Residue specific contributions to stability and activity inferred from saturation mutagenesis and deep sequencing

Prediction of Function Determining and Buried Residues Through Analysis of Saturation Mutagenesis Datasets

Mutational scanning can be used to probe effects of large numbers of point mutations on protein function. Positions affected by mutation are primarily at either buried or at exposed residues directly involved in function, hereafter designated as active-site residues. In the absence of prior structural information, it has not been easy to distinguish between these two categories of residues. We curated and analyzed a set of twelve published deep mutational scanning datasets. The analysis revealed differential patterns of mutational sensitivity and substitution preferences at buried and exposed positions. Prediction of buried-sites solely from the mutational sensitivity data was facilitated by incorporating predicted sequence-based accessibility values. For active-site residues we observed mean sensitivity, specificity and accuracy of 61, 90 and 88% respectively. For buried residues the corresponding figures were 59, 90 and 84% while for exposed non active-site residues these were 98, 44 and 82% respectively. We also identified positions which did not follow these general trends and might require further experimental re-validation. This analysis highlights the ability of deep mutational scans to provide important structural and functional insights, even in the absence of three-dimensional structures determined using conventional structure determination techniques, and also discuss some limitations of the methodology.

Different strategies for the lipase immobilization on the chitosan based supports and their applications

Immobilized enzymes have received incredible interests in industry, pharmaceuticals, chemistry and biochemistry sectors due to their various advantages such as ease of separation, multiple reusability, non-toxicity, biocompatibility, high activity and resistant to environmental changes. This review in between various immobilized enzymes focuses on lipase as one of the most practical enzyme and chitosan as a preferred biosupport for lipase immobilization and provides a broad range of studies of recent decade. We highlight several aspects of lipase immobilization on the surface of chitosan support containing various types of lipase and immobilization techniques from physical adsorption to covalent bonding and cross-linking with their benefits and drawbacks. The recent advances and future perspectives that can improve the present problems with lipase and chitosan such as high-price of lipase and low mechanical resistance of chitosan are also discussed. According to the literature, optimization of immobilization methods, combination of these methods with other techniques, physical and chemical modifications of chitosan, co-immobilization and protein engineering can be useful as a solution to overcome the mentioned limitations.

A facile method of mapping HIV-1 neutralizing epitopes using chemically masked cysteines and deep sequencing

Identification of specific epitopes targeted by neutralizing antibodies is essential to advance epitope-based vaccine design strategies. We report a facile methodology for rapid epitope mapping of neutralizing antibodies (NAbs) against HIV-1 Envelope (Env) at single-residue resolution, using Cys labeling, viral neutralization assays, and deep sequencing. This was achieved by the generation of a library of Cys mutations in Env glycoprotein on the viral surface, covalent labeling of the Cys residues using a Cys-reactive label that masks epitope residues, followed by infection of the labeled mutant virions in mammalian cells in the presence of NAbs. Env gene sequencing from NAb-resistant viruses was used to accurately delineate epitopes for the NAbs VRC01, PGT128, and PGT151. These agreed well with corresponding experimentally determined structural epitopes previously inferred from NAb:Env structures. HIV-1 infection is associated with complex and polyclonal antibody responses, typically composed of multiple antibody specificities. Deconvoluting the epitope specificities in a polyclonal response is a challenging task. We therefore extended our methodology to map multiple specificities of epitopes targeted in polyclonal sera, elicited in immunized animals as well as in an HIV-1-infected elite neutralizer capable of neutralizing tier 3 pseudoviruses with high titers. The method can be readily extended to other viruses for which convenient reverse genetics or lentiviral surface display systems are available.

Advances in Recombinant Lipases: Production, Engineering, Immobilization and Application in the Pharmaceutical Industry

Lipases are one of the most used enzymes in the pharmaceutical industry due to their efficiency in organic syntheses, mainly in the production of enantiopure drugs. From an industrial viewpoint, the selection of an efficient expression system and host for recombinant lipase production is highly important. The most used hosts are Escherichia coli and Komagataella phaffii (previously known as Pichia pastoris) and less often reported Bacillus and Aspergillus strains. The use of efficient expression systems to overproduce homologous or heterologous lipases often require the use of strong promoters and the co-expression of chaperones. Protein engineering techniques, including rational design and directed evolution, are the most reported strategies for improving lipase characteristics. Additionally, lipases can be immobilized in different supports that enable improved properties and enzyme reuse. Here, we review approaches for strain and protein engineering, immobilization and the application of lipases in the pharmaceutical industry.

