De novo antibody design
Computer-implemented methods of designing an antibody that will bind to a target epitope are disclosed. In one arrangement, the method comprises identifying one or more hotspot residues that will each bind to a corresponding one of one or more hotspot sites on the target epitope. Candidate antibody structures are selected from a database such that characteristic atoms within the antibody structure and hotspot characteristic atoms can be superimposed computationally with an averaged spatial deviation less than a predetermined threshold. A designed antibody is generated by replacing matching residues with different residues such that a predicted affinity is increased.
1. A computer-implemented method, comprising:
(a) generating a residue-based triplet hash data set for each of the residue triplets from a cognate protein binder, the residues known to bind to a target epitope, each cognate protein binder residue comprising a cognate protein binder residue sub-structure comprising sub-structure characteristic atoms, the hash key set constructed using the data on the special position of by nine vertexes corresponding to the positions of nine characteristic atoms of the three residues and nine edges corresponding to the edges from the three triangles
wherein the characteristic atoms of the cognate protein binder residue sub-structure comprise any three of the following: the alpha carbon, the backbone carbon atom derived from the carboxyl group, the backbone nitrogen, the backbone oxygen, and the beta carbon of the side chain;
(b) generating a data set from a 3D database of antibody structures, the dataset comprising triplet hash data on any complementarity-determining region (CDR) residues triplet generated in the same way and the same types of atoms as in step (a);
(c) using the data set obtained in step (b) to computationally select one or more candidate antibody structures from the 3D database of antibody structures by identifying antibody scaffold triplet structures which are able to accommodate the three cognate protein binder residues in the geometrically matched positions in CDRs, by comparing the respective triplet hash key values, each candidate antibody structure comprising 3D spatial data on a first matching residue, a second matching residue and a third matching residue each comprising a matching residue sub-structure comprising 3 matching residue sub-structure characteristic atoms; and
(d) calculating a first set of distances representing separations between all possible pairings between characteristic atoms of the same type in different sub-structures of the cognate protein binder residues;
calculating a second set of distances representing separations between all possible pairings between characteristic atoms of the same type in different sub-structures of the matching residues; and
comparing the first set of distances to the second set of distances, and selecting one or more candidate antibody structures wherein the difference in the distances is within a predetermined separation threshold;
(e) outputting the one or more selected candidate antibody structures in a format suitable for use in a process for manufacturing the one or more selected candidate antibodies; and
(f) manufacturing the one or more selected candidate antibodies using, for each of the selected candidate antibodies, the 3 matching residue sub-structure characteristic atoms of each of the matching residue sub-structures for each of the first matching residue, the second matching residue, and the third matching residue.
2. The method of claim 1 , wherein the predetermined threshold is 2.0 Angstroms.
3. The method of claim 1 , further comprising replacing in 3D coordinates the matching residues backbone atoms 3D coordinates with the corresponding 3D coordinates of the corresponding cognate binder residue's backbone atoms.
4. The method of claim 1 , wherein the three substructure characteristic atoms are the alpha carbon atom, the backbone carbon atom, and the backbone nitrogen atom.
5. The method of claim 1 , further comprising iteratively swapping 3D coordinates of the atoms each of one or more of the CDR loops of the candidate antibody structure with 3D coordinates of the atoms of CDR loops from a database of CDR loops.
6. A non-transitory computer readable medium, comprising computer readable instructions which, when executed by a computer, cause the computer to carry out the method of claim 1 .
7. The method of claim 1 , further comprising detecting geometrical clashing by comparing 3D coordinates of the matching residues, where one or more atoms are calculated to occupy positions that are closer together than is physically possible, between one or more atoms in the candidate antibody structure when bound to the target epitope and one or more atoms in the target epitope.
8. The method of claim 7 , further comprising determining whether a detected geometrical clash is with a side chain of a residue of the candidate antibody structure and, if so, replacing the 3D coordinates of the atoms of the side chain by 3D coordinates of atoms of a side chain of another type of amino acid.
9. The method of claim 8 , wherein the 3D coordinates of the atoms of the side chain are replaced by 3D coordinates of atoms of an alanine side chain, a glycine side chain, a valine side chain, a serine side chain, a threonine side chain, or homo-alanine side chain.
