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1.
Nat Methods ; 19(11): 1376-1382, 2022 11.
Article in English | MEDLINE | ID: covidwho-2151063

ABSTRACT

Machine-learning prediction algorithms such as AlphaFold and RoseTTAFold can create remarkably accurate protein models, but these models usually have some regions that are predicted with low confidence or poor accuracy. We hypothesized that by implicitly including new experimental information such as a density map, a greater portion of a model could be predicted accurately, and that this might synergistically improve parts of the model that were not fully addressed by either machine learning or experiment alone. An iterative procedure was developed in which AlphaFold models are automatically rebuilt on the basis of experimental density maps and the rebuilt models are used as templates in new AlphaFold predictions. We show that including experimental information improves prediction beyond the improvement obtained with simple rebuilding guided by the experimental data. This procedure for AlphaFold modeling with density has been incorporated into an automated procedure for interpretation of crystallographic and electron cryo-microscopy maps.


Subject(s)
Algorithms , Proteins , Models, Molecular , Cryoelectron Microscopy/methods , Proteins/chemistry , Machine Learning , Protein Conformation
2.
Structure ; 28(8): 874-878, 2020 08 04.
Article in English | MEDLINE | ID: covidwho-2132441

ABSTRACT

During global pandemics, the spread of information needs to be faster than the spread of the virus in order to ensure the health and safety of human populations worldwide. In our current crisis, the demand for SARS-CoV-2 drugs and vaccines highlights the importance of biological targets and their three-dimensional shape. In particular, structural biology as a field was poised to quickly respond to crises due to previous experience and expertise and because of its early adoption of open access practices.


Subject(s)
Betacoronavirus/chemistry , Coronavirus Infections/epidemiology , Coronavirus Infections/virology , Pandemics , Pneumonia, Viral/epidemiology , Pneumonia, Viral/virology , Viral Proteins/chemistry , COVID-19 , Coronavirus 3C Proteases , Coronavirus RNA-Dependent RNA Polymerase , Cysteine Endopeptidases/chemistry , Databases, Protein , Humans , Models, Molecular , Molecular Biology , Protein Conformation , RNA-Dependent RNA Polymerase/chemistry , SARS-CoV-2 , Spike Glycoprotein, Coronavirus/chemistry , Viral Nonstructural Proteins/chemistry
3.
Nature ; 593(7857): 136-141, 2021 05.
Article in English | MEDLINE | ID: covidwho-2114170

ABSTRACT

Transmission of SARS-CoV-2 is uncontrolled in many parts of the world; control is compounded in some areas by the higher transmission potential of the B.1.1.7 variant1, which has now been reported in 94 countries. It is unclear whether the response of the virus to vaccines against SARS-CoV-2 on the basis of the prototypic strain will be affected by the mutations found in B.1.1.7. Here we assess the immune responses of individuals after vaccination with the mRNA-based vaccine BNT162b22. We measured neutralizing antibody responses after the first and second immunizations using pseudoviruses that expressed the wild-type spike protein or a mutated spike protein that contained the eight amino acid changes found in the B.1.1.7 variant. The sera from individuals who received the vaccine exhibited a broad range of neutralizing titres against the wild-type pseudoviruses that were modestly reduced against the B.1.1.7 variant. This reduction was also evident in sera from some patients who had recovered from COVID-19. Decreased neutralization of the B.1.1.7 variant was also observed for monoclonal antibodies that target the N-terminal domain (9 out of 10) and the receptor-binding motif (5 out of 31), but not for monoclonal antibodies that recognize the receptor-binding domain that bind outside the receptor-binding motif. Introduction of the mutation that encodes the E484K substitution in the B.1.1.7 background to reflect a newly emerged variant of concern (VOC 202102/02) led to a more-substantial loss of neutralizing activity by vaccine-elicited antibodies and monoclonal antibodies (19 out of 31) compared with the loss of neutralizing activity conferred by the mutations in B.1.1.7 alone. The emergence of the E484K substitution in a B.1.1.7 background represents a threat to the efficacy of the BNT162b2 vaccine.


