Stabilizing proteins from sequence statistics: the interplay of conservation and correlation in triosephosphate isomerase stability

The importance of input sequence set to consensus-derived proteins and their relationship to reconstructed ancestral proteins

A protein sequence encodes its energy landscape-all the accessible conformations, energetics, and dynamics. The evolutionary relationship between sequence and landscape can be probed phylogenetically by compiling a multiple sequence alignment of homologous sequences and generating common ancestors via Ancestral Sequence Reconstruction or a consensus protein containing the most common amino acid at each position. Both ancestral and consensus proteins are often more stable than their extant homologs-questioning the differences between them and suggesting that both approaches serve as general methods to engineer thermostability. We used the Ribonuclease H family to compare these approaches and evaluate how the evolutionary relationship of the input sequences affects the properties of the resulting consensus protein. While the consensus protein derived from our full Ribonuclease H sequence alignment is structured and active, it neither shows properties of a well-folded protein nor has enhanced stability. In contrast, the consensus protein derived from a phylogenetically-restricted set of sequences is significantly more stable and cooperatively folded, suggesting that cooperativity may be encoded by different mechanisms in separate clades and lost when too many diverse clades are combined to generate a consensus protein. To explore this, we compared pairwise covariance scores using a Potts formalism as well as higher-order sequence correlations using singular value decomposition (SVD). We find the SVD coordinates of a stable consensus sequence are close to coordinates of the analogous ancestor sequence and its descendants, whereas the unstable consensus sequences are outliers in SVD space.

Unlocking the potential of enzyme engineering via rational computational design strategies

Enzymes play a pivotal role in various industries by enabling efficient, eco-friendly, and sustainable chemical processes. However, the low turnover rates and poor substrate selectivity of enzymes limit their large-scale applications. Rational computational enzyme design, facilitated by computational algorithms, offers a more targeted and less labor-intensive approach. There has been notable advancement in employing rational computational protein engineering strategies to overcome these issues, it has not been comprehensively reviewed so far. This article reviews recent developments in rational computational enzyme design, categorizing them into three types: structure-based, sequence-based, and data-driven machine learning computational design. Case studies are presented to demonstrate successful enhancements in catalytic activity, stability, and substrate selectivity. Lastly, the article provides a thorough analysis of these approaches, highlights existing challenges and potential solutions, and offers insights into future development directions.

Selection pressures on evolution of ribonuclease H explored with rigorous free-energy-based design

Understanding natural protein evolution and designing novel proteins are motivating interest in development of high-throughput methods to explore large sequence spaces. In this work, we demonstrate the application of multisite λ dynamics (MSλD), a rigorous free energy simulation method, and chemical denaturation experiments to quantify evolutionary selection pressure from sequence-stability relationships and to address questions of design. This study examines a mesophilic phylogenetic clade of ribonuclease H (RNase H), furthering its extensive characterization in earlier studies, focusing on E. coli RNase H (ecRNH) and a more stable consensus sequence (AncCcons) differing at 15 positions. The stabilities of 32,768 chimeras between these two sequences were computed using the MSλD framework. The most stable and least stable chimeras were predicted and tested along with several other sequences, revealing a designed chimera with approximately the same stability increase as AncCcons, but requiring only half the mutations. Comparing the computed stabilities with experiment for 12 sequences reveals a Pearson correlation of 0.86 and root mean squared error of 1.18 kcal/mol, an unprecedented level of accuracy well beyond less rigorous computational design methods. We then quantified selection pressure using a simple evolutionary model in which sequences are selected according to the Boltzmann factor of their stability. Selection temperatures from 110 to 168 K are estimated in three ways by comparing experimental and computational results to evolutionary models. These estimates indicate selection pressure is high, which has implications for evolutionary dynamics and for the accuracy required for design, and suggests accurate high-throughput computational methods like MSλD may enable more effective protein design.

Enhancing luciferase activity and stability through generative modeling of natural enzyme sequences

The availability of natural protein sequences synergized with generative AI provides new paradigms to engineer enzymes. Although active enzyme variants with numerous mutations have been designed using generative models, their performance often falls short of their wild type counterparts. Additionally, in practical applications, choosing fewer mutations that can rival the efficacy of extensive sequence alterations is usually more advantageous. Pinpointing beneficial single mutations continues to be a formidable task. In this study, using the generative maximum entropy model to analyze Renilla luciferase (RLuc) homologs, and in conjunction with biochemistry experiments, we demonstrated that natural evolutionary information could be used to predictively improve enzyme activity and stability by engineering the active center and protein scaffold, respectively. The success rate to improve either luciferase activity or stability of designed single mutants is ~50%. This finding highlights nature's ingenious approach to evolving proficient enzymes, wherein diverse evolutionary pressures are preferentially applied to distinct regions of the enzyme, ultimately culminating in an overall high performance. We also reveal an evolutionary preference in RLuc toward emitting blue light that holds advantages in terms of water penetration compared to other light spectra. Taken together, our approach facilitates navigation through enzyme sequence space and offers effective strategies for computer-aided rational enzyme engineering.

Machine Learning-Guided Protein Engineering

Recent progress in engineering highly promising biocatalysts has increasingly involved machine learning methods. These methods leverage existing experimental and simulation data to aid in the discovery and annotation of promising enzymes, as well as in suggesting beneficial mutations for improving known targets. The field of machine learning for protein engineering is gathering steam, driven by recent success stories and notable progress in other areas. It already encompasses ambitious tasks such as understanding and predicting protein structure and function, catalytic efficiency, enantioselectivity, protein dynamics, stability, solubility, aggregation, and more. Nonetheless, the field is still evolving, with many challenges to overcome and questions to address. In this Perspective, we provide an overview of ongoing trends in this domain, highlight recent case studies, and examine the current limitations of machine learning-based methods. We emphasize the crucial importance of thorough experimental validation of emerging models before their use for rational protein design. We present our opinions on the fundamental problems and outline the potential directions for future research.

