DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Information Disclosure Statement
The information disclosure statement (IDS) submitted on 11/25/2024 is/are compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner.
Office Action Summary
Claim(s) 1-3, 5-11, 14-16, and 18-24 is/are rejected under 35 U.S.C. 103 as being unpatentable over Rickgauer et al -(Single-protein detection in crowded molecular environments in cryo-EM images) in view of Barth (US 2023/0227534 A1).
Claim(s) 4, 13, and 17 is/are rejected under 35 U.S.C. 103 as being unpatentable over Rickgauer et al (Single-protein detection in crowded molecular environments in cryo-EM images) in view of Barth (US 2023/0227534 A1), further in view of Saur et al (Fragment-based drug discovery using cryo-EM).
Claim(s) 12 and 25 is/are rejected under 35 U.S.C. 103 as being unpatentable over Rickgauer et al (Single-protein detection in crowded molecular environments in cryo-EM images) in view of Barth (US 2023/0227534 A1), further in view of Hendriksen et al (US 2021/0072170 A1).
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claim(s) 1-3, 5-11, 14-16, and 18-24 is/are rejected under 35 U.S.C. 103 as being unpatentable over Rickgauer et al -(Single-protein detection in crowded molecular environments in cryo-EM images) in view of Barth (US 2023/0227534 A1).
Regarding claim(s) 1 and 14, Rickgauer teaches a method of imaging an interaction of a particle and a fragment in a sample, comprising:
applying a template to one or more images of a sample comprising a particle and a fragment, the template comprising a three-dimensional representation of the particle at a resolution of higher than about 1/8 reciprocal Angstroms and produced by data independent of data provided in the one or more images(Page 1, Introduction, 1st Paragraph: “the detection of unlabeled proteins in cells on the basis of template matching”; Page 1, Introduction, 2nd Paragraph: “Template matching applied to electron cryo-microscopy (cryo-EM)-based tomograms aims to determine whether certain proteins are present in experimental images by comparing computed protein templates, derived from solved atomic models, to 3D reconstructions of samples”; Page 15, Template generation, 1st Paragraph: “Templates were computed using the structural information in the target’s PDB coordinate file retrieved from the RCSB Protein Data Bank (RRID:SCR_012820)”; and Page 19, Code availability, 1st Paragraph: “calculate reference structures (scattering potential matrices) from Protein Data Bank-formatted models, and to search for these structures in images by cross-correlation”);
producing a similarity image (read as “cross-correlation image (CCG)”) comprising a pixel-wise representation of a distance metric between the template and the one or more images, the distance metric enabling detection of at least a portion of the particle or fragment (Page 17, Precision-recall curves, 3rd Paragraph: “These templates were then whitened and cross-correlated with the whitened image. The resulting CCGs were then combined into a maximum intensity projection (MIP) and cross-correlated with a location reference image”; Page 16, Searching the images, 1st Paragraph: “CCGs were calculated as follows: we padded the template to the image size with its own mean value, subtracted the mean from the image and the template […] The CCG was then obtained as […] where * denotes the complex conjugate. Throughout, a FFT normalization was used that preserved the quadratic norm […]”; Abstract: “Our method detects single apoferritin molecules in vitreous ice with high specificity and determines their orientation and location precisely”; and Page 3, 3rd Paragraph: “High-value CCG pixels were typically clustered at locations that—in high-underfocus images—were encircled by the dark ring typical for apoferritin (Figure 1d)”);
applying a probability metric to the similarity image to distinguish positive detections from noise (Page 3, 3rd Paragraph: “where the target molecules are not detectable by eye (Figure 1a), there were typically only a small number of orientations for which the corresponding cross-correlograms (CCGs) contained any (and when they did, only a few) pixels with values of the SNR (the ratio of the peak height and the standard deviation of the CCG noise [Saxton and Frank, 1976], Materials and methods) that were exceptionally high, i.e., substantially exceeded those expected for a Gaussian noise distribution”); and
producing a representation of a volume as a function of the positive detections, the representation of the volume including elements representing an interaction between the particle and the fragment (Figure 4; Abstract: “[…] determines their orientation and location precisely“; Page 1, Introduction, 2nd Paragraph: “[…] This approach has made it possible to map the 3D locations and orientations […]”; and Page 6, Protein background (Simulations), 4th Paragraph: “CCGs now showed strong and narrow peaks at the correct locations […] These simulation results confirm that a major reason for compromised detectability in strongly defocused images is that there the CTF, unlike in close-to-focus images, does not suppress the low-frequency noise that dominates images with a high density of macromolecules”).
