WO2024178232A2 - Multiplication et amélioration de répertoires de nanocorps : ciblage du sars-cov-2 - Google Patents

Multiplication et amélioration de répertoires de nanocorps : ciblage du sars-cov-2 Download PDF

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WO2024178232A2
WO2024178232A2 PCT/US2024/016913 US2024016913W WO2024178232A2 WO 2024178232 A2 WO2024178232 A2 WO 2024178232A2 US 2024016913 W US2024016913 W US 2024016913W WO 2024178232 A2 WO2024178232 A2 WO 2024178232A2
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seq
binding
rbd
nanobodies
cov
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WO2024178232A3 (fr
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Frederick R. Cross
Michael P. Rout
Brian T. Chait
John D. AITCHISON
Peter FRIDY
Natalia KETAREN
Fred Mast
Paul Olivier
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Rockefeller University
Seattle Childrens Hospital
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Seattle Childrens Hospital
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    • C—CHEMISTRY; METALLURGY
    • C07—ORGANIC CHEMISTRY
    • C07K—PEPTIDES
    • C07K16/00—Immunoglobulins [IG], e.g. monoclonal or polyclonal antibodies
    • C07K16/08—Immunoglobulins [IG], e.g. monoclonal or polyclonal antibodies against material from viruses
    • C07K16/10—RNA viruses
    • C07K16/102—Coronaviridae (F)
    • C07K16/104—Severe acute respiratory syndrome coronavirus 2 [SARS‐CoV‐2]
    • C—CHEMISTRY; METALLURGY
    • C07—ORGANIC CHEMISTRY
    • C07K—PEPTIDES
    • C07K2317/00—Immunoglobulins specific features
    • C07K2317/20—Immunoglobulins specific features characterized by taxonomic origin
    • C07K2317/22—Immunoglobulins specific features characterized by taxonomic origin from camelids, e.g. camel, llama or dromedary
    • C—CHEMISTRY; METALLURGY
    • C07—ORGANIC CHEMISTRY
    • C07K—PEPTIDES
    • C07K2317/00—Immunoglobulins specific features
    • C07K2317/50—Immunoglobulins specific features characterized by immunoglobulin fragments
    • C07K2317/56—Immunoglobulins specific features characterized by immunoglobulin fragments variable (Fv) region, i.e. VH and/or VL
    • C07K2317/565—Complementarity determining region [CDR]
    • C—CHEMISTRY; METALLURGY
    • C07—ORGANIC CHEMISTRY
    • C07K—PEPTIDES
    • C07K2317/00—Immunoglobulins specific features
    • C07K2317/50—Immunoglobulins specific features characterized by immunoglobulin fragments
    • C07K2317/56—Immunoglobulins specific features characterized by immunoglobulin fragments variable (Fv) region, i.e. VH and/or VL
    • C07K2317/569—Single domain, e.g. dAb, sdAb, VHH, VNAR or nanobody®
    • C—CHEMISTRY; METALLURGY
    • C07—ORGANIC CHEMISTRY
    • C07K—PEPTIDES
    • C07K2317/00—Immunoglobulins specific features
    • C07K2317/70—Immunoglobulins specific features characterized by effect upon binding to a cell or to an antigen
    • C07K2317/76—Antagonist effect on antigen, e.g. neutralization or inhibition of binding
    • C—CHEMISTRY; METALLURGY
    • C07—ORGANIC CHEMISTRY
    • C07K—PEPTIDES
    • C07K2317/00—Immunoglobulins specific features
    • C07K2317/90—Immunoglobulins specific features characterized by (pharmaco)kinetic aspects or by stability of the immunoglobulin
    • C07K2317/92—Affinity (KD), association rate (Ka), dissociation rate (Kd) or EC50 value

Definitions

  • Said .xml copy, created February 22, 2024, is titled “076091_00170.xml” and is 180,066 bytes in size.
  • BACKGROUND The COVID-19 pandemic, caused by Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has had a profound global impact the likes of which has not been seen in more than a century. The remarkably rapid development and distribution of vaccines undoubtedly saved many millions of lives; nevertheless, at the time of writing, mortality estimates range from 10 – 20 million, with additional profound long-lasting health impacts for many survivors.
  • Spike is a homotrimer of an extensively glycosylated ⁇ 200 kDa protein composed of two major domains: S1, which contains the host receptor binding domain (RBD) that targets the angiotensin-converting enzyme 2 (ACE2) surface receptor on host cells; and S2, which upon host cell binding undergoes major conformational changes to enable viral – host membrane fusion, resulting in virus entry into the cytoplasm.
  • S1 which contains the host receptor binding domain (RBD) that targets the angiotensin-converting enzyme 2 (ACE2) surface receptor on host cells
  • ACE2 angiotensin-converting enzyme 2
  • VoCs SARS-CoV-2 Variants of Concern
  • Alpha, Beta, Gamma, Delta, Omicron and subvariants presents a significant barrier 3399-P41US.PRO -1- to attaining complete control of COVID-19.
  • These VoCs usually have many Spike mutations (especially the RBD), and thus are relatively poorly neutralized by current vaccines and antibody therapies.
  • monoclonal antibodies mAbs
  • mAbs monoclonal antibodies
  • mAbs are limited by challenges in the ease and cost of their large-scale manufacturing, distribution, and intravenous administration.
  • An alternative to mAbs is a particular class of single domain antibodies termed “nanobodies”.
  • Nanobodies are “mini-antibodies”, some 1/10 th the size of regular IgGs, derived from the variable domain (VHH) of variant heavy chain-only IgGs (HCAbs) found in camelids (e.g. llamas).