Customized multiple sequence alignment as an effective strategy to improve performance of Taq DNA polymerase

Engineering Taq DNA polymerase (TaqPol) for improved activity, stability and sensitivity was critical for its wide applications. Multiple sequence alignment (MSA) has been widely used in engineering enzymes for improved properties. Here, we first designed TaqPol mutations based on MSA of 2756 sequences from both thermophilic and non-thermophilic organisms. Two double mutations were generated including a variant H676F/R677G showing a decrease in both activity and stability, and a variant Y686R/E687K showing an improved activity, but a decreased stability. Mutations targeted on coevolutionary residues of Arg677 and Tyr686 were then applied to rescue stability or activity loss of the double mutants, which achieved a partial success. Sequence analysis revealed that the two mutations are abundant in non-thermophilic sequences but not in thermophilic homologues. Then, a small-scale MSA containing sequences from only thermophilic organisms was applied to predict 13 single variants and two of them, E507Q and E734N showed a simultaneous increase in both stability and activity, even in sensitivity. A customized MSA was hence more effective in engineering a thermophilic enzyme and could be used in engineering other enzymes. Molecular dynamics simulations revealed the impact of mutations on the protein dynamics and interactions between TaqPol and substrates. KEY POINTS: • The pool of sequence for alignment is critical to engineering Taq DNA polymerase. • The variants with low properties can be rescued by mutations in coevolving network. • Improving binding with DNA can improve DNA polymerase stability and activity.

LibGENiE - A bioinformatic pipeline for the design of information-enriched enzyme libraries

Enzymes are potent catalysts with high specificity and selectivity. To leverage nature's synthetic potential for industrial applications, various protein engineering techniques have emerged which allow to tailor the catalytic, biophysical, and molecular recognition properties of enzymes. However, the many possible ways a protein can be altered forces researchers to carefully balance between the exhaustiveness of an enzyme screening campaign and the required resources. Consequently, the optimal engineering strategy is often defined on a case-by-case basis. Strikingly, while predicting mutations that lead to an improved target function is challenging, here we show that the prediction and exclusion of deleterious mutations is a much more straightforward task as analyzed for an engineered carbonic acid anhydrase, a transaminase, a squalene-hopene cyclase and a Kemp eliminase. Combining such a pre-selection of allowed residues with advanced gene synthesis methods opens a path toward an efficient and generalizable library construction approach for protein engineering. To give researchers easy access to this methodology, we provide the website LibGENiE containing the bioinformatic tools for the library design workflow.

The importance of input sequence set to consensus-derived proteins and their relationship to reconstructed ancestral proteins

A protein sequence encodes its energy landscape - all the accessible conformations, energetics, and dynamics. The evolutionary relationship between sequence and landscape can be probed phylogenetically by compiling a multiple sequence alignment of homologous sequences and generating common ancestors via Ancestral Sequence Reconstruction or a consensus protein containing the most common amino acid at each position. Both ancestral and consensus proteins are often more stable than their extant homologs - questioning the differences and suggesting that both approaches serve as general methods to engineer thermostability. We used the Ribonuclease H family to compare these approaches and evaluate how the evolutionary relationship of the input sequences affects the properties of the resulting consensus protein. While the overall consensus protein is structured and active, it neither shows properties of a well-folded protein nor has enhanced stability. In contrast, the consensus protein derived from a phylogenetically-restricted region is significantly more stable and cooperatively folded, suggesting that cooperativity may be encoded by different mechanisms in separate clades and lost when too many diverse clades are combined to generate a consensus protein. To explore this, we compared pairwise covariance scores using a Potts formalism as well as higher-order couplings using singular value decomposition (SVD). We find the SVD coordinates of a stable consensus sequence are close to coordinates of the analogous ancestor sequence and its descendants, whereas the unstable consensus sequences are outliers in SVD space.

Improving antibody thermostability based on statistical analysis of sequence and structural consensus data

Background

The use of Monoclonal Antibodies (MAbs) as therapeutics has been increasing over the past 30 years due to their high specificity and strong affinity towards the target. One of the major challenges towarding their use as drugs is their low thermostability, which impacts both efficacy as well as manufacturing and delivery.

Methods

To aid the design of thermally more stable mutants, consensus sequence-based method has been widely used. These methods typically have a success rate of about 50% with maximum melting temperature increment ranging from 10 to 32 °C. In order to improve the prediction performance, we have developed a new and fast MAbs specific method by adding a 3D structural layer to the consensus sequence method. This is done by analyzing the close-by residue pairs which are conserved in more than eight hundred MAbs’ 3D structures.

Results

Combining consensus sequence and structural residue pair covariance methods, we developed an in-house application for predicting human MAb thermostability to guide protein engineers to design stable molecules. Major advantage of this structural level assessment is in significantly reducing the false positives by almost half from the consensus sequence method alone. This application has shown success in designing MAb engineering panels in multiple biologics programs.

Conclusions

Our data science-based method shows impacts in Mab engineering.

Computer-Aided Targeted Mutagenesis of Thermoclostridium caenicola d-Allulose 3-Epimerase for Improved Thermostability

d-Allulose 3-epimerase (DAEase) is a key enzyme in d-allulose bioproduction. DAEase from Thermoclostridium caenicola suffers from poor thermostability, hampering its large-scale applications in industry. In this study, mutants A70P, G107P, F155Y, and D162T with increased melting point temperature (T_m) were obtained by targeted mutagenesis based on the calculation of the free energy of folding. The optimal single-point mutant G107P showed 11.08 h, 5, and 5.70 °C increases in the values of half-life (t_1/2) at 60 °C, the optimum temperature (T_opt), and T_m, respectively. Beneficial mutations were combined by ordered recombination mutagenesis, and the combinational mutant Var3 (G107P/F155Y/D162T/A70P) was generated with ΔT_opt of 10 °C and ΔT_m of 12.25 °C. Its t_1/2 value at 65 °C was more than 140 times higher than that of the wild-type enzyme. Molecular dynamics simulations and homology modeling analysis indicated that the enhanced overall rigidity, increased hydrogen bonds between subunits, and redistributed surface electrostatic charges might be responsible for the improved thermostability of the mutant Var3.