Subject(s)
Antibodies, Neutralizing/immunology , Antibodies, Viral/immunology , COVID-19 Vaccines/immunology , COVID-19/immunology , COVID-19/therapy , SARS-CoV-2/immunology , Spike Glycoprotein, Coronavirus/immunology , Vaccines, Synthetic/immunology , Aged , Aged, 80 and over , Angiotensin-Converting Enzyme 2/metabolism , Antibodies, Monoclonal/immunology , Antibodies, Monoclonal/isolation & purification , Antibodies, Neutralizing/isolation & purification , Antibodies, Viral/isolation & purification , COVID-19/metabolism , COVID-19/virology , Female , HEK293 Cells , Humans , Immune Evasion/genetics , Immune Evasion/immunology , Immunization, Passive , Male , Middle Aged , Models, Molecular , Mutation , Neutralization Tests , SARS-CoV-2/genetics , Spike Glycoprotein, Coronavirus/chemistry , Spike Glycoprotein, Coronavirus/genetics , Spike Glycoprotein, Coronavirus/metabolism , Vaccines, Synthetic/administration & dosage
4.
Sci Adv ; 8(45): eabp9540, 2022 11 11.
Article in English | MEDLINE | ID: covidwho-2119147

ABSTRACT

De novo design methods hold the promise of reducing the time and cost of antibody discovery while enabling the facile and precise targeting of predetermined epitopes. Here, we describe a fragment-based method for the combinatorial design of antibody binding loops and their grafting onto antibody scaffolds. We designed and tested six single-domain antibodies targeting different epitopes on three antigens, including the receptor-binding domain of the SARS-CoV-2 spike protein. Biophysical characterization showed that all designs are stable and bind their intended targets with affinities in the nanomolar range without in vitro affinity maturation. We further discuss how a high-resolution input antigen structure is not required, as similar predictions are obtained when the input is a crystal structure or a computer-generated model. This computational procedure, which readily runs on a laptop, provides a starting point for the rapid generation of lead antibodies binding to preselected epitopes.


Subject(s)
Antibodies, Monoclonal , COVID-19 , Humans , Epitopes , Antibody Affinity , Antibodies, Monoclonal/chemistry , Models, Molecular , SARS-CoV-2 , Antigens
5.
Molecules ; 27(21)2022 Oct 31.
Article in English | MEDLINE | ID: covidwho-2099665

ABSTRACT

Synthesis of sulfonamide through an indirect method that avoids contamination of the product with no need for purification has been carried out using the indirect process. Here, we report the synthesis of a novel sulfonamide compound, ({4-nitrophenyl}sulfonyl)tryptophan (DNSPA) from 4-nitrobenzenesulphonylchloride and L-tryptophan precursors. The slow evaporation method was used to form single crystals of the named compound from methanolic solution. The compound was characterized by X-ray crystallographic analysis and spectroscopic methods (NMR, IR, mass spectrometry, and UV-vis). The sulfonamide N-H NMR signal at 8.07-8.09 ppm and S-N stretching vibration at 931 cm-1 indicate the formation of the target compound. The compound crystallized in the monoclinic crystal system and P21 space group with four molecules of the compound in the asymmetric unit. Molecular aggregation in the crystal structure revealed a 12-molecule aggregate synthon sustained by O-H⋯O hydrogen bonds and stabilised by N-H⋯O intermolecular contacts. Experimental studies were complemented by DFT calculations at the B3LYP/6-311++G(d,p) level of theory. The computed structural and spectroscopic data are in good agreement with those obtained experimentally. The energies of interactions between the units making up the molecule were calculated. Molecular docking studies showed that DNSPA has a binding energy of -6.37 kcal/mol for E. coli DNA gyrase (5MMN) and -6.35 kcal/mol for COVID-19 main protease (6LU7).


