Additivity of mutant effects assessed by binomial mutagenesis

Deploying synthetic coevolution and machine learning to engineer protein-protein interactions

Fine-tuning of protein-protein interactions occurs naturally through coevolution, but this process is difficult to recapitulate in the laboratory. We describe a platform for synthetic protein-protein coevolution that can isolate matched pairs of interacting muteins from complex libraries. This large dataset of coevolved complexes drove a systems-level analysis of molecular recognition between Z domain-affibody pairs spanning a wide range of structures, affinities, cross-reactivities, and orthogonalities, and captured a broad spectrum of coevolutionary networks. Furthermore, we harnessed pretrained protein language models to expand, in silico, the amino acid diversity of our coevolution screen, predicting remodeled interfaces beyond the reach of the experimental library. The integration of these approaches provides a means of simulating protein coevolution and generating protein complexes with diverse molecular recognition properties for biotechnology and synthetic biology.

Binary combinatorial scanning reveals potent poly-alanine-substituted inhibitors of protein-protein interactions

Establishing structure-activity relationships is crucial to understand and optimize the activity of peptide-based inhibitors of protein-protein interactions. Single alanine substitutions provide limited information on the residues that tolerate simultaneous modifications with retention of biological activity. To guide optimization of peptide binders, we use combinatorial peptide libraries of over 4,000 variants-in which each position is varied with either the wild-type residue or alanine-with a label-free affinity selection platform to study protein-ligand interactions. Applying this platform to a peptide binder to the oncogenic protein MDM2, several multi-alanine-substituted analogs with picomolar binding affinity were discovered. We reveal a non-additive substitution pattern in the selected sequences. The alanine substitution tolerances for peptide ligands of the 12ca5 antibody and 14-3-3 regulatory protein are also characterized, demonstrating the general applicability of this new platform. We envision that binary combinatorial alanine scanning will be a powerful tool for investigating structure-activity relationships.

Shotgun scanning glycomutagenesis: A simple and efficient strategy for constructing and characterizing neoglycoproteins

Asparagine-linked (N-linked) protein glycosylation—the covalent attachment of complex sugars to the nitrogen atom in asparagine side chains—is the most widespread posttranslational modification to proteins and also the most complex. N-glycosylation affects a significant number of cellular proteins and can have profound effects on their most important attributes such as biological activity, chemical solubility, folding and stability, immunogenicity, and serum half-life. Accordingly, the strategic installation of glycans at naïve sites has become an attractive means for endowing proteins with advantageous biological and/or biophysical properties. Here, we describe a glycoprotein engineering strategy that enables systematic investigation of the structural and functional consequences of glycan installation at every position along a protein backbone and provides a new route to bespoke glycoproteins.

As a common protein modification, asparagine-linked (N-linked) glycosylation has the capacity to greatly influence the biological and biophysical properties of proteins. However, the routine use of glycosylation as a strategy for engineering proteins with advantageous properties is limited by our inability to construct and screen large collections of glycoproteins for cataloguing the consequences of glycan installation. To address this challenge, we describe a combinatorial strategy termed shotgun scanning glycomutagenesis in which DNA libraries encoding all possible glycosylation site variants of a given protein are constructed and subsequently expressed in glycosylation-competent bacteria, thereby enabling rapid determination of glycosylatable sites in the protein. The resulting neoglycoproteins can be readily subjected to available high-throughput assays, making it possible to systematically investigate the structural and functional consequences of glycan conjugation along a protein backbone. The utility of this approach was demonstrated with three different acceptor proteins, namely bacterial immunity protein Im7, bovine pancreatic ribonuclease A, and human anti-HER2 single-chain Fv antibody, all of which were found to tolerate N-glycan attachment at a large number of positions and with relatively high efficiency. The stability and activity of many glycovariants was measurably altered by N-linked glycans in a manner that critically depended on the precise location of the modification. Structural models suggested that affinity was improved by creating novel interfacial contacts with a glycan at the periphery of a protein–protein interface. Importantly, we anticipate that our glycomutagenesis workflow should provide access to unexplored regions of glycoprotein structural space and to custom-made neoglycoproteins with desirable properties.

Adaptive Landscapes in the Age of Synthetic Biology

For nearly a century adaptive landscapes have provided overviews of the evolutionary process and yet they remain metaphors. We redefine adaptive landscapes in terms of biological processes rather than descriptive phenomenology. We focus on the underlying mechanisms that generate emergent properties such as epistasis, dominance, trade-offs and adaptive peaks. We illustrate the utility of landscapes in predicting the course of adaptation and the distribution of fitness effects. We abandon aged arguments concerning landscape ruggedness in favor of empirically determining landscape architecture. In so doing, we transform the landscape metaphor into a scientific framework within which causal hypotheses can be tested.

Double-mutant cycles: new directions and applications

Double-mutant cycle (DMC) analysis is a powerful approach for detecting and quantifying the energetics of both direct and long-range interactions in proteins and other chemical systems. It can also be used to unravel higher-order interactions (e.g. three-body effects) that lead to cooperativity in protein folding and function. In this review, we describe new applications of DMC analysis based on advances in native mass spectrometry and high-throughput methods such as next generation sequencing and protein complementation assays. These developments have facilitated carrying out high-throughput DMC analysis, which can be used to characterize increasingly higher-order interactions and very large interaction networks in proteins. Such studies have provided insights into the extent of cooperativity (epistasis) in protein structures. High-throughput DMC studies have also been used to validate correlated mutation analysis and can provide restraints for protein docking.

Coevolution-based inference of amino acid interactions underlying protein function

Protein function arises from a poorly understood pattern of energetic interactions between amino acid residues. Sequence-based strategies for deducing this pattern have been proposed, but lack of benchmark data has limited experimental verification. Here, we extend deep-mutation technologies to enable measurement of many thousands of pairwise amino acid couplings in several homologs of a protein family - a deep coupling scan (DCS). The data show that cooperative interactions between residues are loaded in a sparse, evolutionarily conserved, spatially contiguous network of amino acids. The pattern of amino acid coupling is quantitatively captured in the coevolution of amino acid positions, especially as indicated by the statistical coupling analysis (SCA), providing experimental confirmation of the key tenets of this method. This work exposes the collective nature of physical constraints on protein function and clarifies its link with sequence analysis, enabling a general practical approach for understanding the structural basis for protein function.