Rational-Design Engineering to Improve Enzyme Thermostability

The fundamentals of thermostability engineering need to be carried out for proteins with low thermal stability to expand their utilization. Thus, comprehension of the thermal stability regulating factors of proteins is needful for the engineering of their thermostability. Protein engineering aims to overcome their natural limitations in tough conditions by refining protein stability and activity. Rational-design approach requires a crystal structure dataset along with the biophysical information, protein function, and sequence-based data, especially consensus sequence that is favorable for the protein folding during natural evolution. It can be attained by either single- or multiple-point mutation, by which amino acids are changed. In fact, these mutation approaches show several benefits. For example, the offered mutations are produced after an evaluation and design, which raise the chance to acquire favorable mutations. The rational-design engineering can improve the biochemical properties of enzymes, including the kinetic behaviors, substrate specificity, thermostability, and organic solvent tolerance. Moreover, this approach considerably reduces the library size, so less effort and time can be employed. Here, we apply the computational algorithms and programs with experiments to create thermostable enzymes that will be beneficial for future applications.

Surface residues and non-additive interactions stabilize a consensus homeodomain protein

Despite the widely reported success of consensus design in producing highly stabilized proteins, little is known about the physical mechanisms underlying this stabilization. Here we explore the potential sources of stabilization by performing a systematic analysis of the 29 substitutions that we previously found to collectively stabilize a consensus homeodomain compared to an extant homeodomain. By separately introducing groups of consensus substitutions that alter or preserve charge state, occur at varying degrees of residue burial, and occur at positions of varying degrees of conservation, we determine the extent to which these three features contribute to the consensus stability enhancement. Surprisingly, we find that the largest total contribution to stability comes from consensus substitutions on the protein surface and that the largest per-substitution contributions come from substitutions that maintain charge state. This finding suggests that although consensus proteins are often enriched in charged residues, consensus stabilization does not result primarily from interactions involving charged residues. Although consensus substitutions at strongly conserved positions also contribute disproportionately to stabilization, significant stabilization is also contributed from substitutions at weakly conserved positions. Furthermore, we find that identical consensus substitutions show larger stabilizing effects when introduced into the consensus background than when introduced into an extant homeodomain, indicating that synergistic, stabilizing interactions among the consensus residues contribute to consensus stability enhancement of the homeodomain. By measuring DNA binding affinity for the same set of variants, we find that although consensus design of the homeodomain increases both affinity and folding stability, it does so using a largely non-overlapping set of substitutions.

Synergistic stabilization of a double mutant in chymotrypsin inhibitor 2 from a library screen in E. coli

Most single point mutations destabilize folded proteins. Mutations that stabilize a protein typically only have a small effect and multiple mutations are often needed to substantially increase the stability. Multiple point mutations may act synergistically on the stability, and it is often not straightforward to predict their combined effect from the individual contributions. Here, we have applied an efficient in-cell assay in E. coli to select variants of the barley chymotrypsin inhibitor 2 with increased stability. We find two variants that are more than 3.8 kJ mol-1 more stable than the wild-type. In one case, the increased stability is the effect of the single substitution D55G. The other case is a double mutant, L49I/I57V, which is 5.1 kJ mol-1 more stable than the sum of the effects of the individual mutations. In addition to demonstrating the strength of our selection system for finding stabilizing mutations, our work also demonstrate how subtle conformational effects may modulate stability.

Partial Consensus Design and Enhancement of Protein Function by Secondary-Structure-Guided Consensus Mutations

Consensus design (CD) is a representative sequence-based protein design method that enables the design of highly functional proteins by analyzing vast amounts of protein sequence data. This study proposes a partial consensus design (PCD) of a protein as a derivative approach of CD. The method replaces the target protein sequence with a consensus sequence in a secondary-structure-dependent manner (i.e., regionally dependent and divided into α-helix, β-sheet, and loop regions). In this study, we generated several artificial partial consensus l-threonine 3-dehydrogenases (PcTDHs) by PCD using the TDH from Cupriavidus necator (CnTDH) as a target protein. Structural and functional analysis of PcTDHs suggested that thermostability would be independently improved when consensus mutations are introduced into the loop region of TDHs. On the other hand, enzyme kinetic parameters (k_cat/K_m) and average productivity would be synergistically enhanced by changing the combination of the mutations-replacement of one region of CnTDH with a consensus sequence provided only negative effects, but the negative effects were nullified when the two regions were replaced simultaneously. Taken together, we propose the hypothesis that there are protein regions that encode individual protein properties, such as thermostability and activity, and that the introduction of consensus mutations into these regions could additively or synergistically modify their functions.

De novo sequence redesign of a functional Ras-binding domain globally inverted the surface charge distribution and led to extreme thermostability

To acquire extremely thermostable proteins of given functions is challenging for conventional protein engineering. Here we applied ABACUS, a statistical energy function we developed for de novo amino acid sequence design, to globally redesign a Ras-binding domain (RBD), and obtained an extremely thermostable RBD that unfolds reversibly at above 110°C, the redesigned RBD experimentally confirmed to have expected structure and Ras-binding interface. Directed evolution of the redesigned RBD improved its Ras-binding affinity to the native protein level without excessive loss of thermostability. The designed amino acid substitutions were mostly at the protein surface. For many substitutions, strong epistasis or significantly differentiated effects on thermostability in the native sequence context relative to the redesigned sequence context were observed, suggesting the globally redesigned sequence to be unreachable through combining beneficial mutations of the native sequence. Further analyses revealed that by replacing 38 of a total of 48 non-interfacial surface residues at once, ABACUS redesign was able to globally "invert" the protein's charge distribution pattern in an optimized way. Our study demonstrates that computational protein design provides powerful new tools to solve challenging protein engineering problems.

