Abstract
There are more amino acid permutations within a 40-residue sequence than atoms on Earth. This vast chemical search space hinders the use of human learning to design functional polymers. Here we couple supervised and unsupervised deep learning with high-throughput experimentation to drive the design of high-activity, novel sequences reaching 10 kDa that deliver antisense oligonucleotides to the nucleus of cells. The models, in which natural and unnatural residues are represented as topological fingerprints, decipher and visualize sequence-activity predictions. The new variants boost antisense activity by 50-fold, are effective in animals, are nontoxic, and can also deliver proteins into the cytosol. Machine learning can discover functional polymers that enhance cellular uptake of biotherapeutics, with significant implications toward developing therapies for currently untreatable diseases.
One sentence summary Deep learning generates de novo large functional abiotic polymers that deliver antisense oligonucleotides to the nucleus.
Competing Interest Statement
Bradley L. Pentelute is a co-founder of Amide Technologies and Resolute Bio. Both companies focus on the development of protein and peptide therapeutics. The following authors are inventors on patents and patent applications related to the technology described: Justin M. Wolfe, Colin M. Fadzen and Bradley L. Pentelute are co-inventors on patents WO 2020028254A1 (February 6, 2020), WO2019178479A1 (September 19, 2019), WO2019079386A1 (April 25, 2019), and WO2019079367A1 (April 24, 2019), describing trimeric peptides for antisense delivery, chimeric peptides for antisense delivery, cell-penetrating peptides for antisense delivery, and bicyclic peptide oligonucleotide conjugates, respectively. MIT and Sarepta Therapeutics have filed a provisional patent application related to the composition of materials described in this work.
