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

In vitro evolution of uracil glycosylase towards DnaKJ and GroEL binding evolves different misfolded states

Natural evolution is driven by random mutations that improve fitness. In vitro evolution mimics this process, however, on a short time-scale and is driven by the given bait. Here, we used directed in vitro evolution of a random mutant library of Uracil glycosylase (eUNG) displayed on yeast surface to select for binding to chaperones GroEL, DnaK+DnaJ+ATP (DnaKJ) or E.coli cell extract (CE), using binding to the eUNG inhibitor Ugi as probe for native fold. The CE selected population was further divided to Ugi binders (+U) or non-binders (-U). The aim here was to evaluate the sequence space and physical state of the evolved protein binding the different baits. We found that GroEL, DnaKJ and CE-U select and enrich for mutations causing eUNG to misfold, with the three being enriched in mutations in buried and conserved positions, with a tendency to increase positive charge. Still, each selection had its own trajectory, with GroEL and CE-U selecting mutants highly sensitive to protease cleavage while DnaKJ selected partially structured misfolded species with a tendency to refold, making them less sensitive to proteases. More general, our results show that GroEL has a higher tendency to purge promiscuous misfolded protein mutants from the system, while DnaKJ binds misfolding-prone mutant species that are, upon chaperone release, more likely to natively refold. CE-U shares some of the properties of GroEL- and DnaKJ-selected populations, while harboring also unique properties that can be explained by the presence of additional chaperones in CE, such as Trigger factor, HtpG and ClpB.

SARS-CoV-2 Omicron-B.1.1.529 leads to widespread escape from neutralizing antibody responses

On 24th November 2021, the sequence of a new SARS-CoV-2 viral isolate Omicron-B.1.1.529 was announced, containing far more mutations in Spike (S) than previously reported variants. Neutralization titers of Omicron by sera from vaccinees and convalescent subjects infected with early pandemic Alpha, Beta, Gamma, or Delta are substantially reduced, or the sera failed to neutralize. Titers against Omicron are boosted by third vaccine doses and are high in both vaccinated individuals and those infected by Delta. Mutations in Omicron knock out or substantially reduce neutralization by most of the large panel of potent monoclonal antibodies and antibodies under commercial development. Omicron S has structural changes from earlier viruses and uses mutations that confer tight binding to ACE2 to unleash evolution driven by immune escape. This leads to a large number of mutations in the ACE2 binding site and rebalances receptor affinity to that of earlier pandemic viruses.

Mutant libraries reveal negative design shielding proteins from supramolecular self-assembly and relocalization in cells

Genetic mutations fuel organismal evolution but can also cause disease. As proteins are the cell’s workhorses, the ways in which mutations can disrupt their structure, stability, function, and interactions have been studied extensively. However, proteins evolve and function in a cellular context, and our ability to relate changes in protein sequence to cell-level phenotypes remains limited. In particular, the molecular mechanism underlying most disease-associated mutations is unknown. Here, we show that mutations changing a protein’s surface chemistry can dramatically impact its supramolecular self-assembly and localization in the cell. These results highlight the complex nature of genotype–phenotype relationships with a simple system.

Understanding the molecular consequences of mutations in proteins is essential to map genotypes to phenotypes and interpret the increasing wealth of genomic data. While mutations are known to disrupt protein structure and function, their potential to create new structures and localization phenotypes has not yet been mapped to a sequence space. To map this relationship, we employed two homo-oligomeric protein complexes in which the internal symmetry exacerbates the impact of mutations. We mutagenized three surface residues of each complex and monitored the mutations’ effect on localization and assembly phenotypes in yeast cells. While surface mutations are classically viewed as benign, our analysis of several hundred mutants revealed they often trigger three main phenotypes in these proteins: nuclear localization, the formation of puncta, and fibers. Strikingly, more than 50% of random mutants induced one of these phenotypes in both complexes. Analyzing the mutant’s sequences showed that surface stickiness and net charge are two key physicochemical properties associated with these changes. In one complex, more than 60% of mutants self-assembled into fibers. Such a high frequency is explained by negative design: charged residues shield the complex from self-interacting with copies of itself, and the sole removal of the charges induces its supramolecular self-assembly. A subsequent analysis of several other complexes targeted with alanine mutations suggested that such negative design is common. These results highlight that minimal perturbations in protein surfaces’ physicochemical properties can frequently drive assembly and localization changes in a cellular context.