Computational design of enzymes for biotechnological applications

Enzymes are the natural catalysts that execute biochemical reactions upholding life. Their natural effectiveness has been fine-tuned as a result of millions of years of natural evolution. Such catalytic effectiveness has prompted the use of biocatalysts from multiple sources on different applications, including the industrial production of goods (food and beverages, detergents, textile, and pharmaceutics), environmental protection, and biomedical applications. Natural enzymes often need to be improved by protein engineering to optimize their function in non-native environments. Recent technological advances have greatly facilitated this process by providing the experimental approaches of directed evolution or by enabling computer-assisted applications. Directed evolution mimics the natural selection process in a highly accelerated fashion at the expense of arduous laboratory work and economic resources. Theoretical methods provide predictions and represent an attractive complement to such experiments by waiving their inherent costs. Computational techniques can be used to engineer enzymatic reactivity, substrate specificity and ligand binding, access pathways and ligand transport, and global properties like protein stability, solubility, and flexibility. Theoretical approaches can also identify hotspots on the protein sequence for mutagenesis and predict suitable alternatives for selected positions with expected outcomes. This review covers the latest advances in computational methods for enzyme engineering and presents many successful case studies.

FireProtASR: A Web Server for Fully Automated Ancestral Sequence Reconstruction

There is a great interest in increasing proteins’ stability to widen their usability in numerous biomedical and biotechnological applications. However, native proteins cannot usually withstand the harsh industrial environment, since they are evolved to function under mild conditions. Ancestral sequence reconstruction is a well-established method for deducing the evolutionary history of genes. Besides its applicability to discover the most probable evolutionary ancestors of the modern proteins, ancestral sequence reconstruction has proven to be a useful approach for the design of highly stable proteins. Recently, several computational tools were developed, which make the ancestral reconstruction algorithms accessible to the community, while leaving the most crucial steps of the preparation of the input data on users’ side. FireProt^ASR aims to overcome this obstacle by constructing a fully automated workflow, allowing even the unexperienced users to obtain ancestral sequences based on a sequence query as the only input. FireProt^ASR is complemented with an interactive, easy-to-use web interface and is freely available at https://loschmidt.chemi.muni.cz/fireprotasr/.

Improved thermostability of creatinase from Alcaligenes Faecalis through non-biased phylogenetic consensus-guided mutagenesis

Background

Enzymatic quantification of creatinine has become an essential method for clinical evaluation of renal function. Although creatinase (CR) is frequently used for this purpose, its poor thermostability severely limits industrial applications. Herein, we report a novel creatinase from Alcaligenes faecalis (afCR) with higher catalytic activity and lower K_M value, than currently used creatinases. Furthermore, we developed a non-biased phylogenetic consensus method to improve the thermostability of afCR.

Results

We applied a non-biased phylogenetic consensus method to identify 59 candidate consensus residues from 24 creatinase family homologs for screening afCR mutants with improved thermostability. Twenty-one amino acids of afCR were selected to mutagenesis and 11 of them exhibited improved thermostability compared to the parent enzyme (afCR-M0). Combination of single-site mutations in sequential screens resulted in a quadruple mutant D17V/T199S/L6P/T251C (M4-2) which showed ~ 1700-fold enhanced half-life at 57 °C and a 4.2 °C higher T₅₀¹⁵ than that of afCR-M0. The mutant retained catalytic activity equivalent to afCR-M0, and thus showed strong promise for application in creatinine detection. Structural homology modeling revealed a wide range of potential molecular interactions associated with individual mutations that contributed to improving afCR thermostability.

Conclusions

Results of this study clearly demonstrated that the non-biased-phylogenetic consensus design for improvement of thermostability in afCR is effective and promising in improving the thermostability of more enzymes.

The use of consensus sequence information to engineer stability and activity in proteins

The goal of protein design is to create proteins that are stable, soluble, and active. Here we focus on one approach to protein design in which sequence information is used to create a "consensus" sequence. Such consensus sequences comprise the most common residue at each position in a multiple sequence alignment (MSA). After describing some general ideas that relate MSA and consensus sequences and presenting a statistical thermodynamic framework that relates consensus and non-consensus sequences to stability, we detail the process of designing a consensus sequence and survey reports of consensus design and characterization from the literature. Many of these consensus proteins retain native biological activities including ligand binding and enzyme activity. Remarkably, in most cases the consensus protein shows significantly higher stability than extant versions of the protein, as measured by thermal or chemical denaturation, consistent with the statistical thermodynamic model. To understand this stability increase, we compare various features of consensus sequences with the extant MSA sequences from which they were derived. Consensus sequences show enrichment in charged residues (most notably glutamate and lysine) and depletion of uncharged polar residues (glutamine, serine, and asparagine). Surprisingly, a survey of stability changes resulting from point substitutions show little correlation with residue frequencies at the corresponding positions within the MSA, suggesting that the high stability of consensus proteins may result from interactions among residue pairs or higher-order clusters. Whatever the source, the large number of reported successes demonstrates that consensus design is a viable route to generating active and in many cases highly stabilized proteins.

Analysis of Amylin Consensus Sequences Suggests That Human Amylin Is Not Optimized to Minimize Amyloid Formation and Provides Clues to Factors That Modulate Amyloidogenicity

The neuropancreatic polypeptide hormone amylin forms pancreatic islet amyloid in type-2 diabetes. Islet amyloid formation contributes to β-cell death in the disease and to the failure of islet transplants, but the features which influence amylin amyloidogenicity are not understood. We constructed an amino acid sequence alignment of 202 sequences of amylin and used the alignment to design consensus sequences of vertebrate amylins, mammalian amylins, and primate amylins. Amylin is highly conserved, but there are differences between human amylin and each consensus sequence, ranging from one to six substitutions. Biophysical analysis shows that all of the consensus sequences form amyloid but do so more slowly than human amylin in vitro. The rate of amyloid formation by the primate consensus sequence is 3- to 4-fold slower than human amylin; the mammalian consensus sequence is approximately 20- to 25-fold slower, and the vertebrate consensus sequence is approximately 6-fold slower. All of the consensus sequences are moderately less toxic than human amylin toward a cultured β-cell line, with the vertebrate consensus sequence displaying the largest reduction in toxicity of 3- to 4-fold. All of the consensus sequences activate a human amylin receptor and exhibit only modest reductions in activity, ranging from 3- to 4-fold as judged by a cAMP production assay. The analysis argues that there is no strong selective evolutionary pressure to avoid the formation of islet amyloid and provides information relevant to the design of less amyloidogenic amylin variants.