  • VHH variable domain
  • HCAbs variant heavy chain-only IgGs
  • Each nanobody molecule is constructed of a single Ig fold, consisting of four framework regions (FRs) that intersperse and orient three complementarity determining regions (CDRs) that form the nanobody paratope. These regions are similar to FRs and CDRs of conventional antibodies.
  • CDR3 is formed by VDJ recombination of germline DNA; CDR1 and CDR2 come from the germline V region, and all three CDRs are then subject to somatic hypermutation, with selection for improved binding affinity to antigens.
  • VHH variable domain on a heavy chain
  • Nanobodies have several attractive advantages over mAbs, including: fast on-rates leading to high overall affinities; characteristics of small molecules in terms of higher tissue penetration and accessibility to regions of Spike not accessible to the larger mAbs or occluded by glycosylation, greatly enhancing their potential to synergize in combination, a profound advantage they have over often poorly-synergizing conventional antibodies.
  • nanobody binding can be disrupted by mutations in VoCs.
  • mAbs and the advantages of nanobodies, a need remains for rapidly producing nanobodies that target the entirety of the Spike protein as a more effective therapy against the continuing emergence of new SARS-CoV-2 VoCs. The present disclosure addresses these and related needs.
  • the present disclosure provides single domain antibodies that specifically recognize SARS-CoV-2 epitopes.
  • the described antibodies are heavy chain only antibodies.
  • the antibodies contain a single variable domain which comprises three complementarity- determining regions (CDRs).
  • CDRs complementarity- determining regions
  • the disclosure includes all heavy chain only antibodies that contain any CDR1, CDR2, and CDR3 disclosed herein, and may have residue changes in the non-CDR segments.
  • a representative antibody sequence is SEQ ID NO:117.
  • the disclosure provides the described antibodies, compositions comprising the described antibodies, and methods of using the described antibodies for prophylaxis or therapy for SARS-CoV-2 infections.
  • Figure 1 Design of Yeast-Based Nanobody Screen for anti-SARS-CoV-2 Spike Domains. Schematic of our yeast display based strategy for generating, identifying, and characterizing large, diverse repertoires of nanobodies that bind the spike protein of SARS- CoV-2. The highest quality nanobodies were assayed for their ability to neutralize SARS- CoV-2 pseudovirus.
  • FIG. 1 Boxed inset shows 2.8 ⁇ m magnetic beads conjugated with S1 protein from SARS-CoV-2 Spike, after a binding reaction with yeast displaying an anti-S1 nanobody (top) or a nonspecific control (bottom), after non-binding yeast were washed away.
  • Figure 1 Sequence to determine VHH library are ATGGCTGAGGTGCAGTTGG (SEQ ID NO:172); ATGGCTCAGGTGCAGCTGG (SEQ ID NO:173); and ATGGCTGATGTGCAGTTGG (SEQ ID NO:174). Sequences to determine library of captured VHH are ATGGCTCAGGTGCAGCTGG (SEQ ID NO:175) and ATGGCCCAGGTGCAGCTGG (SEQ ID NO:176).
  • Figures 2A and 2B are ATGGCTCAGGTGCAGCTGG (SEQ ID NO:175) and ATGGCCCAGGTGCAGCTGG (SEQ ID NO:176).
  • FIG. 2A Fluorescence microscopy of a yeast competition assay.
  • Figure 2B Plot of the coefficient of variation (CV) of yield for each yeast strain across the experiments in B against the Kd of their displayed nanobodies. As seen in the plot, the yields of yeast bearing low affinity nanobodies were highly variable specifically under competitive conditions. The yield of the highest-affinity Nb-bearing yeast, in contrast, were almost invariant because they always won the competition. Under non-competitive conditions, this differential was lost.
  • Figures 3A through 3C Sequence Diversity of Nanobody Libraries.
  • Nanobody sequences from the unselected yeast library were amplified and sequenced with Illumina Miseq and processed to minimize sequence errors, as described in Methods, yielding 1.2 ⁇ 10 6 distinct nanobody sequences.
  • Framework regions (FRs) and complementarity-determining regions (CDRs) were determined in each encoded nanobody based on the alignment of (41). Unique sequences were determined and aligned by left justification of each region.
  • Figure 3A A seqlogo (44,59) was generated (MATLAB seqlogo command). High variability in the three CDR regions is evident.
  • Figure 3B Plot of proportion of non-consensus residues per residue across the library.
  • FIG. 5A through 5C Screening for New Families of Anti-Spike Nanobodies.
  • Figure 5A The read counts in the unselected and 1 ⁇ and 2 ⁇ selected libraries screened against either the S1, RBD or S2 domains of Spike from the entire llama 7704 nanobody cDNA display library (gray points) are plotted, as the log2 of these values + 1, as shown in Figures 4A, 4B.
  • Sequences displaying different specificities were identified and selected from the graphical display as in Figures 4A, 4B, except here nanobodies specific for only the RBD subdomain of S1 were separately labeled from those that recognized the non-RBD portions of S1. Selection was by a differential polygon function allowing multiple criteria. For example, sequences in an enriched polygon for S1 but not for RBD defines nanobodies binding to the non-RBD subdomain of S1 (also see Introduction). Green: S1 non-RBD; blue: RBD; red: S2.
  • FIG. 6A Testing the standard library against RBD variants Delta and Omicron. Dynabeads conjugated with RBD from the original SARS-CoV-2 and from the Delta and Omicron variants were employed for affinity purification of yeast display clones from the llama 7704 library. Two rounds of selection were carried out, as in Figures 4A, 4B, and 5A-5C. A clear overall reduction in binding was observed, though many clones still bound well to both variants.
  • Results were analyzed based on the fate of CDR3 ‘groups’ (where within a group, a given CDR3 bound to a high diversity of CDR1,2 recombinants). Different behaviors were observed; three are illustrated with colored dots (same color scheme as Figures 7A-7C).