Subject(s)
COVID-19 , Tryptophan , Humans , Quantum Theory , Models, Molecular , Molecular Docking Simulation , Escherichia coli , Spectroscopy, Fourier Transform Infrared , Sulfonamides
6.
Acta Chim Slov ; 69(3): 647-656, 2022 Sep 26.
Article in English | MEDLINE | ID: covidwho-2056608

ABSTRACT

These days, the world is facing the threat of pandemic Coronavirus Disease 2019 (COVID-19). Although a vaccine has been found to combat the pandemic, it is essential to find drugs for an effective treatment method against this disease as soon as possible. In this study, electronic and thermodynamic properties, molecular electrostatic potential (MEP) analysis, and frontier molecular orbitals (FMOs) of nine different covid drugs were studied with Density Functional Theory (DFT). In addition, the relationship between the electronic structures of these drugs and their biological effectiveness was examined. All parameters were computed at the B3LYP/6-311++g(d,p) level. The Solvent effect was evaluated using conductor-like polarizable continuum model (CPCM) as the solvation model. It was observed that electrophilic indexes were important to understand the efficiencies of these drugs in COVID-19 disease. Paxlovid, hydroxyquinone, and nitazoxanide were found as the most thermodynamically stable molecules. Thermodynamic parameters also demonstrated that these drugs were more stable in the aqueous media. Global descriptors and the reactivity of these drugs were found to be related. Nitazoxanide molecule exhibited the highest dipole moment. The high dipole moments of drugs can cause hydrophilic interactions that increase their effectiveness in an aqueous solution.


Subject(s)
COVID-19 , Quantum Theory , COVID-19/drug therapy , Electronics , Humans , Models, Molecular , Nitro Compounds , Solvents/chemistry , Thiazoles , Water/chemistry
7.
Eur Biophys J ; 51(7-8): 555-568, 2022 Dec.
Article in English | MEDLINE | ID: covidwho-2048214

ABSTRACT

Protein structures may be used to draw functional implications at the residue level, but how sensitive are these implications to the exact structure used? Calculation of the effects of SARS-CoV-2 S-protein mutations based on experimental cryo-electron microscopy structures have been abundant during the pandemic. To understand the precision of such estimates, we studied three distinct methods to estimate stability changes for all possible mutations in 23 different S-protein structures (3.69 million ΔΔG values in total) and explored how random and systematic errors can be remedied by structure-averaged mutation group comparisons. We show that computational estimates have low precision, due to method and structure heterogeneity making results for single mutations uninformative. However, structure-averaged differences in mean effects for groups of substitutions can yield significant results. Illustrating this protocol, functionally important natural mutations, despite individual variations, average to a smaller stability impact compared to other possible mutations, independent of conformational state (open, closed). In summary, we document substantial issues with precision in structure-based protein modeling and recommend sensitivity tests to quantify these effects, but also suggest partial solutions to the problem in the form of structure-averaged "ensemble" estimates for groups of residues when multiple structures are available.


Subject(s)
COVID-19 , Spike Glycoprotein, Coronavirus , Humans , Spike Glycoprotein, Coronavirus/genetics , Spike Glycoprotein, Coronavirus/chemistry , Spike Glycoprotein, Coronavirus/metabolism , Cryoelectron Microscopy , SARS-CoV-2/genetics , Models, Molecular , Mutation , Proteins/genetics
8.
Methods Enzymol ; 675: 299-321, 2022.
Article in English | MEDLINE | ID: covidwho-1995924