Consensus Design of an Evolved High-Redox Potential Laccase

Among the broad repertory of protein engineering methods that set out to improve stability, consensus design has proved to be a powerful strategy to stabilize enzymes without compromising their catalytic activity. Here, we have applied an in-house consensus method to stabilize a laboratory evolved high-redox potential laccase. Multiple sequence alignments were carried out and computationally refined by applying relative entropy and mutual information thresholds. Through this approach, an ensemble of 20 consensus mutations were identified, 18 of which were consensus/ancestral mutations. The set of consensus variants was produced in Saccharomyces cerevisiae and analyzed individually, while site directed recombination of the best mutations did not produce positive epistasis. The best single variant carried the consensus-ancestral A240G mutation in the neighborhood of the T2/T3 copper cluster, which dramatically improved thermostability, kinetic parameters and secretion.

Disease-relevant mutations alter amino acid co-evolution networks in the second nucleotide binding domain of CFTR

Cystic Fibrosis (CF) is an inherited disease caused by mutations in the cystic fibrosis transmembrane conductance regulator (CFTR) ion channel. Mutations in CFTR cause impaired chloride ion transport in the epithelial tissues of patients leading to cardiopulmonary decline and pancreatic insufficiency in the most severely affected patients. CFTR is composed of twelve membrane-spanning domains, two nucleotide-binding domains (NBDs), and a regulatory domain. The most common mutation in CFTR is a deletion of phenylalanine at position 508 (ΔF508) in NBD1. Previous research has primarily concentrated on the structure and dynamics of the NBD1 domain; However numerous pathological mutations have also been found in the lesser-studied NBD2 domain. We have investigated the amino acid co-evolved network of interactions in NBD2, and the changes that occur in that network upon the introduction of CF and CF-related mutations (S1251N(T), S1235R, D1270N, N1303K(T)). Extensive coupling between the α- and β-subdomains were identified with residues in, or near Walker A, Walker B, H-loop and C-loop motifs. Alterations in the predicted residue network varied from moderate for the S1251T perturbation to more severe for N1303T. The S1235R and D1270N networks varied greatly compared to the wildtype, but these CF mutations only affect ion transport preference and do not severely disrupt CFTR function, suggesting dynamic flexibility in the network of interactions in NBD2. Our results also suggest that inappropriate interactions between the β-subdomain and Q-loop could be detrimental. We also identified mutations predicted to stabilize the NBD2 residue network upon introduction of the CF and CF-related mutations, and these predicted mutations are scored as benign by the MUTPRED2 algorithm. Our results suggest the level of disruption of the co-evolution predictions of the amino acid networks in NBD2 does not have a straightforward correlation with the severity of the CF phenotypes observed.

Phylogenetic spread of sequence data affects fitness of consensus enzymes: Insights from triosephosphate isomerase

The concept of consensus in multiple sequence alignments (MSAs) has been used to design and engineer proteins previously with some success. However, consensus design implicitly assumes that all amino acid positions function independently, whereas in reality, the amino acids in a protein interact with each other and work cooperatively to produce the optimum structure required for its function. Correlation analysis is a tool that can capture the effect of such interactions. In a previously published study, we made consensus variants of the triosephosphate isomerase (TIM) protein using MSAs that included sequences form both prokaryotic and eukaryotic organisms. These variants were not completely native-like and were also surprisingly different from each other in terms of oligomeric state, structural dynamics, and activity. Extensive correlation analysis of the TIM database has revealed some clues about factors leading to the unusual behavior of the previously constructed consensus proteins. Among other things, we have found that the more ill-behaved consensus mutant had more broken correlations than the better-behaved consensus variant. Moreover, we report three correlation and phylogeny-based consensus variants of TIM. These variants were more native-like than the previous consensus mutants and considerably more stable than a wild-type TIM from a mesophilic organism. This study highlights the importance of choosing the appropriate diversity of MSA for consensus analysis and provides information that can be used to engineer stable enzymes.

FireProt: web server for automated design of thermostable proteins

There is a continuous interest in increasing proteins stability to enhance their usability in numerous biomedical and biotechnological applications. A number of in silico tools for the prediction of the effect of mutations on protein stability have been developed recently. However, only single-point mutations with a small effect on protein stability are typically predicted with the existing tools and have to be followed by laborious protein expression, purification, and characterization. Here, we present FireProt, a web server for the automated design of multiple-point thermostable mutant proteins that combines structural and evolutionary information in its calculation core. FireProt utilizes sixteen tools and three protein engineering strategies for making reliable protein designs. The server is complemented with interactive, easy-to-use interface that allows users to directly analyze and optionally modify designed thermostable mutants. FireProt is freely available at http://loschmidt.chemi.muni.cz/fireprot.

Consensus sequence design as a general strategy to create hyperstable, biologically active proteins

Consensus sequence design offers a promising strategy for designing proteins of high stability while retaining biological activity since it draws upon an evolutionary history in which residues important for both stability and function are likely to be conserved. Although there have been several reports of successful consensus design of individual targets, it is unclear from these anecdotal studies how often this approach succeeds and how often it fails. Here, we attempt to assess generality by designing consensus sequences for a set of six protein families with a range of chain lengths, structures, and activities. We characterize the resulting consensus proteins for stability, structure, and biological activities in an unbiased way. We find that all six consensus proteins adopt cooperatively folded structures in solution. Strikingly, four of six of these consensus proteins show increased thermodynamic stability over naturally occurring homologs. Each consensus protein tested for function maintained at least partial biological activity. Although peptide binding affinity by a consensus-designed SH3 is rather low, K _m values for consensus enzymes are similar to values from extant homologs. Although consensus enzymes are slower than extant homologs at low temperature, they are faster than some thermophilic enzymes at high temperature. An analysis of sequence properties shows consensus proteins to be enriched in charged residues, and rarified in uncharged polar residues. Sequence differences between consensus and extant homologs are predominantly located at weakly conserved surface residues, highlighting the importance of these residues in the success of the consensus strategy.