  • the ‘NAAAW’ (SEQ ID NO:160) group (green) bound well to original and variant RBDs, essentially independent of the recombinant CDRs 1 and 2 it was attached to, suggesting strong ‘CDR3 dominance’ of the ‘NAAAW’ (SEQ ID NO:160) CDR3.
  • the ‘IIDDY’ (SEQ ID NO:164) group exhibited essentially similar behavior when shuffled as when combined with its native CDR1,2 ( Figures 7A-7C): strong binding to original and Omicron, but clearly weaker binding to Delta.
  • the ‘YERLAWD’ (SEQ: ID NO:159) recombinant group bound comparably to all variants, in contrast to its behavior with its native CDRs 1 and 2, which rendered it unable to bind Delta or Omicron.
  • Figure 6B Effectiveness of the shuffle is shown by extracting all sequences bearing a specific CDR3 and examining sequence diversity of CDRs 1 and 2.
  • Sequence logos show that highly diverse CDRs 1 and 2 are observed joined to each of three different CDR3’s, and the pattern of CDR1,2 diversity attached to the CDR3’s was essentially the same.
  • the sequences on Figure 6B are YERLAWD (SEQ: ID NO:159), NAAAW (SEQ ID NO:160), and IIDDY (SEQ ID NO:164).
  • Figures 7A through 7C Biophysical and Neutralization Properties of the Nanobodies. Thirty yeast display nanobodies targeting the S1-RBD, S1 non-RBD, and S2 portions of spike were functionally tested for neutralization of lentivirus pseudotyped with various SARS-CoV spikes and their biophysical properties characterized.
  • FIG. 7A Neutralization data against Original, Delta and Omicron.
  • Figure 7B Kd measurements of 21 of these nanobodies were determined using SPR and affinities plotted. Nanobodies were tested against Original, Delta and Omicron recombinant S1 or RBD. S1 non-RBD nanobodies were not tested against Omicron. Kd measurements for three of the ‘rescue’ constructs plotted at right.
  • Figure 7C The Tm measurements of the nanobodies in (B) were determined using DSF and plotted.
  • CoV2-YD-6 and CoV2-YD-38 resulted in two distinct melting peaks. Open circles indicate less proportion of this species in the sample. Tm measurements for three of the ‘rescue’ constructs plotted at right.
  • Figure 8. Epitope Binning by Yeast Display. Dynabeads conjugated with RBD were blocked with monomer nanobodies representing the 7 epitope classes defined previously (20); with the soluble extracellular domain of the RBD target Ace2; or left unblocked. The 2 ⁇ -RBD-selected library from llama 7704 (Figs.4, 5, S1) was bound to these beads.
  • the bound VHHs were sequenced, and enrichment/depletion upon blocking for each ‘CDR string’ (catenated CDR1/CDR2/CDR3) was calculated as log2 (readcount with blocked beads/readcount with unblocked beads).
  • the sequences were filtered to remove PCR crossover artifacts (Methods).
  • Left The resulting matrix of ⁇ 100,000 sequences X 8 blocking agents was filtered for readcount (at least 100 reads combining all blocking experiments) and clustered using the MATLAB hierarchical clustering algorithm; scale bar on left indicates log2 enrichment/depletion (above).
  • NAAAW SEQ ID NO:160
  • TALLS SEQ ID NO:162
  • TADLY SEQ ID NO:163
  • IIDDY SEQ ID NO:164
  • TVDAQ SEQ ID NO:165
  • AAHVN SEQ ID NO:166
  • MATSEY SEQ ID NO:170
  • GSDFGDH SEQ ID NO:171
  • TVTDR SEQ ID NO:181
  • Figure 9 Binding of nanobodies expressed in yeast to the different recombinant S1, RBD and S2 domains of SARS-Cov2 Spike protein (labeled S1, RBD, and S2 selection respectively) (20) conjugated to Dynabeads. Binding and washing were as described in Methods.
  • Nanobody sequences were amplified and sequenced as in Figures 3A-3C.
  • the CDR regions were extracted from each sequence, and concatenated in a ‘CDR string’.
  • High-affinity binders were recovered from llama 5094, though apparently fewer than from 7704, reflecting the results of (20).
  • the inventors carried out the same assay for these nanobodies and plotted the results as in Figure 4A, with the exception that to get sufficient representation CDR strings with up to 20% sequence variation in each CDR were accepted; each different color of the dots plotted represents a member of a family of a given mass spectrometry-positive nanobody.
  • the same high specificity and recovery in yeast display for the 5094 clones was observed for the 7704 clones.
  • FIGS 11A and 11B Comparison of different methods for screening the display libraries. The entire llama 7704 nanobody cDNA display library was screened against the RBD domain of Spike, and plotted as in Figure 9 (gray points). Two methods of screening were employed. The first was as described in Figure 1 and Methods, using two rounds of Dynabead selection.
  • Figure 11A All sequences recovered are plotted as in Figure 9.
  • Figure 11B Families of MS- positive sequences are plotted on top of the overall graph, as in Figure 10.
  • Figure 12. Testing CDR families of mass-spectrometry positives against RBD variants Delta and Omicron. The data are plotted as in Figures 7A-7C, but plotting CDR families of the mass-spectrometry-positive clones; each different color of the dots plotted represents a different mass spectrometry-positive nanobody.
  • Figure 13
  • Diagram of the splice-overlap extension method for recombining CDRs Degenerate oligos priming in both directions from two highly conserved sequences within framework regions (FRs) 2 and 3, and end oligos tagged for recombination onto the yeast expression vector, were used to amplify fragments containing CDRs 1, 2 and 3 as well as flanking framework regions.
