Diversifying de novo TIM barrels by hallucination.

De novo protein design expands the protein universe by creating new sequences to accomplish tailor-made enzymes in the future. A promising topology to implement diverse enzyme functions is the ubiquitous TIM-barrel fold. Since the initial de novo design of an idealized four-fold symmetric TIM barrel, the family of de novo TIM barrels is expanding rapidly. Despite this and in contrast to natural TIM barrels, these novel proteins lack cavities and structural elements essential for the incorporation of binding sites or enzymatic functions. In this work, we diversified a de novo TIM barrel by extending multiple ßα-loops using constrained hallucination. Experimentally tested designs were found to be soluble upon expression in Escherichia coli and well-behaved. Biochemical characterization and crystal structures revealed successful extensions with defined α-helical structures. These diversified de novo TIM barrels provide a framework to explore a broad spectrum of functions based on the potential of natural TIM barrels.

Engineering PD-1-targeted small protein variants for in vitro diagnostics and in vivo PET imaging.

BACKGROUND: Programmed cell death 1 (PD-1) belongs to immune checkpoint proteins ensuring negative regulation of the immune response. In non-small cell lung cancer (NSCLC), the sensitivity to treatment with anti-PD-1 therapeutics, and its efficacy, mostly correlated with the increase of tumor infiltrating PD-1+ lymphocytes. Due to solid tumor heterogeneity of PD-1+ populations, novel low molecular weight anti-PD-1 high-affinity diagnostic probes can increase the reliability of expression profiling of PD-1+ tumor infiltrating lymphocytes (TILs) in tumor tissue biopsies and in vivo mapping efficiency using immune-PET imaging. METHODS: We designed a 13 kDa ß-sheet Myomedin scaffold combinatorial library by randomization of 12 mutable residues, and in combination with ribosome display, we identified anti-PD-1 Myomedin variants (MBA ligands) that specifically bound to human and murine PD-1-transfected HEK293T cells and human SUP-T1 cells spontaneously overexpressing cell surface PD-1. RESULTS: Binding affinity to cell-surface expressed human and murine PD-1 on transfected HEK293T cells was measured by fluorescence with LigandTracer and resulted in the selection of most promising variants MBA066 (hPD-1 KD = 6.9 nM; mPD-1 KD = 40.5 nM), MBA197 (hPD-1 KD = 29.7 nM; mPD-1 KD = 21.4 nM) and MBA414 (hPD-1 KD = 8.6 nM; mPD-1 KD = 2.4 nM). The potential of MBA proteins for imaging of PD-1+ populations in vivo was demonstrated using deferoxamine-conjugated MBA labeled with 68Galium isotope. Radiochemical purity of 68Ga-MBA proteins reached values 94.7-99.3% and in vitro stability in human serum after 120 min was in the range 94.6-98.2%. The distribution of 68Ga-MBA proteins in mice was monitored using whole-body positron emission tomography combined with computerized tomography (PET/CT) imaging up to 90 min post-injection and post mortem examined in 12 mouse organs. The specificity of MBA proteins was proven by co-staining frozen sections of human tonsils and NSCLC tissue biopsies with anti-PD-1 antibody, and demonstrated their potential for mapping PD-1+ populations in solid tumors. CONCLUSIONS: Using directed evolution, we developed a unique set of small binding proteins that can improve PD-1 diagnostics in vitro as well as in vivo using PET/CT imaging.

Automated optimization of the solubility of a hyper-stable α-amylase.

Most successes in computational protein engineering to date have focused on enhancing one biophysical trait, while multi-trait optimization remains a challenge. Different biophysical properties are often conflicting, as mutations that improve one tend to worsen the others. In this study, we explored the potential of an automated computational design strategy, called CamSol Combination, to optimize solubility and stability of enzymes without affecting their activity. Specifically, we focus on Bacillus licheniformis α-amylase (BLA), a hyper-stable enzyme that finds diverse application in industry and biotechnology. We validate the computational predictions by producing 10 BLA variants, including the wild-type (WT) and three designed models harbouring between 6 and 8 mutations each. Our results show that all three models have substantially improved relative solubility over the WT, unaffected catalytic rate and retained hyper-stability, supporting the algorithm's capacity to optimize enzymes. High stability and solubility embody enzymes with superior resilience to chemical and physical stresses, enhance manufacturability and allow for high-concentration formulations characterized by extended shelf lives. This ability to readily optimize solubility and stability of enzymes will enable the rapid and reliable generation of highly robust and versatile reagents, poised to contribute to advancements in diverse scientific and industrial domains.

