Protein based tumor necrosis factor-receptor variants for the treatment of TNF related disorders Number:7,144,987 from the United States Patent and Trademark Office (PTO) owispatent The invention relates to novel proteins with TNF-receptor antagonist activity and nucleic acids encoding these proteins. The invention further relates to TNF-receptor proteins with reduced immunogenicity and the use of these novel proteins in the treatment of TNF related disorders.<H disorders, treatment, Protein, based, t, 7144987.html, Patent, pto, 7144987

Title: Protein based tumor necrosis factor-receptor variants for the treatment of TNF related disorders

Abstract: The invention relates to novel proteins with TNF-receptor antagonist activity and nucleic acids encoding these proteins. The invention further relates to TNF-receptor proteins with reduced immunogenicity and the use of these novel proteins in the treatment of TNF related disorders.

Patent Number: 7,144,987 Issued on 12/05/2006 to Chirino, et al.

Inventors: Chirino; Arthur J. (Camarillo, CA), Luo; Peizhi (Arcadia, CA), McDonnell; Peter Colon (Thousand Oaks, CA), Muchhal; Umesh (West Covina, CA), Tansey; Malu Lourdes (Coppell, TX)
Assignee: Xencor (Monrovia, CA)

Appl. No.: 10/336,242

Filed: January 3, 2003

Related U.S. Patent Documents


Application Number	Filing Date	Patent Number	Issue Date
10262630	Sep., 2002
09981289	Oct., 2001	7101974
09945150	Aug., 2001
09798789	Mar., 2001	7056695
60186427	Mar., 2000
60345772	Jan., 2002
60415545	Oct., 2002

Current U.S. Class: 530/351 ; 435/335; 435/69.5; 435/7.1; 530/350

Current International Class: C07K 17/00 (20060101); C07K 14/52 (20060101); C12N 15/00 (20060101)

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5395760	March 1995	Smith et al.
5478925	December 1995	Wallach et al.
5512544	April 1996	Wallach et al.
5605690	February 1997	Jacobs et al.
5610279	March 1997	Brockhaus et al.
5695953	December 1997	Wallach et al.
5712155	January 1998	Smith et al.
5808029	September 1998	Brockhaus et al.
5811261	September 1998	Wallach et al.
5925548	July 1999	Beutler et al.
5945397	August 1999	Smith et al.
5981701	November 1999	Wallach et al.
6271346	August 2001	Hauptmann et al.
6433158	August 2002	Pettit

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03-133382	Jun., 1991	JP
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10-191986	Jul., 1998	JP
WO 92/07076	Apr., 1992	WO
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Primary Examiner: Saoud; Christine J.
Assistant Examiner: Seharaseyon; Jegatheesan
Attorney, Agent or Firm: Dorsey & Whitney Silva; Robin M. Worrall; Timothy A.

Parent Case Text

This application claims the benefit of the filing date of U.S. Ser. No. 60/345,772, filed Jan. 4, 2002 and U.S. Ser. No. 60/415,545, filed Oct. 1, 2002, and is a continuation in part of U.S. Ser. No. 10/262,630, filed Sep. 30, 2002; U.S. Ser. No. 09/981,289, filed Oct. 15, 2001 now U.S. Pat. No. 7,101,974; U.S. Ser. No. 09/945,150, filed Aug. 31, 2001, now abandoned; and U.S. Ser. No. 09/798,789, filed Mar. 2, 2001 now U.S. Pat. No. 7,056,695, which claims the benefit of the filing date of U.S. Ser. No. 60/186,427, filed Mar. 2, 2000.

Claims

We claim:

1. An isolated Tumor Necrosis Factor (TNF)-receptor protein comprising an amino acid sequence comprising at least one amino acid substitution as compared to amino acids 15 138 of SEQ ID NO: 1, wherein said amino acid substitution is selected from the group consisting of positions: 65, 66, 67, 69, 72, 75, 77, 78, 79, 80, 105, 107, 108, 111 and 113.

2. An isolated TNF-receptor protein according to claim 1, wherein said TNF-receptor protein has from 2 to 5 amino acid substitutions as compared to said amino acids 15 138 of SEQ ID NO: 1.