Mutational analysis of a catalytically important loop containing active site and substrate-binding site in Escherichia coli phytase AppA

A phytase from Escherichia coli, AppA, has been the target of protein engineering to reduce the amount of undigested phosphates from livestock manure by making phosphorous from phytic acid available as a nutrient. To understand the contribution of each amino acid in the active site loop to the AppA activity, alanine and glycine scanning mutagenesis was undertaken. The results of phytase activity assay demonstrated loss of activity by mutations at charged residues within the conserved motif, supporting their importance in catalytic activity. In contrast, both conserved, non-polar residues and non-conserved residues tended to be tolerant to Ala and/or Gly mutations. Correlation analyses of chemical/structural characteristics of each mutation site against mutant activity revealed that the loop residues located closer to the substrate have greater contribution to the activity of AppA. These results may be useful in efficiently engineering AppA to improve its catalytic activity.

Abbreviations: AppA: pH 2.5 acid phosphatase; CSU: contacts of structural units; HAPs: histidine acid phosphatases; SASA: solvent accessible surface area; SDS-PAGE: sodium dodecyl sulfate-polyacrylamide gel electrophoresis; SSM: site-saturation mutagenesis; WT: wild type

Insights into protein structure, stability and function from saturation mutagenesis

Where convenient phenotypic readouts are available, saturation mutagenesis coupled to deep sequencing provides a rapid and facile method to infer sequence determinants of protein structure, stability and function. We provide brief descriptions and currently available options for the various steps involved, and mention limitations of current implementations. We also highlight recent applications such as estimating relative stabilities and affinities of protein variants, mapping epitopes, protein model discrimination and prediction of mutant phenotypes. Most mutational scans have so far been applied to single genes and proteins. Additional methodological improvements are required to expand the scope to study intergenic epistasis and intermolecular interactions in macromolecular complexes.

Computational tools help improve protein stability but with a solubility tradeoff

Accurately predicting changes in protein stability upon amino acid substitution is a much sought after goal. Destabilizing mutations are often implicated in disease, whereas stabilizing mutations are of great value for industrial and therapeutic biotechnology. Increasing protein stability is an especially challenging task, with random substitution yielding stabilizing mutations in only ∼2% of cases. To overcome this bottleneck, computational tools that aim to predict the effect of mutations have been developed; however, achieving accuracy and consistency remains challenging. Here, we combined 11 freely available tools into a meta-predictor (meieringlab.uwaterloo.ca/stabilitypredict/). Validation against ∼600 experimental mutations indicated that our meta-predictor has improved performance over any of the individual tools. The meta-predictor was then used to recommend 10 mutations in a previously designed protein of moderate thermodynamic stability, ThreeFoil. Experimental characterization showed that four mutations increased protein stability and could be amplified through ThreeFoil's structural symmetry to yield several multiple mutants with >2-kcal/mol stabilization. By avoiding residues within functional ties, we could maintain ThreeFoil's glycan-binding capacity. Despite successfully achieving substantial stabilization, however, almost all mutations decreased protein solubility, the most common cause of protein design failure. Examination of the 600-mutation data set revealed that stabilizing mutations on the protein surface tend to increase hydrophobicity and that the individual tools favor this approach to gain stability. Thus, whereas currently available tools can increase protein stability and combining them into a meta-predictor yields enhanced reliability, improvements to the potentials/force fields underlying these tools are needed to avoid gaining protein stability at the cost of solubility.

Deconstruction of the Ras switching cycle through saturation mutagenesis

Ras proteins are highly conserved signaling molecules that exhibit regulated, nucleotide-dependent switching between active and inactive states. The high conservation of Ras requires mechanistic explanation, especially given the general mutational tolerance of proteins. Here, we use deep mutational scanning, biochemical analysis and molecular simulations to understand constraints on Ras sequence. Ras exhibits global sensitivity to mutation when regulated by a GTPase activating protein and a nucleotide exchange factor. Removing the regulators shifts the distribution of mutational effects to be largely neutral, and reveals hotspots of activating mutations in residues that restrain Ras dynamics and promote the inactive state. Evolutionary analysis, combined with structural and mutational data, argue that Ras has co-evolved with its regulators in the vertebrate lineage. Overall, our results show that sequence conservation in Ras depends strongly on the biochemical network in which it operates, providing a framework for understanding the origin of global selection pressures on proteins.

Low-stringency selection of TEM1 for BLIP shows interface plasticity and selection for faster binders

Protein-protein interactions occur via well-defined interfaces on the protein surface. Whereas the location of homologous interfaces is conserved, their composition varies, suggesting that multiple solutions may support high-affinity binding. In this study, we examined the plasticity of the interface of TEM1 β-lactamase with its protein inhibitor BLIP by low-stringency selection of a random TEM1 library using yeast surface display. Our results show that most interfacial residues could be mutated without a loss in binding affinity, protein stability, or enzymatic activity, suggesting plasticity in the interface composition supporting high-affinity binding. Interestingly, many of the selected mutations promoted faster association. Further selection for faster binders was achieved by drastically decreasing the library-ligand incubation time to 30 s. Preequilibrium selection as suggested here is a novel methodology for specifically selecting faster-associating protein complexes.