  • the template used was a pool after 1 round of selection on RBD.
  • the result of the sequential PCR reactions indicated is a random mix-and-match of the three CDRs and flanking framework regions.
  • Figure 14 Epitope Binning Tests.
  • Dynabeads conjugated with RBD were pre- blocked with saturating amounts of either monomer nanobodies S1-1 or S1-23, with unblocked Dynabeads as control.
  • polynucleotide and amino acid sequences having from 80-99% similarity, inclusive, and including and all numbers and ranges of numbers there between, with the sequences provided here are included in the invention. All of the amino acid sequences described herein can include amino acid substitutions, such as conservative substitutions that do not adversely affect the function of the protein that comprises the amino acid sequences.
  • the present specification also provides polynucleotides that hybridize under selective hybridization conditions to a polynucleotide that encodes a described antibody.
  • a polynucleotide that can hybridize to a polynucleotide that encodes a described antibody has 70-100% complementarity, inclusive, and including all numbers and ranges there between, to the coding polynucleotide.
  • Selective hybridization conditions under which a polynucleotide having at least 70% complementarity to a polynucleotide encoding a described antibody will be known by those skilled in the art.
  • the degree of stringency can be controlled by one or more of temperature, ionic strength, pH, and the presence of a denaturing agent such as formamide.
  • a polynucleotide that hybridize under selective hybridization to a coding polynucleotide can be present in an expression vector.
  • the expression vector can be introduced into a cell of a cell culture to thereby express a described antibody.
  • the antibody can be separated from the cell culture and used to produce a purified form of antibodies.
  • the disclosure provides a VHH chain of an anti-Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) nanobody, wherein the amino acid sequence of the VHH chain comprises any one of the sequences as set forth in SEQ ID NOs:117 – 153.
  • SARS-CoV-2 anti-Severe Acute Respiratory Syndrome Coronavirus 2
  • the disclosure expands the repertoire of VHH chains disclosed in PCT application no. PCT/US2021/047019, published as WO2022040603 on February 2, 2022, the entire disclosure of which is incorporated herein by reference, and beyond the constructs described in Fred D Mast, et al.
  • VHH chains comprising amino acid sequences that have at least 90% sequence identity to any one of the contiguous sequences as set forth in SEQ ID NOs: 117 – 153.
  • the nanobodies are referred to herein from time to time as “binding partners” in the plural and “binding partner” in the singular.
  • the VHH chain can comprise an amino acid sequence comprising any one of the sequences as set forth in SEQ ID NOs:117 – 153.
  • a VHH chain as in any one of SEQ ID NOs:117 – 153 may be combined with a VHH chain as in any one of SEQ ID NOs:1-116 to produce a multi-specific binding partner.
  • the multi- specific binding partner is provided in the form of a dimer that can bind to two different epitopes of a viral spike protein.
  • a VHH chain as in any one of SEQ ID NOs:117 – 153 can be incorporated into, for example, a chimeric antigen receptor, single- chain Diabodies (scDbs), single-chain variable fragment (scFv), and other antibody fragments that retain antigen binding function.
  • a binding partner of this disclosure may be used in combination with a binding partner comprising a sequence of any one of SEQ ID NOs: 1-116.
  • the combination may comprise at least two separate binding partners, or at least two antibodies may be combined into a single binding partner format to provide a multi-specific binding partner, such as a bi-specific antibody.
  • a binding partner of this disclosure may be modified such that it is present in a fusion protein.
  • an antigen binding segment of a binding partner may be present in a fusion protein, and/or a constant region may be a component of a fusion protein.
  • a fusion protein comprises amino acids from at least two different proteins.
  • Fusion proteins can be produced using any of a wide variety of standard molecular biology approaches, including but not necessarily limited to expression from any suitable expression vector.
  • a binding partner described herein may be present in a fusion protein with a detectable protein, such as green fluorescent protein (GFP), enhanced GFP (eGFP), mCherry, and the like.
  • GFP green fluorescent protein
  • eGFP enhanced GFP
  • mCherry a detectable protein
  • an mRNA or chemically modified mRNA encoding any binding partner described herein can be delivered to cells such that the binding partner is translated by the cells.
  • Pharmaceutical formulations containing binding partners are included in the disclosure and can be prepared by mixing them with one or more pharmaceutically acceptable carriers.
  • Pharmaceutically acceptable carriers include solvents, dispersion media, isotonic agents, and the like.
  • an effective amount of one or more binding partners is administered to an individual in need thereof.
  • an effective amount is an amount that reduces one or more signs or symptoms of a disease and/or reduces the severity of the disease.
  • An effective amount may also inhibit or prevent the onset of a disease or a disease relapse.
  • a precise dosage can be selected by the individual physician in view of the patient to be treated. Dosage and administration can be adjusted to provide sufficient levels of binding partner to maintain the desired effect. Additional factors that may be taken into account include the severity and type of the disease state, age, weight, and gender of the patient, desired duration of treatment, method of administration, time and frequency of administration, drug combination(s), reaction sensitivities, and/or tolerance/response to therapy.
  • a described binding partner is administered to an individual who has or is suspected of having or is at risk of contracting a SARS-CoV-2 infection.
  • the SARS-CoV-2 infection is by any type of SARS-CoV-2 that is a variant of high consequence, a variant of concern, a variant of interest, or a variant being monitored.
  • any described antibody can be administered for therapeutic or prophylactic purposes.
  • one or more described antibodies can be administered to an individual who has been diagnosed with COVID-19.
  • Binding partners and pharmaceutical compositions comprising the binding partners can be administered to an individual in need thereof using any suitable route, examples of which include intravenous, intramuscular, intraperitoneal, subcutaneous, oral, or inhalation routes.
