Systemic immune response of young chickens orally immunized with bovine serum albumin.

The efficacy of oral immunization, with and without commercial adjuvants, to mount a systemic immune response in young chickens was studied. Bovine serum albumin (BSA) mixed with a pegylated C8/C10 mono/di-glyceride, (Softigen), or Cholera toxin B-subunit (CTB), administered orally by gavage to 15-day-old chickens resulted in circulating immunospecific anti-BSA IgG, IgM and IgA antibodies. Continuous 5-day oral administration of BSA without adjuvant also resulted in immunospecific IgM and IgA antibodies in the circulation of chickens first immunized at 15 days of age; and immunospecific antibodies of all three classes in chickens first immunized when they were 22 days old. IgG and IgM serum concentrations were more than 4 to 10 times higher, respectively, in CTB- and Softigen-treated chickens as compared to chickens immunized without adjuvants. The IgA response in the orally immunized chickens seemed unaffected by CTB and Softigen. The antibody concentrations in chickens immunized subcutaneously with BSA emulsified in Freund's Incomplete Adjuvant (FIA) were approximately 10 times higher than those of the chickens orally immunized using CTB and Softigen.

De novo backbone and sequence design of an idealized alpha/beta-barrel protein: evidence of stable tertiary structure.

We have designed, synthesized, and characterized a 216 amino acid residue sequence encoding a putative idealized alpha/beta-barrel protein. The design was elaborated in two steps. First, the idealized backbone was defined with geometric parameters representing our target fold: a central eight parallel-stranded beta-sheet surrounded by eight parallel alpha-helices, connected together with short structural turns on both sides of the barrel. An automated sequence selection algorithm, based on the dead-end elimination theorem, was used to find the optimal amino acid sequence fitting the target structure. A synthetic gene coding for the designed sequence was constructed and the recombinant artificial protein was expressed in bacteria, purified and characterized. Far-UV CD spectra with prominent bands at 222nm and 208nm revealed the presence of alpha-helix secondary structures (50%) in fairly good agreement with the model. A pronounced absorption band in the near-UV CD region, arising from immobilized aromatic side-chains, showed that the artificial protein is folded in solution. Chemical unfolding monitored by tryptophan fluorescence revealed a conformational stability (DeltaG(H2O)) of 35kJ/mol. Thermal unfolding monitored by near-UV CD revealed a cooperative transition with an apparent T(m) of 65 degrees C. Moreover, the artificial protein did not exhibit any affinity for the hydrophobic fluorescent probe 1-anilinonaphthalene-8-sulfonic acid (ANS), providing additional evidence that the artificial barrel is not in the molten globule state, contrary to previously designed artificial alpha/beta-barrels. Finally, 1H NMR spectra of the folded and unfolded proteins provided evidence for specific interactions in the folded protein. Taken together, the results indicate that the de novo designed alpha/beta-barrel protein adopts a stable three-dimensional structure in solution. These encouraging results show that de novo design of an idealized protein structure of more than 200 amino acid residues is now possible, from construction of a particular backbone conformation to determination of an amino acid sequence with an automated sequence selection algorithm.

Enzyme-like proteins by computational design.

We report the development and initial experimental validation of a computational design procedure aimed at generating enzyme-like protein catalysts called "protozymes." Our design approach utilizes a "compute and build" strategy that is based on the physical/chemical principles governing protein stability and catalytic mechanism. By using the catalytically inert 108-residue Escherichia coli thioredoxin as a scaffold, the histidine-mediated nucleophilic hydrolysis of p-nitrophenyl acetate as a model reaction, and the ORBIT protein design software to compute sequences, an active site scan identified two promising catalytic positions and surrounding active-site mutations required for substrate binding. Experimentally, both candidate protozymes demonstrated catalytic activity significantly above background. One of the proteins, PZD2, displayed "burst" phase kinetics at high substrate concentrations, consistent with the formation of a stable enzyme intermediate. The kinetic parameters of PZD2 are comparable to early catalytic Abs. But, unlike catalytic Ab design, our design procedure is independent of fold, suggesting a possible mechanism for examining the relationships between protein fold and the evolvability of protein function.

Polar residues in the protein core of Escherichia coli thioredoxin are important for fold specificity.