Characterization of a novel format scFv×VHH single-chain biparatopic antibody against metal binding protein MtsA.

Biparatopic antibodies (bpAbs) are engineered antibodies that bind to multiple different epitopes within the same antigens. bpAbs comprise diverse formats, including fragment-based formats, and choosing the appropriate molecular format for a desired function against a target molecule is a challenging task. Moreover, optimizing the design of constructs requires selecting appropriate antibody modalities and adjusting linker length for individual bpAbs. Therefore, it is crucial to understand the characteristics of bpAbs at the molecular level. In this study, we first obtained single-chain variable fragments and camelid heavy-chain variable domains targeting distinct epitopes of the metal binding protein MtsA and then developed a novel format single-chain bpAb connecting these fragment antibodies with various linkers. The physicochemical properties, binding activities, complex formation states with antigen, and functions of the bpAb were analyzed using multiple approaches. Notably, we found that the assembly state of the complexes was controlled by a linker and that longer linkers tended to form more compact complexes. These observations provide detailed molecular information that should be considered in the design of bpAbs.

Engineering G protein-coupled receptors for stabilization.

G protein-coupled receptors (GPCRs) are one of the most important families of targets for drug discovery. One of the limiting steps in the study of GPCRs has been their stability, with significant and time-consuming protein engineering often used to stabilize GPCRs for structural characterization and drug screening. Unfortunately, computational methods developed using globular soluble proteins have translated poorly to the rational engineering of GPCRs. To fill this gap, we propose GPCR-tm, a novel and personalized structurally driven web-based machine learning tool to study the impacts of mutations on GPCR stability. We show that GPCR-tm performs as well as or better than alternative methods, and that it can accurately rank the stability changes of a wide range of mutations occurring in various types of class A GPCRs. GPCR-tm achieved Pearson's correlation coefficients of 0.74 and 0.46 on 10-fold cross-validation and blind test sets, respectively. We observed that the (structural) graph-based signatures were the most important set of features for predicting destabilizing mutations, which points out that these signatures properly describe the changes in the environment where the mutations occur. More specifically, GPCR-tm was able to accurately rank mutations based on their effect on protein stability, guiding their rational stabilization. GPCR-tm is available through a user-friendly web server at https://biosig.lab.uq.edu.au/gpcr_tm/.

Bioluminescence Imaging of Potassium Ion Using a Sensory Luciferin and an Engineered Luciferase.

Bioluminescent indicators are power tools for studying dynamic biological processes. In this study, we present the generation of novel bioluminescent indicators by modifying the luciferin molecule with an analyte-binding moiety. Specifically, we have successfully developed the first bioluminescent indicator for potassium ions (K+), which are critical electrolytes in biological systems. Our approach involved the design and synthesis of a K+-binding luciferin named potassiorin. Additionally, we engineered a luciferase enzyme called BRIPO (bioluminescent red indicator for potassium) to work synergistically with potassiorin, resulting in optimized K+-dependent bioluminescence responses. Through extensive validation in cell lines, primary neurons, and live mice, we demonstrated the efficacy of this new tool for detecting K+. Our research demonstrates an innovative concept of incorporating sensory moieties into luciferins to modulate luciferase activity. This approach has great potential for developing a wide range of bioluminescent indicators, advancing bioluminescence imaging (BLI), and enabling the study of various analytes in biological systems.

Tailor-Made α-Glucans by Engineering the Processivity of α-Glucanotransferases via Tunnel-Cleft Active Center Interconversions.