Correlated positions in protein evolution and engineering

Statistical analysis of a protein multiple sequence alignment can reveal groups of positions that undergo interdependent mutations throughout evolution. At these so-called correlated positions, only certain combinations of amino acids appear to be viable for maintaining proper folding, stability, catalytic activity or specificity. Therefore, it is often speculated that they could be interesting guides for semi-rational protein engineering purposes. Because they are a fingerprint from protein evolution, their analysis may provide valuable insight into a protein's structure or function and furthermore, they may also be suitable target positions for mutagenesis. Unfortunately, little is currently known about the properties of these correlation networks and how they should be used in practice. This review summarises the recent findings, opportunities and pitfalls of the concept.

■ REVIEW : Olfactory Receptors: A Large Gene Family with Broad Affinities and Multiple Functions

Five years have passed since the first cloning and sequencing of a large family of G protein-coupled receptors from the olfactory epithelium. These receptors are believed to be the initial sites of odor transduction. Although direct experimental evidence concerning the properties of these molecules is still limited, a variety of studies has provided fascinating insights into a range of possible functions, extending beyond olfactory transduction to include functions as diverse as sperm navigation and neural and cardiac development. To serve these functions, the olfactory receptors appear to express interesting adaptations of the basic seven transmembrane domain structures found in the neurotransmitter members of the G protein-coupled receptor superfamily. We review here this evidence and propose hypotheses for the molecular mechanisms underlying several distinct functions for this receptor family as guides for future experimental testing. NEUROSCIENTIST 2:262-271, 1996

A comprehensive biophysical description of pairwise epistasis throughout an entire protein domain

BACKGROUND

Nonadditivity in fitness effects from two or more mutations, termed epistasis, can result in compensation of deleterious mutations or negation of beneficial mutations. Recent evidence shows the importance of epistasis in individual evolutionary pathways. However, an unresolved question in molecular evolution is how often and how significantly fitness effects change in alternative genetic backgrounds.

RESULTS

To answer this question, we quantified the effects of all single mutations and double mutations between all positions in the IgG-binding domain of protein G (GB1). By observing the first two steps of all possible evolutionary pathways using this fitness profile, we were able to characterize the extent and magnitude of pairwise epistasis throughout an entire protein molecule. Furthermore, we developed a novel approach to quantitatively determine the effects of single mutations on structural stability (ΔΔGU). This enabled determination of the importance of stability effects in functional epistasis.

CONCLUSIONS

Our results illustrate common biophysical mechanisms for occurrences of positive and negative epistasis. Our results show pervasive positive epistasis within a conformationally dynamic network of residues. The stability analysis shows that significant negative epistasis, which is more common than positive epistasis, mostly occurs between combinations of destabilizing mutations. Furthermore, we show that although significant positive epistasis is rare, many deleterious mutations are beneficial in at least one alternative mutational background. The distribution of conditionally beneficial mutations throughout the domain demonstrates that the functional portion of sequence space can be significantly expanded by epistasis.

Native chemical ligation: a boon to peptide chemistry

The use of chemical ligation within the realm of peptide chemistry has opened various opportunities to expand the applications of peptides/proteins in biological sciences. Expansion and refinement of ligation chemistry has made it possible for the entry of peptides into the world of viable oral therapeutic drugs through peptide backbone cyclization. This progression has been a journey of chemical exploration and transition, leading to the dominance of native chemical ligation in the present advances of peptide/protein applications. Here we illustrate and explore the historical and current nature of peptide ligation, providing a clear indication to the possibilities and use of these novel methods to take peptides outside their typically defined boundaries.

Characterizing changes in the rate of protein-protein dissociation upon interface mutation using hotspot energy and organization

Predicting the effects of mutations on the kinetic rate constants of protein-protein interactions is central to both the modeling of complex diseases and the design of effective peptide drug inhibitors. However, while most studies have concentrated on the determination of association rate constants, dissociation rates have received less attention. In this work we take a novel approach by relating the changes in dissociation rates upon mutation to the energetics and architecture of hotspots and hotregions, by performing alanine scans pre- and post-mutation. From these scans, we design a set of descriptors that capture the change in hotspot energy and distribution. The method is benchmarked on 713 kinetically characterized mutations from the SKEMPI database. Our investigations show that, with the use of hotspot descriptors, energies from single-point alanine mutations may be used for the estimation of off-rate mutations to any residue type and also multi-point mutations. A number of machine learning models are built from a combination of molecular and hotspot descriptors, with the best models achieving a Pearson's Correlation Coefficient of 0.79 with experimental off-rates and a Matthew's Correlation Coefficient of 0.6 in the detection of rare stabilizing mutations. Using specialized feature selection models we identify descriptors that are highly specific and, conversely, broadly important to predicting the effects of different classes of mutations, interface regions and complexes. Our results also indicate that the distribution of the critical stability regions across protein-protein interfaces is a function of complex size more strongly than interface area. In addition, mutations at the rim are critical for the stability of small complexes, but consistently harder to characterize. The relationship between hotregion size and the dissociation rate is also investigated and, using hotspot descriptors which model cooperative effects within hotregions, we show how the contribution of hotregions of different sizes, changes under different cooperative effects.

Synthetic shuffling and in vitro selection reveal the rugged adaptive fitness landscape of a kinase ribozyme

The relationship between genotype and phenotype is often described as an adaptive fitness landscape. In this study, we used a combination of recombination, in vitro selection, and comparative sequence analysis to characterize the fitness landscape of a previously isolated kinase ribozyme. Point mutations present in improved variants of this ribozyme were recombined in vitro in more than 10(14) different arrangements using synthetic shuffling, and active variants were isolated by in vitro selection. Mutual information analysis of 65 recombinant ribozymes isolated in the selection revealed a rugged fitness landscape in which approximately one-third of the 91 pairs of positions analyzed showed evidence of correlation. Pairs of correlated positions overlapped to form densely connected networks, and groups of maximally connected nucleotides occurred significantly more often in these networks than they did in randomized control networks with the same number of links. The activity of the most efficient recombinant ribozyme isolated from the synthetically shuffled pool was 30-fold greater than that of any of the ribozymes used to build it, which indicates that synthetic shuffling can be a rich source of ribozyme variants with improved properties.

