Structure and mechanisms of transport of human Asc1/CD98hc amino acid transporter.

Recent cryoEM studies elucidated details of the structural basis for the substrate selectivity and translocation of heteromeric amino acid transporters. However, Asc1/CD98hc is the only neutral heteromeric amino acid transporter that can function through facilitated diffusion, and the only one that efficiently transports glycine and D-serine, and thus has a regulatory role in the central nervous system. Here we use cryoEM, ligand-binding simulations, mutagenesis, transport assays, and molecular dynamics to define human Asc1/CD98hc determinants for substrate specificity and gain insights into the mechanisms that govern substrate translocation by exchange and facilitated diffusion. The cryoEM structure of Asc1/CD98hc is determined at 3.4-3.8 Å resolution, revealing an inward-facing semi-occluded conformation. We find that Ser 246 and Tyr 333 are essential for Asc1/CD98hc substrate selectivity and for the exchange and facilitated diffusion modes of transport. Taken together, these results reveal the structural bases for ligand binding and transport features specific to human Asc1.

Immunization with V987H-stabilized Spike glycoprotein protects K18-hACE2 mice and golden Syrian hamsters upon SARS-CoV-2 infection.

Safe and effective severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) vaccines are crucial to fight against the coronavirus disease 2019 pandemic. Most vaccines are based on a mutated version of the Spike glycoprotein [K986P/V987P (S-2P)] with improved stability, yield and immunogenicity. However, S-2P is still produced at low levels. Here, we describe the V987H mutation that increases by two-fold the production of the recombinant Spike and the exposure of the receptor binding domain (RBD). S-V987H immunogenicity is similar to S-2P in mice and golden Syrian hamsters (GSH), and superior to a monomeric RBD. S-V987H immunization confer full protection against severe disease in K18-hACE2 mice and GSH upon SARS-CoV-2 challenge (D614G or B.1.351 variants). Furthermore, S-V987H immunized K18-hACE2 mice show a faster tissue viral clearance than RBD- or S-2P-vaccinated animals challenged with D614G, B.1.351 or Omicron BQ1.1 variants. Thus, S-V987H protein might be considered for future SARS-CoV-2 vaccines development.

Immunisation efficacy of a stabilised SARS-CoV-2 spike glycoprotein in two geriatric animal models.

Age is associated with reduced efficacy of vaccines and linked to higher risk of severe COVID-19. Here we determined the impact of ageing on the efficacy of a SARS-CoV-2 vaccine based on a stabilised Spike glycoprotein (S-29) that had previously shown high efficacy in young animals. Thirteen to 18-month-old golden Syrian hamsters (GSH) and 22-23-month-old K18-hCAE2 mice were immunised twice with S-29 protein in AddaVaxTM adjuvant. GSH were intranasally inoculated with SARS-CoV-2 either two weeks or four months after the booster dose, while all K18-hACE2 mice were intranasally inoculated two weeks after the second immunisation. Body weight and clinical signs were recorded daily post-inoculation. Lesions and viral load were investigated in different target tissues. Immunisation induced seroconversion and production of neutralising antibodies; however, animals were only partially protected from weight loss. We observed a significant reduction in the amount of viral RNA and a faster viral protein clearance in the tissues of immunized animals. Infectious particles showed a faster decay in vaccinated animals while tissue lesion development was not altered. In GSH, the shortest interval between immunisation and inoculation reduced RNA levels in the lungs, while the longest interval was equally effective in reducing RNA in nasal turbinates; viral nucleoprotein amount decreased in both tissues. In mice, immunisation was able to improve the survival of infected animals. Despite the high protection shown in young animals, S-29 efficacy was reduced in the geriatric population. Our research highlights the importance of testing vaccine efficacy in older animals as part of preclinical vaccine evaluation.

Exploiting cyclodextrins as artificial chaperones to enhance enzyme protection through supramolecular engineering.