The function of polysaccharides is intimately associated with their size, which is largely determined by the processivity of transferases responsible for their synthesis. A tunnel active center architecture has been recognized as a key factor that governs processivity of several glycoside hydrolases (GHs), e.g., cellulases and chitinases. Similar tunnel architecture is also observed in the Limosilactobacillus reuteri 121 GtfB (Lr121 GtfB) α-glucanotransferase from the GH70 family. The molecular element underpinning processivity of these transglucosylases remains underexplored. Here, we report the synthesis of the smallest (α1 → 4)-α-glucan interspersed with linear and branched (α1 → 6) linkages by a novel 4,6-α-glucanotransferase from L. reuteri N1 (LrN1 GtfB) with an open-clefted active center instead of the tunnel structure. Notably, the loop swapping engineering of LrN1 GtfB and Lr121 GtfB based on their crystal structures clarified the impact of the loop-mediated tunnel/cleft structure at the donor subsites -2 to -3 on processivity of these α-glucanotransferases, enabling the tailoring of both product sizes and substrate preferences. This study provides unprecedented insights into the processivity determinants and evolutionary diversification of GH70 α-glucanotransferases and offers a simple route for engineering starch-converting α-glucanotransferases to generate diverse α-glucans for different biotechnological applications.

Computer-Aided Semi-Rational Design to Enhance the Activity of l-Sorbosone Dehydrogenase from Gluconobacter oxidans WSH-004.

The titer of the microbial fermentation products can be increased by enzyme engineering. l-Sorbosone dehydrogenase (SNDH) is a key enzyme in the production of 2-keto-l-gulonic acid (2-KLG), which is the precursor of vitamin C. Enhancing the activity of SNDH may have a positive impact on 2-KLG production. In this study, a computer-aided semirational design of SNDH was conducted. Based on the analysis of SNDH's substrate pocket and multiple sequence alignment, three modification strategies were established: (1) expanding the entrance of SNDH's substrate pocket, (2) engineering the residues within the substrate pocket, and (3) enhancing the electron transfer of SNDH. Finally, mutants S453A, L460V, and E471D were obtained, whose specific activity was increased by 20, 100, and 10%, respectively. In addition, the ability of Gluconobacter oxidans WSH-004 to synthesize 2-KLG was improved by eliminating H2O2. This study provides mutant enzymes and metabolic engineering strategies for the microbial-fermentation-based production of 2-KLG.

Improving plastic degrading enzymes via directed evolution.

Plastic degrading enzymes have immense potential for use in industrial applications. Protein engineering efforts over the last decade have resulted in considerable enhancement of many properties of these enzymes. Directed evolution, a protein engineering approach that mimics the natural process of evolution in a laboratory, has been particularly useful in overcoming some of the challenges of structure-based protein engineering. For example, directed evolution has been used to improve the catalytic activity and thermostability of polyethylene terephthalate (PET)-degrading enzymes, although its use for the improvement of other desirable properties, such as solvent tolerance, has been less studied. In this review, we aim to identify some of the knowledge gaps and current challenges, and highlight recent studies related to the directed evolution of plastic-degrading enzymes.

Self-driving autonomous machines to engineer novel enzymes.

Can one design and automate a computational and experimental platform such that each platform iteratively guides and drives the other to achieve a pre-determined goal? Rapp and colleagues (2024) describe just this possibility in a paper that details a prototype of a self-driven laboratory that can navigate autonomously to yield an engineered enzyme with a desired attribute. This laboratory, rather, the automated protocol, is referred to by an acronym - SAMPLE. This refers to Self-driving Autonomous Machines for Protein Landscape Exploration. The paper describes a prototype involving the engineering of a glycoside hydrolase for enhanced thermostability. The 'brain', the computational component behind this automated system, was designed to learn protein sequence- function relationships from a curated dataset. These designer proteins were then evaluated by a fully automated robotic system that could synthesize and experimentally characterize the designed protein and provide feedback to the agent, i.e., the computational component, to fine-tune its understanding of the system. The SAMPLE agents were thus designed to continually refine their understanding of the protein landscape by actively acquiring information in the search process. As this intelligent agent learns protein sequence-function relationships from a curated, diverse dataset, this feedback is crucial to refine landscape exploration and the design of new proteins based on the updated hypothesis. In this prototype, four SAMPLE agents were tasked with this goal. The goal of each of these agents was to navigate the glycoside hydrolase landscape and identify enzymes with enhanced thermal tolerance. Differences in the search behavior of individual agents primarily arise from experimental measurement noise. However, despite differences in their search behavior, all four agents could converge on a thermostable glycoside hydrolase - a remarkable feat as it apparently did not need any human intervention.

