Nucleome Therapeutics has announced that the US Patent & Trademark Office (USPTO) has granted US patent number US12,674,197 entitled "Process for producing a chromatin conformation capture (3C) library."
The new patent covers the technology that underpins Nucleome's 3D genomics platform: Micro Capture-C (MCC).
The approach is an advanced 3D genomics and chromatin conformation capture method that maps reproducible interactions between specific regions of the genome.
Developed by researchers at Oxford University, it achieves unprecedented base-pair to sub-nucleosomal resolution using a sequence-agnostic nuclease to digest chromatin, followed by proximity ligation and deep sequencing of the ligation junctions.
Unlike conventional techniques, MCC pinpoints exact molecular contacts, including identifying transcription factor binding sites and enhancer-promoter networks.
MCC is exclusively licensed by Oxford University to Nucleome.
Most disease-related genetic variations are single-nucleotide polymorphisms (SNPs) in the largely unexplored non-coding genome. These SNPs regulate gene expression and protein levels through three-dimensional interactions that cannot be identified by DNA sequence alone.
The advanced capabilities of MCC enable Nucleome to decode the genetic basis of non-coding regions in human diseases, leading to new targeted therapies.
Nucleome said that the firm's approach can be applied to the "vast repositories of variants" that cover most diseases. The company has so far focused on discovering novel antibody targets for inflammatory diseases and is developing a pipeline of first-in-class medicines to target the inflammatory diseases identified by MCC.
Its lead programme, NTP464, a first-in-class monoclonal antibody agonist programme for resolving inflammation, has already initiated IND-enabling studies.
Dr Mark Bodmer, CEO of Nucleome, said: "Most drugs fail in development because we lack enough understanding of the molecular biology of human disease."
MCC is the core of a lab [and] AI capability that can finally unlock the mystery of how non-coding genetic variations can guide the selection of drug targets with a high probability of clinical success.