3. A TNF-receptor protein according to claim 1, wherein said TNF-receptor protein has enhanced antagonistic properties as compared to SEQ ID NO: 1.

4. A TNF-receptor protein according to claims 1, 2 or 3 wherein said TNF-receptor protein has reduced immunogenicity.

5. A TNF-receptor protein according to claim 1, wherein said substitution is selected from the group consisting of N65E, N65F, N65V, H66F, H66K, H66R, H66W, L67F, L67K, H69A, H69D, H69E, H69F, H69K, H69R, H69T, H69Y, H69Q, S72A, S72L, S72G, S72N, S72R, S72Q, K75Q, K75R, R77D, R77K, R77L, R77Q, R77V, K78D, K78R, E79A, E79H, E79K, E79S, E79T, E79W, M80A, M80D, M80E, M80L, H105K, W107A, W107B, W107D, W107E, W107F and combinations thereof.

6. A TNF-receptor protein according to claim 5, wherein said substitutions are selected from the group consisting of: N65F, H66F, H69A, H69D, H69F, H69Y, H69Q, K75R, K78D, M80E, H105K, L67F, S72Q and combinations thereof.

7. A TNF-receptor protein according to claim 6, wherein said TNF-receptor protein is a double point variant having substitutions selected from the group consisting of H66F and H69A, H66F and H69Y, H66F and H69D, H66F and H69Q, H66F and K75R, K75R and H69A, K75R and H69D, K75R and H69Q, and K75R and H69Y.

8. A TNF-receptor protein according to claim 7, wherein said double point variant comprises H66F and either H69A or H69D.

9. A TNF-receptor protein according to claim 8, wherein said double point variant proteins possess reduced immunogenicity.

10. A TNF-receptor protein according to claims 1, wherein said TNF-receptor protein is PEGylated.

11. A TNF-receptor protein according to claim 1, wherein the C-terminal leucine of said amino acids 15 138 of SEQ ID NO: 1 is deleted.

12. A TNF-receptor protein according to claims 1, 2, or 3, wherein two or more TNF-receptor variants are covalently linked via disulfide bonds.

13. A TNF-receptor protein according to claims 1, 2, or 3, wherein two or more TNF-receptor variants are covalently linked via chemical cross linking.

14. A TNF-receptor protein according to claims 1, 2, or 3, wherein two or more TNF-receptor variants are covalently linked by a linker peptide.

15. A TNF-receptor protein according to claim 14, wherein said linker peptide is a sequence of at least one and not more than about 30 amino acid residues.

16. A TNF-receptor protein according to claim 14, wherein said linker peptide is a sequence of at least 5 and not more than about 20 amino acid residues.

17. A TNF-receptor protein according to claim 16, wherein said linker peptide is a sequence of at least 10 and not more than about 15 amino acid residues.

18. A TNF-receptor protein according to claims 14, wherein the linker peptide comprises one or more of the following amino acid residues: Gly, Ser, Ala, or Thr.

19. A pharmaceutical composition comprising a TNF-receptor protein according to claim 1 and a pharmaceutical carrier.

Description

FIELD OF THE INVENTION

The invention relates to novel proteins with TNF-receptor antagonist activity and nucleic acids encoding these proteins. The invention further relates to novel TNF-receptor proteins with reduced immunogenicity and the use of these novel proteins in the treatment of TNF related disorders, such as autoimmune and inflammatory conditions.

BACKGROUND OF THE INVENTION

Tumor Necrosis Factor (TNF) was originally discovered as a naturally occurring secreted protein with potent cytotoxic activity on tumor cells (Carswell, E. A., et al. (1075) PNAS, 72:3666 3670; Old, L. J. (1985) Science, 230:630 632; and Beutler, B. et al. (1985) Nature, 316:552 554). TNF exerts its biological effects through interaction with high-affinity cell surface receptors which trigger specific cellular responses. Two distinct membrane TNF-receptors have been cloned and characterized. These are a 55 kDa species, designated p55 TNF-R1 and a 75 kDa species designated p75 TNF-R2 (Loetscher, H. Y. et al. (1990), Cell 61:351 360; Schall, T. J. et al. (1990), Cell 61:361; Smith, C. A. et al. (1990), Science 248:1019; Corcoran, A. E., et al., (1994) Eur. J. Biochem., 223:831 840).