ABSTRACT

Mutations on the spike (S) protein of SARS-CoV-2 could induce structural changes that help increase viral transmissibility and enhance resistance to antibody neutralization. Here, we report a robust workflow to prepare recombinant S protein variants and its host receptor angiotensin-convert enzyme 2 (ACE2) by using a mammalian cell expression system. The functional states of the S protein variants are investigated by cryo-electron microscopy (cryo-EM) and negative staining electron microscopy (NSEM) to visualize their molecular structures in response to mutations, receptor binding, antibody binding, and environmental changes. The folding stabilities of the S protein variants can be deduced from morphological changes based on NSEM imaging analysis. Differential scanning calorimetry provides thermodynamic information to complement NSEM. Impacts of the mutations on host receptor binding and antibody neutralization are in vitro by kinetic binding analyses in addition to atomic insights gleaned from cryo-electron microscopy (cryo-EM). This experimental strategy is generally applicable to studying the molecular basis of host-pathogen interactions.


Subject(s)
COVID-19 , Spike Glycoprotein, Coronavirus , Angiotensin-Converting Enzyme 2/genetics , Angiotensins/genetics , Angiotensins/metabolism , Animals , COVID-19/genetics , Cryoelectron Microscopy , Humans , Mammals/metabolism , Models, Molecular , Mutation , Peptidyl-Dipeptidase A/chemistry , Peptidyl-Dipeptidase A/genetics , Peptidyl-Dipeptidase A/metabolism , Protein Binding , Receptors, Virus/chemistry , Receptors, Virus/genetics , Receptors, Virus/metabolism , SARS-CoV-2/genetics , Spike Glycoprotein, Coronavirus/genetics , Spike Glycoprotein, Coronavirus/metabolism , Structure-Activity Relationship
9.
Faraday Discuss ; 240(0): 184-195, 2022 Nov 08.
Article in English | MEDLINE | ID: covidwho-1984449

ABSTRACT

AlphaFold2 is a machine-learning based program that predicts a protein structure based on the amino acid sequence. In this article, we report on the current usages of this new tool and give examples from our work in the Coronavirus Structural Task Force. With its unprecedented accuracy, it can be utilized for the design of expression constructs, de novo protein design and the interpretation of Cryo-EM data with an atomic model. However, these methods are limited by their training data and are of limited use to predict conformational variability and fold flexibility; they also lack co-factors, post-translational modifications and multimeric complexes with oligonucleotides. They also are not always perfect in terms of chemical geometry. Nevertheless, machine learning-based fold prediction is a game changer for structural bioinformatics and experimentalists alike, with exciting developments ahead.


Subject(s)
Computational Biology , Proteins , Models, Molecular , Amino Acid Sequence , Proteins/chemistry , Machine Learning , Protein Conformation
10.
Molecules ; 27(15)2022 Aug 05.
Article in English | MEDLINE | ID: covidwho-1979318

ABSTRACT

Morin (M) is one of the most widely distributed flavonoids with several beneficial effects on human health, and has the potential of being used as a possible treatment for COVID-19. To achieve a better understanding of the process of M dissolution, the fluorescent (FL) emission from M solutions prepared with different polar and nonpolar solvents (methanol, DMSO, and chloroform) was measured and compared with the FL emission from M powder and M crystals. In the FL spectra of the solutions with high M concentration, as well as in the spectra of M in solid state, two features, at 615 nm and 670 nm, were observed. As the solution concentration decreases, the maxima of FL spectra of the M solutions in all considered solvents shift to the blue side of the spectrum until reaching the value of 520 nm. To explain the experimental results, the TDDFT-M06-2X/6-31++G(d,p) method was used to determine the possible electronic transitions in the M molecule. The computations show that the FL emission in the spectral range of detection of our setup (405-800 nm) is related to the excited state intramolecular proton transfer (ESIPT). Comparison of the experimental data with the computations strongly suggests that in low-concentrated solutions, the FL emission is mostly due to electronic transitions in the keto OH3 form, whereas in aggregated states, the dominate contribution to the FL emission spectra is due to the transitions in keto OH5 form. Moreover, the time evolution of the M solutions FL spectra was observed, measured and explained for the first time.


