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Abstract 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.

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.

Acid mine drainage (AMD) systems are extremely acidic and are metal-rich formations inhabited by relatively low-complexity communities of acidophiles whose enzymes remain mostly uncharacterized. Indeed, enzymes from only a few AMD sites have been studied. The low number of available cultured representatives and genome sequences of acidophiles inhabiting AMDs makes it difficult to assess the potential of these environments for enzyme bioprospecting. In this study, using naïve and in silico metagenomic approaches, we retrieved 16 esterases from the α/β-hydrolase fold superfamily with the closest match from uncultured acidophilic Acidobacteria, Actinobacteria (Acidithrix, Acidimicrobium, and Ferrimicrobium), Acidiphilium, and other Proteobacteria inhabiting the Los Rueldos site, which is a unique AMD formation in northwestern Spain with a pH of ∼2. Within this set, only two polypeptides showed high homology (99.4%), while for the rest, the pairwise identities ranged between 4 and 44.9%, suggesting that the diversity of active polypeptides was dominated not by a particular type of protein or highly similar clusters of proteins, but by diverse non-redundant sequences. The enzymes exhibited amino acid sequence identities ranging from 39 to 99% relative to homologous proteins in public databases, including those from other AMDs, thus indicating the potential novelty of proteins associated with a specialized acidophilic community. Ten of the 16 hydrolases were successfully expressed in Escherichia coli. The pH for optimal activity ranged from 7.0 to 9.0, with the enzymes retaining 33–68% of their activities at pH 5.5, which was consistent with the relative frequencies of acid residues (from 54 to 67%). The enzymes were the most active at 30–65°C, retaining 20–61% of their activity under the thermal conditions characterizing Los Rueldos (13.8 ± 0.6°C). The analysis of the substrate specificity revealed the capacity of six hydrolases to efficiently degrade (up to 1,652 ± 75 U/g at pH 8.0 and 30°C) acrylic- and terephthalic-like [including bis(2-hydroxyethyl)-terephthalate, BHET] esters, and these enzymes could potentially be of use for developing plastic degradation strategies yet to be explored. Our assessment uncovers the novelty and potential biotechnological interest of enzymes present in the microbial populations that inhibit the Los Rueldos AMD system.

Abstract The protective effect of neutralizing antibodies in SARS-CoV-2 infected individuals is not yet well defined. To address this issue, we have analyzed the kinetics of neutralizing antibody responses and their association with disease severity. Between March and May 2020, the prospective KING study enrolled 72 COVID-19+ participants grouped according to disease severity. SARS-CoV-2 infection was diagnosed by serological and virological tests. Plasma neutralizing responses were assessed against replicative virus and pseudoviral particles. Multiple regression and non-parametric tests were used to analyze dependence of parameters. The magnitude of neutralizing titers significantly increased with disease severity. Hospitalized individuals developed higher titers compared to mild-symptomatic and asymptomatic individuals, which together showed titers below the detection limit in 50% of cases. Longitudinal analysis confirmed the strong differences in neutralizing titers between non-hospitalized and hospitalized participants and showed rapid kinetics of appearance of neutralizing antibodies (50% and 80% of maximal activity reached after 11 and 17 days after symptoms onset, respectively) in hospitalized patients. No significant impact of age, gender or treatment on the neutralizing titers was observed in this limited cohort. These data identify a clear association of humoral immunity with disease severity and point to immune mechanisms other than antibodies as relevant players in COVID-19 protection.

Reinfections with SARS-CoV-2 have already been documented in humans, although its real incidence is currently unknown. Besides having a great impact on public health, this phenomenon raises the question of immunity generated by a single infection is sufficient to provide sterilizing/protective immunity to a subsequent SARS-CoV-2 re-exposure. The Golden Syrian hamster is a manageable animal model to explore immunological mechanisms able to counteract COVID-19, as it recapitulates pathological aspects of mild to moderately affected patients. Here, we report that SARS-CoV-2-inoculated hamsters resolve infection in the upper and lower respiratory tracts within seven days upon inoculation with the Cat01 (G614) SARS-CoV-2 isolate. Three weeks after the primary challenge, and despite high titres of neutralizing antibodies, half of the animals were susceptible to reinfection by both identical (Cat01, G614) and variant (WA/1, D614) SARS-CoV-2 isolates. However, upon re-inoculation, only nasal tissues were transiently infected with much lower viral replication than those observed after the first inoculation. These data indicate that a primary SARS-CoV-2 infection is not sufficient to elicit a sterilizing immunity in hamster models but protects against lung disease.