Development of a dehalogenase-based protein fusion tag capable of rapid, selective and covalent attachment to customizable ligands

Our fundamental understanding of proteins and their biological significance has been enhanced by genetic fusion tags, as they provide a convenient method for introducing unique properties to proteins so that they can be examinedin isolation. Commonly used tags satisfy many of the requirements for applications relating to the detection and isolation of proteins from complex samples. However, their utility at low concentration becomes compromised if the binding affinity for a detection or capture reagent is not adequate to produce a stable interaction. Here, we describe HaloTag® (HT7), a genetic fusion tag based on a modified haloalkane dehalogenase designed and engineered to overcome the limitation of affinity tags by forming a high affinity, covalent attachment to a binding ligand. HT7 and its ligand have additional desirable features. The tag is relatively small, monomeric, and structurally compatible with fusion partners, while the ligand is specific, chemically simple, and amenable to modular synthetic design. Taken together, the design features and molecular evolution of HT7 have resulted in a superior alternative to common tags for the overexpression, detection, and isolation of target proteins.

Bound water at protein-protein interfaces: partners, roles and hydrophobic bubbles as a conserved motif

Background

There is a great interest in understanding and exploiting protein-protein associations as new routes for treating human disease. However, these associations are difficult to structurally characterize or model although the number of X-ray structures for protein-protein complexes is expanding. One feature of these complexes that has received little attention is the role of water molecules in the interfacial region.

Methodology

A data set of 4741 water molecules abstracted from 179 high-resolution (≤ 2.30 Å) X-ray crystal structures of protein-protein complexes was analyzed with a suite of modeling tools based on the HINT forcefield and hydrogen-bonding geometry. A metric termed Relevance was used to classify the general roles of the water molecules.

Results

The water molecules were found to be involved in: a) (bridging) interactions with both proteins (21%), b) favorable interactions with only one protein (53%), and c) no interactions with either protein (26%). This trend is shown to be independent of the crystallographic resolution. Interactions with residue backbones are consistent for all classes and account for 21.5% of all interactions. Interactions with polar residues are significantly more common for the first group and interactions with non-polar residues dominate the last group. Waters interacting with both proteins stabilize on average the proteins' interaction (−0.46 kcal mol⁻¹), but the overall average contribution of a single water to the protein-protein interaction energy is unfavorable (+0.03 kcal mol⁻¹). Analysis of the waters without favorable interactions with either protein suggests that this is a conserved phenomenon: 42% of these waters have SASA ≤ 10 Ų and are thus largely buried, and 69% of these are within predominantly hydrophobic environments or “hydrophobic bubbles”. Such water molecules may have an important biological purpose in mediating protein-protein interactions.

Synthetic approach to stop-codon scanning mutagenesis

A general combinatorial mutagenesis strategy using common dimethoxytrityl-protected mononucleotide phosphoramidites and a single orthogonally protected trinucleotide phosphoramidite (Fmoc-TAG; Fmoc = 9-fluorenylmethoxycarbonyl) was developed to scan a gene with the TAG amber stop codon with complete synthetic control. In combination with stop-codon suppressors that insert natural (e.g., alanine) or unnatural (e.g., p-benzoylphenylalanine, Bpa) amino acids, a single DNA library can be used to incorporate different amino acids for diverse purposes. Here, we scanned TAG codons through part of the gene for a model four-helix bundle protein, Rop, which regulates the copy number of ColE1 plasmids. Alanine was incorporated into Rop for mapping its binding site using an in vivo activity screen, and subtle but important differences from in vitro gel-shift studies of Rop function are evident. As a test, Bpa was incorporated using a Phe14 amber mutant isolated from the scanning library. Surprisingly, Phe14Bpa-Rop is weakly active, despite the critical role of Phe14 in Rop activity. Bpa is a photoaffinity label unnatural amino acid that can form covalent bonds with adjacent molecules upon UV irradiation. Irradiation of Phe14Bpa-Rop, which is a dimer in solution like wild-type Rop, results in covalent dimers, trimers, and tetramers. This suggests that Phe14Bpa-Rop weakly associates as a tetramer in solution and highlights the use of Bpa cross-linking as a means of trapping weak and transient interactions.

Thermodynamic additivity of sequence variations: an algorithm for creating high affinity peptides without large libraries or structural information

Background

There is a significant need for affinity reagents with high target affinity/specificity that can be developed rapidly and inexpensively. Existing affinity reagent development approaches, including protein mutagenesis, directed evolution, and fragment-based design utilize large libraries and/or require structural information thereby adding time and expense. Until now, no systematic approach to affinity reagent development existed that could produce nanomolar affinity from small chemically synthesized peptide libraries without the aid of structural information.

Methodology/Principal Findings

Based on the principle of additivity, we have developed an algorithm for generating high affinity peptide ligands. In this algorithm, point-variations in a lead sequence are screened and combined in a systematic manner to achieve additive binding energies. To demonstrate this approach, low-affinity lead peptides for multiple protein targets were identified from sparse random sequence space and optimized to high affinity in just two chemical steps. In one example, a TNF-α binding peptide with K_d = 90 nM and high target specificity was generated. The changes in binding energy associated with each variation were generally additive upon combining variations, validating the basis of the algorithm. Interestingly, cooperativity between point-variations was not observed, and in a few specific cases, combinations were less than energetically additive.

Conclusions/Significance

By using this additivity algorithm, peptide ligands with high affinity for protein targets were generated. With this algorithm, one of the highest affinity TNF-α binding peptides reported to date was produced. Most importantly, high affinity was achieved from small, chemically-synthesized libraries without the need for structural information at any time during the process. This is significantly different than protein mutagenesis, directed evolution, or fragment-based design approaches, which rely on large libraries and/or structural guidance. With this algorithm, high affinity/specificity peptide ligands can be developed rapidly, inexpensively, and in an entirely chemical manner.