Subject(s)
COVID-19 , Flavonoids , Humans , Models, Molecular , Solvents/chemistry , Spectrometry, Fluorescence
11.
Faraday Discuss ; 240(0): 196-209, 2022 Nov 08.
Article in English | MEDLINE | ID: covidwho-1972674

ABSTRACT

Cryogenic electron microscopy (cryo-EM) has recently been established as a powerful technique for solving macromolecular structures. Although the best resolutions achievable are improving, a significant majority of data are still resolved at resolutions worse than 3 Å, where it is non-trivial to build or fit atomic models. The map reconstructions and atomic models derived from the maps are also prone to errors accumulated through the different stages of data processing. Here, we highlight the need to evaluate both model geometry and fit to data at different resolutions. Assessment of cryo-EM structures from SARS-CoV-2 highlights a bias towards optimising the model geometry to agree with the most common conformations, compared to the agreement with data. We present the CoVal web service which provides multiple validation metrics to reflect the quality of atomic models derived from cryo-EM data of structures from SARS-CoV-2. We demonstrate that further refinement can lead to improvement of the agreement with data without the loss of geometric quality. We also discuss the recent CCP-EM developments aimed at addressing some of the current shortcomings.


Subject(s)
COVID-19 , SARS-CoV-2 , Humans , Cryoelectron Microscopy/methods , Models, Molecular , Protein Conformation , Software
12.
Int J Mol Sci ; 21(16)2020 Aug 06.
Article in English | MEDLINE | ID: covidwho-1934101

ABSTRACT

The recently discovered 340-cavity in influenza neuraminidase (NA) N6 and N7 subtypes has introduced new possibilities for rational structure-based drug design. However, the plasticity of the 340-loop (residues 342-347) and the role of the 340-loop in NA activity and substrate binding have not been deeply exploited. Here, we investigate the mechanism of 340-cavity formation and demonstrate for the first time that seven of nine NA subtypes are able to adopt an open 340-cavity over 1.8 µs total molecular dynamics simulation time. The finding that the 340-loop plays a role in the sialic acid binding pathway suggests that the 340-cavity can function as a druggable pocket. Comparing the open and closed conformations of the 340-loop, the side chain orientation of residue 344 was found to govern the formation of the 340-cavity. Additionally, the conserved calcium ion was found to substantially influence the stability of the 340-loop. Our study provides dynamical evidence supporting the 340-cavity as a druggable hotspot at the atomic level and offers new structural insight in designing antiviral drugs.


Subject(s)
Antiviral Agents/pharmacology , Drug Development , Neuraminidase/chemistry , Orthomyxoviridae/enzymology , Binding Sites , Calcium/chemistry , Ions , Models, Molecular , Molecular Dynamics Simulation , N-Acetylneuraminic Acid/chemistry , Principal Component Analysis , Protein Structure, Secondary , Thermodynamics
13.
Int J Mol Sci ; 23(13)2022 Jun 21.
Article in English | MEDLINE | ID: covidwho-1934117

ABSTRACT

RNA-protein complexes regulate a variety of biological functions. Thus, it is essential to explore and visualize RNA-protein structural interaction features, especially pocket interactions. In this work, we develop an easy-to-use bioinformatics resource: RPpocket. This database provides RNA-protein complex interactions based on sequence, secondary structure, and pocket topology analysis. We extracted 793 pockets from 74 non-redundant RNA-protein structures. Then, we calculated the binding- and non-binding pocket topological properties and analyzed the binding mechanism of the RNA-protein complex. The results showed that the binding pockets were more extended than the non-binding pockets. We also found that long-range forces were the main interaction for RNA-protein recognition, while short-range forces strengthened and optimized the binding. RPpocket could facilitate RNA-protein engineering for biological or medical applications.