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.

There is an urgent need to identify therapeutics for the treatment of Coronavirus disease 2019 (COVID-19). Although different antivirals are given for the clinical management of SARS-CoV-2 infection, their efficacy is still under evaluation. Here, we have screened existing drugs approved for human use in a variety of diseases, to compare how they counteract SARS-CoV-2-induced cytopathic effect and viral replication in vitro. Among the potential 72 antivirals tested herein that were previously proposed to inhibit SARS-CoV-2 infection, only 18 % had an IC50 below 25 µM or 102 IU/ml. These included plitidepsin, novel cathepsin inhibitors, nelfinavir mesylate hydrate, interferon 2-alpha, interferon-gamma, fenofibrate, camostat along the well-known remdesivir and chloroquine derivatives. Plitidepsin was the only clinically approved drug displaying nanomolar efficacy. Four of these families, including novel cathepsin inhibitors, blocked viral entry in a cell—type specific manner. Since the most effective antivirals usually combine therapies that tackle the virus at different steps of infection, we also assessed several drug combinations. Although no particular synergy was found, inhibitory combinations did not reduce their antiviral activity. Thus, these combinations could decrease the potential emergence of resistant viruses. Antivirals prioritized herein identify novel compounds and their mode of action, while independently replicating the activity of a reduced proportion of drugs which are mostly approved for clinical use. Combinations of these drugs should be tested in animal models to inform the design of fast track clinical trials.

Abstract 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.

Abstract 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.

Abstract 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.

Protein engineering is the design and modification of protein structures to optimize their functions or create novel functionalities for applications in biotechnology, medicine or industry. It represents an essential scientific solution for many of the environmental and societal challenges ahead of us, such as polymer degradation. Unlike traditional chemical methods, enzyme-mediated degradation is selective and environmentally friendly and requires milder conditions. Computational methods will play a critical role in developing such solutions by enabling more efficient bioprospecting of natural polymer-degrading enzymes. They provide structural information, generate mechanistic studies, and formulate new hypotheses, facilitating the modeling and modification of these biocatalysts through enzyme engineering. The recent development of pluriZymes constitutes an example, providing a rational mechanism to integrate different biochemical processes into one single enzyme. In this review, we summarize our recent efforts in this line and introduce our early work towards polymer degradation using a pluriZyme-like technology, including our latest development in PET nanoparticle degradation. Moreover, we provide a comprehensive recipe for developing one’s own pluriZyme so that different laboratories can experiment with them and establish new limits. With modest computational resources and with help from this review, your first pluriZyme is one step closer.

Abstract 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.

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.

Abstract Antigens presented on the cell surface have been subjected to multiple biological processes. Among them, C-terminal antigen processing constitutes one of the main bottlenecks of the peptide presentation pathways, as it delimits the peptidome that will be subjected downstream. Here, we present NetCleave, an open-source and retrainable algorithm for the prediction of the C-terminal antigen processing for both MHC-I and MHC-II pathways. NetCleave architecture consists of a neural network trained on 46 different physicochemical descriptors of the cleavage site amino acids. Our results demonstrate that prediction of C-terminal antigen processing achieves high accuracy on MHC-I (AUC of 0.91), while it remains challenging for MHC-II (AUC of 0.66). Moreover, we evaluated the performance of NetCleave and other prediction tools for the evaluation of four independent immunogenicity datasets (H2-Db, H2-Kb, HLA-A*02:01 and HLA-B:07:02). Overall, we demonstrate that NetCleave stands out as one of the best algorithms for the prediction of C-terminal processing, and we provide one of the first evidence that C-terminal processing predictions may help in the discovery of immunogenic peptides.