Intra-protein compensatory mutations analysis highlights the tRNA recognition regions in aminoacyl-tRNA synthetases

The aminoacyl-tRNA synthetases (aaRSs) covalently attach amino acids to their corresponding nucleic acid adapter molecules, tRNAs. The interactions in the tRNA-aaRSs complexes are mostly non-specific, and largely electrostatic. Tracing a way of aaRS-tRNA mutual adaptation throughout evolution offers a clearer view of understanding how aaRS-tRNA systems preserve patterns of tRNA recognition and binding. In this study, we used the compensatory mutations analysis to explore adaptation of aaRSs in respond to random mutations that can occur in the tRNA-recognition area. We showed that the frequency of compensatory mutations among residues that belong to the recognition region is 1.75-fold higher than that of the exposed residues. The highest frequencies of compensatory mutations are observed for pairs of charged residues, wherein one residue is located within the tRNA-recognition area, while the second is placed outside of the area, and contributes to the formation of the aaRS electrostatic landscape. Given charged residues are compensated by buried charge residues in more than 60% of the analyzed mutations. The cytoplasmatic and mitochondrial aaRSs preserve similar patterns of compensatory mutations in the tRNA recognition areas. Moreover, we found that mitochondrial aaRSs demonstrate a significant increase in the frequency of compensatory mutations in the area. Our findings shed light on the physical nature of compensatory mutations in aaRSs, thereby keeping unchanged tRNA-recognition patterns.

Analysis of the impact of solvent on contacts prediction in proteins

Background

The correlated mutations concept is based on the assumption that interacting protein residues coevolve, so that a mutation in one of the interacting counterparts is compensated by a mutation in the other. Approaches based on this concept have been widely used for protein contacts prediction since the 90s. Previously, we have shown that water-mediated interactions play an important role in protein interfaces. We have observed that current "dry" correlated mutations approaches might not properly predict certain interactions in protein interfaces due to the fact that they are water-mediated.

Results

The goal of this study has been to analyze the impact of including solvent into the concept of correlated mutations. For this purpose we use linear combinations of the predictions obtained by the application of two different similarity matrices: a standard "dry" similarity matrix (DRY) and a "wet" similarity matrix (WET) derived from all water-mediated protein interfacial interactions in the PDB. We analyze two datasets containing 50 domains and 10 domain pairs from PFAM and compare the results obtained by using a combination of both matrices. We find that for both intra- and interdomain contacts predictions the introduction of a combination of a "wet" and a "dry" similarity matrix improves the predictions in comparison to the "dry" one alone.

Conclusion

Our analysis, despite the complexity of its possible general applicability, opens up that the consideration of water may have an impact on the improvement of the contact predictions obtained by correlated mutations approaches.

Remote changes in the dynamics of the phosphotyrosine-binding domain of insulin receptor substrate-1 induced by phosphopeptide binding

Protein structures consist of cooperative networks of interactions that can extend substantial distances across the protein structure and have significant consequences for stability and function. To characterize such interaction networks within the phosphotyrosine-binding domain of insulin receptor substrate-1 (IRS-PTB), we have used NMR relaxation to determine the dynamics of backbone amide groups, side chain methyl groups, and tryptophan side chain indole groups in IRS-PTB, both in the absence and in the presence of a bound phosphotyrosine-containing peptide. Although there are minimal differences between the structures of apo and peptide-bound forms, primarily localized close to the peptide binding site, we observe significant changes in dynamics for residues located remotely from the binding site. These residues are clustered together and appear to constitute a network of interactions that is coupled to the peptide binding site through intervening residues.

New insight into long-range nonadditivity within protein double-mutant cycles

Additivity principles in chemistry, biochemistry, and biophysics have been used extensively for decades. Nevertheless, it is well known that additivity frequently breaks down in complex biomacromolecules. Nonadditivity within protein double mutant free energy cycles of spatially close residue pairs is a generally well-understood phenomenon, whereas a robust description of nonadditivity extending over large distances remains to be developed. Here, we test the hypothesis that the mutational effects tend to be nonadditive if two structurally well-separated mutated residues belong to the same rigid cluster within the wild type protein, and additive if they are located within different clusters. We find the hypothesis to be statistically significant with P-values that range from 10(-5) to 10(-6). To the best of our knowledge, this result represents the first demonstration of a statistically significant preponderance for nonadditivity over long distances. These findings provide new insight into the origins of long-range nonadditivity in double mutant cycles, which complements the conventional wisdom that nonadditivity arises in double mutations involving contacting residues. Consequently, these results should have far-reaching implications for a proper understanding of protein stability, structure/function analyses, and protein design.

Exploring and designing protein function with restricted diversity

Combinatorial libraries with restricted diversity can be used to rapidly map binding energetics across protein interfaces. Shotgun scanning strategies have been used for alanine scanning and for alternative mutagenesis schemes that provide high-resolution functional views of binding interfaces. In addition, synthetic antibodies have been derived from naïve libraries restricted to a binary code to explore the minimal requirements for molecular recognition. These studies shed light on the underlying principles governing molecular recognition, and provide rapid yet quantitative alternatives to conventional biophysical methods for exploring protein structure and function.

Hot spots-A review of the protein-protein interface determinant amino-acid residues

Proteins tendency to bind to one another in a highly specific manner forming stable complexes is fundamental to all biological processes. A better understanding of complex formation has many practical applications, which include the rational design of new therapeutic agents, and the analysis of metabolic and signal transduction networks. Alanine-scanning mutagenesis made possible the detection of the functional epitopes, and demonstrated that most of the protein-protein binding energy is related only to a group of few amino acids at intermolecular protein interfaces: the hot spots. The scope of this review is to summarize all the available information regarding hot spots for a better atomic understanding of their structure and function. The ultimate objective is to improve the rational design of complexes of high affinity and specificity as well as that of small molecules, which can mimic the functional epitopes of the proteic complexes.

Mutation-biased adaptation in a protein NK model

Evolutionary trends responsible for systematic differences in genome and proteome composition have been attributed to GC:AT mutation bias in the context of neutral evolution or to selection acting on genome composition. A possibility that has been ignored, presumably because it is part of neither the Modern Synthesis nor the Neutral Theory, is that mutation may impose a directional bias on adaptation. This possibility is explored here with simulations of the effect of a GC:AT bias on amino acid composition during adaptive walks on an abstract protein fitness landscape called an "NK" model. The results indicate that adaptation does not preclude mutation-biased evolution. In the complete absence of neutral evolution, a modest GC:AT bias of realistic magnitude can displace the trajectory of adaptation in a mutationally favored direction, to such a degree that amino acid composition is biased substantially and persistently. Thus, mutational explanations for evolved patterns need not presuppose neutral evolution.