  • compositions may be introduced as a single administration or as multiple administrations or may be introduced in a continuous manner over a period of time.
  • the administration(s) can be a pre-specified number of administrations or daily, weekly, or monthly administrations, which may be continuous or intermittent, as may be therapeutically indicated.
  • the VHH chain can comprise an amino acid sequence comprising any one of the sequences as set forth in SEQ ID Nos: 117-120, 147, and 148.
  • SEQ ID NOs: 117-120, 147, and 148 can be selective for binding to non-Receptor Binding Domain (RBD) of SARS-CoV-2 spike protein.
  • RBD non-Receptor Binding Domain
  • the disclosure provides for an immunoconjugate comprising: (a) a VHH chain as recited above; and (b) a conjugating part comprising a detectable marker, a drug, a radionuclide, or an enzyme, or a toxin.
  • the VHH chain can comprise an amino acid sequence comprising at least 90% sequence identity to any one of the sequences as set forth in SEQ ID NOs: 150- 157.
  • SEQ ID NOs: 150-157 are selective for binding to Receptor Binding Domain (RBD) of SARS-CoV-2 spike protein.
  • the VHH chain can comprise an amino acid sequence comprising at least 90% sequence identity to any one of the sequences as set forth in SEQ ID NOs: 117- 120, 147, and 148.
  • SEQ ID NOs: 117-120, 147, and 148 are selective for binding to non-Receptor Binding Domain (RBD) of SARS-CoV-2 spike protein.
  • RBD non-Receptor Binding Domain
  • the disclosure provides for an immunoconjugate comprising: (a) a VHH chain as described above; and (b) a conjugating part comprising a detectable marker, a drug, a radionuclide, or an enzyme. Such constructs may be used for therapeutic or diagnostic purposes.
  • the disclosure provides for a pharmaceutical composition
  • a pharmaceutical composition comprising: (a) a VHH chain as above or an immunoconjugate as described above; and (b) a pharmaceutically acceptable carrier.
  • a pharmaceutical composition comprising: (a) a VHH chain as above or an immunoconjugate as described above; and (b) a pharmaceutically acceptable carrier.
  • the terms “nanobody”, “nanobodies”, “SARS-CoV-2 nanobody”, or “SARS-CoV-2 nanobodies” are exchangeable and refer to nanobodies that specifically recognize and bind to the Spike protein of SARS-CoV-2 and to the Spike protein of any variants of concern (VoC).
  • single domain antibody VHH
  • nanobodies have the same meaning referring to a variable region of a heavy chain of an antibody, and construct a single domain antibody (VHH) consisting of only one heavy chain variable region. It is the smallest antigen-binding fragment with complete function.
  • variable means that certain portions of the variable region in the nanobodies vary in sequences, which forms the binding and specificity of various specific antibodies to their particular antigen. However, variability is not uniformly distributed throughout the nanobody variable region. It is concentrated in three segments called complementarity-determining regions (CDRs) or hypervariable regions in the variable regions of the light and heavy chain.
  • CDRs complementarity-determining regions
  • variable region The more conserved part of the variable region is called the framework region (FR).
  • the variable regions of the natural heavy and light chains each contain four FR regions, which are present in a ⁇ -folded configuration, joined by three CDRs which form a linking loop, and in some cases can form a partially ⁇ -folded structure.
  • the CDRs in each chain are closely adjacent to the others by the FR regions and form an antigen- binding site of the nanobody with the CDRs of the other chain (see Kabat et al., NIH Publ. No.91-3242, Volume I, pages 647-669. (1991)).
  • the constant regions are not directly involved in the binding of the nanobody to the antigen, but they exhibit different effects or functions, for example, in antibody-dependent cytotoxicity of the antibodies.
  • the described antibodies may have changes from the sequences expressly described herein, including conservative amino acid substitutions in the framework regions.
  • the heavy chain variable region of described nanobody comprises 3 complementary determining regions: CDR1, CDR2, and CDR3 having at least 95% sequence identity to a described CDR amino acid sequence.
  • sequence similarity refers to the likeness between at least two sequences in comparison.
  • Sequence identity refers to the number of characters that match exactly between the two different sequences.
  • sequence identity addresses the degree of similarity of two sequences, such as protein sequences. Determination of sequence identity can be readily accomplished by persons of ordinary skill in the art using accepted algorithms and/or techniques.
  • Sequence identity is typically determined by comparing two optimally aligned sequences over a comparison window, where the portion of the peptide sequence in the comparison window may comprise additions or deletions (i.e., gaps) as compared to the reference sequence (which does not comprise additions or deletions) for optimal alignment of the two sequences.
  • the percentage is calculated by determining the number of positions at which the identical amino-acid residues occur in both sequences to yield the number of matched positions, dividing the number of matched positions by the total number of positions in the window of comparison and multiplying the result by 100 to yield the percentage of sequence identity.
  • Various software driven algorithms are readily available, such as BLAST N or BLAST P to perform such comparisons. Any described antibody may be humanized. Methods for humanization are known in the art.
  • human framework sequences are substituted for the described framework sequences, suitable human framework sequences being known in the art.
  • EXAMPLES To produce the described nanobody repertoires, we employed a mass spectrometry- based approach (20,22) in which llamas were immunized with Spike constructs. This permits affinity maturation processes in vivo (33). High-throughput DNA sequencing of VHH libraries PCR-amplified from marrow lymphocyte cDNA from the immunized llamas in combination with mass spectrometric (MS) identification of high-affinity VHH regions derived from the serum of the same animal was performed.
  • MS mass spectrometric
  • VHH cDNA sequences Computational matching of MS- sequenced peptides to VHH cDNA sequences allowed high-confidence identification of sequences encoding high-affinity nanobodies.