Yeast Mating as a Tool for Highly Effective Discovery and Engineering of Antibodies via Display Methodologies

Yeast surface display (YSD) is a powerful methodology for discovery and engineering of antibodies, and the yeast mating has been used to overcome low transformation efficiency of yeast in antibody library generation. We developed an optimized method of yeast mating for generating a large, combinatorial antibody fragment library and heterodimeric protein library by cellular fusion between two haploid cells carrying different library each other. This method allows for increased diversity in screening of target-specific fragment antigen-binding (Fab) antibodies as well as in the development of heterodimeric Fc variants for bi-specific antibody generation and T-cell receptor (TCR). Here we describe the efficient isolation of human antibodies against the activated GTP-bound form of the oncogenic Ras mutant (KRas^G12D-GTP) by sequential isolation of their heavy chains (HCs) followed by combination with light chains (LCs) via the yeast mating process. This strategy facilitates guided selection of the antigen-specific HC with either a fixed functional LC, which has cytosol penetrating ability, or an LC library to generate the Fab. It also allows for deeper exploration of a sequence space with fixed diversity, leading to a higher probability of successful isolation of human antibodies with high specificity and affinity.

Omicron-B.1.1.529 leads to widespread escape from neutralizing antibody responses

On the 24 th November 2021 the sequence of a new SARS CoV-2 viral isolate spreading rapidly in Southern Africa was announced, containing far more mutations in Spike (S) than previously reported variants. Neutralization titres of Omicron by sera from vaccinees and convalescent subjects infected with early pandemic as well as Alpha, Beta, Gamma, Delta are substantially reduced or fail to neutralize. Titres against Omicron are boosted by third vaccine doses and are high in cases both vaccinated and infected by Delta. Mutations in Omicron knock out or substantially reduce neutralization by most of a large panel of potent monoclonal antibodies and antibodies under commercial development. Omicron S has structural changes from earlier viruses, combining mutations conferring tight binding to ACE2 to unleash evolution driven by immune escape, leading to a large number of mutations in the ACE2 binding site which rebalance receptor affinity to that of early pandemic viruses.

A Protein-Engineered, Enhanced Yeast Display Platform for Rapid Evolution of Challenging Targets

Here, we enhanced the popular yeast display method by multiple rounds of DNA and protein engineering. We introduced surface exposure-tailored reporters, eUnaG2 and DnbALFA, creating a new platform of C and N terminal fusion vectors. The optimization of eUnaG2 resulted in five times brighter fluorescence and 10 °C increased thermostability than UnaG. The optimized DnbALFA has 10-fold the level of expression of the starting protein. Following this, different plasmids were developed to create a complex platform allowing a broad range of protein expression organizations and labeling strategies. Our platform showed up to five times better separation between nonexpressing and expressing cells compared with traditional pCTcon2 and c-myc labeling, allowing for fewer rounds of selection and achieving higher binding affinities. Testing 16 different proteins, the enhanced system showed consistently stronger expression signals over c-myc labeling. In addition to gains in simplicity, speed, and cost-effectiveness, new applications were introduced to monitor protein surface exposure and protein retention in the secretion pathway that enabled successful protein engineering of hard-to-express proteins. As an example, we show how we optimized the WD40 domain of the ATG16L1 protein for yeast surface and soluble bacterial expression, starting from a nonexpressing protein. As a second example, we show how using the here-presented enhanced yeast display method we rapidly selected high-affinity binders toward two protein targets, demonstrating the simplicity of generating new protein-protein interactions. While the methodological changes are incremental, it results in a qualitative enhancement in the applicability of yeast display for many applications.