Consensus designs and thermal stability determinants of a human glutamate transporter

Human excitatory amino acid transporters (EAATs) take up the neurotransmitter glutamate in the brain and are essential to maintain excitatory neurotransmission. Our understanding of the EAATs’ molecular mechanisms has been hampered by the lack of stability of purified protein samples for biophysical analyses. Here, we present approaches based on consensus mutagenesis to obtain thermostable EAAT1 variants that share up to ~95% amino acid identity with the wild type transporters, and remain natively folded and functional. Structural analyses of EAAT1 and the consensus designs using hydrogen-deuterium exchange linked to mass spectrometry show that small and highly cooperative unfolding events at the inter-subunit interface rate-limit their thermal denaturation, while the transport domain unfolds at a later stage in the unfolding pathway. Our findings provide structural insights into the kinetic stability of human glutamate transporters, and introduce general approaches to extend the lifetime of human membrane proteins for biophysical analyses.

Consensus design for improved thermostability of lipoxygenase from Anabaena sp. PCC 7120

Background

Lipoxygenase (LOX) from Anabaena sp. PCC 7120 (Ana-rLOX) offers important applications in the food industry, especially for improving aroma and dough rheological properties. However, industrial applications of LOXs have been limited by their poor thermostability. Herein, we report a bioinformatics-based consensus concept approach for the engineering of thermostable Ana-rLOX.

Results

A series of mutations (N130D, G260A, S437T, N130D/G260Q, N130D/S437Y) showed higher thermostability and activity than the wild-type enzyme. Thus, N130D/G260Q exhibited a 6.6-fold increase in half-life and 2.45 °C increase in unfolding temperature; N130D/S437Y showed a 10 °C increase in optimal temperature. The secondary structure did not change much that contributed to improved thermostability were investigated in detail using circular dichroism. Homology modeling suggested that enhanced thermostability and specific activity may result from favorable hydrophobic interactions.

Conclusions

A series of mutations were achieved, showing higher thermostability and activity than the wild-type enzyme by semi-rational mutagenesis with limited structure information. Our findings provide important new insights into molecular modifications aimed at improving Ana-rLOX thermostability and activity.

Electronic supplementary material

The online version of this article (10.1186/s12896-018-0468-4) contains supplementary material, which is available to authorized users.

Phylogenetic divergence of cell biological features

Most cellular features have a range of states, but understanding the mechanisms responsible for interspecific divergence is a challenge for evolutionary cell biology. Models are developed for the distribution of mean phenotypes likely to evolve under the joint forces of mutation and genetic drift in the face of constant selection pressures. Mean phenotypes will deviate from optimal states to a degree depending on the effective population size, potentially leading to substantial divergence in the absence of diversifying selection. The steady-state distribution for the mean can even be bimodal, with one domain being largely driven by selection and the other by mutation pressure, leading to the illusion of phenotypic shifts being induced by movement among alternative adaptive domains. These results raise questions as to whether lineage-specific selective pressures are necessary to account for interspecific divergence, providing a possible platform for the establishment of null models for the evolution of cell-biological traits.

Benchmark Analysis of Native and Artificial NAD+-Dependent Enzymes Generated by a Sequence-Based Design Method with or without Phylogenetic Data

The expansion of protein sequence databases has enabled us to design artificial proteins by sequence-based design methods, such as full-consensus design (FCD) and ancestral-sequence reconstruction (ASR). Artificial proteins with enhanced activity levels compared with native ones can potentially be generated by such methods, but successful design is rare because preparing a sequence library by curating the database and selecting a method is difficult. Utilizing a curated library prepared by reducing conservation energies, we successfully designed two artificial l-threonine 3-dehydrogenases (SDR-TDH) with higher activity levels than native SDR-TDH, FcTDH-N1, and AncTDH, using FCD and ASR, respectively. The artificial SDR-TDHs had excellent thermal stability and NAD⁺ recognition compared to native SDR-TDH from Cupriavidus necator (CnTDH); the melting temperatures of FcTDH-N1 and AncTDH were about 10 and 5 °C higher than that of CnTDH, respectively, and the dissociation constants toward NAD⁺ of FcTDH-N1 and AncTDH were 2- and 7-fold lower than that of CnTDH, respectively. Enzymatic efficiency of the artificial SDR-TDHs were comparable to that of CnTDH. Crystal structures of FcTDH-N1 and AncTDH were determined at 2.8 and 2.1 Å resolution, respectively. Structural and MD simulation analysis of the SDR-TDHs indicated that only the flexibility at specific regions was changed, suggesting that multiple mutations introduced in the artificial SDR-TDHs altered their flexibility and thereby affected their enzymatic properties. Benchmark analysis of the SDR-TDHs indicated that both FCD and ASR can generate highly functional proteins if a curated library is prepared appropriately.

Phylogenetic spread of sequence data affects fitness of SOD1 consensus enzymes: Insights from sequence statistics and structural analyses

Non-natural protein sequences with native-like structures and functions can be constructed successfully using consensus design. This design strategy is relatively well understood in repeat proteins with simple binding function, however detailed studies are lacking in globular enzymes. The SOD1 family is a good model for such studies due to the availability of large amount of sequence and structure data motivated by involvement of human SOD1 in the fatal motor neuron disease amyotrophic lateral sclerosis (ALS). We constructed two consensus SOD1 enzymes from multiple sequence alignments from all organisms and eukaryotic organisms. A significant difference in their catalytic activities shows that the phylogenetic spread of the sequences used affects the fitness of the construct obtained. A mutation in an electrostatic loop and overall design incompatibilities between bacterial and eukaryotic sequences were implicated in this disparity. Based on this analysis, a bioinformatics approach was used to classify mutations thought to cause familial ALS providing a unique high level view of the physical basis of disease-causing aggregation of human SOD1.