We report a method of enzyme stabilisation exploiting the artificial protein chaperone properties of ß-cyclodextrin (ß-CD) covalently embedded in an ultrathin organosilica layer. Putative interaction points of this artificial chaperone system with the surface of the selected enzyme were studied in silico using a protein energy landscape exploration simulation algorithm. We show that this enzyme shielding method allows for drastic enhancement of enzyme stability under thermal and chemical stress conditions, along with broadening the optimal temperature range of the biocatalyst. The presence of the ß-CD macrocycle within the protective layer supports protein refolding after treatment with a surfactant.

Virus-like particle-mediated delivery of structure-selected neoantigens demonstrates immunogenicity and antitumoral activity in mice.

BACKGROUND: Neoantigens are patient- and tumor-specific peptides that arise from somatic mutations. They stand as promising targets for personalized therapeutic cancer vaccines. The identification process for neoantigens has evolved with the use of next-generation sequencing technologies and bioinformatic tools in tumor genomics. However, in-silico strategies for selecting immunogenic neoantigens still have very low accuracy rates, since they mainly focus on predicting peptide binding to Major Histocompatibility Complex (MHC) molecules, which is key but not the sole determinant for immunogenicity. Moreover, the therapeutic potential of neoantigen-based vaccines may be enhanced using an optimal delivery platform that elicits robust de novo immune responses. METHODS: We developed a novel neoantigen selection pipeline based on existing software combined with a novel prediction method, the Neoantigen Optimization Algorithm (NOAH), which takes into account structural features of the peptide/MHC-I interaction, as well as the interaction between the peptide/MHC-I complex and the TCR, in its prediction strategy. Moreover, to maximize neoantigens' therapeutic potential, neoantigen-based vaccines should be manufactured in an optimal delivery platform that elicits robust de novo immune responses and bypasses central and peripheral tolerance. RESULTS: We generated a highly immunogenic vaccine platform based on engineered HIV-1 Gag-based Virus-Like Particles (VLPs) expressing a high copy number of each in silico selected neoantigen. We tested different neoantigen-loaded VLPs (neoVLPs) in a B16-F10 melanoma mouse model to evaluate their capability to generate new immunogenic specificities. NeoVLPs were used in in vivo immunogenicity and tumor challenge experiments. CONCLUSIONS: Our results indicate the relevance of incorporating other immunogenic determinants beyond the binding of neoantigens to MHC-I. Thus, neoVLPs loaded with neoantigens enhancing the interaction with the TCR can promote the generation of de novo antitumor-specific immune responses, resulting in a delay in tumor growth. Vaccination with the neoVLP platform is a robust alternative to current therapeutic vaccine approaches and a promising candidate for future personalized immunotherapy.

Discovery and biochemical characterization of thermostable glycerol oxidases.

Alditol oxidases are promising tools for the biocatalytic oxidation of glycerol to more valuable chemicals. By integrating in silico bioprospecting with cell-free protein synthesis and activity screening, an effective pipeline was developed to rapidly identify enzymes that are active on glycerol. Three thermostable alditol oxidases from Actinobacteria Bacterium, Streptomyces thermoviolaceus, and Thermostaphylospora chromogena active on glycerol were discovered. The characterization of these three flavoenzymes demonstrated their glycerol oxidation activities, preference for alkaline conditions, and excellent thermostabilities with melting temperatures higher than 75 °C. Structural elucidation of the alditol oxidase from Actinobacteria Bacterium highlighted a constellation of side chains that engage the substrate through several hydrogen bonds, a histidine residue covalently bound to the FAD prosthetic group, and a tunnel leading to the active site. Upon computational simulations of substrate binding, a double mutant targeting a residue pair at the tunnel entrance was created and found to display an improved thermal stability and catalytic efficiency for glycerol oxidation. The hereby described alditol oxidases form a valuable panel of oxidative biocatalysts that can perform regioselective oxidation of glycerol and other polyols. KEY POINTS: • Rapid pipeline designed to identify putative oxidases • Biochemical and structural characterization of alditol oxidases • Glycerol oxidation to more valuable derivatives.

Novel Spike-stabilized trimers with improved production protect K18-hACE2 mice and golden Syrian hamsters from the highly pathogenic SARS-CoV-2 Beta variant.

