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Biomedical subjects

Stephen L Mayo

Publications and source records attributed to Stephen L Mayo.

At least 19 recordsLinked to original sources
PubMed2006

Computationally designed libraries of fluorescent proteins evaluated by preservation and diversity of function.

To determine which of seven library design algorithms best introduces new protein function without destroying it altogether, seven combinatorial libraries of green fluorescent protein variants were designed and synthesized. Each was evaluated by distributions of emission intensity and color compiled from measurements made in vivo. Additional comparisons were made with a library constructed by error-prone PCR. Among the designed libraries, fluorescent function was preserved for the greatest fraction of samples in a library designed by using a structure-based computational method developed and described here. A trend was observed toward greater diversity of color in designed libraries that better preserved fluorescence. Contrary to trends observed among libraries constructed by error-prone PCR, preservation of function was observed to increase with a library's average mutation level among the four libraries designed with structure-based computational methods.

Combinatorial Chemistry Techniques↗
PubMed2006

Blue fluorescent proteins with enhanced brightness and photostability from a structurally targeted library.

The utility of blue fluorescent protein (BFP) has been limited by its low quantum yield and rapid photobleaching. A library targeting residues neighboring the chromophore yielded a variant with enhanced quantum yield (0.55 versus 0.34), reduced pH sensitivity and a 40-fold increase in photobleaching half-life. This BFP, named Azurite, is well expressed in bacterial and mammalian cells and extends the palette of fluorescent proteins that can be used for imaging.

Flow Cytometry↗
PubMed2006

Combinatorial methods for small-molecule placement in computational enzyme design.

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.

Catalytic Domain↗
PubMed2006

Ca2+/calmodulin-dependent protein kinase II (CaMKII) is activated by calmodulin with two bound calciums.

Changes in synaptic strength that underlie memory formation in the CNS are initiated by pulses of Ca2+ flowing through NMDA-type glutamate receptors into postsynaptic spines. Differences in the duration and size of the pulses determine whether a synapse is potentiated or depressed after repetitive synaptic activity. Calmodulin (CaM) is a major Ca2+ effector protein that binds up to four Ca2+ ions. CaM with bound Ca2+ can activate at least six signaling enzymes in the spine. In fluctuating cytosolic Ca2+, a large fraction of free CaM is bound to fewer than four Ca2+ ions. Binding to targets increases the affinity of CaM's remaining Ca2+-binding sites. Thus, initial binding of CaM to a target may depend on the target's affinity for CaM with only one or two bound Ca2+ ions. To study CaM-dependent signaling in the spine, we designed mutant CaMs that bind Ca2+ only at the two N-terminal or two C-terminal sites by using computationally designed mutations to stabilize the inactivated Ca2+-binding domains in the "closed" Ca2+-free conformation. We have measured their interactions with CaMKII, a major Ca2+/CaM target that mediates initiation of long-term potentiation. We show that CaM with two Ca2+ ions bound in its C-terminal lobe not only binds to CaMKII with low micromolar affinity but also partially activates kinase activity. Our results support the idea that competition for binding of CaM with two bound Ca2+ ions may influence significantly the outcome of local Ca2+ signaling in spines and, perhaps, in other signaling pathways.

Calcium↗
PubMed2006

Dramatic performance enhancements for the FASTER optimization algorithm.

FASTER is a combinatorial optimization algorithm useful for finding low-energy side-chain configurations in side-chain placement and protein design calculations. We present two simple enhancements to FASTER that together improve the computational efficiency of these calculations by as much as two orders of magnitude with no loss of accuracy. Our results highlight the importance of choosing appropriate initial configurations, and show that efficiency can be improved by stringently limiting the number of positions that are allowed to relax in response to a perturbation. The changes we describe improve the quality of solutions found for large-scale designs, and allow them to be found in hours rather than days. The improved FASTER algorithm finds low-energy solutions more efficiently than common optimization schemes based on the dead-end elimination theorem and Monte Carlo. These advances have prompted investigations into new methods for force field parameterization and multiple state design.

Algorithms↗
PubMed2006

Simple electrostatic model improves designed protein sequences.