Expression of TNFR1 can be demonstrated on almost every mammalian cell while TNFR2 expression is largely limited to cells of the immune system and endothelial cells. Each receptor elicits a distinct signal: the intracellular portion of TNFR1 contains a "death domain" which initiates the apoptotic pathway and NFkB activation when triggered (Tartaglia, L. A. et al. (1991) PNAS 88:9292 10296; Tartaglia, L. A. et al. (1993), Cell 74: 845 853). The role of TNFR2 is less clear as it has no direct apoptotic signaling but can activate NFkB, resulting in transcriptional activation of genes required for the inflammatory and immune response.

The two TNF receptors exhibit 28% similarity at the amino acid level. This is confined to the extracellular domain and consists of four repeating cysteine-rich motifs, each of approximately 40 amino acids. Each motif contains four to six cysteines in conserved positions. Dayhoff analysis shows the greatest intersubunit similarity among the first three repeats which contains the ligand binding section. This characteristic structure is shared with a number of other receptors and cell surface molecules, which comprise the TNF-R/nerve growth factor receptor superfamily (Corcoran, A. E., et al., (1994) Eur. J. Biochem., 223:831 840).

Crystallographic studies of TNF-alpha and the structurally related cytokine, lymphotoxin or TNF-beta (LT) have shown that both cytokines exist as homotrimers, with subunits packed edge to edge in a threefold symmetry (Hakoshima, T. and Tomita, K. (1988) J. Mol. Biol. 201:455 457; Jones, E. Y. et al. (1989) Nature 338:225 228; Eck, M. J. et al. (1992) J. Biol. Chem. 267:2119 2122).

TNF signaling is initiated by receptor clustering, either by the trivalent ligand TNF or by cross-linking monoclonal antibodies (Vandevoorde, V., et al., (1997) J. Cell Biol., 137:1627 1638). Structurally, neither TNF or LT reflect the repeating pattern of the their receptors. Each monomer is cone shaped and contains two hydrophilic loops on opposite sides of the base of the cone. The crystal structure determination of a p55 soluble TNF-R/LT complex has confirmed the hypothesis that loops from adjacent monomers join together to form a groove between monomers and that TNF-R binds in these grooves (Banner, E. W. et al. (1993) Cell, 73:431 435).

TNF plays an important role in regulating inflammation, cellular immune response, and host defense. Conversely in diseases such as rheumatoid arthritis, osteoarthritis, psoriasis, Crohn's disease, inflammatory bowel disease and other chronic disorders of the immune system, excessive levels of TNF play a role in the pathophysiology. Indeed, blocking TNF can halt disease progression and

has led to the search for antagonists of TNF.

Several strategies at blocking TNF signaling can be employed: inhibiting TNF biosynthesis, inhibiting TNF secretion or shedding, or blocking the interaction of TNF with its receptors. A natural mechanism to down regulate TNF exists whereby the extra-cellular portion of the TNF receptor is enzymatically cleaved resulting in a freely circulating TNF binding protein or "soluble receptor" which retains its affinity for TNF but neutralizes its ability to signal through its cell surface receptor (Engelmann, H. et al. (1990) J. Biol. Chem. 265:1531 1536; Olsson, et al. (1989) Eur. J. Haematol. 42:270 275; Seckinger et al. (1990) Eur. J. Immunol. 20: 1167 1174). In cases such as autoimmune disease and chronic inflammation excessively high levels of TNF overwhelms the ability to self-regulate.

The therapeutic use of soluble TNF receptors has been proven to be an effective way to block TNF signaling. For example, ENBREL.RTM., a soluble bivalent form of TNFR2 fused to a human immunoglobulin fragment (Fc) is used for the treatment of rheumatoid arthritis and psoriasis. Soluble TNFR1-Fc has also been shown to effectively block TNF-mediated effects in animal models but has not been approved for use in humans (Lenercept) due to immunogenicity concerns (Christen, U. et al Human Immunol. 60:774 790, 1999).