Subject(s)
Proteins , RNA , Binding Sites , Databases, Protein , Ligands , Models, Molecular , Proteins/chemistry
14.
Acta Crystallogr D Struct Biol ; 78(Pt 7): 806-816, 2022 Jul 01.
Article in English | MEDLINE | ID: covidwho-1922451

ABSTRACT

The availability of new artificial intelligence-based protein-structure-prediction tools has radically changed the way that cryo-EM maps are interpreted, but it has not eliminated the challenges of map interpretation faced by a microscopist. Models will continue to be locally rebuilt and refined using interactive tools. This inevitably results in occasional errors, among which register shifts remain one of the most difficult to identify and correct. Here, checkMySequence, a fast, fully automated and parameter-free method for detecting register shifts in protein models built into cryo-EM maps, is introduced. It is shown that the method can assist model building in cases where poorer map resolution hinders visual interpretation. It is also shown that checkMySequence could have helped to avoid a widely discussed sequence-register error in a model of SARS-CoV-2 RNA-dependent RNA polymerase that was originally detected thanks to a visual residue-by-residue inspection by members of the structural biology community. The software is freely available at https://gitlab.com/gchojnowski/checkmysequence.


Subject(s)
Artificial Intelligence , COVID-19 , Cryoelectron Microscopy/methods , Humans , Models, Molecular , Proteins/chemistry , RNA, Viral , SARS-CoV-2
15.
Int J Mol Sci ; 23(3)2022 Jan 30.
Article in English | MEDLINE | ID: covidwho-1917507

ABSTRACT

Traditionally, drug development involved the individual synthesis and biological evaluation of hundreds to thousands of compounds with the intention of highlighting their biological activity, selectivity, and bioavailability, as well as their low toxicity. On average, this process of new drug development involved, in addition to high economic costs, a period of several years before hopefully finding a drug with suitable characteristics to drive its commercialization. Therefore, the chemical synthesis of new compounds became the limiting step in the process of searching for or optimizing leads for new drug development. This need for large chemical libraries led to the birth of high-throughput synthesis methods and combinatorial chemistry. Virtual combinatorial chemistry is based on the same principle as real chemistry-many different compounds can be generated from a few building blocks at once. The difference lies in its speed, as millions of compounds can be produced in a few seconds. On the other hand, many virtual screening methods, such as QSAR (Quantitative Sturcture-Activity Relationship), pharmacophore models, and molecular docking, have been developed to study these libraries. These models allow for the selection of molecules to be synthesized and tested with a high probability of success. The virtual combinatorial chemistry-virtual screening tandem has become a fundamental tool in the process of searching for and developing a drug, as it allows the process to be accelerated with extraordinary economic savings.


Subject(s)
Combinatorial Chemistry Techniques/methods , Small Molecule Libraries/pharmacology , Drug Design , Models, Molecular , Molecular Docking Simulation , Quantitative Structure-Activity Relationship
16.
PLoS One ; 17(2): e0263582, 2022.
Article in English | MEDLINE | ID: covidwho-1910522

ABSTRACT

The membrane protein M of the Porcine Epidemic Diarrhea Virus (PEDV) is the most abundant component of the viral envelope. The M protein plays a central role in the morphogenesis and assembly of the virus through protein interactions of the M-M, M-Spike (S) and M-nucleocapsid (N) type. The M protein is known to induce protective antibodies in pigs and to participate in the antagonistic response of the cellular antiviral system coordinated by the type I and type III interferon pathways. The 3D structure of the PEDV M protein is still unknown. The present work exposes a predicted 3D model of the M protein generated using the Robetta protocol. The M protein model is organized into a transmembrane and a globular region. The obtained 3D model of the PEDV M protein was compared with 3D models of the SARS-CoV-2 M protein created using neural networks and with initial machine learning-based models created using trRosetta. The 3D model of the present study predicted four linear B-cell epitopes (RSVNASSGTG and KHGDYSAVSNPSALT peptides are noteworthy), six discontinuous B-cell epitopes, forty weak binding and fourteen strong binding T-cell epitopes in the CV777 M protein. A high degree of conservation of the epitopes predicted in the PEDV M protein was observed among different PEDV strains isolated in different countries. The data suggest that the M protein could be a potential candidate for the development of new treatments or strategies that activate protective cellular mechanisms against viral diseases.