Rickgauer fails to teach the fragment not represented in the template. However, Barth teaches the fragment not represented in the template (Paragraph [0142]: “For the ligand free 3D structures, the closest structurally characterized homologs available were used as templates to model the inactive and active state […] Models of D2 inactive and active states were generated without bound ligand or G protein using the homology mode of RosettaMembrane”; and Paragraph [0143]: “ensembles of low energy models were clustered and centers of the most populated clusters were selected as templates for each ligand-free state in the design calculations of stability microswitches”, Examiner’s Note: the present Specification Paragraph [0050] expressly identifies a ligand as an example of the claimed fragment (“fragment (e.g., a ligand)”).
Rickgauer teaches a computer-implemented cryo-electron microscopy (cryo-EM) image processing method in which computed three-dimensional structural templates derived from solved atomic models are applied to experimental cryo-EM images to perform template matching, generate similarity measurements through cross-correlation, identify positive detections, distinguish true detections from background noise using statistical analysis, and reconstruct three-dimensional structural information based on the detected particles. Rickgauer further teaches that the structural templates are generated from structural data independent of the acquired cryo-EM images. Barth teaches generating three-dimensional structural models without a bound ligand and selecting representative ligand-free structural models as templates for subsequent structural analysis.
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to employ the ligand-free structural template of Barth in the template matching method of Rickgauer. The motivation for this combination of references would have been to employ ligand-free structural models selected as templates to determine whether certain proteins are present in experimental images. This motivation for the combination of Rickgauer and Barth is supported by KSR exemplary rationale (G) Some teaching, suggestion, or motivation in the prior art that would have led one of ordinary skill to modify the prior art reference or to combine prior art reference teachings to arrive at the claimed invention. MPEP 2141 (III).
Regarding claim(s) 2 and 15, Rickgauer as modified by Barth teaches the method of claim 1, where Rickgauer teaches wherein the representation of the volume produced comprises elements representing at least one of a location and an orientation of the fragment with respect to the particle (Figure 4; Abstract: “[…] determines their orientation and location precisely“; Page 1, Introduction, 2nd Paragraph: “[…] This approach has made it possible to map the 3D locations and orientations […]”; and Page 6, Protein background (Simulations), 4th Paragraph: “CCGs now showed strong and narrow peaks at the correct locations […] These simulation results confirm that a major reason for compromised detectability in strongly defocused images is that there the CTF, unlike in close-to-focus images, does not suppress the low-frequency noise that dominates images with a high density of macromolecules”).
Regarding claim(s) 3 and 16, Rickgauer as modified by Barth teaches the method of claim 1, where Rickgauer teaches wherein the representation of the volume produced comprises elements representing molecular interactions of the fragment and the particle (Page 14, 4th Paragraph: “Detection of the rotavirus RNA polymerase and the mapping of the occupied binding sites inside the virus capsid (Figure 6d–e) illustrates how one can analyze partially stochastic protein assemblies, in which a ligand protein (here, VP1) binds at only some of the available binding sites on a molecular host (the virus capsid) […] Often the structures of key components and their interaction partners are known […] If the steric constraints of the interaction are known (Figure 6d–e), even ligands below the unconstrained detection limit should be detectable”).
Regarding claim(s) 5 and 18, Rickgauer as modified by Barth teaches the method of claim 1, where Rickgauer teaches further comprising producing a representation of a difference volume as a function of the template and the representation of the volume produced, the difference volume including elements representing the at least one fragment (Page 18, 4th Paragraph: “The 3D difference map comparing the experimental reconstruction to a model was generated in Diffmap. The real part of the electrostatic potential map of the DLP-VP1 complex used in this comparison [...] The map was then rotated to the expected orientation, and aligned with the reconstruction by 3D cross correlation”; and Page 18, 1st Paragraph: “The search for VP1 LOCs was performed by cross-correlating the image with a set of 60 templates generated using only the VP1 fragment of the structure […] and at the orientations expected).