While protein engineering techniques resulting in loss-of-function (i.e. random mutagenesis) have defined regions of TNF-TNFR interaction, no successful gain-of-function has been engineered into soluble TNFR. That is, there are no known designs of a less immunogenic soluble TNFR1 protein with an enhanced ability (relative to wild-type) to block TNF-mediated effects.

Therefore, a need still exists to develop more potent, less immunogenic TNF-receptor antagonists for use as therapeutic agents. Accordingly, it is an object of the invention to provide proteins with TNF-receptor antagonist activity and nucleic acids encoding these proteins for the treatment of TNF related disorders.

SUMMARY OF THE INVENTION

In accordance with the objects outlined above, the present invention provides non-naturally occurring variant TNF-receptor proteins (e.g. proteins not found in nature) comprising amino acid sequences with at least one non-conservative amino acid change compared to the wild type TNF-receptor proteins.

Preferred embodiments utilize variant TNF-receptor proteins that interact with the wild type TNF to inactivate receptor signaling.

Other embodiments include TNF-receptor proteins that have enhanced antagonistic properties as compared to wild type TNF-receptors.

Preferably, variant TNF-receptor proteins with 1, 2, 3, 4, and 5 amino acid changes are used as compared to wild type TNF-receptor protein. In a preferred embodiment, at least one of these changes is non-conservative. More preferably, these changes are selected from positions 65, 66, 67, 69, 72, 75, 77, 78, 79, 80, 105, 107, 108, 111 and 113.

In an additional aspect, the non-naturally occurring variant TNF-receptor proteins have substitutions selected from the group of substitutions consisting of N65E, N65F, N65V, H66F, H66K, H66R, H66W, L67F, L67K, H69A, H69D, H69E, H69F, H69K, H69R, H69T, H69Y, H69Q, S72A, S72L, S72G, S72N, S72R, S720, K75Q, K75R, R77D, R77K, R77L, R77Q, R77V, K78D, K78R, E79A, E79H, E79K, E79S, E79T, E79W, M80A, M80D, M80E, M80L, H105K, W107A, W107B, W107D, W107E, W107F, W107K, W107Q, W107T, S108H, S108T, S108W, L111E, L111K, L111Q, L111R, Q113F, Q1131, Q113K, Q113R, and Q113Y and combinations thereof.

Another aspect provides a non-naturally occurring TNF-receptor molecule that has reduced immunogenicity. Preferred variants for reduced immunogenicity include changes at positions 66, 69 and 75. More specifically, the TNF-receptor variants that are preferred include H69A, H69D, H69Q, K75R and H66F and H69D. The variant H69D and the double variant H69D+H.sub.66F are most preferred.

In a further embodiment, the TNF-receptor molecule may be chemically modified. In addition, portions of the N- or C-termini may deleted. In an additional aspect, the two or more receptor interaction domains of the naturally occurring TNF-receptor or the TNF-receptor variant proteins may be covalently linked by a linker peptide or by other means.

In a further aspect, the invention provides recombinant nucleic acids encoding the non-naturally occurring variant TNF-receptor proteins, expression vectors, and host cells.

In an additional aspect, the invention provides methods of producing a non-naturally occurring variant TNF-receptor protein comprising culturing the host cell of the invention under conditions suitable for expression of the nucleic acid. In a further aspect, the invention provides pharmaceutical compositions comprising a variant TNF-receptor protein of the invention and a pharmaceutical carrier.

In a further aspect, the invention provides methods for treating an TNF related disorder comprising administering a variant TNF-receptor protein of the invention to a patient in need of said treatment.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1A depicts the structure of the p55 TNF-R extra-cellular domain. The darker appearing regions represent residues required for contact with TNF-receptor. FIG. 1B depicts the sequence of the p55 TNF-R extra-cellular domain used as the starting structure in the present invention--a flag tagged truncated soluble TNF-R. The sequence depicted in FIG. 1B differs from the wild type p55TNF-R sequence in that the ligand binding region, which is composed of the first 3 cysteine rich domains (the 4.sup.th domain is omitted), is C-terminally fused to a flag sequence. The initiator methionine and the signal peptide are from wild-type gene (the signal peptide is deleted as well as the N-terminal sequence (IYPSGVIG)). As shown in FIG. 1B, a 14 amino acid deletion was engineered between residues -1 and 15 (LVPHLGDREKRDSV). The initial leucine residue of this section corresponds to the first residue of the crystallized structure and is considered residue 1 for the TNF-R starting point molecule of the present invention.