Subject(s)
Coronavirus Infections/virology , Coronavirus M Proteins/chemistry , Porcine epidemic diarrhea virus/chemistry , Swine Diseases/virology , Swine/virology , Amino Acid Sequence , Animals , Coronavirus Infections/immunology , Coronavirus Infections/veterinary , Coronavirus M Proteins/immunology , Epitopes, B-Lymphocyte/chemistry , Epitopes, B-Lymphocyte/immunology , Epitopes, T-Lymphocyte/chemistry , Epitopes, T-Lymphocyte/immunology , Models, Molecular , Porcine epidemic diarrhea virus/immunology , Protein Conformation , Swine Diseases/immunology
17.
Chem Rev ; 122(13): 11287-11368, 2022 07 13.
Article in English | MEDLINE | ID: covidwho-1860269

ABSTRACT

Despite tremendous efforts in the past two years, our understanding of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), virus-host interactions, immune response, virulence, transmission, and evolution is still very limited. This limitation calls for further in-depth investigation. Computational studies have become an indispensable component in combating coronavirus disease 2019 (COVID-19) due to their low cost, their efficiency, and the fact that they are free from safety and ethical constraints. Additionally, the mechanism that governs the global evolution and transmission of SARS-CoV-2 cannot be revealed from individual experiments and was discovered by integrating genotyping of massive viral sequences, biophysical modeling of protein-protein interactions, deep mutational data, deep learning, and advanced mathematics. There exists a tsunami of literature on the molecular modeling, simulations, and predictions of SARS-CoV-2 and related developments of drugs, vaccines, antibodies, and diagnostics. To provide readers with a quick update about this literature, we present a comprehensive and systematic methodology-centered review. Aspects such as molecular biophysics, bioinformatics, cheminformatics, machine learning, and mathematics are discussed. This review will be beneficial to researchers who are looking for ways to contribute to SARS-CoV-2 studies and those who are interested in the status of the field.


Subject(s)
COVID-19 , SARS-CoV-2 , Humans , Models, Molecular
18.
PLoS One ; 16(4): e0250780, 2021.
Article in English | MEDLINE | ID: covidwho-1833531

ABSTRACT

The spike protein receptor-binding domain (RBD) of SARS-CoV-2 is the molecular target for many vaccines and antibody-based prophylactics aimed at bringing COVID-19 under control. Such a narrow molecular focus raises the specter of viral immune evasion as a potential failure mode for these biomedical interventions. With the emergence of new strains of SARS-CoV-2 with altered transmissibility and immune evasion potential, a critical question is this: how easily can the virus escape neutralizing antibodies (nAbs) targeting the spike RBD? To answer this question, we combined an analysis of the RBD structure-function with an evolutionary modeling framework. Our structure-function analysis revealed that epitopes for RBD-targeting nAbs overlap one another substantially and can be evaded by escape mutants with ACE2 affinities comparable to the wild type, that are observed in sequence surveillance data and infect cells in vitro. This suggests that the fitness cost of nAb-evading mutations is low. We then used evolutionary modeling to predict the frequency of immune escape before and after the widespread presence of nAbs due to vaccines, passive immunization or natural immunity. Our modeling suggests that SARS-CoV-2 mutants with one or two mildly deleterious mutations are expected to exist in high numbers due to neutral genetic variation, and consequently resistance to vaccines or other prophylactics that rely on one or two antibodies for protection can develop quickly -and repeatedly- under positive selection. Predicted resistance timelines are comparable to those of the decay kinetics of nAbs raised against vaccinal or natural antigens, raising a second potential mechanism for loss of immunity in the population. Strategies for viral elimination should therefore be diversified across molecular targets and therapeutic modalities.