The emerging SARS-CoV-2 variants of concern (VOCs) may display enhanced transmissibility, more severity and/or immune evasion; however, the pathogenesis of these new VOCs in experimental SARS-CoV-2 models or the potential infection of other animal species is not completely understood. Here we infected K18-hACE2 transgenic mice with B.1, B.1.351/Beta, B.1.617.2/Delta and BA.1.1/Omicron isolates and demonstrated heterogeneous infectivity and pathogenesis. B.1.351/Beta variant was the most pathogenic, while BA.1.1/Omicron led to lower viral RNA in the absence of major visible clinical signs. In parallel, we infected wildtype (WT) mice and confirmed that, contrary to B.1 and B.1.617.2/Delta, B.1.351/Beta and BA.1.1/Omicron can infect them. Infection in WT mice coursed without major clinical signs and viral RNA was transient and undetectable in the lungs by day 7 post-infection. In silico modeling supported these findings by predicting B.1.351/Beta receptor binding domain (RBD) mutations result in an increased affinity for both human and murine ACE2 receptors, while BA.1/Omicron RBD mutations only show increased affinity for murine ACE2.

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.

Type IV pili are bacterial surface-exposed filaments that are built up by small monomers called pilin proteins. Pilins are synthesized as longer precursors (prepilins), the N-terminal signal peptide of which must be removed by the processing protease PilD. A mutant of the cyanobacterium Synechocystis sp. PCC 6803 lacking the PilD protease is not capable of photoautotrophic growth because of the impaired function of Sec translocons. Here, we isolated phototrophic suppressor strains of the original ΔpilD mutant and, by sequencing their genomes, identified secondary mutations in the SigF sigma factor, the γ subunit of RNA polymerase, the signal peptide of major pilin PilA1, and in the pilA1-pilA2 intergenic region. Characterization of suppressor strains suggests that, rather than the total prepilin level in the cell, the presence of non-glycosylated PilA1 prepilin is specifically harmful. We propose that the restricted lateral mobility of the non-glycosylated PilA1 prepilin causes its accumulation in the translocon-rich membrane domains, which attenuates the synthesis of membrane proteins.

Fungal unspecific peroxygenases (UPOs) are hybrid biocatalysts with peroxygenative activity that insert oxygen into non-activated compounds, while also possessing convergent peroxidative activity for one electron oxidation reactions. In several ligninolytic peroxidases, the site of peroxidative activity is associated with an oxidizable aromatic residue at the protein surface that connects to the buried heme domain through a long-range electron transfer (LRET) pathway. However, the peroxidative activity of these enzymes may also be initiated at the heme access channel. In this study, we examined the origin of the peroxidative activity of UPOs using an evolved secretion variant (PaDa-I mutant) from Agrocybe aegerita as our point of departure. After analyzing potential radical-forming aromatic residues at the PaDa-I surface by QM/MM, independent saturation mutagenesis libraries of Trp24, Tyr47, Tyr79, Tyr151, Tyr265, Tyr281, Tyr293 and Tyr325 were constructed and screened with both peroxidative and peroxygenative substrates. These mutant libraries were mostly inactive, with only a few functional clones detected, none of these showing marked differences in the peroxygenative and peroxidative activities. By contrast, when the flexible Gly314-Gly318 loop that is found at the outer entrance to the heme channel was subjected to combinatorial saturation mutagenesis and computational analysis, mutants with improved kinetics and a shift in the pH activity profile for peroxidative substrates were found, while they retained their kinetic values for peroxygenative substrates. This striking change was accompanied by a 4.5°C enhancement in kinetic thermostability despite the variants carried up to four consecutive mutations. Taken together, our study proves that the origin of the peroxidative activity in UPOs, unlike other ligninolytic peroxidases described to date, is not dependent on a LRET route from oxidizable residues at the protein surface, but rather it seems to be exclusively located at the heme access channel.

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.

Guaianolides are pharmaceutically interesting molecules. Here, the authors isolate the enzyme kauniolide synthase from feverfew, show that it converts constunolide into a guaianolide via an unusual mechanism of action, and reconstruct the full kauniolide biosynthesis pathway in host organisms.