Protein Engineering in the Design of Protein-Protein Interactions: SARS-CoV-2 Inhibitors as a Test Case

The formation of specific protein-protein interactions (PPIs) drive most biological processes. Malfunction of such interactions is the molecular driver of many diseases. Our ability to engineer existing PPIs or create new ones has become a vital research tool. In addition, engineered proteins with new or altered interactions are among the most critical drugs that have been developed in recent years. These include antibodies, cytokines, inhibitors, and others. Here, we provide a perspective on the current status of the methods used to engineer new or altered PPIs. The emergence of the COVID-19 pandemic, which resulted in a worldwide quest to develop specific PPI inhibitors as drugs, provided an up-to-date and state-of-the-art status report on the methodologies for engineering PPIs targeting the interaction of the viral spike protein with its cellular target, ACE2. Multiple, very high affinity binders were generated within a few months using in vitro evolution by itself, or in combination with computational design. The different experimental and computational methods used to block this interaction provide a road map for the future of PPI engineering.

Conformational Dynamics of the Helix 10 Region as an Allosteric Site in Class A β-Lactamase Inhibitory Binding

β-Lactamase inhibitory protein (BLIP) can effectively inactivate class A β-lactamases, but with very different degrees of potency. Understanding the different roles of BLIP in class A β-lactamases inhibition can provide insights for inhibitor design. However, this problem was poorly solved on the basis of the static structures obtained by X-ray crystallography. In this work, ion mobility mass spectrometry, hydrogen-deuterium exchange mass spectrometry, and molecular dynamics simulation revealed the conformational dynamics of three class A β-lactamases with varying inhibition efficiencies by BLIP. A more extended conformation of PC1 was shown compared to those of TEM1 and SHV1. Localized dynamics differed in several important loop regions, that is, the protruding loop, H10 loop, Ω loop, and SDN loop. Upon binding with BLIP, these loops cooperatively rearranged to enhance the binding interface and to inactivate the catalytic sites. In particular, unfavorable changes in conformational dynamics were found in the protruding loop of SHV1 and PC1, showing less effective binding. Intriguingly, the single mutation on BLIP could compensate for the unfavored changes in this region, and thus exhibit enhanced inhibition toward SHV1 and PC1. Additionally, the H10 region was revealed as an important allosteric site that could modulate the inhibition of class A β-lactamases. It was suggested that the rigid protruding loop and flexible H10 region might be determinants for the effective inhibition of TEM1. Our findings provided unique and explicit insights into the conformational dynamics of β-lactamases and their bindings with BLIP. This work can be extended to other β-lactamases of interest and inspire the design of novel inhibitors.

Insight into Structure-Function Relationships of β-Lactamase and BLIPs Interface Plasticity using Protein-Protein Interactions

BACKGROUND

Mostly BLIPs are identified in soil bacteria Streptomyces and originally isolated from Streptomyces clavuligerus and can be utilized as a model system for biophysical, structural, mutagenic and computational studies. BLIP possess homology with two proteins viz., BLIP-I (Streptomyces exofoliatus) and BLP (beta-lactamase inhibitory protein like protein from S. clavuligerus). BLIP consists of 165 amino acid, possessing two homologues domains comprising helix-loop-helix motif packed against four stranded beta-sheet resulting into solvent exposed concave surface with extended four stranded beta-sheet. BLIP-I is a 157 amino acid long protein obtained from S. exofoliatus having 37% sequence identity to BLIP and inhibits beta-lactamase.

METHODS

This review is intended to briefly illustrate the beta-lactamase inhibitory activity of BLIP via proteinprotein interaction and aims to open up a new avenue to combat antimicrobial resistance using peptide based inhibition.