Subject(s)
COVID-19/genetics , SARS-CoV-2/genetics , Spike Glycoprotein, Coronavirus/genetics , Antibodies, Monoclonal/immunology , Antibodies, Neutralizing/immunology , Antibodies, Viral/immunology , Binding Sites/genetics , COVID-19/metabolism , Epitopes/immunology , Evolution, Molecular , Humans , Immune Evasion/immunology , Models, Molecular , Neutralization Tests/methods , Peptidyl-Dipeptidase A/metabolism , Protein Binding/genetics , Protein Domains/genetics , Receptors, Virus/metabolism , SARS-CoV-2/pathogenicity , Spike Glycoprotein, Coronavirus/metabolism , Structure-Activity Relationship
19.
Radiat Res ; 198(1): 68-80, 2022 07 01.
Article in English | MEDLINE | ID: covidwho-1793416

ABSTRACT

Here we show an interplay between the structures present in ionization tracks and nucleocapsid RNA structural biology, using fast ion-beam inactivation of the severe acute respiratory syndrome coronavirus (SARS-CoV) virion as an example. This interplay could be a key factor in predicting dose-inactivation curves for high-energy ion-beam inactivation of virions. We also investigate the adaptation of well-established cross-section data derived from radiation interactions with water to the interactions involving the components of a virion, going beyond the density-scaling approximation developed previously. We conclude that solving one of the grand challenges of structural biology - the determination of RNA tertiary/quaternary structure - is linked to predicting ion-beam inactivation of viruses and that the two problems can be mutually informative. Indeed, our simulations show that fast ion beams have a key role to play in elucidating RNA tertiary/quaternary structure.


Subject(s)
Nucleic Acid Conformation , RNA, Viral/chemistry , SARS-CoV-2 , Virus Inactivation , Ions , Models, Molecular , RNA, Viral/metabolism , Radiobiology/methods , SARS-CoV-2/chemistry , Viral Proteins/chemistry , Viral Proteins/metabolism , Virion/chemistry
20.
Viruses ; 14(2)2022 02 17.
Article in English | MEDLINE | ID: covidwho-1786043

ABSTRACT

Various adenoviruses are being used as viral vectors for the generation of vaccines against chronic and emerging diseases (e.g., AIDS, COVID-19). Here, we report the improved capsid structure for one of these vectors, human adenovirus D26 (HAdV-D26), at 3.4 Å resolution, by reprocessing the previous cryo-electron microscopy dataset and obtaining a refined model. In addition to overall improvements in the model, the highlights of the structure include (1) locating a segment of the processed peptide of VIII that was previously believed to be released from the mature virions, (2) reorientation of the helical appendage domain (APD) of IIIa situated underneath the vertex region relative to its counterpart observed in the cleavage defective (ts1) mutant of HAdV-C5 that resulted in the loss of interactions between the APD and hexon bases, and (3) the revised conformation of the cleaved N-terminal segments of pre-protein VI (pVIn), located in the hexon cavities, is highly conserved, with notable stacking interactions between the conserved His13 and Phe18 residues. Taken together, the improved model of HAdV-D26 capsid provides a better understanding of protein-protein interactions in HAdV capsids and facilitates the efforts to modify and/or design adenoviral vectors with altered properties. Last but not least, we provide some insights into clotting factors (e.g., FX and PF4) binding to AdV vectors.


Subject(s)
Adenoviruses, Human/chemistry , Capsid/chemistry , Capsid/ultrastructure , Cryoelectron Microscopy/methods , Adenoviruses, Human/genetics , Capsid Proteins/genetics , Humans , Models, Molecular , Protein Conformation , Protein Interaction Domains and Motifs , Virus Assembly , Virus Internalization
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