Construction of diverse synthetic peptide and polypeptide libraries
The present invention concerns the design and construction of diverse peptide and polypeptide libraries. In particular, the invention concerns methods of analytical database design for creating datasets using multiple relevant parameters as filters, and methods for generating sequence diversity by directed multisyntheses oligonucleotide synthesis. The present methods enable the reduction of large complex annotated databases to simpler datasets of related sequences, based upon relevant single or multiple key parameters that can be individually directly defined. The methods further enable the creation of diverse libraries based on this approach, using multisynthetic collections of discrete and degenerate oligonucleotides to capture the diverse collection of sequences, or portions thereof.
1. A method of making a library of antibody heavy or light chains, comprising the steps of
(a) aligning a plurality of antibody heavy or light chain sequences comprising one or more CDR sequence motifs;
(b) creating a first dataset by applying a predetermined combination of two or more filters based on parameters of said antibody heavy or light chain sequences;
(c) analyzing said first dataset for positional amino acid usage frequency within at least one of said CDR sequence motifs;
(d) creating a second dataset characterized by a minimum threshold amino acid usage frequency at one or more amino acid positions within said CDR sequence motif; and
(e) synthesizing an antibody heavy or light chain library designed with the aid of the first and second datasets identified, by generating a discrete number of defined or degenerate oligonucleotides such that only defined amino acids are generated.
2. The method of claim 1 wherein said sequence motif is a CDR sequence selected from the group consisting of CDR1, CDR2 and CDR3 sequences.
3. The method of claim 1 wherein in step (b) said predetermined combination of filters is selected from the group consisting of: (1) the isotype of said antibody heavy or light chain; (2) the length of one or more CDR1, CDR2 and CDR3 sequences; (3) the presence of one or more predetermined amino acid residues at one or more predetermined positions within one or more CDR1, CDR2 and CDR3 sequences; (4) type of framework; (5) antigen to which said antibody binds; (6) affinity of said antibody; and (7) positional amino acid residues outside said CDR sequences.
4. The method of claim 3 wherein at least one of the antibody heavy and/or light chain CDR1, CDR2 and CDR3 sequences is size matched.
5. The method of claim 4 wherein an additional filter is the isotype of said antibody heavy and/or light chain sequences.
6. The method of claim 1 wherein said positional amino acid usage frequency is between at least about 3% and at least about 15%.
7. The method of claim 1 wherein the same positional amino acid usage frequency characterizes each amino acid within said CDR sequence.
8. The method of claim 1 wherein the positional amino acid usage frequencies differ at least two amino acid residues within said CDR sequence.
9. The method of claim 3 wherein said predetermined combination of filters includes the type of framework.
10. The method of claim 1 wherein both antibody heavy and light chain sequences are analyzed, and the antibody heavy chain sequences are paired to predetermined antibody light chain characteristics, or the antibody light chain sequences are paired to predetermined antibody heavy chain characteristics.
11. The method of claim 1 wherein said related antibody sequences are from at least one functional antibody.
12. The method of claim 1 wherein one of said filters applied in step (b) is the germline sequence most similar to the framework sequence of the heavy and/or light chain of said functional antibody.
13. The method of claim 1 wherein said functional antibody binds to a polypeptide selected from the group consisting of cell surface and soluble receptors, cytokines, growth factors, enzymes; proteases; and hormones.
14. The method of claim 1 wherein in step (d) a minimum threshold amino acid usage frequency is assigned to at least the majority of amino acid positions within said shared sequence motif.
15. The method of claim 1 wherein said minimum threshold amino acid usage frequency is set to provide a minimum sum amino acid usage for the majority of amino acid positions within said shared sequence motif.
16. The method of claim 1 wherein said minimum threshold amino acid usage frequency is set to provide a minimum sum amino acid usage for all amino acid positions within said shared sequence motif.
17. The method of claim 15 wherein said minimum sum amino acid usage is between at least about 60% and at least about 90%.
18. The method of claim 1 wherein said library is expressed using a prokaryotic or eukaryotic expression system.
19. The method of claim 1 wherein said library is expressed and displayed using a phagemid display, mRNA display, microbial cell display, mammalian cell display, microbead display technique, antibody array, or display based on protein-DNA linkage.
20. The method of claim 1 wherein said library is screened for one or more chemical and/or biological properties of its members.
21. The method of claim 20 wherein said biological property is selected from the group consisting of half-life, potency, efficacy, binding affinity, and immunogenicity.