Enzyme engineering lets us play with new building blocks in non-ribosomal peptide synthesis.

In a recent issue of Nature Chemical Biology, Folger et al. demonstrated a high-throughput approach for engineering peptide bond forming domains from non-ribosomal peptide synthesis. A non-ribosomal peptide synthetase module from surfactin biosynthesis was reprogrammed to accept a fatty acid substrate into peptide biosynthesis, thus illustrating the potential of this approach for generating novel bioactive peptides.

Biosynthetic production of anticoagulant heparin polysaccharides through metabolic and sulfotransferases engineering strategies.

Heparin is an important anticoagulant drug, and microbial heparin biosynthesis is a potential alternative to animal-derived heparin production. However, effectively using heparin synthesis enzymes faces challenges, especially with microbial recombinant expression of active heparan sulfate N-deacetylase/N-sulfotransferase. Here, we introduce the monosaccharide N-trifluoroacetylglucosamine into Escherichia coli K5 to facilitate sulfation modification. The Protein Repair One-Stop Service-Focused Rational Iterative Site-specific Mutagenesis (PROSS-FRISM) platform is used to enhance sulfotransferase efficiency, resulting in the engineered NST-M8 enzyme with significantly improved stability (11.32-fold) and activity (2.53-fold) compared to the wild-type N-sulfotransferase. This approach can be applied to engineering various sulfotransferases. The multienzyme cascade reaction enables the production of active heparin from bioengineered heparosan, demonstrating anti-FXa (246.09 IU/mg) and anti-FIIa (48.62 IU/mg) activities. This study offers insights into overcoming challenges in heparin synthesis and modification, paving the way for the future development of animal-free heparins using a cellular system-based semisynthetic strategy.

An integrated technology for quantitative wide mutational scanning of human antibody Fab libraries.

Antibodies are engineerable quantities in medicine. Learning antibody molecular recognition would enable the in silico design of high affinity binders against nearly any proteinaceous surface. Yet, publicly available experiment antibody sequence-binding datasets may not contain the mutagenic, antigenic, or antibody sequence diversity necessary for deep learning approaches to capture molecular recognition. In part, this is because limited experimental platforms exist for assessing quantitative and simultaneous sequence-function relationships for multiple antibodies. Here we present MAGMA-seq, an integrated technology that combines multiple antigens and multiple antibodies and determines quantitative biophysical parameters using deep sequencing. We demonstrate MAGMA-seq on two pooled libraries comprising mutants of nine different human antibodies spanning light chain gene usage, CDR H3 length, and antigenic targets. We demonstrate the comprehensive mapping of potential antibody development pathways, sequence-binding relationships for multiple antibodies simultaneously, and identification of paratope sequence determinants for binding recognition for broadly neutralizing antibodies (bnAbs). MAGMA-seq enables rapid and scalable antibody engineering of multiple lead candidates because it can measure binding for mutants of many given parental antibodies in a single experiment.

Engineering of the Long-Main-Chain Monomer-Incorporating Polyhydroxyalkanoate Synthase PhaCAR for the Biosynthesis of Poly[(R)-3-hydroxybutyrate-co-6-hydroxyhexanoate].