Most COVID-19 vaccines are based on the SARS-CoV-2 Spike glycoprotein (S) or their subunits. However, S shows some structural instability that limits its immunogenicity and production, hampering the development of recombinant S-based vaccines. The introduction of the K986P and V987P (S-2P) mutations increases the production and immunogenicity of the recombinant S trimer, suggesting that these two parameters are related. Nevertheless, S-2P still shows some molecular instability and it is produced with low yield. Here we described a novel set of mutations identified by molecular modeling and located in the S2 region of the S-2P that increase its production up to five-fold. Besides their immunogenicity, the efficacy of two representative S-2P-based mutants, S-29 and S-21, protecting from a heterologous SARS-CoV-2 Beta variant challenge was assayed in K18-hACE2 mice (an animal model of severe SARS-CoV-2 disease) and golden Syrian hamsters (GSH) (a moderate disease model). S-21 induced higher level of WH1 and Delta variants neutralizing antibodies than S-2P in K18-hACE2 mice three days after challenge. Viral load in nasal turbinate and oropharyngeal samples were reduced in S-21 and S-29 vaccinated mice. Despite that, only the S-29 protein protected 100% of K18-hACE2 mice from severe disease. When GSH were analyzed, all immunized animals were protected from disease development irrespectively of the immunogen they received. Therefore, the higher yield of S-29, as well as its improved immunogenicity and efficacy protecting from the highly pathogenic SARS-CoV-2 Beta variant, pinpoint the S-29 mutant as an alternative to the S-2P protein for future SARS-CoV-2 vaccine development.

Enhancing the Hydrolytic Activity of a Lipase towards Larger Triglycerides through Lid Domain Engineering.

Lipases have valuable potential for industrial use, particularly those mostly active against water-insoluble substrates, such as triglycerides composed of long-carbon chain fatty acids. However, in most cases, engineered variants often need to be constructed to achieve optimal performance for such substrates. Protein engineering techniques have been reported as strategies for improving lipase characteristics by introducing specific mutations in the cap domain of esterases or in the lid domain of lipases or through lid domain swapping. Here, we improved the lipase activity of a lipase (WP_075743487.1, or LipMRD) retrieved from the Marine Metagenomics MarRef Database and assigned to the Actinoalloteichus genus. The improvement was achieved through site-directed mutagenesis and by substituting its lid domain (FRGTEITQIKDWLTDA) with that of Rhizopus delemar lipase (previously R. oryzae; UniProt accession number, I1BGQ3) (FRGTNSFRSAITDIVF). The results demonstrated that the redesigned mutants gain activity against bulkier triglycerides, such as glyceryl tridecanoate and tridodecanoate, olive oil, coconut oil, and palm oil. Residue W89 (LipMRD numbering) appears to be key to the increase in lipase activity, an increase that was also achieved with lid swapping. This study reinforces the importance of the lid domains and their amino acid compositions in determining the substrate specificity of lipases, but the generalization of the lid domain swapping between lipases or the introduction of specific mutations in the lid domain to improve lipase activity may require further investigation.

Insights into peculiar fungal LPMO family members holding a short C-terminal sequence reminiscent of phosphate binding motifs.

Lytic polysaccharide monooxygenases (LPMOs) are taxonomically widespread copper-enzymes boosting biopolymers conversion (e.g. cellulose, chitin) in Nature. White-rot Polyporales, which are major fungal wood decayers, may possess up to 60 LPMO-encoding genes belonging to the auxiliary activities family 9 (AA9). Yet, the functional relevance of such multiplicity remains to be uncovered. Previous comparative transcriptomic studies of six Polyporales fungi grown on cellulosic substrates had shown the overexpression of numerous AA9-encoding genes, including some holding a C-terminal domain of unknown function ("X282"). Here, after carrying out structural predictions and phylogenetic analyses, we selected and characterized six AA9-X282s with different C-term modularities and atypical features hitherto unreported. Unexpectedly, after screening a large array of conditions, these AA9-X282s showed only weak binding properties to cellulose, and low to no cellulolytic oxidative activity. Strikingly, proteomic analysis revealed the presence of multiple phosphorylated residues at the surface of these AA9-X282s, including a conserved residue next to the copper site. Further analyses focusing on a 9 residues glycine-rich C-term extension suggested that it could hold phosphate-binding properties. Our results question the involvement of these AA9 proteins in the degradation of plant cell wall and open new avenues as to the divergence of function of some AA9 members.