Regarding claim(s) 6 and 19, Rickgauer as modified by Barth teaches the method of claim 1, where Rickgauer teaches wherein applying the probability metric to the similarity image comprises iteratively applying one or more probability metrics to one or more similarity images and producing one or more cumulative similarity images comprising positive detections (Page 18, 3rd Paragraph: “The searches for VP1 yielded a set of 2 x 3296 x 12 x 5 x 5 CCG values (Supplementary file 3), which represent five values (for the predicted pixel and the four closest pixels) for each of the five possible VP1 locations in each of the 12 five-fold vertices in each of the 3,296 particles using two templates (target and control) […] all potential VP1 locations for which the maximum across the pixel-neighborhood […] were counted as detected VP1s […] For each detected VP1 in the dataset (15,265 in total) […]; and Page 17, Precision-recall curves, 3rd Paragraph: “These templates were then whitened and cross-correlated with the whitened image. The resulting CCGs were then combined into a maximum intensity projection (MIP) and cross-correlated with a location reference image […] with subpixel resolution to the expected locations of all ASUs whose CCG included a value above 5.47 […]”).
Regarding claim(s) 7 and 20, Rickgauer as modified by Barth teaches the method of claim 1, where Rickgauer teaches wherein the one or more images are cryogenic electron microscopy images (Page 8, Protein background (experiments), 1st Paragraph: “To test whether single proteins can be detected in actual cryo-EM images of densely protein-packed biological samples, we analyzed images of rotavirus double-layered particles (DLPs) […]”).
Regarding claim(s) 8 and 21, Rickgauer as modified by Barth teaches the method of claim 1, where Rickgauer teaches wherein the resolution of the volume produced is higher than about 1/5 reciprocal Angstroms (Page 8, 2nd Paragraph: “In a simulation using the same parameters the SNR closely followed the experimental curve up to a resolution of 2.4 nm-1 beyond which it diverged upward to reach a value of 17.6 at 5.2 nm-1”).
Regarding claim(s) 9 and 22, Rickgauer as modified by Barth teaches the method of claim 1, where Rickgauer teaches wherein the template comprises a plurality of two-dimensional representations of the particle (Page 2, Detection of protein in isolation, 1st Paragraph: “By suitably varying the projection direction we can generate a set of two-dimensional templates that represent all possible electron distributions (for a given resolution) that this protein could produce in such an image”; and Page 17, Precision-recall curves, 3rd Paragraph: “we generated ASU templates at the 60 orientations obtained by expanding the particle’s orientation into a full icosahedrally symmetric set. These templates were then whitened and cross-correlated with the whitened image. The resulting CCGs were then combined into a maximum intensity projection (MIP) and cross-correlated with a location reference image”).
Regarding claim(s) 10 and 23, Rickgauer as modified by Barth teaches the method of claim 1, where Rickgauer teaches wherein the template is generated from at least one of a density map of the particle, a set of atomic coordinates of the particle, a predicted three-dimensional structure of the particle, or a combination thereof (Page 2, Detection of protein in isolation, 1st Paragraph: “The expectation value for the electron count in each pixel can be calculated directly from the known three-dimensional arrangement of atoms in the target and the optical parameters of the electron microscope […] By suitably varying the projection direction we can generate a set of two-dimensional templates that represent all possible electron distributions (for a given resolution) that this protein could produce in such an image”; and Page 15, Template generation, 1st Paragraph: “Templates were computed using the structural information in the target’s PDB coordinate file retrieved from the RCSB Protein Data Bank (RRID:SCR_012820)”).
Regarding claim(s) 11 and 24, Rickgauer as modified by Barth teaches the method of claim 1, where Rickgauer teaches wherein applying the template to the one or more images comprises performing at least one of pattern-recognition, rigid-body search, and machine learning (Page 2, Detection of proteins in isolation, 1st Paragraph: “By suitably varying the projection direction we can generate a set of two-dimensional templates that represent all possible electron distributions (for a given resolution) that this protein could produce in such an image […] Whether an image is likely to contain the target can be established by cross-correlating the image with that template”; and Page 17, Precision-recall curves, 3rd Paragraph: “These templates were then whitened and cross-correlated with the whitened image. The resulting CCGs were then combined into a maximum intensity projection (MIP) and cross-correlated with a location reference image […] with subpixel resolution to the expected locations of all ASUs whose CCG included a value above 5.47 […]”).