Polyhydroxyalkanoate (PHA) synthases (PhaCs) are useful and versatile tools for the production of aliphatic polyesters. Here, the chimeric PHA synthase PhaCAR was engineered to increase its capacity to incorporate unusual 6-hydroxyhexanoate (6HHx) units. Mutations at positions 149 and 314 in PhaCAR were previously found to increase the incorporation of an analogous natural monomer, 3-hydroxyhexanoate (3HHx). We attempted to repurpose the mutations to produce 6HHx-containing polymers. Site-directed saturation mutants at these positions were applied for P(3HB-co-6HHx) synthesis in Escherichia coli. As a result, the N149D and F314Y mutants effectively increased the 6HHx fraction. Moreover, the pairwise NDFY mutation further increased the 6HHx fraction, which reached 22 mol %. This increase was presumably caused by altered enzyme activity rather than altered expression levels, as assessed based on immunoblot analysis. The glass transition temperature and crystallinity of P(3HB-co-6HHx) decreased as the 6HHx fraction increased.

Coiled-Coil Protein Hydrogels Engineered with Minimized Fiber Diameters for Sustained Release of Doxorubicin in Triple-Negative Breast Cancer.

Triple-negative breast cancer (TNBC) lacks expressed protein targets, making therapy development challenging. Hydrogels offer a promising new route in this regard by improving the chemotherapeutic efficacy through increased solubility and sustained release. Moreover, subcutaneous hydrogel administration reduces patient burden by requiring less therapy and shorter treatment times. We recently established the design principles for the supramolecular assembly of single-domain coiled-coils into hydrogels. Using a modified computational design algorithm, we designed Q8, a hydrogel with rapid assembly for faster therapeutic hydrogel preparation. Q8 encapsulates and releases doxorubicin (Dox), enabling localized sustained release via subcutaneous injection. Remarkably, a single subcutaneous injection of Dox-laden Q8 (Q8•Dox) significantly suppresses tumors within just 1 week. This work showcases the bottom-up engineering of a fully protein-based drug delivery vehicle for improved TBNC treatment via noninvasive localized therapy.

Protein Engineering with Lightweight Graph Denoising Neural Networks.

Protein engineering faces challenges in finding optimal mutants from a massive pool of candidate mutants. In this study, we introduce a deep-learning-based data-efficient fitness prediction tool to steer protein engineering. Our methodology establishes a lightweight graph neural network scheme for protein structures, which efficiently analyzes the microenvironment of amino acids in wild-type proteins and reconstructs the distribution of the amino acid sequences that are more likely to pass natural selection. This distribution serves as a general guidance for scoring proteins toward arbitrary properties on any order of mutations. Our proposed solution undergoes extensive wet-lab experimental validation spanning diverse physicochemical properties of various proteins, including fluorescence intensity, antigen-antibody affinity, thermostability, and DNA cleavage activity. More than 40% of ProtLGN-designed single-site mutants outperform their wild-type counterparts across all studied proteins and targeted properties. More importantly, our model can bypass the negative epistatic effect to combine single mutation sites and form deep mutants with up to seven mutation sites in a single round, whose physicochemical properties are significantly improved. This observation provides compelling evidence of the structure-based model's potential to guide deep mutations in protein engineering. Overall, our approach emerges as a versatile tool for protein engineering, benefiting both the computational and bioengineering communities.

A general approach for selection of epitope-directed binders to proteins.

Directing antibodies to a particular epitope among many possible on a target protein is a significant challenge. Here, we present a simple and general method for epitope-directed selection (EDS) using a differential phage selection strategy. This involves engineering the protein of interest (POI) with the epitope of interest (EOI) mutated using a systematic bioinformatics algorithm to guide the local design of an EOI decoy variant. Using several alternating rounds of negative selection with the EOI decoy variant followed by positive selection on the wild-type POI, we were able to identify highly specific and potent antibodies to five different EOI antigens that bind and functionally block known sites of proteolysis. Among these, we developed highly specific antibodies that target the proteolytic site on the CUB domain containing protein 1 (CDCP1) to prevent its proteolysis allowing us to study the cellular maturation of this event that triggers malignancy. We generated antibodies that recognize the junction between the pro- and catalytic domains for three different matrix metalloproteases (MMPs), MMP1, MMP3, and MMP9, that selectively block activation of each of these enzymes and impair cell migration. We targeted a proteolytic epitope on the cell surface receptor, EPH Receptor A2 (EphA2), that is known to transform it from a tumor suppressor to an oncoprotein. We believe that the EDS method greatly facilitates the generation of antibodies to specific EOIs on a wide range of proteins and enzymes for broad therapeutic and diagnostic applications.