  • Genes encoding nanobodies were synthesized and expressed in bacteria, and nanobodies were purified, and characterized for their specificity and affinity.
  • These V H H cDNA libraries also represent a resource that can be used for an orthogonal approach for nanobody production, employing display screening methods instead (34-37). This approach could discover additional nanobodies, and also serve as a platform to explore the specificity and VoC sensitivity of a large number of nanobodies in parallel.
  • a robust and efficient yeast display method was designed and validated specifically for screening nanobodies, in particular against Spike (34,38).
  • the present disclosure includes evaluation of the cDNA library made from immunized llamas (20), which was transferred into a nanobody display vector (34).
  • a nanobody display vector 34
  • yeast expressing high-affinity nanobodies displayed little variation in yield even under competitive conditions, because they ‘won’ the competition.
  • each sequence to a representation consisting solely of its three CDR regions (CDRs 1,2,3) (referred to as a ‘CDR string’).
  • CDRs 1,2,3 CDR regions 1,2,3
  • Fig.9 shows the behavior of the entire library.
  • the screen clearly distinguished specifically binding and non-binding clones; for example, biochemically defined S2-specific nanobodies bound to S2 beads but not S1 or RBD beads when expressed in yeast, and vice versa.
  • biochemically defined S2-specific nanobodies bound to S2 beads but not S1 or RBD beads when expressed in yeast, and vice versa We plotted enrichment of these MS positive sequences after both 1 and 2 rounds of selection against their measured K D s (20). While the relationship was noisy, a statistically significant negative slope was observed (Fig.4B), especially for two rounds of selection (likely to be more competitive conditions based on our analysis of anti-GFPs above), once again confirming the competitive and affinity-sensitive nature of the screen.
  • Fig.4B a statistically significant negative slope was observed (Fig.4B), especially for two rounds of selection (likely to be more competitive conditions based on our analysis of anti-GFPs above), once again confirming the competitive and affinity-sensitive nature of the screen.
  • the S1-non-RBD clones are dominated by members of one family, defined by its ‘IAQY’ (SEQ ID NO:185) consensus CDR3 sequence (Fig.5B,C; family (i)). This family was missed in the MS-based approach (20), possibly because the CDR3 was too small for reliable peptide identification.
  • numerous other new S1-specific families are present, for example the “RGLGRGLGFY” (SEQ ID NO:186) CDR3 consensus sequence (Fig 5B, family (ii)).
  • the RBD domain isolated a large and diverse set of families.
  • Fig 5B, family (v) contains the consensus CDR3 “TVDAQSDY” (SEQ ID NO:184), which is also found in the mass spectrometrically identified nanobody S1-RBD-38.
  • Two large families identified here contain divergent relatives among the MS-identified nanobodies (20), the ‘‘LRSRFNAAAWTTEAAFDY’ ’ (SEQ ID NO:158) (previous MS-identified S1-RBD-6 and S1-RBD-31) and ‘YERLAWDTSTY’ (SEQ ID NO:177) families (previous MS-identified S1-RBD-35), the remaining four indicated families being completely novel.
  • the S2-specific clones were also very diverse and not dominated by any single family (Fig.5B,C), with limited overlap with the mass spectrometrically identified clones (20).
  • the screening method identified a large number of new clones recognizing different Spike domains. We then analyzed if these new clones had high affinity binding and strong antiviral activity when expressed as monomers. Testing the Library against the Major VoCs Delta and Omicron
  • One of the greatest challenges to managing COVID-19 is the ability of the SARS- CoV-2 virus to mutate into new VoCs that can resist prevalent vaccines and therapeutics.
  • An advantage of generating large repertoires of nanobodies is that one maximizes the likelihood of finding VoC-resistant, broadly specific nanobodies (20,47-49).
  • the large ‘TVDAQSDY’ (SEQ ID NO:184) (Fig.5C, (v)) family binds comparably to the original SARS-CoV-2 and both variants.
  • the ‘‘LRSRFNAAAWTTEAAFDY’ (SEQ ID NO:158) ‘NAAAW’ (SEQ ID NO:160) (Fig.5C, (iv)) family binds comparably to the original SARS-CoV-2 and the Delta VoC RBDs, and appears collectively slightly weaker against the Omicron RBD.
  • YERLAWDTSTY SEQ ID NO:177
  • YERLAWD YERLAWD
  • SEQ: ID NO:159 Fig.5C, (iii)
  • the ‘IIDDYGVQY’ (SEQ ID NO:178) (‘IIDDY’ IIDDY (SEQ ID NO:164)) (Fig.5C, (vi)) family (Fig.6A, ‘IIDDY’ (SEQ ID NO:164)) and a family not indicated on Fig.5 but comprising a family characterized by a ‘TADLYSDY’ (SEQ ID NO:179) (‘TADLY’) (SEQ ID NO:163) CDR3 sequence binds well to original SARS-CoV-2 and the Omicron variant but more weakly to the Delta variant, especially after two rounds of selection. These families contain considerable sequence diversity within them (Fig.5).
  • DNA shuffling is an established in vitro method for improvement of binding or catalytic activity. Typically it is applied to a library of randomly point-mutagenized sequences that have been selected for improved activity, from which starting point splice- overlap-extension (SOE) PCR is carried out to produce mix-and-match recombinants.
  • SOE starting point splice- overlap-extension
  • VDJ recombination shares some features, but with the critical difference that only a single round of shuffling occurs rather than multiple rounds interleaved with the recombinations. Neither the extremely high density of recombination joins that can be attained by in vitro shuffling, and its highly multiparental nature, are shared by natural biological systems, to our knowledge. DNA shuffling has been applied to nanobodies with recombination between CDRs, with improvement of binding noted in the progeny (52-54). However, the specificity and number of potential parental sequences was not established. We started with the library selected on SARS-Cov2 RBD, carried out SOE recombining CDRs 1, 2 and 3 at random from that library (Fig.13).