The evolution of new protein functions is dependent upon inherent biophysical features of proteins. Whereas, it has been shown that changes in protein dynamics can occur in the course of directed molecular evolution trajectories and contribute to new function, it is not known whether varying protein dynamics modify the course of evolution. We investigate this question using three related ß-lactamases displaying dynamics that differ broadly at the slow timescale that corresponds to catalytic turnover yet have similar fast dynamics, thermal stability, catalytic, and substrate recognition profiles. Introduction of substitutions E104K and G238S, that are known to have a synergistic effect on function in the parent ß-lactamase, showed similar increases in catalytic efficiency toward cefotaxime in the related ß-lactamases. Molecular simulations using Protein Energy Landscape Exploration reveal that this results from stabilizing the catalytically-productive conformations, demonstrating the dominance of the synergistic effect of the E014K and G238S substitutions in vitro in contexts that vary in terms of sequence and dynamics. Furthermore, three rounds of directed molecular evolution demonstrated that known cefotaximase-enhancing mutations were accessible regardless of the differences in dynamics. Interestingly, specific sequence differences between the related ß-lactamases were shown to have a higher effect in evolutionary outcomes than did differences in dynamics. Overall, these ß-lactamase models show tolerance to protein dynamics at the timescale of catalytic turnover in the evolution of a new function.

With the spread of new variants of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), there is a need to assess the protection conferred by both previous infections and current vaccination. Here we tested the neutralizing activity of infected and/or vaccinated individuals against pseudoviruses expressing the spike of the original SARS-CoV-2 isolate Wuhan-Hu-1 (WH1), the D614G mutant and the B.1.1.7 variant. Our data show that parameters of natural infection (time from infection and nature of the infecting variant) determined cross-neutralization. Uninfected vaccinees showed a small reduction in neutralization against the B.1.1.7 variant compared to both the WH1 strain and the D614G mutant. Interestingly, upon vaccination, previously infected individuals developed more robust neutralizing responses against B.1.1.7, suggesting that vaccines can boost the neutralization breadth conferred by natural infection.

Abstract Modeling the dynamic nature of protein-ligand binding with atomistic simulations is one of the main challenges in computational biophysics, with important implications in the drug design process. Although in the past few years hardware and software advances have significantly revamped the use of molecular simulations, we still lack a fast and accurate ab initio description of the binding mechanism in complex systems, available only for up-to-date techniques and requiring several hours or days of heavy computation. Such delay is one of the main limiting factors for a larger penetration of protein dynamics modeling in the pharmaceutical industry. Here we present a game-changing technology, opening up the way for fast reliable simulations of protein dynamics by combining an adaptive reinforcement learning procedure with Monte Carlo sampling in the frame of modern multi-core computational resources. We show remarkable performance in mapping the protein-ligand energy landscape, being able to reproduce the full binding mechanism in less than half an hour, or the active site induced fit in less than 5 minutes. We exemplify our method by studying diverse complex targets, including nuclear hormone receptors and GPCRs, demonstrating the potential of using the new adaptive technique in screening and lead optimization studies.

Human Immunodeficiency Virus 1 (HIV-1) evades adaptive immunity by means of its extremely high mutation rate, which allows the HIV envelope glycoprotein to continuously escape from the action of antibodies. However, some broadly neutralizing antibodies (bNAbs) targeting specific viral regions show the ability to block the infectivity of a large number of viral variants. The discovery of these antibodies opens new avenues in anti-HIV therapy; however, they are still suboptimal tools as their amplitude of action ranges between 50% and 90% of viral variants. In this context, being able to discriminate between sensitive and resistant strains to an antibody would be of great interest for the design of optimal clinical antibody treatments and to engineer potent bNAbs for clinical use. Here, we describe a hierarchical procedure to predict the antibody neutralization efficacy of multiple viral isolates to three well-known anti-CD4bs bNAbs: VRC01, NIH45-46 and 3BNC117. Our method consists of simulating the three-dimensional binding process between the gp120 and the antibody by using Protein Energy Landscape Exploration (PELE), a Monte Carlo stochastic approach. Our results clearly indicate that the binding profiles of sensitive and resistant strains to a bNAb behave differently, showing the latter’s weaker binding profiles, that can be exploited for predicting antibody neutralization efficacy in hypermutated HIV-1 strains.