Most globular proteins contain a core of hydrophobic residues that are inaccessible to solvent in the folded state. In general, polar residues in the core are thermodynamically unfavorable except when they are able to form intramolecular hydrogen bonds. Compared to hydrophobic interactions, polar interactions are more directional in character and may aid in fold specificity. In a survey of 263 globular protein structures, we found a strong positive correlation between the number of polar residues at core positions and protein size. To probe the importance of buried polar residues, we experimentally tested the effects of hydrophobic mutations at the five polar core residues in Escherichia coli thioredoxin. Proteins with single hydrophobic mutations (D26I, C32A, C35A, T66L, and T77V) all have cooperative unfolding transitions like the wild type (wt), as determined by chemical denaturation. Relative to wt, D26I is more stable while the other point mutants are less stable. The combined 5-fold mutant protein (IAALV) is less stable than wt and has an unfolding transition that is substantially less cooperative than that of wt. NMR spectra as well as amide deuterium exchange indicate that IAALV is likely sampling a number of low-energy structures in the folded state, suggesting that polar residues in the core are important for specifying a well-folded native structure.

The beta-beta-alpha fold: explorations in sequence space.

The computational redesign of the second zinc finger of Zif268 to produce a 28 residue peptide (FSD-1) that assumes a betabetaalpha fold without metal binding was recently reported. In order to explore the tolerance of this metal-free fold towards sequence variability, six additional peptides resulting from the ORBIT computational protein design process were synthesized and characterized. The experimental stabilities of five of these peptides are strongly correlated with the energies calculated by ORBIT. However, when a peptide with a mutation in the beta-turn is examined, the calculated stability does not accurately predict the experimentally determined stability. The NMR solution structure of a peptide incorporating this mutation (FSD-EY) reveals that the register between the beta-strands is different from the model structure used to select and score the sequences. FSD-EY has a type I' turn instead of the target EbaaagbE turn (rubredoxin knuckle). Two additional peptides that have improved side-chain to backbone hydrogen bonding and turn propensity for the target turn were characterized. Both are of stability comparable to that of FSD-1. These results demonstrate the robustness of the ORBIT protein design methods and underscore the need for continued improvements in negative design.

Designed protein G core variants fold to native-like structures: sequence selection by ORBIT tolerates variation in backbone specification.

The solution structures of two computationally designed core variants of the beta 1 domain of streptococcal protein G (G beta 1) were solved by (1)H NMR methods to assess the robustness of amino acid sequence selection by the ORBIT protein design package under changes in protein backbone specification. One variant has mutations at three of 10 core positions and corresponds to minimal perturbations of the native G beta 1 backbone. The other, with mutations at six of 10 positions, was calculated for a backbone in which the separation between G beta 1's alpha-helix and beta-sheet was increased by 15% relative to native G beta 1. Exchange broadening of some resonances and the complete absence of others in spectra of the sixfold mutant bespeak conformational heterogeneity in this protein. The NMR data were sufficiently abundant, however, to generate structures of similar, moderately high quality for both variants. Both proteins adopt backbone structures similar to their target folds. Moreover, the sequence selection algorithm successfully predicted all core chi(1) angles in both variants, five of six chi(2) angles in the threefold mutant and four of seven chi(2) angles in the sixfold mutant. We conclude that ORBIT calculates sequences that fold specifically to a geometry close to the template, even when the template is moderately perturbed relative to a naturally occurring structure. There are apparently limits to the size of acceptable perturbations: In this study, the larger perturbation led to undesired dynamic behavior.

Computational method to reduce the search space for directed protein evolution.

We introduce a computational method to optimize the in vitro evolution of proteins. Simulating evolution with a simple model that statistically describes the fitness landscape, we find that beneficial mutations tend to occur at amino acid positions that are tolerant to substitutions, in the limit of small libraries and low mutation rates. We transform this observation into a design strategy by applying mean-field theory to a structure-based computational model to calculate each residue's structural tolerance. Thermostabilizing and activity-increasing mutations accumulated during the experimental directed evolution of subtilisin E and T4 lysozyme are strongly directed to sites identified by using this computational approach. This method can be used to predict positions where mutations are likely to lead to improvement of specific protein properties.

Achieving stability and conformational specificity in designed proteins via binary patterning.

We have developed a method to determine the optimal binary pattern (arrangement of hydrophobic and polar amino acids) of a target protein fold prior to amino acid sequence selection in protein design studies. A solvent accessible surface is generated for a target fold using its backbone coordinates and "generic" side-chains, which are constructs whose size and shape are similar to an average amino acid. Each position is classified as hydrophobic or polar according to the solvent exposure of its generic side-chain. The method was tested by analyzing a set of proteins in the Protein Data Bank and by experimentally constructing and analyzing a set of engrailed homeodomain variants whose binary patterns were systematically varied. Selection of the optimal binary pattern results in a designed protein that is monomeric, well-folded, and hyperthermophilic. Homeodomain variants with fewer hydrophobic residues are destabilized, while additional hydrophobic residues induce aggregation. Binary patterning, in conjunction with a force field that models folded state energies, appears sufficient to satisfy two basic goals of protein design: stability and conformational specificity.