RESULTS

D49A mutation in BLIP-I results in a decrease in affinity for TEM-1 from 0.5 nM to 10 nM (Ki). It is capable of inhibiting TEM-1 and bactopenemase and differs from BLIP only in modulating cell wall synthesis enzyme. Whereas, BLP is a 154 amino acid long protein isolated from S. clavuligerus via DNA sequencing analysis of Cephamycin-Clavulanate gene bunch. It shares 32% sequence similarity with BLIP and 42% with BLIP-I. Its biological function is unclear and lacks beta-lactamase inhibitory activity.

CONCLUSION

Protein-protein interactions mediate a significant role in regulation and modulation of cellular developments and processes. Specific biological markers and geometric characteristics are manifested by active site binding clefts of protein surfaces which determines the specificity and affinity for their targets. TEM1.BLIP is a classical model to study protein-protein interaction. β-Lactamase inhibitory proteins (BLIPs) interacts and inhibits various β-lactamases with extensive range of affinities.

Quantitative mapping of binding specificity landscapes for homologous targets by using a high-throughput method

To facilitate investigations of protein-protein interactions (PPIs), we developed a novel platform for quantitative mapping of protein binding specificity landscapes, which combines the multi-target screening of a mutagenesis library into high- and low-affinity populations with sophisticated next-generation sequencing analysis. Importantly, this method generates accurate models to predict affinity and specificity values for any mutation within a protein complex, and requires only a few experimental binding affinity measurements using purified proteins for calibration. We demonstrated the utility of the approach by mapping quantitative landscapes for interactions between the N-terminal domain of the tissue inhibitor of metalloproteinase 2 (N-TIMP2) and three matrix metalloproteinases (MMPs) having homologous structures but different affinities (MMP-1, MMP-3, and MMP-14). The binding landscapes for N-TIMP2/MMP-1 and N-TIMP2/MMP-3 showed the PPIs to be almost fully optimized, with most single mutations giving a loss of affinity. In contrast, the non-optimized PPI for N-TIMP2/MMP-14 was reflected in a wide range of binding affinities, where single mutations exhibited a far more attenuated effect on the PPI. Our new platform reliably and comprehensively identified not only hot- and cold-spot residues, but also specificity-switch mutations that shape target affinity and specificity. Thus, our approach provides a methodology giving an unprecedentedly rich quantitative analysis of the binding specificity landscape, which will broaden the understanding of the mechanisms and evolutionary origins of specific PPIs and facilitate the rational design of specific inhibitors for structurally similar target proteins.

SKEMPI 2.0: an updated benchmark of changes in protein-protein binding energy, kinetics and thermodynamics upon mutation

Motivation

Understanding the relationship between the sequence, structure, binding energy, binding kinetics and binding thermodynamics of protein–protein interactions is crucial to understanding cellular signaling, the assembly and regulation of molecular complexes, the mechanisms through which mutations lead to disease, and protein engineering.

Results

We present SKEMPI 2.0, a major update to our database of binding free energy changes upon mutation for structurally resolved protein–protein interactions. This version now contains manually curated binding data for 7085 mutations, an increase of 133%, including changes in kinetics for 1844 mutations, enthalpy and entropy changes for 443 mutations, and 440 mutations, which abolish detectable binding.

Availability and implementation

The database is available as supplementary data and at https://life.bsc.es/pid/skempi2/.

Supplementary information

Supplementary data are available at Bioinformatics online.

Mapping protein selectivity landscapes using multi-target selective screening and next-generation sequencing of combinatorial libraries

Characterizing the binding selectivity landscape of interacting proteins is crucial both for elucidating the underlying mechanisms of their interaction and for developing selective inhibitors. However, current mapping methods are laborious and cannot provide a sufficiently comprehensive description of the landscape. Here, we introduce a novel and efficient strategy for comprehensively mapping the binding landscape of proteins using a combination of experimental multi-target selective library screening and in silico next-generation sequencing analysis. We map the binding landscape of a non-selective trypsin inhibitor, the amyloid protein precursor inhibitor (APPI), to each of the four human serine proteases (kallikrein-6, mesotrypsin, and anionic and cationic trypsins). We then use this map to dissect and improve the affinity and selectivity of APPI variants toward each of the four proteases. Our strategy can be used as a platform for the development of a new generation of target-selective probes and therapeutic agents based on selective protein-protein interactions.