10. The method of claim 7 , further comprising calculating presence of geometrical clash is with a backbone or beta carbon atoms of any candidate antibody residue and, if so, discarding the selected candidate antibody structure and repeating the determination for a different candidate antibody structure selected from the database.
11. The method of claim 1 , wherein the method comprises additional step of generation of an index key lookup table comprising residue triplet's information for the residues of a cognate protein binder and the CDR residues of antibodies, the lookup table comprising each vertex residue types and atomic coordinates data.
12. The method of claim 1 , further comprising updating one of the candidate antibody 3D structure data for one or more of the matching residues that is an amino-acid residue of a different type compared to the cognate protein binder amino-acid residue type, the updating comprising replacing the 3D atomic coordinates the matching residue with 3D atomic coordinates of a different residue such that a calculated affinity between the resulting 3D antibody structure and the target epitope is higher than a calculated affinity between the candidate antibody structure and the target epitope.
13. The method of claim 1 , wherein manufacturing the one or more selected candidate antibodies comprises chemically synthesizing genes encoding variable regions of the candidate antibodies.
14. A method, comprising:
identifying one or more candidate antibody structures that will bind to a target epitope by:
(a) generating a residue-based triplet hash data set for each of the residue triplets from a cognate protein binder, the residues known to bind to the target epitope, each cognate protein binder residue comprising a cognate protein binder residue sub-structure comprising sub-structure characteristic atoms, the hash key set constructed using the data on the special position of by nine vertexes corresponding to the positions of nine characteristic atoms of the three residues and nine edges corresponding to the edges from the three triangles;
wherein the characteristic atoms of the cognate protein binder residue sub-structure comprise any three of the following: the alpha carbon, the backbone carbon atom derived from the carboxyl group, the backbone nitrogen, the backbone oxygen, and the beta carbon of the side chain;
(b) generating a data set from a 3D database of antibody structures, the dataset comprising triplet hash data on any complementarity-determining region (CDR) residues triplet generated in the same way and the same types of atoms as in step (a);
(c) using the data set obtained in step (b) to computationally select one or more candidate antibody structures from the 3D database of antibody structures by identifying antibody scaffold triplet structures which are able to accommodate the three cognate protein binder residues in the geometrically matched positions in CDRs, by comparing the respective triplet hash key values, each candidate antibody structure comprising 3D spatial data on a first matching residue, a second matching residue and a third matching residue each comprising a matching residue sub-structure comprising 3 matching residue sub-structure characteristic atoms; and
(d) calculating a first set of distances representing separations between all possible pairings between characteristic atoms of the same type in different sub-structures of the cognate protein binder residues;
calculating a second set of distances representing separations between all possible pairings between characteristic atoms of the same type in different sub-structures of the matching residues; and
comparing the first set of distances to the second set of distances, and selecting one or more candidate antibody structures wherein the difference in the distances is within a predetermined separation threshold;
manufacturing an antibody according to the identified one or more candidate antibody structures; and
applying a therapy using the manufactured antibody, wherein applying the therapy comprises:
the manufactured antibody achieving a desired mechanism of action based on the target epitope;
the manufactured antibody binding with high affinity to the target epitope; and
the manufactured antibody blocking cognate protein-protein interactions or capturing predicted transition states.
15. The method of claim 14 , wherein applying the therapy further comprises the manufactured antibody binding to a BTB-Kelch substrate adaptor protein.
16. The method of claim 15 , wherein the BTB-Kelch substrate adaptor protein regulates steady-state levels of a bZIP transcription factor.
17. The method of claim 16 , wherein the BTB-Kelch substrate adaptor protein regulates steady-state levels of a bZIP transcription factor in response to oxidative stress.
18. The method of claim 14 , wherein the manufactured antibody binding with high affinity to the target epitope comprises the manufactured antibody binding with an affinity of at least the low-to-mid nanomolar range.
19. The method of claim 14 , wherein applying the therapy further comprises the manufactured antibody targeting an intracellular protein.
20. The method of claim 14 , wherein applying the therapy further comprises the manufactured antibody affecting immune homeostastis.
21. The method of claim 14 , wherein applying the therapy further comprises the manufactured antibody affecting fibrosis regulation.
22. The method of claim 13 , wherein manufacturing the one or more selected candidate antibodies further comprises transfecting the chemically synthesized genes into a host cell.