Selective inhibitors of the PSEN1-gamma-secretase complex.

Clinical development of γ-secretases, a family of intramembrane cleaving proteases, as therapeutic targets for a variety of disorders including cancer and Alzheimer's disease was aborted because of serious mechanism-based side effects in the phase III trials of unselective inhibitors. Selective inhibition of specific γ-secretase complexes, containing either PSEN1 or PSEN2 as the catalytic subunit and APH1A or APH1B as supporting subunits, does provide a feasible therapeutic window in preclinical models of these disorders. We explore here the pharmacophoric features required for PSEN1 versus PSEN2 selective inhibition. We synthesized a series of brain penetrant 2-azabicyclo[2,2,2]octane sulfonamides and identified a compound with low nanomolar potency and high selectivity (>250-fold) toward the PSEN1-APH1B subcomplex versus PSEN2 subcomplexes. We used modeling and site-directed mutagenesis to identify critical amino acids along the entry part of this inhibitor into the catalytic site of PSEN1. Specific targeting one of the different γ-secretase complexes might provide safer drugs in the future.

NetCleave: An Open-Source Algorithm for Predicting C-Terminal Antigen Processing for MHC-I and MHC-II.

T cell epitopes presented on the surface of mammalian cells are subjected to a complex network of antigen processing and presentation. Among them, C-terminal antigen processing constitutes one of the main bottlenecks for the generation of epitopes, as it defines the C-terminal end of the final epitope and delimits the peptidome that will be presented downstream. Previously (Amengual-Rigo and Guallar, Sci Rep 111(11):1-8, 2021), we demonstrated that NetCleave stands out as one of the best algorithms for the prediction of C-terminal processing, which in its turn can be crucial to design peptide-based vaccination strategies. In this chapter, we provide a pipeline to exploit the full capabilities of NetCleave, an open-source and retrainable algorithm for predicting the C-terminal antigen processing for the MHC-I and MHC-II pathways.

Peroxygenase-Catalysed Selective Oxidation of Silanes to Silanols.

A peroxygenase-catalysed hydroxylation of organosilanes is reported. The recombinant peroxygenase from Agrocybe aegerita (AaeUPO) enabled efficient conversion of a broad range of silane starting materials in attractive productivities (up to 300 mM h-1 ), catalyst performance (up to 84 s-1 and more than 120 000 catalytic turnovers). Molecular modelling of the enzyme-substrate interaction puts a basis for the mechanistic understanding of AaeUPO selectivity.

AsiteDesign: a Semirational Algorithm for an Automated Enzyme Design.

With advances in protein structure predictions, the number of available high-quality structures has increased dramatically. In light of these advances, structure-based enzyme engineering is expected to become increasingly important for optimizing biocatalysts for industrial processes. Here, we present AsiteDesign, a Monte Carlo-based protocol for structure-based engineering of active sites. AsiteDesign provides a framework for introducing new catalytic residues in a given binding pocket to either create a new catalytic activity or alter the existing one. AsiteDesign is implemented using pyRosetta and incorporates enhanced sampling techniques to efficiently explore the search space. The protocol was tested by designing an alternative catalytic triad in the active site of Pseudomonas fluorescens esterase (PFE). The designed variant was experimentally verified to be active, demonstrating that AsiteDesign can find alternative catalytic triads. Additionally, the AsiteDesign protocol was employed to enhance the hydrolysis of a bulky chiral substrate (1-phenyl-2-pentyl acetate) by PFE. The experimental verification of the designed variants demonstrated that F158L/F198A and F125A/F158L mutations increased the hydrolysis of 1-phenyl-2-pentyl acetate from 8.9 to 66.7 and 23.4%, respectively, and reversed the enantioselectivity of the enzyme from (R) to (S)-enantiopreference, with 32 and 55% enantiomeric excess (ee), respectively.