Claim(s) 4, 13, and 17 is/are rejected under 35 U.S.C. 103 as being unpatentable over Rickgauer et al (Single-protein detection in crowded molecular environments in cryo-EM images) in view of Barth (US 2023/0227534 A1), further in view of Saur et al (Fragment-based drug discovery using cryo-EM).
Regarding claim(s) 4 and 17, Rickgauer as modified by Barth teaches the method of claim 3, where Rickgauer teaches wherein the molecular interactions (Page 14, 4th Paragraph: “Detection of the rotavirus RNA polymerase and the mapping of the occupied binding sites inside the virus capsid (Figure 6d–e) illustrates how one can analyze partially stochastic protein assemblies, in which a ligand protein (here, VP1) binds at only some of the available binding sites on a molecular host (the virus capsid) […] Often the structures of key components and their interaction partners are known […] If the steric constraints of the interaction are known (Figure 6d–e), even ligands below the unconstrained detection limit should be detectable”).
Rickgauer and Barth fails to teach wherein the molecular interactions represented comprise representations of coordinated water molecules. However, Saur teaches wherein the molecular interactions represented comprise representations of coordinated water molecules (Figure 1; and Page 488, Left Col., 4th Paragraph: “Our cryo-EM structure shows a well-ordered and conserved network of water molecules, forming hydrogen bonds with both the ligand and the side chains lining the active site […]”).
Therefore, it would have been obvious to one of ordinary skill in the art to combine Rickgauer, Barth, and Saur before the effective filing date of the claimed invention. The motivation for this combination of references would have been to represent a well-ordered and conserved network of water molecules forming hydrogen bonds with both the ligand and the side chains lining the active site as part of the molecular interaction representation. This motivation for the combination of Rickgauer, Barth, and Saur is/are supported by KSR exemplary rationale (G) Some teaching, suggestion, or motivation in the prior art that would have led one of ordinary skill to modify the prior art reference or to combine prior art reference teachings to arrive at the claimed invention. MPEP 2141 (III).
Regarding claim(s) 13, Rickgauer as modified by Barth teaches a method of performing drug discovery, where Rickgauer teaches comprising:
imaging interactions of at least one particle and a plurality of fragments according to the method of claim 1 (Page 2, Detection of proteins in isolation, 1st Paragraph: “By suitably varying the projection direction we can generate a set of two-dimensional templates that represent all possible electron distributions (for a given resolution) that this protein could produce in such an image […] Whether an image is likely to contain the target can be established by cross-correlating the image with that template”; Page 18, 1st Paragraph: “The search for VP1 LOCs was performed by cross-correlating the image with a set of 60 templates generated using only the VP1 fragment of the structure […] and at the orientations expected”; and Page 18, 3rd Paragraph: “we generated a copy of the original image, padded it to 2048 x 2048 pixels, shifted it to position the associated ASU at the center pixel, and together with the expected orientation and defocus, incorporated it into a set that was then provided as input to a development version of Frealign (Grigorieff, 2007), which was used to calculate the reconstruction directly […]”).
Rickgauer and Barth fail to teach to detecting, from the representation of the volume produced, a binding interaction between the at least one particle and at least one of the plurality of fragments; and identifying the at least one of the plurality of fragments as a candidate drug fragment based on the binding interaction detected.
However, Saur teaches to detecting, from the representation of the volume produced, a binding interaction between the at least one particle and at least one of the plurality of fragments (Page 488, 3rd Col., 2nd Paragraph: “We performed a fragment screen of 68 fragments by adding a high concentration of a ligand to the protein before sample preparation for cryo-EM data collection […] Fragments are generally known to have weak interactions with proteins, and one of the benefits of structure-based fragment screening is to detect binding without knowing the specific affinity of the fragments to be screened”); and
identifying the at least one of the plurality of fragments as a candidate drug fragment based on the binding interaction detected (Page 488, 3rd Col., 2nd Paragraph: “We performed a fragment screen of 68 fragments by adding a high concentration of a ligand to the protein before sample preparation for cryo-EM data collection […] We present here two of the resulting co-complexes [L-threonine and Compound 5 (Cmp5); Table S1 in the supplemental information online], which highlight two of the main challenges that need to be considered for FBDD with cryo-EM, namely fragment size and structure resolution”).