Electrostatic interactions are important for both protein stability and function, including binding and catalysis. As protein design moves into these areas, an accurate description of electrostatic energy becomes necessary. Here, we show that a simple distance-dependent Coulombic function parameterized by a comparison to Poisson-Boltzmann calculations is able to capture some of these electrostatic interactions. Specifically, all three helix N-capping interactions in the engrailed homeodomain fold are recovered using the newly parameterized model. The stability of this designed protein is similar to a protein forced by sequence restriction to have beneficial electrostatic interactions.

Amino Acid Sequence↗
PubMed2006

Generation and analysis of proline mutants in protein G.

The pyrrolidine ring of the amino acid proline reduces the conformational freedom of the protein backbone in its unfolded form and thus enhances protein stability. The strategy of inserting proline into regions of the protein where it does not perturb the structure has been utilized to stabilize many different proteins including enzymes. However, most of these efforts have been based on trial and error, rather than rational design. Here, we try to understand proline's effect on protein stability by introducing proline mutations into various regions of the B1 domain of Streptococcal protein G. We also applied the Optimization of Rotamers By Iterative Techniques computational protein design program, using two different solvation models, to determine the extent to which it could predict the stabilizing and destabilizing effects of prolines. Use of a surface area dependent solvation model resulted in a modest correlation between the experimental free energy of folding and computed energies; on the other hand, use of a Gaussian solvent exclusion model led to significant positive correlation. Including a backbone conformational entropy term to the computational energies increases the statistical significance of the correlation between the experimental stabilities and both solvation models.

Mutation↗
PubMed2006

A search algorithm for fixed-composition protein design.

We present a computational protein design algorithm for finding low-energy sequences of fixed amino acid composition. The search algorithms used in protein design typically do not restrict amino acid composition. However, the random energy model of Shakhnovich suggests that the use of fixed-composition sequences may circumvent defects in the modeling of the denatured state. Our algorithm, FC_FASTER, links fixed-composition versions of Monte Carlo and the FASTER algorithm. As proof of principle, FC_FASTER was tested on an experimentally validated, full-sequence design of the beta1 domain of protein G. For the wild-type composition, FC_FASTER found a lower energy sequence than the experimentally validated sequence. Also, for a different composition, FC_FASTER found the hypothetical lowest-energy sequence in 14 out of 32 trials.

Algorithms↗
PubMed2005

Electrostatics in computational protein design.

Catalytic activity and protein-protein recognition have proven to be significant challenges for computational protein design. Electrostatic interactions are crucial for these and other protein functions, and therefore accurate modeling of electrostatics is necessary for successfully advancing protein design into the realm of protein function. This review focuses on recent progress in modeling electrostatic interactions in computational protein design, with particular emphasis on continuum models.

Computer Simulation↗
PubMed2005

Hydroxyl groups in the (beta)beta sandwich of metallo-beta-lactamases favor enzyme activity: a computational protein design study.

Metallo-beta-lactamases challenge antimicrobial therapies by their ability to hydrolyze and inactivate a broad spectrum of beta-lactam antibiotics. The potential of these enzymes to acquire enhanced catalytic efficiency through mutation is of great concern. Here, we explore the potential of computational protein design to predict mutants of the imipenemase IMP-1 that modulate the catalytic efficiency of the enzyme against a range of substrates. Focusing on the four amino acid positions 69, 121, 218, and 262, we carried out a number of design calculations. Two mutant enzymes were predicted: the single mutant S262A and the double mutant F218Y-S262A. Compared to IMP-1, the single mutant (S262A) results in the loss of a hydroxyl group and the double mutant (F218Y-S262A) results in a hydroxyl transfer from position 262 to position 218. The presence of both hydroxyl groups at positions 218 and 262 was tested by examining the mutant F218Y. Kinetic constants of IMP-1, the two computationally designed mutants (S262A and F218Y-S262A), and the hydroxyl addition mutant (F218Y) were determined with seven substrates. Catalytic efficiencies are highest for the enzyme with both hydroxyl groups (F218Y) and lowest for the enzyme lacking both hydroxyl groups (S262A). The catalytic efficiencies of the two enzymes with one hydroxyl group each are intermediate, with the F218Y-S262A double mutant exhibiting enhanced hydrolysis of nitrocefin, cephalothin, and cefotaxime relative to IMP-1.