FIGS. 2A M are graphical representations of percent inhibition of apoptosis of TNF-induced capase-3 activity by TNFR1 variants of the present invention v. wild type TNFR1 (R&D Systems, Inc.).

DETAILED DESCRIPTION OF THE INVENTION

The present invention is directed to novel proteins and nucleic acids possessing TNF-receptor antagonist activity. The proteins may be preferably generated using PDA.TM. technology previously described in WO98/47089 and U.S. Ser. Nos. 09/058,459, 09/127,926, 60/104,612, 60/158,700, 09/419,351, 60/181,630, 60/186,904, 09/419,351, 09/782,004 and 09/927,790, 60/347,772, and 10/218,102, all of which are expressly incorporated by reference in their entirety. In general, these applications describe a variety of computational modeling systems that allow the generation of extremely stable proteins. In this way, variants of TNF-R proteins are generated that act as antagonists for wild type TNF. Variant TNF-R proteins may be generated from wild type TNF-receptor, p55 TNF-R and p75 TNF-R proteins, with preferred embodiments including variant TNF-receptor proteins, more preferred is the p55 TNF-R.

Generally, there are a variety of computational methods that can be used to generate a library of primary variant sequences. In a preferred embodiment, sequence-based methods are used. Other models for assessing the relative energies of sequences with high precision include Warshel, Computer Modeling of Chemical Reactions in Enzymes and Solutions, Wiley & Sons, New York, (1991), as well as the models identified in U.S. Ser. No. 10/218,102, filed Aug. 12, 2002, all hereby expressly incorporated by reference. Similarly, molecular dynamics calculations can be used to computationally screen sequences by individually calculating mutant sequence scores and compiling a list.

In a preferred embodiment, residue pair potentials can be used to score sequences (Miyazawa et al., Macromolecules 18(3):534 552 (1985), expressly incorporated by reference) during computational screening.

In a preferred embodiment, sequence profile scores (Bowie et al., Science 253(5016):164 70 (1991), incorporated by reference) and/or potentials of mean force (Hendlich et al., J. Mol. Biol. 216(1):167 180 (1990), also incorporated by reference) may also be calculated to score sequences. These methods assess the match between a sequence and a 3-D protein structure and hence can act to screen for fidelity to the protein structure. By using different scoring functions to rank sequences, different regions of sequence space can be sampled in the computational screen.

Furthermore, scoring functions may be used to screen for sequences that would create metal or co-factor binding sites in the protein (Hellinga, Fold Des. 3(1): R1 8 (1998), hereby expressly incorporated by reference). Similarly, scoring functions may be used to screen for sequences that would create disulfide bonds in the protein. These potentials attempt to specifically modify a protein structure to introduce a new structural motif.

In a preferred embodiment, sequence and/or structural alignment programs may be used to generate the variant TNF-receptor proteins of the invention. As is known in the art, there are a number of sequence-based alignment programs; including for example, Smith-Waterman searches, Needleman-Wunsch, Double Affine Smith-Waterman, frame search, Gribskov/GCG profile search, Gribskov/GCG profile scan, profile frame search, Bucher generalized profiles, Hidden Markov models, Hframe, Double Frame, Blast, Psi-Blast, Clustal, and GeneWise.