Computationally focusing the directed evolution of proteins.

Directed evolution has proven to be a successful strategy for the modification of enzyme properties. To date, the preferred experimental procedure has been to apply mutations or crossovers randomly throughout the gene. With the emergence of powerful computational methods, it has become possible to develop focused combinatorial searches, guided by computer algorithms. Here, we describe several computational methods that have emerged to aid the optimization of mutant libraries, the targeting of specific residues for mutagenesis, and the design of recombination experiments.

Designing protein beta-sheet surfaces by Z-score optimization.

Studies of lattice models of proteins have suggested that the appropriate energy expression for protein design may include nonthermodynamic terms to accommodate negative design concerns. One method, developed in lattice model studies, maximizes a quantity known as the " Z-score," which compares the lowest energy sequence whose ground state structure is the target structure to an ensemble of random sequences. Here we show that, in certain circumstances, the technique can be applied to real proteins. The resulting energy expression is used to design the beta-sheet surfaces of two real proteins. We find experimentally that the designed proteins are stable and well folded, and in one case is even more thermostable than the wild type.

Structure of a protein G helix variant suggests the importance of helix propensity and helix dipole interactions in protein design.

Six helix surface positions of protein G (Gbeta1) were redesigned using a computational protein design algorithm, resulting in the five fold mutant Gbeta1m2. Gbeta1m2 is well folded with a circular dichroism spectrum nearly identical to that of Gbeta1, and a melting temperature of 91 degrees C, approximately 6 degrees C higher than that of Gbeta1. The crystal structure of Gbeta1m2 was solved to 2.0 A resolution by molecular replacement. The absence of hydrogen bond or salt bridge interactions between the designed residues in Gbeta1m2 suggests that the increased stability of Gbeta1m2 is due to increased helix propensity and more favorable helix dipole interactions.

Computational design of an integrin I domain stabilized in the open high affinity conformation.

We have taken a computational approach to design mutations that stabilize a large protein domain of approximately 200 residues in two alternative conformations. Mutations in the hydrophobic core of the alphaMbeta2 integrin I domain were designed to stabilize the crystallographically defined open or closed conformers. When expressed on the cell surface as part of the intact heterodimeric receptor, binding of the designed open and closed I domains to the ligand iC3b, a form of the complement component C3, was either increased or decreased, respectively, compared to wild type. Moreover, when expressed in isolation from other integrin domains using an artificial transmembrane domain, designed open I domains were active in ligand binding, whereas designed closed and wild type I domains were inactive. Comparison to a human expert designed open mutant showed that the computationally designed mutants are far more active. Thus, computational design can be used to stabilize a molecule in a desired conformation, and conformational change in the I domain is physiologically relevant to regulation of ligand binding.

Trading accuracy for speed: A quantitative comparison of search algorithms in protein sequence design.

Finding the minimum energy amino acid side-chain conformation is a fundamental problem in both homology modeling and protein design. To address this issue, numerous computational algorithms have been proposed. However, there have been few quantitative comparisons between methods and there is very little general understanding of the types of problems that are appropriate for each algorithm. Here, we study four common search techniques: Monte Carlo (MC) and Monte Carlo plus quench (MCQ); genetic algorithms (GA); self-consistent mean field (SCMF); and dead-end elimination (DEE). Both SCMF and DEE are deterministic, and if DEE converges, it is guaranteed that its solution is the global minimum energy conformation (GMEC). This provides a means to compare the accuracy of SCMF and the stochastic methods. For the side-chain placement calculations, we find that DEE rapidly converges to the GMEC in all the test cases. The other algorithms converge on significantly incorrect solutions; the average fraction of incorrect rotamers for SCMF is 0.12, GA 0.09, and MCQ 0.05. For the protein design calculations, design positions are progressively added to the side-chain placement calculation until the time required for DEE diverges sharply. As the complexity of the problem increases, the accuracy of each method is determined so that the results can be extrapolated into the region where DEE is no longer tractable. We find that both SCMF and MCQ perform reasonably well on core calculations (fraction amino acids incorrect is SCMF 0.07, MCQ 0.04), but fail considerably on the boundary (SCMF 0.28, MCQ 0.32) and surface calculations (SCMF 0.37, MCQ 0.44).