Molecular Determinants of Mutant Phenotypes, Inferred from Saturation Mutagenesis Data

Understanding how mutations affect protein activity and organismal fitness is a major challenge. We used saturation mutagenesis combined with deep sequencing to determine mutational sensitivity scores for 1,664 single-site mutants of the 101 residue Escherichia coli cytotoxin, CcdB at seven different expression levels. Active-site residues could be distinguished from buried ones, based on their differential tolerance to aliphatic and charged amino acid substitutions. At nonactive-site positions, the average mutational tolerance correlated better with depth from the protein surface than with accessibility. Remarkably, similar results were observed for two other small proteins, PDZ domain (PSD95^pdz3) and IgG-binding domain of protein G (GB1). Mutational sensitivity data obtained with CcdB were used to derive a procedure for predicting functional effects of mutations. Results compared favorably with those of two widely used computational predictors. In vitro characterization of 80 single, nonactive-site mutants of CcdB showed that activity in vivo correlates moderately with thermal stability and solubility. The inability to refold reversibly, as well as a decreased folding rate in vitro, is associated with decreased activity in vivo. Upon probing the effect of modulating expression of various proteases and chaperones on mutant phenotypes, most deleterious mutants showed an increased in vivo activity and solubility only upon over-expression of either Trigger factor or SecB ATP-independent chaperones. Collectively, these data suggest that folding kinetics rather than protein stability is the primary determinant of activity in vivo. This study enhances our understanding of how mutations affect phenotype, as well as the ability to predict fitness effects of point mutations.

Engineering Highly Potent and Selective Microproteins against Nav1.7 Sodium Channel for Treatment of Pain

The prominent role of voltage-gated sodium channel 1.7 (Nav1.7) in nociception was revealed by remarkable human clinical and genetic evidence. Development of potent and subtype-selective inhibitors of this ion channel is crucial for obtaining therapeutically useful analgesic compounds. Microproteins isolated from animal venoms have been identified as promising therapeutic leads for ion channels, because they naturally evolved to be potent ion channel blockers. Here, we report the engineering of highly potent and selective inhibitors of the Nav1.7 channel based on tarantula ceratotoxin-1 (CcoTx1). We utilized a combination of directed evolution, saturation mutagenesis, chemical modification, and rational drug design to obtain higher potency and selectivity to the Nav1.7 channel. The resulting microproteins are highly potent (IC50 to Nav1.7 of 2.5 nm) and selective. We achieved 80- and 20-fold selectivity over the closely related Nav1.2 and Nav1.6 channels, respectively, and the IC50 on skeletal (Nav1.4) and cardiac (Nav1.5) sodium channels is above 3000 nm The lead molecules have the potential for future clinical development as novel therapeutics in the treatment of pain.

ScaffoldSeq: Software for characterization of directed evolution populations

ScaffoldSeq is software designed for the numerous applications-including directed evolution analysis-in which a user generates a population of DNA sequences encoding for partially diverse proteins with related functions and would like to characterize the single site and pairwise amino acid frequencies across the population. A common scenario for enzyme maturation, antibody screening, and alternative scaffold engineering involves naïve and evolved populations that contain diversified regions, varying in both sequence and length, within a conserved framework. Analyzing the diversified regions of such populations is facilitated by high-throughput sequencing platforms; however, length variability within these regions (e.g., antibody CDRs) encumbers the alignment process. To overcome this challenge, the ScaffoldSeq algorithm takes advantage of conserved framework sequences to quickly identify diverse regions. Beyond this, unintended biases in sequence frequency are generated throughout the experimental workflow required to evolve and isolate clones of interest prior to DNA sequencing. ScaffoldSeq software uniquely handles this issue by providing tools to quantify and remove background sequences, cluster similar protein families, and dampen the impact of dominant clones. The software produces graphical and tabular summaries for each region of interest, allowing users to evaluate diversity in a site-specific manner as well as identify epistatic pairwise interactions. The code and detailed information are freely available at http://research.cems.umn.edu/hackel. Proteins 2016; 84:869-874. © 2016 Wiley Periodicals, Inc.