Review: Engineering of thermostable enzymes for industrial applications

The catalytic properties of some selected enzymes have long been exploited to carry out efficient and cost-effective bioconversions in a multitude of research and industrial sectors, such as food, health, cosmetics, agriculture, chemistry, energy, and others. Nonetheless, for several applications, naturally occurring enzymes are not considered to be viable options owing to their limited stability in the required working conditions. Over the years, the quest for novel enzymes with actual potential for biotechnological applications has involved various complementary approaches such as mining enzyme variants from organisms living in extreme conditions (extremophiles), mimicking evolution in the laboratory to develop more stable enzyme variants, and more recently, using rational, computer-assisted enzyme engineering strategies. In this review, we provide an overview of the most relevant enzymes that are used for industrial applications and we discuss the strategies that are adopted to enhance enzyme stability and/or activity, along with some of the most relevant achievements. In all living species, many different enzymes catalyze fundamental chemical reactions with high substrate specificity and rate enhancements. Besides specificity, enzymes also possess many other favorable properties, such as, for instance, cost-effectiveness, good stability under mild pH and temperature conditions, generally low toxicity levels, and ease of termination of activity. As efficient natural biocatalysts, enzymes provide great opportunities to carry out important chemical reactions in several research and industrial settings, ranging from food to pharmaceutical, cosmetic, agricultural, and other crucial economic sectors.

Thermal stabilization of the deglycating enzyme Amadoriase I by rational design

Amadoriases are a class of FAD-dependent enzymes that are found in fungi, yeast and bacteria and that are able to hydrolyze glycated amino acids, cleaving the sugar moiety from the amino acidic portion. So far, engineered Amadoriases have mostly found practical application in the measurement of the concentration of glycated albumin in blood samples. However, these engineered forms of Amadoriases show relatively low absolute activity and stability levels, which affect their conditions of use. Therefore, enzyme stabilization is desirable prior to function-altering molecular engineering. In this work, we describe a rational design strategy based on a computational screening method to evaluate a library of potentially stabilizing disulfide bonds. Our approach allowed the identification of two thermostable Amadoriase I mutants (SS03 and SS17) featuring a significantly higher T₅₀ (55.3 °C and 60.6 °C, respectively) compared to the wild-type enzyme (52.4 °C). Moreover, SS17 shows clear hyperstabilization, with residual activity up to 95 °C, whereas the wild-type enzyme is fully inactive at 55 °C. Our computational screening method can therefore be considered as a promising approach to expedite the design of thermostable enzymes.

FoldX as Protein Engineering Tool: Better Than Random Based Approaches?

Improving protein stability is an important goal for basic research as well as for clinical and industrial applications but no commonly accepted and widely used strategy for efficient engineering is known. Beside random approaches like error prone PCR or physical techniques to stabilize proteins, e.g. by immobilization, in silico approaches are gaining more attention to apply target-oriented mutagenesis. In this review different algorithms for the prediction of beneficial mutation sites to enhance protein stability are summarized and the advantages and disadvantages of FoldX are highlighted. The question whether the prediction of mutation sites by the algorithm FoldX is more accurate than random based approaches is addressed.

Principles of Protein Stability and Their Application in Computational Design

Proteins are increasingly used in basic and applied biomedical research. Many proteins, however, are only marginally stable and can be expressed in limited amounts, thus hampering research and applications. Research has revealed the thermodynamic, cellular, and evolutionary principles and mechanisms that underlie marginal stability. With this growing understanding, computational stability design methods have advanced over the past two decades starting from methods that selectively addressed only some aspects of marginal stability. Current methods are more general and, by combining phylogenetic analysis with atomistic design, have shown drastic improvements in solubility, thermal stability, and aggregation resistance while maintaining the protein's primary molecular activity. Stability design is opening the way to rational engineering of improved enzymes, therapeutics, and vaccines and to the application of protein design methodology to large proteins and molecular activities that have proven challenging in the past.

The visualCMAT: A web-server to select and interpret correlated mutations/co-evolving residues in protein families

The visualCMAT web-server was designed to assist experimental research in the fields of protein/enzyme biochemistry, protein engineering, and drug discovery by providing an intuitive and easy-to-use interface to the analysis of correlated mutations/co-evolving residues. Sequence and structural information describing homologous proteins are used to predict correlated substitutions by the Mutual information-based CMAT approach, classify them into spatially close co-evolving pairs, which either form a direct physical contact or interact with the same ligand (e.g. a substrate or a crystallographic water molecule), and long-range correlations, annotate and rank binding sites on the protein surface by the presence of statistically significant co-evolving positions. The results of the visualCMAT are organized for a convenient visual analysis and can be downloaded to a local computer as a content-rich all-in-one PyMol session file with multiple layers of annotation corresponding to bioinformatic, statistical and structural analyses of the predicted co-evolution, or further studied online using the built-in interactive analysis tools. The online interactivity is implemented in HTML5 and therefore neither plugins nor Java are required. The visualCMAT web-server is integrated with the Mustguseal web-server capable of constructing large structure-guided sequence alignments of protein families and superfamilies using all available information about their structures and sequences in public databases. The visualCMAT web-server can be used to understand the relationship between structure and function in proteins, implemented at selecting hotspots and compensatory mutations for rational design and directed evolution experiments to produce novel enzymes with improved properties, and employed at studying the mechanism of selective ligand's binding and allosteric communication between topologically independent sites in protein structures. The web-server is freely available at https://biokinet.belozersky.msu.ru/visualcmat and there are no login requirements.

Rational identification of aggregation hotspots based on secondary structure and amino acid hydrophobicity

Insolubility of proteins expressed in the Escherichia coli expression system hinders the progress of both basic and applied research. Insoluble proteins contain residues that decrease their solubility (aggregation hotspots). Mutating these hotspots to optimal amino acids is expected to improve protein solubility. To date, however, the identification of these hotspots has proven difficult. In this study, using a combination of approaches involving directed evolution and primary sequence analysis, we found two rules to help inductively identify hotspots: the α-helix rule, which focuses on the hydrophobicity of amino acids in the α-helix structure, and the hydropathy contradiction rule, which focuses on the difference in hydrophobicity relative to the corresponding amino acid in the consensus protein. By properly applying these two rules, we succeeded in improving the probability that expressed proteins would be soluble. Our methods should facilitate research on various insoluble proteins that were previously difficult to study due to their low solubility.