A protein interaction surface in nonribosomal peptide synthesis mapped by combinatorial mutagenesis and selection

Nonribosomal peptide synthetases (NRPSs) and polyketide synthases are large, multidomain enzymes that biosynthesize a number of pharmaceutically important natural products. The recognition of biosynthetic intermediates, displayed via covalent attachment to carrier proteins, by catalytic domains is critical for NRPS and polyketide synthase function. We report the use of combinatorial mutagenesis coupled with in vivo selection for the production of the Escherichia coli NRPS product enterobactin to map the surface of the aryl carrier protein (ArCP) domain of EntB that interacts with the downstream elongation module EntF. Two libraries spanning the predicted helix 2 and loop 2/helix 3 of EntB-ArCP were generated by shotgun alanine scanning and selected for their ability to support enterobactin production. From the surviving pools, we identified several hydrophobic residues (M249, F264, and A268) that were highly conserved. These residues cluster near the phosphopantetheinylated serine in a structural model, and two of these positions are in the predicted helix 3 region. Subsequent in vitro studies are consistent with the hypothesis that these residues form a surface on EntB required for interaction with EntF. These results suggest that helix 3 is a major recognition element in EntB-ArCP and demonstrate the utility of selection-based approaches for studying NRPS biosynthesis.

MAVL/StickWRLD for protein: visualizing protein sequence families to detect non-consensus features

A fundamental problem with applying Consensus, Weight-Matrix or hidden Markov models as search tools for biosequences is that there is no way to know, from the model, if the modeled sequences display any dependencies between positional identities. In some instances, these dependencies are crucial in correctly accepting or rejecting other sequences as members of the family. MAVL (multiple alignment variation linker) and StickWRLD provide a web-based method to visually survey the model-training sequences to discover and characterize possible dependencies. Initially introduced for nucleic acid sequences, with MAVL/StickWRLD, it is easy to distinguish typical DNA or RNA structural dependencies in input families, identify mixed populations of distinct subfamilies, or discover novel dependencies that result from binding interactions or other selective pressures [W. Ray (2004) Nucleic Acids Res., 32, W59-W63]. Since the announcement of MAVL/StickWRLD for nucleic acids, one of the most requested new features has been the extension of this visualization method to support protein alignments. We are pleased to report that this extension has been successful, that the basic visualization has been augmented in several ways to enhance protein viewing, and that the results with protein alignments are even more dramatic than with NA alignments. MAVL/StickWRLD can be accessed at http://www.microbial-pathogenesis.org/stickwrld/.

Intramolecular cooperativity in a protein binding site assessed by combinatorial shotgun scanning mutagenesis

Combinatorial shotgun alanine-scanning was used to assess intramolecular cooperativity in the high affinity site (site 1) of human growth hormone (hGH) for binding to its receptor. A total of 19 side-chains were analyzed and statistically significant data were obtained for 145 of the 171 side-chain pairs. The analysis revealed that 90% of the side-chain pairs exhibited no statistically significant pair interactions, and the remaining 10% of side-chain pairs exhibited only small interactions corresponding to cooperative interaction energies with magnitudes less than 0.4 kcal/mol. The statistical predictions were tested by measuring affinities for purified mutant proteins and were found to be accurate for five of six side-chain pairs tested. The results reveal that hGH site 1 behaves in a highly additive manner and suggest that shotgun scanning should be useful for assessing cooperative effects in other protein-protein interactions.

Mapping key elements of a protein motif

In this issue of Chemistry & Biology, Weiss and colleagues use phage display to map residues in the engrailed homeodomain that influence DNA recognition. Their shotgun scanning data provides surprising new insights into the importance of regions outside the recognition helix and N-terminal arm for DNA binding.

Quantitative modeling of DNA-protein interactions: effects of amino acid substitutions on binding specificity of the Mnt repressor

Understanding DNA-protein recognition quantitatively is essential to developing computational algorithms for accurate transcriptional binding site prediction. Using a quantitative, multiple fluorescence, relative affinity (QuMFRA) assay, we determine the binding specificity of 11 different position 6 variants of the Mnt repressor for operators containing all 16 possible dinucleotides at operator positions 16 and 17. We show that the wild-type and all variant proteins interact with the two positions in a non-independent manner, but that a simple independent model provides a close approximation to the true binding affinities. The wild-type His at amino acid 6 is the only protein to prefer the AC sequence of the wild-type operator, whereas most of the variant proteins prefer TA. H6R is unique in having a strong preference for C at position 16. A comparison of the quantitative binding data for all of the protein variants with a model for recognition of the early growth response (EGR) zinc finger family suggests that interactions of Mnt with positions 16 and 17 are similar to interactions of EGR with positions 1 and 2, respectively. This information leads to an augmented model for the interaction of Mnt with its operator.

Protein tolerance to random amino acid change

Mutagenesis of protein-encoding sequences occurs ubiquitously; it enables evolution, accumulates during aging, and is associated with disease. Many biotechnological methods exploit random mutations to evolve novel proteins. To quantitate protein tolerance to random change, it is vital to understand the probability that a random amino acid replacement will lead to a protein's functional inactivation. We define this probability as the "x factor." Here, we develop a broadly applicable approach to calculate x factors and demonstrate this method using the human DNA repair enzyme 3-methyladenine DNA glycosylase (AAG). Three gene-wide mutagenesis libraries were created, each with 10(5) diversity and averaging 2.2, 4.6, and 6.2 random amino acid changes per mutant. After determining the percentage of functional mutants in each library using high-stringency selection (>19,000-fold), the x factor was found to be 34% +/- 6%. Remarkably, reanalysis of data from studies of diverse proteins reveals similar inactivation probabilities. To delineate the nature of tolerated amino acid substitutions, we sequenced 244 surviving AAG mutants. The 920 tolerated substitutions were characterized by substitutability index and mapped onto the AAG primary, secondary, and known tertiary structures. Evolutionarily conserved residues show low substitutability indices. In AAG, beta strands are on average less substitutable than alpha helices; and surface loops that are not involved in DNA binding are the most substitutable. Our results are relevant to such diverse topics as applied molecular evolution, the rate of introduction of deleterious alleles into genomes in evolutionary history, and organisms' tolerance of mutational burden.