Vanillyl alcohol oxidase (VAO) is a homo-octameric flavoenzyme belonging to the VAO/PCMH family. Each VAO subunit consists of two domains, the FAD-binding and the cap domain. VAO catalyses, among other reactions, the two-step conversion of p-creosol (2-methoxy-4-methylphenol) to vanillin (4-hydroxy-3-methoxybenzaldehyde). To elucidate how different ligands enter and exit the secluded active site, Monte Carlo based simulations have been performed. One entry/exit path via the subunit interface and two additional exit paths have been identified for phenolic ligands, all leading to the si side of FAD. We argue that the entry/exit path is the most probable route for these ligands. A fourth path leading to the re side of FAD has been found for the co-ligands dioxygen and hydrogen peroxide. Based on binding energies and on the behaviour of ligands in these four paths, we propose a sequence of events for ligand and co-ligand migration during catalysis. We have also identified two residues, His466 and Tyr503, which could act as concierges of the active site for phenolic ligands, as well as two other residues, Tyr51 and Tyr408, which could act as a gateway to the re side of FAD for dioxygen. Most of the residues in the four paths are also present in VAO's closest relatives, eugenol oxidase and p-cresol methylhydroxylase. Key path residues show movements in our simulations that correspond well to conformations observed in crystal structures of these enzymes. Preservation of other path residues can be linked to the electron acceptor specificity and oligomerisation state of the three enzymes. This study is the first comprehensive overview of ligand and co-ligand migration in a member of the VAO/PCMH family, and provides a proof of concept for the use of an unbiased method to sample this process.

Ligninolytic peroxidases are enzymes of biotechnological interest due to their ability to oxidize high redox potential aromatic compounds, including the recalcitrant lignin polymer. However, different obstacles prevent their use in industrial and environmental applications, including low stability towards their natural oxidizing-substrate H2O2. In this work, versatile peroxidase was taken as a model ligninolytic peroxidase, its oxidative inactivation by H2O2 was studied and different strategies were evaluated with the aim of improving H2O2 stability. Oxidation of the methionine residues was produced during enzyme inactivation by H2O2 excess. Substitution of these residues, located near the heme cofactor and the catalytic tryptophan, rendered a variant with a 7.8-fold decreased oxidative inactivation rate. A second strategy consisted in mutating two residues (Thr45 and Ile103) near the catalytic distal histidine with the aim of modifying the reactivity of the enzyme with H2O2. The T45A/I103T variant showed a 2.9-fold slower reaction rate with H2O2 and 2.8-fold enhanced oxidative stability. Finally, both strategies were combined in the T45A/I103T/M152F/M262F/M265L variant, whose stability in the presence of H2O2 was improved 11.7-fold. This variant showed an increased half-life, over 30 min compared with 3.4 min of the native enzyme, under an excess of 2000 equivalents of H2O2. Interestingly, the stability improvement achieved was related with slower formation, subsequent stabilization and slower bleaching of the enzyme Compound III, a peroxidase intermediate that is not part of the catalytic cycle and leads to the inactivation of the enzyme.

Correlated inter-domain motions in proteins can mediate fundamental biochemical processes such as signal transduction and allostery. Here we characterize at structural level the inter-domain coupling in a multidomain enzyme, Adenylate Kinase (AK), using computational methods that exploit the shape information encoded in residual dipolar couplings (RDCs) measured under steric alignment by nuclear magnetic resonance (NMR). We find experimental evidence for a multi-state equilibrium distribution along the opening/closing pathway of Adenylate Kinase, previously proposed from computational work, in which inter-domain interactions disfavour states where only the AMP binding domain is closed. In summary, we provide a robust experimental technique for study of allosteric regulation in AK and other enzymes.