The source of the sequences may vary widely, and include taking sequences from one or more of the known databases, including, but not limited to, SCOP (Hubbard, et al., Nucleic Acids Res 27(1):254 256. (1999)); PFAM (Bateman, et al., Nucleic Acids Res 27(1):260 262. (1999)); VAST (Gibrat, et al., Curr Opin Struct Biol 6(3):377 385. (1996)); CATH (Orengo, et al., Structure 5(8):1093 1108. (1997)); PhD Predictor (http://www.embl-heidelberg.de/predictprotein/predictprotein.html); Prosite (Hofmann, et al., Nucleic Acids Res 27(1):215 219. (1999)); PIR (http://www.mips.biochem.mpg.de/proj/protseqdb/); GenBank (http://www.ncbi.nlm.nih.gov/); PDB (www.rcsb.org) and BIND (Bader, et al., Nucleic Acids Res 29(1):242 245. (2001)).

In addition, sequences from these databases may be subjected to contiguous analysis or gene prediction; see Wheeler, et al., Nucleic Acids Res 28(1):10 14. (2000) and Burge and Karlin, J Mol Biol 268(1):78 94. (1997).

As is known in the art, there are a number of sequence alignment methodologies that may be used. For example, sequence homology based alignment methods may be used to create sequence alignments of proteins related to the target structure (Altschul et al., J. Mol. Biol. 215(3):403 410 (1990), Altschul et al., Nucleic Acids Res. 25:3389 3402 (1997), both incorporated by reference). These sequence alignments are then examined to determine the observed sequence variations. These sequence variations are tabulated to define a set of variant TNF-receptor proteins.

Sequence based alignments may be used in a variety of ways. For example, a number of related proteins may be aligned, as is known in the art, and the "variable" and "conserved" residues defined; that is, the residues that vary or remain identical between the family members can be defined. These results may be used to generate a probability table, as outlined below. Similarly, these sequence variations may be tabulated and a secondary library defined from them as defined below. Alternatively, the allowed sequence variations may be used to define the amino acids considered at each position during the computational screening. Another variation, is to bias the score for amino acids that occur in the sequence alignment, thereby increasing the likelihood that they are found during computational screening but still allowing consideration of other amino acids. This bias would result in a focused library of variant TNF-receptor proteins but would not eliminate from consideration amino acids not found in the alignment. In addition, a number of other types of bias may be introduced. For example, diversity may be forced; that is, a "conserved" residue is chosen and altered to force diversity on the protein and thus sample a greater portion of the sequence space. Alternatively, the positions of high variability between family members (i.e. low conservation) may be randomized, either using all or a subset of amino acids. Similarly, outlier residues, either positional outliers or side chain outliers, may be eliminated.

Similarly, structural alignment of structurally related proteins may be done to generate sequence alignments. There are a wide variety of such structural alignment programs known. See for example VAST from the NCBI (http://www.ncbi.nlm.nih.gov:80/Structure/VAST/vast.shtml); SSAP (Orengo and Taylor, Methods Enzymol 266(617 635 (1996)) SARF2 (Alexandrov, Protein Eng 9(9):727 732. (1996)) CE (Shindyalov and Bourne, Protein Eng 11(9):739 747. (1998)); (Orengo et al., Structure 5(8):1093 108 (1997); Dali (Holm et al., Nucleic Acid Res. 26(1):316 9 (1998), all of which are incorporated by reference). These sequence alignments may then be examined to determine the observed sequence variations. Libraries may be generated by predicting secondary structure from sequence, and then selecting sequences that are compatible with the predicted secondary structure. There are a number of secondary structure prediction methods such as helix-coil transition theory (Munoz and Serrano, Biopolymers 41:495,1997), neural networks, local structure alignment and others (e.g., see in Selbig et al., Bioinformatics 15:1039 46, 1999).