Tackling the Antibiotic Resistance Caused by Class A β-Lactamases through the Use of β-Lactamase Inhibitory Protein

β-Lactams are the most widely used and effective antibiotics for the treatment of infectious diseases. Unfortunately, bacteria have developed several mechanisms to combat these therapeutic agents. One of the major resistance mechanisms involves the production of β-lactamase that hydrolyzes the β-lactam ring thereby inactivating the drug. To overcome this threat, the small molecule β-lactamase inhibitors (e.g., clavulanic acid, sulbactam and tazobactam) have been used in combination with β-lactams for treatment. However, the bacterial resistance to this kind of combination therapy has evolved recently. Therefore, multiple attempts have been made to discover and develop novel broad-spectrum β-lactamase inhibitors that sufficiently work against β-lactamase producing bacteria. β-lactamase inhibitory proteins (BLIPs) (e.g., BLIP, BLIP-I and BLIP-II) are potential inhibitors that have been found from soil bacterium Streptomyces spp. BLIPs bind and inhibit a wide range of class A β-lactamases from a diverse set of Gram-positive and Gram-negative bacteria, including TEM-1, PC1, SME-1, SHV-1 and KPC-2. To the best of our knowledge, this article represents the first systematic review on β-lactamase inhibitors with a particular focus on BLIPs and their inherent properties that favorably position them as a source of biologically-inspired drugs to combat antimicrobial resistance. Furthermore, an extensive compilation of binding data from β-lactamase–BLIP interaction studies is presented herein. Such information help to provide key insights into the origin of interaction that may be useful for rationally guiding future drug design efforts.

Selecting for Fast Protein-Protein Association As Demonstrated on a Random TEM1 Yeast Library Binding BLIP

Protein-protein interactions mediate the vast majority of cellular processes. Though protein interactions obey basic chemical principles also within the cell, the in vivo physiological environment may not allow for equilibrium to be reached. Thus, in vitro measured thermodynamic affinity may not provide a complete picture of protein interactions in the biological context. Binding kinetics composed of the association and dissociation rate constants are relevant and important in the cell. Therefore, changes in protein-protein interaction kinetics have a significant impact on the in vivo activity of the proteins. The common protocol for the selection of tighter binders from a mutant library selects for protein complexes with slower dissociation rate constants. Here we describe a method to specifically select for variants with faster association rate constants by using pre-equilibrium selection, starting from a large random library. Toward this end, we refine the selection conditions of a TEM1-β-lactamase library against its natural nanomolar affinity binder β-lactamase inhibitor protein (BLIP). The optimal selection conditions depend on the ligand concentration and on the incubation time. In addition, we show that a second sort of the library helps to separate signal from noise, resulting in a higher percent of faster binders in the selected library. Fast associating protein variants are of particular interest for drug development and other biotechnological applications.

Efficient production of secretory Streptomyces clavuligerus β-lactamase inhibitory protein (BLIP) in Pichia pastoris

β-Lactamase inhibitory protein (BLIP), a low molecular weight protein from Streptomyces clavuligerus, has a wide range of potential applications in the fields of biotechnology and pharmaceutical industry because of its tight interaction with and potent inhibition on clinically important class A β-lactamases. To meet the demands for considerable amount of highly pure BLIP, this study aimed at developing an efficient expression system in eukaryotic Pichia pastoris (a methylotrophic yeast) for production of BLIP. With methanol induction, recombinant BLIP was overexpressed in P. pastoris X-33 and secreted into the culture medium. A high yield of ~ 300 mg/L culture secretory BLIP recovered from the culture supernatant without purification was found to be > 90% purity. The recombinant BLIP was fully active and showed an inhibition constant (K_i) for TEM-1 β-lactamase (0.55 ± 0.07 nM) comparable to that of the native S. clavuligerus-expressed BLIP (0.5 nM). Yeast-produced BLIP in combination with ampicillin effectively inhibited the growth of β-lactamase-producing Gram-positive Bacillus. Our approach of expressing secretory BLIP in P. pastoris gave 71- to 1200-fold more BLIP with high purity than the other conventional methods, allowing efficient production of large amount of highly pure BLIP, which merits fundamental science studies, drug development and biotechnological applications.

