Alteration of enzyme specificity by computational loop remodeling and design

Abstract

Altering the specificity of an enzyme requires precise positioning of side-chain functional groups that interact with the modified groups of the new substrate. This requires not only sequence changes that introduce the new functional groups but also sequence changes that remodel the structure of the protein backbone so that the functional groups are properly positioned. We describe a computational design method for introducing specific enzyme-substrate interactions by directed remodeling of loops near the active site. Benchmark tests on 8 native protein-ligand complexes show that the method can recover native loop lengths and, often, native loop conformations. We then use the method to redesign a critical loop in human guanine deaminase such that a key side-chain interaction is made with the substrate ammelide. The redesigned enzyme is 100-fold more active on ammelide and 2.5e4-fold less active on guanine than wild-type enzyme: The net change in specificity is 2.5e6-fold. The structure of the designed protein was confirmed by X-ray crystallographic analysis: The remodeled loop adopts a conformation that is within 1-Å C␣ RMSD of the computational model. computational protein design ͉ loop modeling C omputational protein design methodology has been used to optimize properties such as protein stability (1, 2) and to introduce functions such as binding of small molecules (3), proteins (4), and nucleic acids (5), as well as enzymatic activity (6, 7). In most of these studies, the implicit assumption that the structure of the polypeptide backbone would remain largely fixed despite mutations of amino acid side chains was made for the sake of computational tractability.Explicit remodeling of the polypeptide backbone makes possible further optimization of these and other structural or functional properties. The set of combinations of protein sequences and structures is considerably larger when backbone flexibility is allowed and is likely to contain conformations that optimize a desired property to a greater degree than the original scaffold. This is illustrated by the backbone shifts that accompany functional divergence in natural protein evolution. Previous studies have achieved functional changes by backbone alteration, but relied on grafting methods that are restricted to sequences of known structure and function (8-10), which may be suboptimal with respect to the desired property.De novo protein structure prediction methods are well suited for sampling novel backbone conformations (11). These methods have recently been extended to focus sampling on conformations that satisfy specific positional constraints (12, 13). Computational design algorithms that iterate between sequence design and backbone optimization using structure-prediction methods have been used to design previously unobserved protein fold and loop conformations (2, 14), but have not yet been applied to achieving functional changes such as alteration of an enzyme's substrate specificity.We have developed a computational design algorithm that uses constr...

Bacterial Ammeline Metabolism via Guanine Deaminase

“…The enzymes were expressed as His-tagged proteins and puri- fied to homogeneity using a nickel affinity column. The activities of the enzymes with guanine were comparable to previously reported values (18,21). Measured activities with ammeline were 73 and 57 nmol per min per mg for the B. japonicum USDA 110 and human guanine deaminases, respectively (Table 1).…”

“…However, B. japonicum USDA 110, from which the guanine deaminase catalyzes ammeline deamination in vitro, grew on ammeline as the sole nitrogen source (data not shown). Human guanine deaminase was found to be inactive with ammeline but was engineered for activity with this new substrate (21). The engineered human guanine deaminase had a reported specific activity, at saturating ammelide concentration, of 0.25 nmol per min per mg of protein, which is 2 orders of magnitude less than the activity of the wild-type human enzyme shown here with ammeline.…”

Computational design of a red fluorophore ligase for site-specific protein labeling in living cells

“…First, the redesign from lipoic acid recognition to resorufin recognition required a larger change in size, shape, and location of the binding pocket than in previous enzyme substrate specificity redesigns and began with a wild-type template that had no detectable activity for resorufin ligation. Despite this, our design lost less than 10 2 -fold catalytic efficiency compared wild-type activity, whereas a previous redesign of guanine deaminase lost ∼10 7 -fold catalytic efficiency (18). This enabled our designed ligase to have practical utility without the need for further directed evolution of catalytic efficiency.…”

Synthetic beta-solenoid proteins with the fragment-free computational design of a beta-hairpin extension

“…However, it is likely that most arbitrary backbone conformations are not designable. The incorporation of backbone flexibility in protein design has been recognized as a key challenge in computational protein design (30), with current methods typically reusing backbone fragments from other known protein structures (31,32). Recently, we have developed algorithms to sample loop conformations rapidly using a coarse-grained C α model (33) and to reconstruct proteins backbones accurately (34) as part of an approach that often gave subangstrom root-mean-square deviation (RMSD) loop predictions (35).…”