PATENT CLAIM ANALYSIS

Application Number: 16235096
Application Type: Utility
Filing Date: 2018-12
Publication Date: 2019-09
Patent Classification: ["506", "009000"]

Abstract:
Disclosed herein are methods, compositions, probes, assays and kits for identifying a lipid binding protein as a drug binding target. Also disclosed herein are methods, compositions, and probes for mapping a ligand binding site on a lipid binding protein, identification of lipid binding proteins, generating drug-lipid binding protein profiles, high throughput drug screening, and identification of drugs as potential lipid binding protein ligands.

Claim (Index 30):
A process of generating a lipid probe-protein composition, comprising:\n contacting a sample with a lipid probe; and treating the sample comprising the lipid probe by a photoreactive means to generate the lipid probe-protein composition, wherein the treating time is from about 5 minutes to about 1 hour; and wherein the lipid probe is a lipid probe of Formula (I): wherein: A is C 16 -C 20 alkyl or C 16 -C 20 alkenyl; D is \u2014OH, \u2014NH 2 , \u2014NHR 7 , or \u2014OR;\n R 7  is C 1 -C 4 alkyl, (C 1 -C 5 alkyl)OH, or (C 1 -C 5 )SO 3 M; \n R 8  is (CH 2 OH)n; \n M is monovalent or divalent cation; \n n is 1, 2, or 3; \n PG is a photoreactive group; and AH is an affinity handle; and wherein PG is attached to A or D and AH is attached to A or D.

Metadata:
- Claim Count in Document: 11.0
- Percentile: 98.0
- Lexical Diversity: 1.94737
- Patent Class: 506.0
- Transitional Phrase Type: open
- Component Type: 1
- Foreign Priority: False
- Related Applications: ['15080767', '15331745', '13568898', '12816207', '11085792']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.5806268799307992
- 35 USC 102 Novelty (BERT): 0.5895202564492895
- Combined Prediction Score: 0.5815162175826483
- Mean Citation Score: 294.664672
- Max Citation Score: 615.8741
- Similarity Product: 398.3330767600178

Labels:
- Claim Label 101: 1
- Claim Label 102: 0
- Claim Label 103: 0
- Claim Label 112: 1
- Combined Label: 0
- Label 101 Adjusted: 1

Dataset: test