Residue proximity information and protein model discrimination using saturation-suppressor mutagenesis

Identification of residue-residue contacts from primary sequence can be used to guide protein structure prediction. Using Escherichia coli CcdB as the test case, we describe an experimental method termed saturation-suppressor mutagenesis to acquire residue contact information. In this methodology, for each of five inactive CcdB mutants, exhaustive screens for suppressors were performed. Proximal suppressors were accurately discriminated from distal suppressors based on their phenotypes when present as single mutants. Experimentally identified putative proximal pairs formed spatial constraints to recover >98% of native-like models of CcdB from a decoy dataset. Suppressor methodology was also applied to the integral membrane protein, diacylglycerol kinase A where the structures determined by X-ray crystallography and NMR were significantly different. Suppressor as well as sequence co-variation data clearly point to the X-ray structure being the functional one adopted in vivo. The methodology is applicable to any macromolecular system for which a convenient phenotypic assay exists.

DOI:http://dx.doi.org/10.7554/eLife.09532.001

Common techniques to determine the three-dimensional structures of proteins can help researchers to understand these molecules’ activities, but are often time-consuming and do not work for all proteins. Proteins are made of chains of amino acids. When a protein chain folds, some of these amino acids interact with other amino acids and these contacts dictate the overall shape of the protein. This means that identifying the pairs of contacting amino acids could make it possible to predict the protein’s structure.

Interactions between pairs of contacting amino acids tend to remain conserved throughout evolution, and if a mutation alters one of the amino acids in a pair then a 'compensatory' change often occurs to alter the second amino acid as well. Compensatory mutations can suggest that two amino acids are close to each other in the three-dimensional shape of a protein, but the computational methods used to identify such amino acid pairs can sometimes be inaccurate.

In 2012, researchers generated mutants of a bacterial protein called CcdB with changes to single amino acids that caused the protein to fail to fold correctly. Now, Sahoo et al. – who include two of the researchers involved in the 2012 work – have developed an experimental method to identify contacting amino acids and use the CcdB protein as a test case. The approach involved searching for additional mutations that could restore the activity of five of the original mutant proteins when the proteins were produced in yeast cells. The rationale was that any secondary mutations that restored the activity must have corrected the folding defect caused by the original mutation. Sahoo et al. then predicted how close the amino acids affected by the secondary mutations were to the amino acids altered by the original mutations. This information was used to select reliable three-dimensional models of CcdB from a large set of possible structures that had been generated previously using computer models.

Next, the technique was applied to a protein called diacylglycerol kinase A. The structure of this protein had previously been inferred using techniques such as X-ray crystallography and nuclear magnetic resonance, but there was a mismatch between the two methods. Sahoo et al. found that the amino acid contacts derived from their experimental method matched those found in the crystal structure, suggesting that the functional protein structure in living cells is similar to the crystal structure. In the future, the experimental approach developed in this work could be combined with existing methods to reliably guide protein structure prediction.

DOI:http://dx.doi.org/10.7554/eLife.09532.002

High-resolution sequence-function mapping of full-length proteins

Comprehensive sequence-function mapping involves detailing the fitness contribution of every possible single mutation to a gene by comparing the abundance of each library variant before and after selection for the phenotype of interest. Deep sequencing of library DNA allows frequency reconstruction for tens of thousands of variants in a single experiment, yet short read lengths of current sequencers makes it challenging to probe genes encoding full-length proteins. Here we extend the scope of sequence-function maps to entire protein sequences with a modular, universal sequence tiling method. We demonstrate the approach with both growth-based selections and FACS screening, offer parameters and best practices that simplify design of experiments, and present analytical solutions to normalize data across independent selections. Using this protocol, sequence-function maps covering full sequences can be obtained in four to six weeks. Best practices introduced in this manuscript are fully compatible with, and complementary to, other recently published sequence-function mapping protocols.

Engineering deamidation-susceptible asparagines leads to improved stability to thermal cycling in a lipase

At high temperatures, protein stability is influenced by chemical alterations; most important among them is deamidation of asparagines. Deamidation kinetics of asparagines depends on the local sequence, solvent, pH, temperature, and the tertiary structure. Suitable replacement of deamidated asparagines could be a viable strategy to improve deamidation-mediated loss in protein properties, specifically protein thermostability. In this study, we have used nano RP-HPLC coupled ESI MS/MS approach to identify residues susceptible to deamidation in a lipase (6B) on heat treatment. Out of 15 asparagines and six glutamines in 6B, only five asparagines were susceptible to deamidation at temperatures higher than 75°C. These five positions were subjected to site saturation mutagenesis followed by activity screen to identify the most suitable substitutions. Only three of the five asparagines were found to be tolerant to substitutions. Best substitutions at these positions were combined into a mutant. The resultant lipase (mutC) has near identical secondary structure and improved thermal tolerance as compared to its parent. The triple mutant has shown almost two-fold higher residual activity compared to 6B after four cycles at 90°C. MutC has retained more than 50% activity even after incubation at 100°C. Engineering asparagines susceptible to deamidation would be a potential strategy to improve proteins to withstand very high temperatures.