Global and cell-type specific properties of lincRNAs with ribosome occupancy

Advances in transcriptomics have led to the discovery of a large number of long intergenic non-coding RNAs (lincRNAs), which are now recognized as important regulators of diverse cellular processes. Although originally thought to be non-coding, recent studies have revealed that many lincRNAs are bound by ribosomes, with a few lincRNAs even having ability to generate micropeptides. The question arises: how widespread the translation of lincRNAs may be and whether such translation is likely to be functional. To better understand biological relevance of lincRNA translation, we systematically characterized lincRNAs with ribosome occupancy by the expression, structural, sequence, evolutionary and functional features for eight human cell lines, revealed that lincRNAs with ribosome occupancy have remarkably distinctive properties compared with those without ribosome occupancy, indicating that translation has important biological implication in categorizing and annotating lincRNAs. Further analysis revealed lincRNAs exhibit remarkable cell-type specificity with differential translational repertoires and substantial discordance in functionality. Collectively, our analyses provide the first attempt to characterize global and cell-type specific properties of translation of lincRNAs in human cells, highlighting that translation of lincRNAs has clear molecular, evolutionary and functional implications. This study will facilitate better understanding of the diverse functions of lincRNAs.

Creating a Homeodomain with High Stability and DNA Binding Affinity by Sequence Averaging

There is considerable interest in generating proteins with both high stability and high activity for biomedical and industrial purposes. One approach that has been used successfully to increase the stability of linear repeat proteins is consensus design. It is unclear the extent over which the consensus design approach can be used to produce folded and hyperstable proteins, and importantly, whether such stabilized proteins would retain function. Here we extend the consensus strategy to design a globular protein. We show that a consensus-designed homeodomain (HD) sequence adopts a cooperatively folded homeodomain structure. The unfolding free energy of the consensus-HD is 5 kcal·mol^-1 higher than that of the naturally occurring engrailed-HD from Drosophila melanogaster. Remarkably, the consensus-HD binds the engrailed-HD cognate DNA in a similar mode as the engrailed-HD with approximately 100-fold higher affinity. ¹⁵N relaxation studies show a decrease in ps-ns backbone dynamics in the free state of consensus-HD, suggesting that increased affinity is not a result of increased plasticity. In addition to demonstrating the potential for consensus design of globular proteins with increased stability, these results demonstrate that greatly stabilized proteins can bind cognate substrates with increased affinities, showing that high stability is compatible with function.

Protein Stability: Enhancement and Measurement

This article defines protein stability, emphasizes its importance and surveys the field of protein stabilization, with summary reference to a selection of 2009-2015 publications. One can enhance stability by, in particular, protein engineering strategies and by chemical modification (including conjugation) in solution. General protocols are set out on how to measure a given protein's (1) kinetic thermal stability, and (2) oxidative stability, and (3) how to undertake chemical modification of a protein in solution.

Pairwise contact energy statistical potentials can help to find probability of point mutations

To adopt a particular fold, a protein requires several interactions between its amino acid residues. The energetic contribution of these residue-residue interactions can be approximated by extracting statistical potentials from known high resolution structures. Several methods based on statistical potentials extracted from unrelated proteins are found to make a better prediction of probability of point mutations. We postulate that the statistical potentials extracted from known structures of similar folds with varying sequence identity can be a powerful tool to examine probability of point mutation. By keeping this in mind, we have derived pairwise residue and atomic contact energy potentials for the different functional families that adopt the (α/β)₈ TIM-Barrel fold. We carried out computational point mutations at various conserved residue positions in yeast Triose phosphate isomerase enzyme for which experimental results are already reported. We have also performed molecular dynamics simulations on a subset of point mutants to make a comparative study. The difference in pairwise residue and atomic contact energy of wildtype and various point mutations reveals probability of mutations at a particular position. Interestingly, we found that our computational prediction agrees with the experimental studies of Silverman et al. (Proc Natl Acad Sci 2001;98:3092-3097) and perform better prediction than i_Mutant and Cologne University Protein Stability Analysis Tool. The present work thus suggests deriving pairwise contact energy potentials and molecular dynamics simulations of functionally important folds could help us to predict probability of point mutations which may ultimately reduce the time and cost of mutation experiments. Proteins 2016; 85:54-64. © 2016 Wiley Periodicals, Inc.

Protein stability: computation, sequence statistics, and new experimental methods

Calculating protein stability and predicting stabilizing mutations remain exceedingly difficult tasks, largely due to the inadequacy of potential functions, the difficulty of modeling entropy and the unfolded state, and challenges of sampling, particularly of backbone conformations. Yet, computational design has produced some remarkably stable proteins in recent years, apparently owing to near ideality in structure and sequence features. With caveats, computational prediction of stability can be used to guide mutation, and mutations derived from consensus sequence analysis, especially improved by recent co-variation filters, are very likely to stabilize without sacrificing function. The combination of computational and statistical approaches with library approaches, including new technologies such as deep sequencing and high throughput stability measurements, point to a very exciting near term future for stability engineering, even with difficult computational issues remaining.

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.

Automated Structure- and Sequence-Based Design of Proteins for High Bacterial Expression and Stability

Upon heterologous overexpression, many proteins misfold or aggregate, thus resulting in low functional yields. Human acetylcholinesterase (hAChE), an enzyme mediating synaptic transmission, is a typical case of a human protein that necessitates mammalian systems to obtain functional expression. We developed a computational strategy and designed an AChE variant bearing 51 mutations that improved core packing, surface polarity, and backbone rigidity. This variant expressed at ∼2,000-fold higher levels in E. coli compared to wild-type hAChE and exhibited 20°C higher thermostability with no change in enzymatic properties or in the active-site configuration as determined by crystallography. To demonstrate broad utility, we similarly designed four other human and bacterial proteins. Testing at most three designs per protein, we obtained enhanced stability and/or higher yields of soluble and active protein in E. coli. Our algorithm requires only a 3D structure and several dozen sequences of naturally occurring homologs, and is available at http://pross.weizmann.ac.il.

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A new computational method is used to stabilize five recalcitrant proteins

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Designed variants show higher expression and stability with unmodified function

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A designed human acetylcholinesterase variant expresses solubly in bacteria

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The method is fully automated and implemented on a webserver