Contribution of surface salt bridges to protein stability.

The role of surface salt bridges in protein stabilization has been a source of controversy. Here we present the NMR structure of a hyperthermophilic rubredoxin variant (PFRD-XC4) and the thermodynamic analysis of two surface salt bridges by double mutant cycles. This analysis shows that the surface side chain to side chain salt bridge between Lys 6 and Glu 49 does not stabilize PFRD-XC4. The main chain to side chain salt bridge between the N-terminus and Glu 14 was, however, found to stabilize PFRD-XC4 by 1. 5 kcal mol(-)(1). The entropic cost of making a surface salt bridge involving the protein's backbone is reduced, since the backbone has already been immobilized upon protein folding.

Branch-and-terminate: a combinatorial optimization algorithm for protein design.

BACKGROUND: Several deterministic and stochastic combinatorial optimization algorithms have been applied to computational protein design and homology modeling. As structural targets increase in size, however, it has become necessary to find more powerful methods to address the increased combinatorial complexity. RESULTS: We present a new deterministic combinatorial search algorithm called 'Branch-and-Terminate' (B&T), which is derived from the Branch-and-Bound search method. The B&T approach is based on the construction of an efficient but very restrictive bounding expression, which is used for the search of a combinatorial tree representing the protein system. The bounding expression is used both to determine the optimal organization of the tree and to perform a highly effective pruning procedure named 'termination'. For some calculations, the B&T method rivals the current deterministic standard, dead-end elimination (DEE), sometimes finding the solution up to 21 times faster. A more significant feature of the B&T algorithm is that it can provide an efficient way to complete the optimization of problems that have been partially reduced by a DEE algorithm. CONCLUSIONS: The B&T algorithm is an effective optimization algorithm when used alone. Moreover, it can increase the problem size limit of amino acid sidechain placement calculations, such as protein design, by completing DEE optimizations that reach a point at which the DEE criteria become inefficient. Together the two algorithms make it possible to find solutions to problems that are intractable by either algorithm alone.

Energy functions for protein design.

Recent successes in protein design have illustrated the promise of computational approaches. These methods rely on energy expressions to evaluate the quality of different amino acid sequences for target protein structures. The force fields optimized for design differ from those typically used in molecular mechanics and molecular dynamics calculations.

Intrinsic beta-sheet propensities result from van der Waals interactions between side chains and the local backbone.

The intrinsic secondary structure-forming propensities of the naturally occurring amino acids have been measured both experimentally in host-guest studies and statistically by examination of the protein structure databank. There has been significant progress in understanding the origins of intrinsic alpha-helical propensities, but a unifying theme for understanding intrinsic beta-sheet propensities has remained elusive. To this end, we modeled dipeptides by using a van der Waals energy function and derived Ramachandran plots for each of the amino acids. These data were used to determine the entropy and Helmholtz free energy of placing each amino acid in the beta-sheet region of phi-psi space. We quantitatively establish that the dominant cause of intrinsic beta-sheet propensity is the avoidance of steric clashes between an amino acid side chain and its local backbone. Standard implementations of coulombic and solvation effects are seen to be less important.

Computational protein design.

A 'protein design cycle', involving cycling between theory and experiment, has led to recent advances in rational protein design. A reductionist approach, in which protein positions are classified by their local environments, has aided development of an appropriate energy expression. The computational principles and practicalities of the protein design cycle are discussed.

Pairwise calculation of protein solvent-accessible surface areas.

BACKGROUND: The tractability of many algorithms for determining the energy state of a system depends on the pairwise nature of an energy expression. Some energy terms, such as the standard implementation of the van der Waals potential, satisfy this criterion whereas others do not. One class of important potentials that are not pairwise involves benefits and penalties for burying hydrophobic and/or polar surface areas. It has been found previously that, in some cases, a pairwise approximation to these surface areas correlates with the true surface areas. We set out to generalize the applicability of this approximation. RESULTS: We develop a pairwise expression with one scalable parameter that closely reproduces both the true buried and the true exposed solvent-accessible surface areas. We then refit our previously published coiled-coil stability data to give solvation parameters of 26 cal/mol A2 favoring hydrophobic burial and 100 cal/mol A2 opposing polar burial. CONCLUSIONS: An accurate pairwise approximation to calculate exposed and buried protein solvent-accessible surface area is achieved.