Identification of residues critical for catalysis in a class C beta-lactamase by combinatorial scanning mutagenesis

Despite their clinical importance, the mechanism of action of the class C beta-lactamases is poorly understood. In contrast to the class A and class D beta-lactamases, which contain a glutamate residue and a carbamylated lysine in their respective active sites that are thought to serve as general base catalysts for beta-lactam hydrolysis, the mechanism of activation of the serine and water nucleophiles in the class C enzymes is unclear. To probe for residues involved in catalysis, the class C beta-lactamase from Enterobacter cloacae P99 was studied by combinatorial scanning mutagenesis at 122 positions in and around the active site. Over 1000 P99 variants were screened for activity in a high-throughput in vivo antibiotic resistance assay and sequenced by 96-capillary electrophoresis to identify residues that are important for catalysis. P99 mutants showing reduced capability to convey antibiotic resistance were purified and characterized in vitro. The screen identified an active-site hydrogen-bonding network that is key to catalysis. A second cluster of residues was identified that likely plays a structural role in the enzyme. Otherwise, residues not directly contacting the substrate showed tolerance to substitution. The study lends support to the notion that the class C beta-lactamases do not have a single residue that acts as the catalytic general base. Rather, catalysis is affected by a hydrogen-bonding network in the active site, suggesting a possible charge relay system.

Hyperthermostabilization of Bacillus licheniformis alpha-amylase and modulation of its stability over a 50 degrees C temperature range

Bacillus licheniformis alpha-amylase (BLA) is a highly thermostable starch-degrading enzyme that has been extensively studied in both academic and industrial laboratories. For over a decade, we have investigated BLA thermal properties and identified amino acid substitutions that significantly increase or decrease the thermostability. This paper describes the cumulative effect of some of the most beneficial point mutations identified in BLA. Remarkably, the Q264S-N265Y double mutation led to a rather limited gain in stability but significantly improved the amylolytic function. The most hyperthermostable variants combined seven amino acid substitutions and inactivated over 100 times more slowly and at temperatures up to 23 degrees C higher than the wild-type enzyme. In addition, two highly destabilizing mutations were introduced in the metal binding site and resulted in a decrease of 25 degrees C in the half-inactivation temperature of the double mutant enzyme compared with wild-type. These mutational effects were analysed by protein modelling based on the recently determined crystal structure of a hyperthermostable BLA variant. Our engineering work on BLA shows that the thermostability of an already naturally highly thermostable enzyme can be substantially improved and modulated over a temperature range of 50 degrees C through a few point mutations.

Sequence analysis of an artificial family of RNA-binding peptides

Diverse peptide sequences recognizing the lambda boxB RNA hairpin were previously isolated from a library encoding the 22-residue lambda N peptide with random amino acids at positions 13-22 using mRNA display. We have statistically analyzed amino acid distributions in 65 unique sequences from rounds 11 and 12 of this selection and evaluated the resulting structural and functional predictions by alanine-scanning mutagenesis and circular dichroism spectrometry. This artificial sequence family has a consensus structure that continues the bent alpha helix of lambda N up to position 17 when bound to lambda boxB. A charge pair (E(14)R(15)) and hydrophobic patch (A(21)L(22) or V(21)L(22)) have important functional roles in this context. Notably, amino acid covariance reveals six specific pairs of random region positions with >95% significant linkage and strong overall helical (i+1, i+3, and i+4) couplings. The covariance analysis suggests that (1) the sequence context of every residue in each insert has been optimized, (2) selected sequences are local optima on a rugged fitness landscape, and (3) it is possible to detect more subtle structural features with artificial protein sequence families than natural homologs. Our results provide a framework for investigating the structures of in vitro selected proteins by functional minimization, reselection, and covariance analysis.

Thermostability of doubly glycosylated recombinant lysozyme

We prepared a lysozyme mutant (Q41S/R61S) introducing Asn-type glycosylation signal sites by yeast expression system. On purification by cation exchange column at pH 7, three fractions were obtained. Peptide mapping and mass-spectrometry showed the fractions were the derivatives glycosylated at both Asn39 and Asn59, at only Asn39, and not glycosylated. It was revealed that the processing of Asn-linked oligosaccharide at Asn39 and Asn59 occurred independently in yeast cells. The denaturation temperatures of these derivatives by differential scanning calorimetry were 76.0, 68.8, and 67.5 degrees C at pH 3, respectively. The stabilization of glycosylated lysozyme depends on the degree of glycosylation. We concluded that stabilized proteins can be constructed by glycosylation at proper sites. Thermodynamic stabilization by the artificial double glycosylations on a protein has not yet been reported.

Combinatorial alanine-scanning

Combinatorial libraries of alanine-substituted proteins can be used to rapidly identify residues important for protein function, stability and shape. Each alanine substitution examines the contribution of an individual amino acid sidechain to the functionality of the protein. The recently described method of shotgun scanning uses phage-displayed libraries of alanine-substituted proteins for high-throughput analysis.

Rapid mapping of protein functional epitopes by combinatorial alanine scanning

A combinatorial alanine-scanning strategy was used to determine simultaneously the functional contributions of 19 side chains buried at the interface between human growth hormone and the extracellular domain of its receptor. A phage-displayed protein library was constructed in which the 19 side chains were preferentially allowed to vary only as the wild type or alanine. The library pool was subjected to binding selections to isolate functional clones, and DNA sequencing was used to determine the alanine/wild-type ratio at each varied position. This ratio was used to calculate the effect of each alanine substitution as a change in free energy relative to that of wild type. Only seven side chains contribute significantly to the binding interaction, and these conserved residues form a compact cluster in the human growth hormone tertiary structure. The results were in excellent agreement with free energy data previously determined by conventional alanine-scanning mutagenesis and suggest that this technology should be useful for analyzing functional epitopes in proteins.