Bacteroides fragilis↗
PubMed2005

One- and two-body decomposable Poisson-Boltzmann methods for protein design calculations.

Successfully modeling electrostatic interactions is one of the key factors required for the computational design of proteins with desired physical, chemical, and biological properties. In this paper, we present formulations of the finite difference Poisson-Boltzmann (FDPB) model that are pairwise decomposable by side chain. These methods use reduced representations of the protein structure based on the backbone and one or two side chains in order to approximate the dielectric environment in and around the protein. For the desolvation of polar side chains, the two-body model has a 0.64 kcal/mol RMSD compared to FDPB calculations performed using the full representation of the protein structure. Screened Coulombic interaction energies between side chains are approximated with an RMSD of 0.13 kcal/mol. The methods presented here are compatible with the computational demands of protein design calculations and produce energies that are very similar to the results of traditional FDPB calculations.

Poisson Distribution↗
PubMed2005

Dioxane contributes to the altered conformation and oligomerization state of a designed engrailed homeodomain variant.

Our goal was to compute a stable, full-sequence design of the Drosophila melanogaster engrailed homeodomain. Thermal and chemical denaturation data indicated the design was significantly more stable than was the wild-type protein. The data were also nearly identical to those for a similar, later full-sequence design, which was shown by NMR to adopt the homeodomain fold: a three-helix, globular monomer. However, a 1.65 A crystal structure of the design described here turned out to be of a completely different fold: a four-helix, rodlike tetramer. The crystallization conditions included approximately 25% dioxane, and subsequent experiments by circular dichroism and sedimentation velocity analytical ultracentrifugation indicated that dioxane increases the helicity and oligomerization state of the designed protein. We attribute at least part of the discrepancy between the target fold and the crystal structure to the presence of a high concentration of dioxane.

Animals↗
PubMed2005

Adaptation of a fast Fourier transform-based docking algorithm for protein design.

Designing proteins with novel protein/protein binding properties can be achieved by combining the tools that have been developed independently for protein docking and protein design. We describe here the sequence-independent generation of protein dimer orientations by protein docking for use as scaffolds in protein sequence design algorithms. To dock monomers into sequence-independent dimer conformations, we use a reduced representation in which the side chains are approximated by spheres with atomic radii derived from known C2 symmetry-related homodimers. The interfaces of C2-related homodimers are usually more hydrophobic and protein core-like than the interfaces of heterodimers; we parameterize the radii for docking against this feature to capture and recreate the spatial characteristics of a hydrophobic interface. A fast Fourier transform-based geometric recognition algorithm is used for docking the reduced representation protein models. The resulting docking algorithm successfully predicted the wild-type homodimer orientations in 65 out of 121 dimer test cases. The success rate increases to approximately 70% for the subset of molecules with large surface area burial in the interface relative to their chain length. Forty-five of the predictions exhibited less than 1 A C(alpha) RMSD compared to the native X-ray structures. The reduced protein representation therefore appears to be a reasonable approximation and can be used to position protein backbones in plausible orientations for homodimer design.

Algorithms↗
PubMed2005

Impact of remote mutations on metallo-beta-lactamase substrate specificity: implications for the evolution of antibiotic resistance.

