Combinatorial methods for small-molecule placement in computational enzyme design

Abstract

The incorporation of small-molecule transition state structures into protein design calculations poses special challenges because of the need to represent the added translational, rotational, and conformational freedoms within an already difficult optimization problem. Successful approaches to computational enzyme design have focused on catalytic side-chain contacts to guide placement of small molecules in active sites. We describe a process for modeling small molecules in enzyme design calculations that extends previously described methods, allowing favorable small-molecule positions and conformations to be explored simultaneously with sequence optimization. Because all current computational enzyme design methods rely heavily on sampling of possible active site geometries from discrete conformational states, we tested the effects of discretization parameters on calculation results. Rotational and translational step sizes as well as side-chain library types were varied in a series of computational tests designed to identify native-like binding contacts in three natural systems. We find that conformational parameters, especially the type of rotamer library used, significantly affect the ability of design calculations to recover native binding-site geometries. We describe the construction and use of a crystallographic conformer library and find that it more reliably captures active-site geometries than traditional rotamer libraries in the systems tested.

Fig. 1.

Contact geometries specified in small-molecule pruning step. Ranges of distances, angles, and torsions were allowed that included the crystallographic geometries. Exact geometry definitions are included in Appendix. (A) Chorismate mutase. (B) Biotin in streptavidin. (C) Triosephosphate isomerase Michaelis complex, modeled by using an approach similar to that of ref. . Asterisks indicate pseudoatoms used in geometry definitions.

Fig. 2.

Sample results from test calculations presented in Table 1. Crystallographic side chains and ligands are shown in gray. Results from three trials using different initial random rotational positions are shown in red, teal, and orange. In cases where three colors are not visible, the selected rotamers from two or more calculations were identical. Results are shown from calculations with 5° rotation and the backbone-independent conformer library. (A) Chorismate mutase. An alternate backbone position was chosen for a glutamate-hydroxyl contact in one trial (red side chain, lower left). (B) Biotin in streptavidin. Note that the biotin pentanoic acid moiety samples different conformations in the calculation and the surrounding side chains were not designed. (C) Triosephosphate isomerase.

Fig. 3.

Effect of rotational and translational step sizes. Each spot represents the average of three trials with initial random starting positions. Missing points indicate that one or more trials could not identify wild-type-like contacts or else that the calculation was prohibitively large; no calculations were performed with the 25° rotational step size. Colors indicate nonhydrogen atom rmsd, as described in Tables 1–3. (A) Chorismate mutase (minimum, 0.53 Å; maximum, 2.61 Å). (B) Streptavidin–biotin (minimum, 0.57 Å; maximum, 2.05 Å). (C) Triosephosphate isomerase (minimum, 0.44 Å; maximum, 5.64 Å).

Fig. 4.

Targeted placement procedure. For a given side-chain rotamer, small-molecule ligands are placed such that they are able to meet specified geometric criteria. This is repeated for every possible conformation of the amino acid at every designed position. Shown is a subset of orientations of a chorismate mutase transition-state structure in contact with one conformation of arginine. This figure was created with PyMOL (40).