Are Deep Learning Structural Models Sufficiently Accurate for Virtual Screening? Application of Docking Algorithms to AlphaFold2 Predicted Structures.

Machine learning-based protein structure prediction algorithms, such as RosettaFold and AlphaFold2, have greatly impacted the structural biology field, arousing a fair amount of discussion around their potential role in drug discovery. While there are few preliminary studies addressing the usage of these models in virtual screening, none of them focus on the prospect of hit-finding in a real-world virtual screen with a model based on low prior structural information. In order to address this, we have developed an AlphaFold2 version where we exclude all structural templates with more than 30% sequence identity from the model-building process. In a previous study, we used those models in conjunction with state-of-the-art free energy perturbation methods and demonstrated that it is possible to obtain quantitatively accurate results. In this work, we focus on using these structures in rigid receptor-ligand docking studies. Our results indicate that using out-of-the-box Alphafold2 models is not an ideal scenario for virtual screening campaigns; in fact, we strongly recommend to include some post-processing modeling to drive the binding site into a more realistic holo model.

Rational engineering of AA5_2 copper radical oxidases to probe the molecular determinants governing their substrate selectivity.

Fungal copper radical oxidases (CROs) from the Auxiliary Activity family 5 (AA5) constitute a group of metalloenzymes that oxidize a wide panel of natural compounds, such as galactose-containing saccharides or primary alcohols, into product derivatives exhibiting promising biotechnological interests. Despite a well-conserved first copper-coordination sphere and overall fold, some members of the AA5_2 subfamily are incapable of oxidizing galactose and galactosides but conversely efficiently catalyse the oxidation of diverse aliphatic alcohols. The objective of this study was to understand which residues dictate the substrate preferences between alcohol oxidases and galactose oxidases within the AA5_2 subfamily. Based on structural differences and molecular modelling predictions between the alcohol oxidase from Colletotrichum graminicola (CgrAlcOx) and the archetypal galactose oxidase from Fusarium graminearum (FgrGalOx), a rational mutagenesis approach was developed to target regions or residues potentially driving the substrate specificity of these enzymes. A set of 21 single and multiple CgrAlcOx variants was produced and characterized leading to the identification of six residues (W39, F138, M173, F174, T246, L302), in the vicinity of the active site, crucial for substrate recognition. Two multiple CgrAlcOx variants, i.e. M4F (W39F, F138W, M173R and T246Q) and M6 (W39F, F138W, M173R, F174Y, T246Q and L302P), exhibited a similar affinity for carbohydrate substrates when compared to FgrGalOx. In conclusion, using a rational site-directed mutagenesis approach, we identified key residues involved in the substrate selectivity of AA5_2 enzymes towards galactose-containing saccharides.

Structural Elucidation and Engineering of a Bacterial Carbohydrate Oxidase.

Flavin-dependent carbohydrate oxidases are valuable tools in biotechnological applications due to their high selectivity in the oxidation of carbohydrates. In this study, we report the biochemical and structural characterization of a recently discovered carbohydrate oxidase from the bacterium Ralstonia solanacearum, which is a member of the vanillyl alcohol oxidase flavoprotein family. Due to its exceptionally high activity toward N-acetyl-d-galactosamine and N-acetyl-d-glucosamine, the enzyme was named N-acetyl-glucosamine oxidase (NagOx). In contrast to most known (fungal) carbohydrate oxidases, NagOx could be overexpressed in a bacterial host, which facilitated detailed biochemical and enzyme engineering studies. Steady state kinetic analyses revealed that non-acetylated hexoses were also accepted as substrates albeit with lower efficiency. Upon determination of the crystal structure, structural insights into NagOx were obtained. A large cavity containing a bicovalently bound FAD, tethered via histidyl and cysteinyl linkages, was observed. Substrate docking highlighted how a single residue (Leu251) plays a key role in the accommodation of N-acetylated sugars in the active site. Upon replacement of Leu251 (L251R mutant), an enzyme variant was generated with a drastically modified substrate acceptance profile, tuned toward non-N-acetylated monosaccharides and disaccharides. Furthermore, the activity toward bulkier substrates such as the trisaccharide maltotriose was introduced by this mutation. Due to its advantage of being overexpressed in a bacterial host, NagOx can be considered a promising alternative engineerable biocatalyst for selective oxidation of monosaccharides and oligosaccharides.