Mutually compensatory mutations during evolution of the tetramerization domain of tumor suppressor p53 lead to impaired hetero-oligomerization

We have measured the stability and stoichiometry of variants of the human p53 tetramerization domain to assess the effects of mutation on homo- and hetero-oligomerization. The residues chosen for mutation were those in the hydrophobic core that we had previously found to be critical for its stability but are not conserved in human p73 or p51 or in p53-related proteins from invertebrates or vertebrates. The mutations introduced were either single natural mutations or combinations of mutations present in p53-like proteins from different species. Most of the mutations were substantially destabilizing when introduced singly. The introduction of multiple mutations led to two opposite effects: some combinations of mutations that have occurred during the evolution of the hydrophobic core of the domain in p53-like proteins had additive destabilizing effects, whereas other naturally occurring combinations of mutations had little or no net effect on the stability, there being mutually compensating effects of up to 9.5 kcal/mol of tetramer. The triple mutant L332V/F341L/L344I, whose hydrophobic core represents that of the chicken p53 domain, was nearly as stable as the human domain but had impaired hetero-oligomerization with it. Thus, engineering of a functional p53 variant with a reduced capacity to hetero-oligomerize with wild-type human p53 can be achieved without any impairment in the stability and subunit affinity of the engineered homo-oligomer.

Tolerance of Arc repressor to multiple-alanine substitutions

Arc repressor mutants containing from three to 15 multiple-alanine substitutions have spectral properties expected for native Arc proteins, form heterodimers with wild-type Arc, denature cooperatively with Tms equal to or greater than wild type, and, in some cases, fold as much as 30-fold faster and unfold as much as 50-fold slower than wild type. Two of the mutants, containing a total of 14 different substitutions, also footprint operator DNA in vitro. The stability of some of the proteins with multiple-alanine mutations is significantly greater than that predicted from the sum of the single substitutions, suggesting that a subset of the wild-type residues in Arc may interact in an unfavorable fashion. Overall, these results show that almost half of the residues in Arc can be replaced by alanine en masse without compromising the ability of this small, homodimeric protein to fold into a stable, native-like structure.

Tolerance of a protein helix to multiple alanine and valine substitutions

BACKGROUND

Protein stability is influenced by the intrinsic secondary structure propensities of the amino acids and by tertiary interactions, but which of these factors dominates is not known in most cases. We have used combinatorial mutagenesis to examine the effects of substituting a good helix-forming residue (alanine) and a poor helix-forming residue (valine) at many positions in an alpha helix of a native protein. This has allowed us to average over many molecular environments and assess to what extent the results reflect intrinsic helical propensities or are masked by tertiary effects.

RESULTS

Alanine or valine residues were combinatorially substituted at 12 positions in alpha-helix lambda repressor. Functional proteins were selected and sequenced to determine the degree to which each residue type was tolerated. On average, valine substitutions were accommodated slightly less well than alanine substitutions. On a positional basis, however, valine was tolerated as well as alanine at the majority of sites. In fact, alanine was preferred over valine statistically significantly only at four sites. Studies of mutant protein and peptide stabilities suggest that tertiary interactions mask the intrinsic secondary structure propensity differences at most of the remaining residue positions in this alpha helix.

CONCLUSIONS

At the majority of positions in alpha-helix lambda repressor, tertiary interactions with other parts of the protein can be viewed as an environmental "buffer" that help to diminish the helix destabilizing effects of valine mutations and allow these mutations to be tolerated at frequencies similar to alanine mutations.

SWIM analysis allows rapid identification of residues involved in invasin-mediated bacterial uptake

The Yersinia pseudotuberculosis invasin protein promotes bacterial uptake into normally non-phagocytic cells. Combinations of six alanine substitutions in a region of invasin previously shown to be important for bacterial internalization were analyzed using binomial and codon mutagenesis strategies. A single pool of mutants, potentially containing 64 derivatives with various combinations of alanine substitutions, was enriched by one passage through HEp2 cells. DNA was isolated from the resulting pool of internalization-competent bacteria and sequenced in a single set of reactions to determine which alanine substitutions maintained activity. Results of the single sequencing run performed on the pool indicated that strains harboring the D911A substitution were absent after enrichment, confirming the importance of an aspartate residue at this site. When single clones were subsequently isolated from the pool, those containing multiple alanine substitutions in invasin showed uptake defects that were additive, with the exception of S904A/M912A and S910A/M912A double mutants. Binomial mutagenesis combined with a pooled enrichment and sequencing strategy, called 'SWIM' mutagenesis (selection without isolation of mutants), could be applied to any system for which there exists an enrichment scheme, using a single oligonucleotide pool to analyze multiple residues.

Correlated mutations contain information about protein-protein interaction

Many proteins have evolved to form specific molecular complexes and the specificity of this interaction is essential for their function. The network of the necessary inter-residue contacts must consequently constrain the protein sequences to some extent. In other words, the sequence of an interacting protein must reflect the consequence of this process of adaptation. It is reasonable to assume that the sequence changes accumulated during the evolution of one of the interacting proteins must be compensated by changes in the other. Here we apply a method for detecting correlated changes in multiple sequence alignments to a set of interacting protein domains and show that positions where changes occur in a correlated fashion in the two interacting molecules tend to be close to the protein-protein interfaces. This leads to the possibility of developing a method for predicting contacting pairs of residues from the sequence alone. Such a method would not need the knowledge of the structure of the interacting proteins, and hence would be both radically different and more widely applicable than traditional docking methods. We indeed demonstrate here that the information about correlated sequence changes is sufficient to single out the right inter-domain docking solution amongst many wrong alternatives of two-domain proteins. The same approach is also used here in one case (haemoglobin) where we attempt to predict the interface of two different proteins rather than two protein domains. Finally, we report here a prediction about the inter-domain contact regions of the heat- shock protein Hsc70 based only on sequence information.

Improving contact predictions by the combination of correlated mutations and other sources of sequence information

We have previously developed a method for predicting interresidue contacts using information about correlated mutations in multiple sequence alignments. The predictions generated with this method were clearly better than random but not enough for their use in de novo protein folding experiments. We assess the possibility of improving contact predictions combining information from the following variables: correlated mutations, sequence conservation, sequence separation along the chain, alignment stability, family size, residue-specific contact occupancy and formation of contact networks. The application of a protocol for combining these independent variables leads to contact predictions that are on average two times better than those obtained initially with correlated mutations. Correlated mutations can be effectively combined with other types of information derived from multiple sequence alignments. Among the different variables tried, sequence conservation and contact density are particularly relevant for the combination with correlated mutations.