Therefore, it would have been obvious to one of ordinary skill in the art to combine Rickgauer, Barth, and Saur before the effective filing date of the claimed invention. The motivation for this combination of references would have been to detect binding without knowing the specific affinity of the fragments to be screened in order to perform structure-based fragment screening for drug discovery. This motivation for the combination of Rickgauer, Barth, and Saur is/are supported by KSR exemplary rationale (G) Some teaching, suggestion, or motivation in the prior art that would have led one of ordinary skill to modify the prior art reference or to combine prior art reference teachings to arrive at the claimed invention. MPEP 2141 (III).
Claim(s) 12 is/are rejected under 35 U.S.C. 103 as being unpatentable over Rickgauer et al (Single-protein detection in crowded molecular environments in cryo-EM images) in view of Barth (US 2023/0227534 A1), further in view of Hendriksen et al (US 2021/0072170 A1).
Regarding claim(s) 12 and 25, Rickgauer as modified by Barth teaches the method of claim 1, but do not specifically teach wherein the sample is a sample that comprises the particle and the fragment without extraneous cellular material. However, Hendriksen teaches wherein the sample is a sample that comprises the particle and the fragment without extraneous cellular material (Paragraph [0020]: “The sample preparation steps may include purifying the sample, mixing the purified sample with buffers, and vitrifying the mixture […]”; Paragraph [0072]: “For example, a purified protein solution may be mixed with multiple buffer solutions to obtain samples with different sample conditions”; and Paragraph [0078]: “[…] different protein complexes of a target protein with a variety of ligand or compounds may be loaded and inspected using one sample inspection device”).
Therefore, it would have been obvious to one of ordinary skill in the art to combine Rickgauer, Barth and Hendriksen before the effective filing date of the claimed invention. The motivation for this combination of references would have been to achieve an optimal sample condition and improve sample quality for cryo-EM single particle analysis by purifying the sample, mixing the purified sample with buffers, and vitrifying the mixture. This motivation for the combination of Rickgauer, Barth and Hendriksen is/are supported by KSR exemplary rationale (G) Some teaching, suggestion, or motivation in the prior art that would have led one of ordinary skill to modify the prior art reference or to combine prior art reference teachings to arrive at the claimed invention. MPEP 2141 (III).
Relevant Prior Art Directed to State of Art
Vogel et al (US 2025/0180574 A1) are relevant prior art not applied in the rejection(s) above. Vogel discloses a method for determining a protein structure using cryo-electron microscopy, the method comprising: enabling a target protein to contain a tag; enabling a resulting target containing the tag to bind a scaffold protein to form a complex between the target protein and the scaffold protein; and performing single-particle imaging using the cryo-electron microscopy to determine a structure of the target protein in complex with the scaffold protein; wherein the scaffold protein is any one of streptavidin, avidin, or derivatives thereof; the tag is configured for selectively binding to the scaffold protein; and the tag is one selected from the group consisting of: a biotin tag, comprising a biotin; a biotinylated protein or polypeptide tag, comprising a protein sequence and a biotin covalently linked to the protein sequence; a Strep-tag; and a biotinylated or strep-tagged antibody, or antibody Fab fragment, or single-chain antibody.
Wu et al (US 2023/0093123 A1) are relevant prior art not applied in the rejection(s) above. XXX discloses a polypeptide composition or kit comprising at least one of: a) a first polypeptide comprising an antibody, antigen-binding portion thereof, or antibody reagent that specifically binds a target molecule; b) a second polypeptide comprising an antibody, antigen-binding portion thereof, or antibody reagent that specifically binds the first polypeptide; and c) a third polypeptide comprising: i) at least one maltose binding protein (MBP) domain; ii) at least one domain of Protein A; and iii) at least one Protein G, Protein L, or Protein M domain.
Conclusion
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/JONGBONG NAH/Examiner, Art Unit 2674
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