Tandem metalloenzymes gate plant cell entry by pathogenic fungi.

Global food security is endangered by fungal phytopathogens causing devastating crop production losses. Many of these pathogens use specialized appressoria cells to puncture plant cuticles. Here, we unveil a pair of alcohol oxidase-peroxidase enzymes to be essential for pathogenicity. Using Colletotrichum orbiculare, we show that the enzyme pair is cosecreted by the fungus early during plant penetration and that single and double mutants have impaired penetration ability. Molecular modeling, biochemical, and biophysical approaches revealed a fine-tuned interplay between these metalloenzymes, which oxidize plant cuticular long-chain alcohols into aldehydes. We show that the enzyme pair is involved in transcriptional regulation of genes necessary for host penetration. The identification of these infection-specific metalloenzymes opens new avenues on the role of wax-derived compounds and the design of oxidase-specific inhibitors for crop protection.

Recent PELE Developments and Applications in Drug Discovery Campaigns.

Computer simulation techniques are gaining a central role in molecular pharmacology. Due to several factors, including the significant improvements of traditional molecular modelling, the irruption of machine learning methods, the massive data generation, or the unlimited computational resources through cloud computing, the future of pharmacology seems to go hand in hand with in silico predictions. In this review, we summarize our recent efforts in such a direction, centered on the unconventional Monte Carlo PELE software and on its coupling with machine learning techniques. We also provide new data on combining two recent new techniques, aquaPELE capable of exhaustive water sampling and fragPELE, for fragment growing.

Design and Characterization of In-One Protease-Esterase PluriZyme.

Proteases are abundant in prokaryotic genomes (~10 per genome), but their recovery encounters expression problems, as only 1% can be produced at high levels; this value differs from that of similarly abundant esterases (1-15 per genome), 50% of which can be expressed at good levels. Here, we design a catalytically efficient artificial protease that can be easily produced. The PluriZyme EH1AB1 with two active sites supporting the esterase activity was employed. A Leu24Cys mutation in EH1AB1, remodelled one of the esterase sites into a proteolytic one through the incorporation of a catalytic dyad (Cys24 and His214). The resulting artificial enzyme, EH1AB1C, efficiently hydrolysed (azo)casein at pH 6.5-8.0 and 60-70 °C. The presence of both esterase and protease activities in the same scaffold allowed the one-pot cascade synthesis (55.0 ± 0.6% conversion, 24 h) of L-histidine methyl ester from the dipeptide L-carnosine in the presence of methanol. This study demonstrates that active sites supporting proteolytic activity can be artificially introduced into an esterase scaffold to design easy-to-produce in-one protease-esterase PluriZymes for cascade reactions, namely, the synthesis of amino acid esters from dipeptides. It is also possible to design artificial proteases with good production yields, in contrast to natural proteases that are difficult to express.

EP-Pred: A Machine Learning Tool for Bioprospecting Promiscuous Ester Hydrolases.

When bioprospecting for novel industrial enzymes, substrate promiscuity is a desirable property that increases the reusability of the enzyme. Among industrial enzymes, ester hydrolases have great relevance for which the demand has not ceased to increase. However, the search for new substrate promiscuous ester hydrolases is not trivial since the mechanism behind this property is greatly influenced by the active site's structural and physicochemical characteristics. These characteristics must be computed from the 3D structure, which is rarely available and expensive to measure, hence the need for a method that can predict promiscuity from sequence alone. Here we report such a method called EP-pred, an ensemble binary classifier, that combines three machine learning algorithms: SVM, KNN, and a Linear model. EP-pred has been evaluated against the Lipase Engineering Database together with a hidden Markov approach leading to a final set of ten sequences predicted to encode promiscuous esterases. Experimental results confirmed the validity of our method since all ten proteins were found to exhibit a broad substrate ambiguity.