Pre-equilibrium competitive library screening for tuning inhibitor association rate and specificity toward serine proteases

High structural and sequence similarity within protein families can pose significant challenges to the development of selective inhibitors, especially toward proteolytic enzymes. Such enzymes usually belong to large families of closely similar proteases and may also hydrolyze, with different rates, protein- or peptide-based inhibitors. To address this challenge, we employed a combinatorial yeast surface display library approach complemented with a novel pre-equilibrium, competitive screening strategy for facile assessment of the effects of multiple mutations on inhibitor association rates and binding specificity. As a proof of principle for this combined approach, we utilized this strategy to alter inhibitor/protease association rates and to tailor the selectivity of the amyloid β-protein precursor Kunitz protease inhibitor domain (APPI) for inhibition of the oncogenic protease mesotrypsin, in the presence of three competing serine proteases, anionic trypsin, cationic trypsin and kallikrein-6. We generated a variant, designated APPI_{P13W/M17G/I18F/F34V}, with up to 30-fold greater specificity relative to the parental APPI_{M17G/I18F/F34V} protein, and 6500- to 230 000-fold improved specificity relative to the wild-type APPI protein in the presence of the other proteases tested. A series of molecular docking simulations suggested a mechanism of interaction that supported the biochemical results. These simulations predicted that the selectivity and specificity are affected by the interaction of the mutated APPI residues with nonconserved enzyme residues located in or near the binding site. Our strategy will facilitate a better understanding of the binding landscape of multispecific proteins and will pave the way for design of new drugs and diagnostic tools targeting proteases and other proteins.

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.

Beyond antibody engineering: directed evolution of alternative binding scaffolds and enzymes using yeast surface display

Pioneered exactly 20 years ago, yeast surface display (YSD) continues to take a major role in protein engineering among the high-throughput display methodologies that have been developed to date. The classical yeast display technology relies on tethering an engineered protein to the cell wall by genetic fusion to one subunit of a dimeric yeast-mating agglutination receptor complex. This method enables an efficient genotype-phenotype linkage while exploiting the benefits of a eukaryotic expression machinery. Over the past two decades, a plethora of protein engineering efforts encompassing conventional antibody Fab and scFv fragments have been reported. In this review, we will focus on the versatility of YSD beyond conventional antibody engineering and, instead, place the focus on alternative scaffold proteins and enzymes which have successfully been tailored for purpose with regard to improving binding, activity or specificity.

Electrostatic Interactions in Protein Structure, Folding, Binding, and Condensation

Charged and polar groups, through forming ion pairs, hydrogen bonds, and other less specific electrostatic interactions, impart important properties to proteins. Modulation of the charges on the amino acids, e.g., by pH and by phosphorylation and dephosphorylation, have significant effects such as protein denaturation and switch-like response of signal transduction networks. This review aims to present a unifying theme among the various effects of protein charges and polar groups. Simple models will be used to illustrate basic ideas about electrostatic interactions in proteins, and these ideas in turn will be used to elucidate the roles of electrostatic interactions in protein structure, folding, binding, condensation, and related biological functions. In particular, we will examine how charged side chains are spatially distributed in various types of proteins and how electrostatic interactions affect thermodynamic and kinetic properties of proteins. Our hope is to capture both important historical developments and recent experimental and theoretical advances in quantifying electrostatic contributions of proteins.