Metallo-beta-lactamases have raised concerns due to their ability to hydrolyze a broad spectrum of beta-lactam antibiotics. The G262S point mutation distinguishing the metallo-beta-lactamase IMP-1 from IMP-6 has no effect on the hydrolysis of the drugs cephalothin and cefotaxime, but significantly improves catalytic efficiency toward cephaloridine, ceftazidime, benzylpenicillin, ampicillin, and imipenem. This change in specificity occurs even though residue 262 is remote from the active site. We investigated the substrate specificities of five other point mutants resulting from single-nucleotide substitutions at positions near residue 262: G262A, G262V, S121G, F218Y, and F218I. The results suggest two types of substrates: type I (nitrocefin, cephalothin, and cefotaxime), which are converted equally well by IMP-6, IMP-1, and G262A, but even more efficiently by the other mutants, and type II (ceftazidime, benzylpenicillin, ampicillin, and imipenem), which are hydrolyzed much less efficiently by all the mutants. G262V, S121G, F218Y, and F218I improve conversion of type I substrates, whereas G262A and IMP-1 improve conversion of type II substrates, indicating two distinct evolutionary adaptations from IMP-6. Substrate structure may explain the catalytic efficiencies observed. Type I substrates have R2 electron donors, which may stabilize the substrate intermediate in the binding pocket. In contrast, the absence of these stabilizing interactions with type II substrates may result in poor conversion. This observation may assist future drug design. As the G262A and F218Y mutants confer effective resistance to Escherichia coli BL21(DE3) cells (high minimal inhibitory concentrations), they are likely to evolve naturally.

Biological Evolution↗
PubMed2004

Preprocessing of rotamers for protein design calculations.

We have developed a process that significantly reduces the number of rotamers in computational protein design calculations. This process, which we call Vegas, results in dramatic computational performance increases when used with algorithms based on the dead-end elimination (DEE) theorem. Vegas estimates the energy of each rotamer at each position by fixing each rotamer in turn and utilizing various search algorithms to optimize the remaining positions. Algorithms used for this context specific optimization can include Monte Carlo, self-consistent mean field, and the evaluation of an expression that generates a lower bound energy for the fixed rotamer. Rotamers with energies above a user-defined cutoff value are eliminated. We found that using Vegas to preprocess rotamers significantly reduced the calculation time of subsequent DEE-based algorithms while retaining the global minimum energy conformation. For a full boundary design of a 51 amino acid fragment of engrailed homeodomain, the total calculation time was reduced by 12-fold.

Algorithms↗
PubMed2004

A designed protein interface that blocks fibril formation.

Protein fibril formation is implicated in many diseases, and therefore much effort has been focused toward the development of inhibitors of this process. In a previous project, a monomeric protein was computationally engineered to bind itself and form a heterodimer complex following interfacial redesign. One of the protein monomers, termed monomer-B, was unintentionally destabilized and shown to form macroscopic fibrils. Interestingly, in the presence of the designed binding partner, fibril formation was blocked. Here we describe the complete characterization of the amyloid properties of monomer-B and the inhibition of fiber formation by the designed binding partner, monomer-A. Both proteins are mutants of the betal domain of streptococcal protein-G. The free monomer-B protein forms amyloid-type fibrils, as determined by transmission electron microscopy and the change in fluorescence of Thioflavin T, an amyloid-specific dye. Fibril formation kinetics are influenced by pH, protein concentration, and seeding with preformed fibrils. Under all conditions tested, monomer-A was able to inhibit the formation of monomer-B fibrils. This inhibition is specific to the engineered interaction, as incubation of monomer-B with wild-type protein-G (a structural homologue) did not result in inhibition under the same conditions. Thus, this de novo-designed heterodimeric complex is an excellent model system for the study of protein-based fibril formation and inhibition. This system provides additional insight into the development of pharmaceuticals for amyloid disorders, as well as the potential use of amyloid fibrils for self-assembling nanostructures.

Amyloid↗
PubMed2003

Exploring the origins of binding specificity through the computational redesign of calmodulin.

Calmodulin (CaM) is a second messenger protein that has evolved to bind tightly to a variety of targets and, as such, exhibits low binding specificity. We redesigned CaM by using a computational protein design algorithm to improve its binding specificity for one of its targets, smooth muscle myosin light chain kinase (smMLCK). Residues in or near the CaM/smMLCK binding interface were optimized; CaM interactions with alternative targets were not directly considered in the optimization. The predicted CaM sequences were constructed and tested for binding to a set of eight targets including smMLCK. The best CaM variant, obtained from a calculation that emphasized intermolecular interactions, showed up to a 155-fold increase in binding specificity. The increase in binding specificity was not due to improved binding to smMLCK, but due to decreased binding to the alternative targets. This finding is consistent with the fact that the sequence of wild-type CaM is nearly optimal for interactions with numerous targets.

Algorithms↗