A salivary proteome-transcriptome project on the hard tick Ixodes scapularis revealed that Kunitz peptides are the most abundant salivary proteins. Ticks use Kunitz peptides (among other salivary proteins) to combat host defense mechanisms and to obtain a blood meal. Most of these Kunitz peptides, however, remain functionally uncharacterized, thus limiting our knowledge about their biochemical interactions.We discovered an unusual cysteine motif in a Kunitz peptide. This peptide inhibits several serine proteases with high affinity and was named tryptogalinin due to its high affinity for β-tryptase. Compared with other functionally described peptides from the Acari subclass, we showed that tryptogalinin is phylogenetically related to a Kunitz peptide from Rhipicephalus appendiculatus, also reported to have a high affinity for β-tryptase. Using homology-based modeling (and other protein prediction programs) we were able to model and explain the multifaceted function of tryptogalinin. The N-terminus of the modeled tryptogalinin is detached from the rest of the peptide and exhibits intrinsic disorder allowing an increased flexibility for its high affinity with its inhibiting partners (i.e., serine proteases).By incorporating experimental and computational methods our data not only describes the function of a Kunitz peptide from Ixodes scapularis, but also allows us to hypothesize about the molecular basis of this function at the atomic level.

The fast development of software and hardware is notably helping in closing the gap between macroscopic and microscopic data. Using a novel theoretical strategy combining molecular dynamics simulations, conformational clustering, ab-initio quantum mechanics and electronic coupling calculations, we show how computational methodologies are mature enough to provide accurate atomistic details into the mechanism of electron transfer (ET) processes in complex protein systems, known to be a significant challenge. We performed a quantitative study of the ET between Cytochrome c Peroxidase and its redox partner Cytochrome c. Our results confirm the ET mechanism as hole transfer (HT) through residues Ala194, Ala193, Gly192 and Trp191 of CcP. Furthermore, our findings indicate the fine evolution of the enzyme to approach an elevated turnover rate of 5.47 × 10(6) s(-1) for the ET between Cytc and CcP through establishment of a localized bridge state in Trp191.

Prodigiosin and obatoclax, members of the prodiginines family, are small molecules with anti-cancer properties that are currently under preclinical and clinical trials. The molecular target(s) of these agents, however, is an open question. Combining experimental and computational techniques we find that prodigiosin binds to the BH3 domain in some BCL-2 protein families, which play an important role in the apoptotic programmed cell death. In particular, our results indicate a large affinity of prodigiosin for MCL-1, an anti-apoptotic member of the BCL-2 family. In melanoma cells, we demonstrate that prodigiosin activates the mitochondrial apoptotic pathway by disrupting MCL-1/BAK complexes. Computer simulations with the PELE software allow the description of the induced fit process, obtaining a detailed atomic view of the molecular interactions. These results provide new data to understand the mechanism of action of these molecules, and assist in the development of more specific inhibitors of anti-apoptotic BCL-2 proteins.

The cytosol is the major environment in all bacterial cells. The true physical and dynamical nature of the cytosol solution is not fully understood and here a modeling approach is applied. Using recent and detailed data on metabolite concentrations, we have created a molecular mechanical model of the prokaryotic cytosol environment of Escherichia coli, containing proteins, metabolites and monatomic ions. We use 200 ns molecular dynamics simulations to compute diffusion rates, the extent of contact between molecules and dielectric constants. Large metabolites spend ∼80% of their time in contact with other molecules while small metabolites vary with some only spending 20% of time in contact. Large non-covalently interacting metabolite structures mediated by hydrogen-bonds, ionic and π stacking interactions are common and often associate with proteins. Mg(2+) ions were prominent in NIMS and almost absent free in solution. Κ(+) is generally not involved in NIMSs and populates the solvent fairly uniformly, hence its important role as an osmolyte. In simulations containing ubiquitin, to represent a protein component, metabolite diffusion was reduced owing to long lasting protein-metabolite interactions. Hence, it is likely that with larger proteins metabolites would diffuse even more slowly. The dielectric constant of these simulations was found to differ from that of pure water only through a large contribution from ubiquitin as metabolite and monatomic ion effects cancel. These findings suggest regions of influence specific to particular proteins affecting metabolite diffusion and electrostatics. Also some proteins may have a higher propensity for associations with metabolites owing to their larger electrostatic fields. We hope that future studies may be able to accurately predict how binding interactions differ in the cytosol relative to dilute aqueous solution.