protein design tasks and demonstrate in silico its capabilities at two design tasks: one of redesigning an obligate homodimer into an obligate heterodimer such that the new monomers would not homodimerize, and one of redesigning a promiscuous interface to bind to only a single partner and to no longer bind the rest of its partners. Both tasks contained negative design in that multistate design was asked to find sequences that would produce high energies for several of the states being modeled. Success at negative design was assessed by computationally redocking the undesired protein-pair interactions; we found that multistate design's accuracy improved as the diversity of conformations for the undesired protein-pair interactions increased. The paper concludes with a discussion of the pitfalls of negative design, which has proven considerably more challenging than positive design.

Figure 1. Iterative multistate design.

This flow chart summarizes the way we used rigid-body docking to expand the set of conformations that we designed against. A “round” of multistate design is a single execution of the multistate design executable with a given set of input positive and negative states. The first round begins using the experimentally determined structure(s) (either from x-ray crystallography or NMR) for both positive and negative states; subsequent rounds include low-energy conformations for the undesired interactions in the set of negative states generated by redocking the models for those interactions generated by prior rounds of multistate design.

Figure 2. Iterative expansion of the negative state set.

A) the original 1USM homodimeric complex used as both the positive and negative states in the first round of multistate design, B) the thirteen negative states used in the second round, C) the forty one negative states used in the third round, and D) the sixty seven negative states used in the fourth round.

Figure 3. Binding energies differences for the heterodimerization redesign task.

A) The distribution of s for the homodimers vs the heterodimers comparing single state design (SSD) against multistate design (MSD). Binding energies were computed by redocking each of the complexes, and computing the difference between the lowest-energy from docking and the energies of the unbound monomers after their interface residues were allowed to pack. B) Histogram of the homodimer binding energy errors for each of the four rounds of multistate design. Errors were measured as the difference in the binding energies as computed by multistate design and as computed after redocking.

Figure 4. Binding energy differences for the orthogonal interface redesign task.

Binding energy differences between the positive state AB (Ral/RalBP1) and negative states AC (RalA/Sec5) and AD(RalA/Exo84) following multistate design (MSD) and single state design (SSD). Binding energy differences between the native AB and AC, and AB and AD states (black) are shown for reference. Consecutive rounds of MSD (red, blue, and purple) on protein A residues, listed in Methods, decrease the binding energy to C and D by a larger magnitude than SSD. Two different methods of SSD are shown: SSD 1 (green) allows design on the same residues as MSD, and SSD 2 (orange) allows design on residues that are at the AB interface. Neither of the SSD methods explicitly disfavor binding to C or D. AB binding energy maintained, in all cases, between −22.0 and −25.0 REU.

Figure 5. Sequence propensity of RalA residues from multistate-design.

Sequence logo of the designs produced by multistate design in setup-scheme 2 for the RalA orthogonal interface redesign task. Positions 50, 67, and 16 showed preferences for amino acids that stabilized the RalA monomer or that stabilized the Ral/RalBP1 complex. Positions 36 and 52 showed preferences for amino acids that destabilized the RalA/Sec5 interaction; positions 14, 77, 78, and 81 showed preferences for amino acids that destabilized the RalA/Exo84 interface. Positions 47, 73, 74 and 75 displayed no clear preferences, except for non-wildtype amino acids, as the native amino acids formed favorable contacts with either Sec5 or Exo84.

Figure 6. Curious cases from negative design.

A) Placing both F52 and W63 on RalA (green) destabilizes its interaction with Sec5 (magenta). In the docked conformation, the F52 and W63 rotamers collide in the least-awful-rotamer placement available. In the unbound state (orange) these residues relax out of collision. W63 disrupts binding with Sec5 through F52, but neither residue disrupts binding on its own. Unfortunately, W63 is incompatible with the RalA backbones from the crystal structures, though it is compatible with the RalB backbone in the NMR structure. Here, a discrepancy between the backbone conformations of Ral in its various states lead to a questionable design. B) The Missing Rotamer Problem encountered while trying to redesign chain E of human uracil-DNA glycosylase bound to a protein inhibitor (PDB ID: 1UGH). The mutation F267 on chain E (green) is consistently chosen by multistate design when optimizing for binding energy, not because F267 forms favorable contacts with its (polar) neighbors on chain I (cyan), but because the rotamer it finds in the bound state is absent from the set of rotamers for the unbound state; the best available rotamer for the unbound state (orange) has a high-energy collision with the C atom on residue 279. The green rotamer collides with the chain E backbone (with an energy 5.1 REU) and, in the unbound, is pruned by Rosetta's bump check machinery (threshold of 5.0 REU); however, in the bound state, slightly favorable interactions with the chain I backbone rescue this rotamer by pushing its energy just beneath the bump-check threshold (4.9 REU). Placing phenylalanine at 267 and anything besides glycine at 279 produces a large energy difference in the bound and unbound states which masquerades as an excellent binding energy.

Figure 7. Packing failures from the (negative state) monomers of 1USM.

A) Due to the nature of the BMEC+sPR algorithm, it systematically failed to relieve the Y28/T44 collision in the presence of M46. The colliding rotamers are shown in green; the collision-free placement is shown in orange. The collision is highlighted with a red circle. When multistate design encountered these three amino acids, the bound state produced a decent energy, the unbound state produced a high energy, and the strength of the apparent binding energy caused the fitness to be exceptional. Since this is a systematic failure, all the sequences in the genetic algorithm's pool at the end of the design trajectory that produced this sequence contained these three amino acids and their unrelieved collision. Fortunately, not all multistate design trajectories encountered these three amino acids together. B) The Multicool Annealer also fails randomly; in one multistate-design trajectory, a single packing failure left an unresolved collision (red circle) between E24 and the backbone of D20 (green sidechains) that was in fact resolvable (orange sidechains). This collision made this sequence appear to have the best fitness. Since this was a random and not a systematic failure, none of the other sequences in the genetic algorithm's pool exhibited this flawed packing.