Protein folding from a combinatorial perspective

Combinatorial mutagenesis experiments show the existence of many different solutions to the problem of complementary packing of non-polar sidechains in the protein core. They suggest that a significant amount of structural information is carried by the simple pattern of polar and non-polar residues along the polypeptide chain, indicate that the formation of buried polar interactions may be a fundamentally slow step in protein folding and show that proteins with many native properties occur at reasonable frequencies in random sequence libraries.

Double-mutant cycles: a powerful tool for analyzing protein structure and function

A double-mutant cycle involves wild-type protein, two single mutants and the corresponding double mutant protein. If the change in free energy associated with a structural or functional property of the protein upon a double mutation differs from the sum of changes in free energy due to the single mutations, then the residues at the two positions are coupled. Such coupling reflects either direct or indirect interactions between these residues. Double-mutant cycle analysis can be used to measure the strength of intramolecular and intermolecular pairwise interactions in proteins or protein-ligand complexes with known structure. Double-mutant cycles can also be employed to characterize structures that are inaccessible to NMR and X-ray crystallography, such as those of transition states for protein folding, ligand binding and enzyme catalysis, or of membrane proteins. Multidimensional mutant cycle analysis can be used to measure higher-order cooperativity between intramolecular or intermolecular interactions. In the absence of coupling between residues, prediction of mutational effects is possible by assuming their additivity.

Why do protein architectures have Boltzmann-like statistics?

A theoretical study has shown that the occurrence of various structural elements in stable folds of random copolymers is exponentially dependent on the own energy of the element. A similar occurrence-on-energy dependence is observed in globular proteins from the level of amino acid conformations to the level of overall architectures. Thus, the structural features stabilized by many random sequences are typical of globular proteins while the features rarely observed in proteins are those which are stabilized by only a minor part of the random sequences.

Perfect temperature for protein structure prediction and folding

We have investigated the influence of the "noise" of inevitable errors in energetic parameters on protein structure prediction. Because of this noise, only a part of all the interactions operating in a protein chain can be taken into account, and therefore a search for the energy minimum becomes inadequate for protein structure prediction. One can rather rely on statistical mechanics: a calculation carried out at a temperature T* somewhat below that of protein melting gives the best possible, though always approximate prediction. The early stages of protein folding also "take into account" only a part of all the interactions; consequently, the same temperature T* is favorable for the self-organization of native-like intermediates in protein folding.

A phage display system for studying the sequence determinants of protein folding

We have developed a phage display system that provides a means to select variants of the IgG binding domain of peptostreptococcal protein L that fold from large combinatorial libraries. The premise underlying the selection scheme is that binding of protein L to IgG requires that the protein be properly folded. Using a combination of molecular biological and biophysical methods, we show that this assumption is valid. First, the phage selection procedure strongly selects against a point mutation in protein L that disrupts folding but is not in the IgG binding interface. Second, variants recovered from a library in which the first third of protein L was randomized are properly folded. The degree of sequence variation in the selected population is striking: the variants have as many as nine substitutions in the 14 residues that were mutagenized. The approach provides a selection for "foldedness" that is potentially applicable to any small binding protein.

Dissecting the energetics of an antibody-antigen interface by alanine shaving and molecular grafting

Alanine-scanning mutagenesis on human growth hormone (hGH) identified 5 primary determinants (Arg 8, Asn 12, Arg 16, Asp 112, and Asp 116) for binding to a monoclonal antibody (MAb 3) (Jin L, Fendly BM, Wells JA, 1992, J Mol Biol 226:851-865). To further analyze the energetic importance of residues surrounding these five, we mutated all neighboring residues to alanine in groups of 7-16 (a procedure we call alanine shaving). Even the most extremely mutated variant, with 16 alanine substitutions, caused less than a 10-fold reduction in binding affinity to MAb3. By comparison, mutating any 1 of the 5 primary determinants to alanine caused a 6- to > 500-fold reduction in affinity. Replacing any of the 4 charged residues (Arg 8, Arg 16, Asp 112, and Asp 116) with a homologous residue (i.e., Arg to Lys or Asp to Glu) caused nearly as large a reduction in affinity as the corresponding alanine replacement. It was possible to graft the 5 primary binding determinants onto a nonbinding homologue of hGH, human placental lactogen (hPL), which has 86% sequence identity to hGH. The grafted hPL mutant bound 10-fold less tightly than hGH to MAb3 but bound as well as hGH when 2 additional framework mutations were introduced. Attempts to recover binding affinity by grafting the MAb3 epitope onto more distantly related scaffolds having a similar 4-helix bundle motif, such as human prolactin (23% sequence identity) or granulocyte colony-stimulating factor, were unsuccessful.(ABSTRACT TRUNCATED AT 250 WORDS)

Stabilization of myoglobin by multiple alanine substitutions in helical positions

We have carried out a series of multiple Xaa-->Ala changes at nonadjacent surface positions in the sequence of sperm whale myoglobin. Although the corresponding single substitutions do not increase the thermal stability of the protein, multiple substitutions enhance the stability of the resulting myoglobins. The effect observed is an increase in the observed Tm (midpoint unfolding temperature) relative to that predicted from assuming additivity of the free energy changes corresponding to single mutations. The stabilization occurs in the presence of urea, as measured by the dependence of the unfolding temperature on urea concentration. The sites that have been altered occur in different helices and are not close in sequence or in the native structure of myoglobin. The observed effect is consistent with a role of multiple alanines in residual interactions in the unfolded state of the mutant proteins.

Correlated mutations and residue contacts in proteins

The maintenance of protein function and structure constrains the evolution of amino acid sequences. This fact can be exploited to interpret correlated mutations observed in a sequence family as an indication of probable physical contact in three dimensions. Here we present a simple and general method to analyze correlations in mutational behavior between different positions in a multiple sequence alignment. We then use these correlations to predict contact maps for each of 11 protein families and compare the result with the contacts determined by crystallography. For the most strongly correlated residue pairs predicted to be in contact, the prediction accuracy ranges from 37 to 68% and the improvement ratio relative to a random prediction from 1.4 to 5.1. Predicted contact maps can be used as input for the calculation of protein tertiary structure, either from sequence information alone or in combination with experimental information.