  • the shuffled YERLAWD (SEQ: ID NO:159) group in contrast, contained abundant members that bound equally well to Original and to Delta RBD, while remaining almost completely defective in Omicron binding.
  • Examination of the sequences associated with this high Delta binding revealed specific enrichment of sequences highly similar to the native ‘NAAAW’ (SEQ ID NO:160) CDR1 and CDR2, recombined with the ‘YERLAWD’ (SEQ: ID NO:159) CDR3 (Fig.6B).
  • the native ‘NAAAW’ (SEQ ID NO:160) family CDR1 and CDR2 have specific ability to bind to Delta RBD, independent of CDR3 content.
  • a subset of the anti-S1 nanobodies were tested for binding affinity against recombinant S1 or RBD from either Original, Delta or Omicron (S1 non-RBD nanobodies were not tested against omicron) (Fig.7B); all bound strongly to Original, displaying affinities in the nM - pM range. Two of these failed to bind only Delta, two failed to bind only Omicron and CoV2-YD-33 and CoV2-YD-34 failed to bind both variants.
  • CoV2-YD-10 neutralizes yet shows no binding to the RBD of omicron using SPR. It is possible the binding site of the nanobody may be slightly truncated in the RBD construct used for SPR resulting in the no binding result. Lastly, all showed a moderate to strong degree of thermal stability, typical of nanobodies (Fig.7C) (21).
  • the nanobody binding in the yeast display screening correlates reasonably well with that seen in the biochemical assay of the corresponding expressed nanobody (Fig.7B).
  • the differential affinities of the ‘YERLAWD’ (SEQ: ID NO:159) and ‘NAAAW’ (SEQ ID NO:160) nanobodies for Delta RBD in both yeast display screening (Fig.6) and in the biochemical assay of the corresponding expressed nanobody (Fig.7B) agree, as discussed in the previous section.
  • ‘LAYVT’ SEQ ID NO:161) (CoV2-YD-7) shows no significant loss of affinity for either Delta or Omicron RBD in both yeast display screening and in the biochemical assay of the corresponding expressed nanobody.
  • ‘TALLS’ (SEQ ID NO:162) (CoV2-YD-6) show partial loss of affinity for Delta RBD while retaining Omicron affinity in both yeast display screening and in the biochemical assay of the corresponding expressed nanobody.
  • ‘TADLY’ (SEQ ID NO:163) (CoV-YD-9) shows complete loss of affinity for Delta RBD in both yeast display screening and in the biochemical assay of the corresponding expressed nanobody, while again retaining Omicron affinity in both assays.
  • Epitope Mapping of the Nanobody Repertoire Another important characterization of any nanobody repertoire is to determine the different epitopes being recognized by each nanobody, as in the case of anti-SARS-CoV-2 Spike nanobodies, exploration of a larger epitope space increases the likelihood of discovering variant resistant, strongly neutralizing nanobodies (20). This is usually done by ‘epitope binning’: finding classes of nanobodies that reciprocally inhibit each others’ binding due to competition for the same epitope. Epitope binning is generally carried out by one-on- one competitions between pairs of nanobodies; therefore, the number of assays scales with the square of the number of nanobodies to test.
  • the blocked beads were used to select binders from a library of 2-times-selected RBD binders (Figs.4, 5). V H H sequences from the bound population were determined, and the read counts of the sequences bound to RBD beads blocked with each nanobody were determined. The read count recovered from the blocked beads was divided by the read count from the unblocked beads, and the resulting ratios hierarchically clustered (Fig.8). These 7 epitope classes were selected to collectively encompass essentially all of the available RBD surface (20). Consistent with this, the majority of nanobodies in our population are inhibited by blocking the RBD beads with at least one of the seven nanobody classes (Fig.8). A minority of nanobodies were not so inhibited and may represent new epitope class(es).
  • nanobodies fall into more than one epitope class, as defined by this assay. Thus, most nanobodies in class #1 are also in class #2, and vice versa; and a similar mutuality is seen between classes #3 and #4, which in turn contains a smaller subgroup that is also found in class #5 (Fig.8).
  • the positions of the ‘founding’ epitopes for these classes was estimated previously from MS cross-linking data and escape mutants (20). Examination of the estimated position of these epitopes on RBD indeed indicates that there is significant overlap or adjacency between #1 and #2, and between #3, #4 (and even #5 or #6), consistent with steric clashes that could lead to the class overlaps observed (Fig.8) (20).
  • sequence variants within families generally fell together on the clustergram, which was generated sequence-blind, based solely on the binding behavior in the 7 blocked populations. This result supports the similar behavior of almost all the sequence variants assigned to the families. For example, essentially all of the sequences in the ‘YERLAWD’ (SEQ: ID NO:159) CDR3 family were specifically blocked by #6, and essentially all of the sequences in the ‘NAAAW’ (SEQ ID NO:160) and ‘LAYVT’ (SEQ ID NO:161) CDR3 families (Figs. 5, 6) were specifically blocked by #7 (Fig.8). Many other smaller CDR3 families also displayed similar behaviors. Interestingly, classes #1 to #4 did not singly block any significant CDR3 families, but rather acted to block them in different combinations.
  • CDR3 families were blocked by both #3 and #4, of note being the large CDR3 family characterized by the starting sequence TVDAQ (SEQ ID NO:165); however, there appears to be a range of behaviors in this large class (Fig.8). So, some CDR3 families are essentially exclusively blocked by #3 and #4, such as those CDR3 sequences characterized by CDR3s starting with ARDD (SEQ ID NO:180), ARNQ (SEQ ID NO:81), and WRYF (SEQ ID NO:182).