Engineered protein cages with enhanced extracellular drug release for elevated antitumor efficacy.

Human heavy chain ferritin (HFn) protein cage has been explored as a nanocarrier for targeted anticancer drug delivery. Here, we introduced a matrix metalloproteinases (MMPs)-cleavable sequence into the DE loop of HFn, creating an MMP-responsive variant, MR-HFn, for localized and extracellular drug release. The crystal structure of MR-HFn revealed that the addition of the MMPs recognition sequence did not affect the self-assembly of HFn but presented a surface-exposed loop susceptible to MMPs cleavage. Biochemical analysis indicated that this engineered protein cage is responsive to MMPs, enabling the targeted release of encapsulated drugs. To evaluate the therapeutic potential of this engineered protein cage, monosubstituted ß-carboxy phthalocyanine zinc (CPZ), a type of photosensitizer, was loaded inside this protein cage. The prepared CPZ@MR-HFn showed higher uptake and stronger phototoxicity in MMPs overexpressed tumor cells, as well as enhanced penetration into multicellular tumor spheroids compared with its counterpart CPZ@HFn in vitro. In vivo, CPZ@MR-HFn displayed a higher tumor inhibitory rate than CPZ@HFn under illumination. These results indicated that MR-HFn is a promising nanocarrier for anticancer drug delivery and the MMP-responsive strategy here can also be adapted for other stimuli.

Origin of Enantioselectivity in Engineered Cytochrome c-Catalyzed Carbon-Radical FePP Hydrolysis Revealed Using QM/MM (ABEEM Polarizable Force Field) and MD Simulations.

The origin of highly efficient asymmetric aminohydroxylation of styrene catalyzed by engineered cytochrome c is investigated by the developed Atom-Bond Electronegativity Equalization Method polarizable force field (ABEEM PFF), which is a combined outcome of electronic and steric effects. Model molecules were used to establish the charge parameters of the ABEEM PFF, for which the bond-stretching and angle-bending parameters were obtained by using a combination of modified Seminario and scan methods. The interactions between carbon-radical Fe-porphyrin (FePP) and waters are simulated by molecular dynamics, which shows a clear preference for the pre-R over the pre-S. This preference is attributed to the hydrogen-bond between the mutated 100S and 101P residues as well as van der Waals interactions, enforcing a specific conformation of the carbon-radical FePP complex within the binding pocket. Meanwhile, the hydrogen-bond between water and the nitrogen atom in the active intermediate dictates the stereochemical outcome. Quantum mechanics/molecular mechanics (QM/MM (ABEEM PFF)) and free-energy perturbation calculations elucidate that the 3RTS is characterized by sandwich-like structure among adjacent amino acid residues, which exhibits greater stability than crowed arrangement in 3STS and enables the R enantiomer to form more favorably. Thus, this study provides mechanistic insight into the catalytic reaction of hemoproteins.

Electrochemical Impedance Spectroscopy for the Sensing of the Kinetic Parameters of Engineered Enzymes.

The study presents a promising approach to enzymatic kinetics using Electrochemical Impedance Spectroscopy (EIS) to assess fundamental parameters of modified enteropeptidases. Traditional methods for determining these parameters, while effective, often lack versatility and convenience, especially under varying environmental conditions. The use of EIS provides a novel approach that overcomes these limitations. The enteropeptidase underwent genetic modification through the introduction of single amino acid modifications to assess their effect on enzyme kinetics. However, according to the one-sample t-test results, the difference between the engineered enzymes and hEKL was not statistically significant by conventional criteria. The kinetic parameters were analyzed using fluorescence spectroscopy and EIS, which was found to be an effective tool for the real-time measurement of enzyme kinetics. The results obtained through EIS were not significantly different from those obtained through traditional fluorescence spectroscopy methods (p value >> 0.05). The study validates the use of EIS for measuring enzyme kinetics and provides insight into the effects of specific amino acid changes on enteropeptidase function. These findings have potential applications in biotechnology and biochemical research, suggesting a new method for rapidly assessing enzymatic activity.