  • a number of families are similarly strongly blocked by #3 and #4, but also partially blocked (to lesser or greater extents) by #5 (Fig.8); these include the large TVDAQ (SEQ ID NO:165), TALLS, (SEQ ID NO:162) and AAHVN (SEQ ID NO:166) CDR3 starting sequence families (Fig.8; see also Figs.5, 6). Then there are those nanobody CDR3 families almost equally strongly blocked by #3, #4 and #5, including S1-RBD-43 and related nanobodies (characterized by the CDR3 starting sequence AGHV (SEQ ID NO:167)).
  • the third is that the method can be adapted to allow massively parallel epitope binning, a step for generating fully characterized nanobodies, including with diagnostic or therapeutic potential.
  • the disclosure provides new nanobodies with strong neutralization activity that may used for treatments for the continuing fight against COVID-19 (20).
  • METHODS Library construction Starting with B cell cDNA from the same immunized llamas described previously (20), we amplified V H H sequences with oligos providing flanking homology for cloning into the yeast display vector (34). We carried out gap-repair using a high-efficiency yeast transformation method (55),which in our hands yielded a maximum efficiency of colony recovery of ⁇ 1.5 * 10 ⁇ 7 colonies.
  • Yeast were vitally fluorescently labeled on their cell surfaces as previously described (40). We used GFP-Dynabeads and yeast expressing surface anti-GFP to establish conditions for binding and washing. The optimal binding buffer we discovered is described below. A 1 hr binding of yeast to beads with rotation at 30°C was followed by 4-5 washes with purification of bead-bound cells on a magnet using a Dynal MPC-6 magnetic stand, with samples kept at 2 cm from the magnet, 5 min binding per wash. All yeast affinity captures were performed in 1% BSA (Fraction V, protease-free; GoldBio (St.
  • Affinity capture with Miltenyi beads and subsequent fluorescence-activated cell sorting (FACS) were performed as described (34). Sequencing of nanobody clones in the purified yeast library After binding, beads with bound cells were transferred to ScMin-2% glucose and grown out for 14-48 hrs. Cells were pelleted, lysed with Zymolyase and DNA purified on Qiagen miniprep columns following manufacturer’s procedures. The DNA prep was amplified with sequencing primers and sequenced at the Rockefeller Genomics facility using an Illumina MiSeq, PE250 (early experiments), PE300 (most experiments; better sequence quality due to longer overlap between the paired reads).
  • Nanobody cloning, expression and characterization Cloning, expression and purification of the nanobodies were performed as described (20).
  • Computational methods Nanobody sequences were obtained by paired-end sequencing (300 bp readlength) using Illumina MiSeq. Since each nanobody sequence was potentially represented by exactly one pair of reads, it was important to filter the data for quality. The computation was as follows: for positions covered only by one of the two paired-end reads, the quality score for that position was the one assigned by MiSeq.
  • the base call was that for the higher-quality-scored position, and the final score was the sum of quality scores for the two reads if the base call was the same, and the higher minus the lower score if the base call was different.
  • the overall nominal probability of having no error anywhere in the sequence was then computed as 1 – Product(-Q/10), product taken over all positions in the sequence, where Q is the final quality score at each position, and a cutoff of 0.9 applied.
  • a similar calculation was applied to sequences approximately encoding CDR1, CDR2 and CDR3, with a cutoff of 0.95.
  • the CDR sequences were extracted from the complete nanobody sequence using the consensus FR region sequences from (41). Their consensus sequences were used to generate multiple alternate FR regions (usually with one or two substitutions each) and the best alignment to each FR (testing separately all of the candidate FR regions) was found. Sequences between FRs were assigned as CDRs 1,2,3. Subsequent computations were done using the ‘CDR string’ composed of the catenated CDR1,2,3 sequences. Due to minor FR variability there were approximately 1/3 as many CDR strings as full nanobody sequences. The data indicated strong concordance among nanobodies with the same CDR string, consistent with the known primacy of CDR sequence for binding specificity (see Introduction).
  • CDR strings were ranked in order of abundance. The most abundant initiated a list of ‘native’ (non-crossover sequences). Subsequent (decreasing abundance) sequences were then examined for a good match in some CDRs to a sequence in the ‘native’ list combined with a bad match in other CDRs. Such cases were assigned to a list of ‘crossover’ sequences; others (either distinct in all three CDRs, or similar in all three CDRs, to members of the native list) were appended to the native list. All computations were carried out by MATLAB code, available upon request. Sequence logos and phylogenetic trees were calculated using built-in functions in the MATLAB Bioinformatics toolbox.
  • Respective K on , K off , and K D values are shown for each component.
  • b Curves were fit to two-state reaction model.
  • Respective K on , K off , and K D values are shown for each binding state.
  • cTwo peaks were observed in the melting curve. Tms for both are reported.
  • Nanobody cocktails potently neutralize SARS-CoV-2 D614G N501Y variant and protect mice. Proc Natl Acad Sci U S A 118 50. Starr, T. N., Greaney, A. J., Hannon, W. W., Loes, A. N., Hauser, K., Dillen, J. R., Ferri, E., Farrell, A. G., Dadonaite, B., McCallum, M., Matreyek, K.

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Abstract

L'invention concerne des anticorps VHH anti-coronavirus du syndrome respiratoire aigu sévère 2 (SARS-CoV-2), et des procédés de fabrication et d'utilisation des anticorps à chaîne VHH.
PCT/US2024/016913 2023-02-22 2024-02-22 Multiplication et amélioration de répertoires de nanocorps : ciblage du sars-cov-2 Ceased WO2024178232A2 (fr)

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