Similarly, as outlined above, other computational methods are known, including, but not limited to, sequence profiling [Bowie and Eisenberg, Science 253(5016):164 70, (1991)], rotamer library selections [Dahiyat and Mayo, Protein Sci. 5(5):895 903 (1996); Dahiyat and Mayo, Science 278(5335):82 7 (1997); Desjarlais and Handel, Protein Science 4:2006 2018 (1995); Harbury et al, Proc. Natl. Acad. Sci. U.S.A. 92(18):8408 8412 (1995); Kono et al., Proteins: Structure, Function and Genetics 19:244 255 (1994); Hellinga and Richards, Proc. Natl. Acad. Sci. U.S.A. 91:5803 5807 (1994)]; and residue pair potentials [Jones, Protein Science 3: 567 574, (1994)]; PROSA [Heindlich et al., J. Mol. Biol. 216:167 180 (1990)]; THREADER [Jones et al., Nature 358:86 89 (1992)], and other inverse folding methods such as those described by Simons et al. [Proteins, 34:535 543, (1999)], Levitt and Gerstein [Proc. Natl. Acad. Sci. U.S.A., 95:5913 5920, (1998)], Godzik and Skolnick [Proc. Natl. Acad. Sci. U.S.A., 89:12098 102, (1992)], Godzik et al. [J. Mol. Biol. 227:227 38, (1992)] and two profile methods [Gribskov et al. Proc. Natl. Acad. Sci. U.S.A. 84:4355 4358 (1987) and Fischer and Eisenberg, Protein Sci. 5:947 955 (1996), Rice and Eisenberg J. Mol. Biol. 267:1026 1038(1997)], all of which are expressly incorporated by reference.

In addition, other computational methods such as those described by Koehl and Levitt (J. Mol. Biol. 293:1161 1181 (1999); J. Mol. Biol. 293:1183 1193 (1999); expressly incorporated by reference) may be used to create a variant TNF-receptor library which may optionally then be used to generate a smaller secondary library for use in experimental screening for improved properties and function. In addition, there are computational methods based on force field calculations such as SCMF, see Delarue et al. Pac. Symp. Biocomput. 109 21 (1997); Koehl et al., J. Mol. Biol. 239:249 75 (1994); Koehl et al., Nat. Struct. Biol. 2:163 70 (1995); Koehl et al., Curr. Opin. Struct. Biol. 6:222 6 (1996); Koehl et al., J. Mol. Biol. 293:1183 93 (1999); Koehl et al., J. Mol. Biol. 293:1161 81 (1999); Lee J., Mol. Biol. 236:918 39 (1994); and Vasquez Biopolymers 36:53 70 (1995); all of which are expressly incorporated by reference. Other force field calculations that can be used to optimize the conformation of a sequence within a computational method, or to generate de novo optimized sequences as outlined herein include, but are not limited to, OPLS-AA [Jorgensen et al., J. Am. Chem. Soc. 118:11225 11236 (1996); Jorgensen, W. L.; BOSS, Version 4.1; Yale University: New Haven, Conn. (1999)]; OPLS [Jorgensen et al., J. Am. Chem. Soc. 110:1657ff (1988); Jorgensen et al., J. Am. Chem. Soc.112:4768ff (1990)]; UNRES (United Residue Forcefield; Liwo et al., Protein Science 2:1697 1714 (1993); Liwo et al., Protein Science 2:1715 1731 (1993); Liwo et al., J. Comp. Chem. 18:849 873 (1997); Liwo et al., J. Comp. Chem. 18:874 884 (1997); Liwo et al., J. Comp. Chem. 19:259 276 (1998); Forcefield for Protein Structure Prediction (Liwo et al., Proc. Natl. Acad. Sci. U.S.A. 96:5482 5485 (1999)]; ECEPP/3 [Liwo et al., J Protein Chem. 13(4):375 80 (1994)]; AMBER 1.1 force field (Weiner et al., J. Am. Chem. Soc. 106:765 784); AMBER 3.0 force field [U. C. Singh et al., Proc. Natl. Acad. Sci. U.S.A. 82:755 759 (1985)]; CHARMM and CHARMM22 (Brooks et al., J. Comp. Chem. 4:187 217); cvff3.0 [Dauber-Osguthorpe et al., Proteins: Structure, Function and Genetics, 4:31 47 (1988)]; cff91 (Maple et al., J. Comp. Chem. 15:162 182); also, the DISCOVER (cvff and cff91) and AMBER forcefields are used in the INSIGHT molecular modeling package (Biosym/MSI, San Diego Calif.) and HARMM is used in the QUANTA molecular modeling package (Biosym/MSI, San Diego Calif.), all of which are expressly incorporated by reference. In fact, as is outlined below, these force field methods may be used to generate the variant TNF-receptor library directly; these methods may be used to generate a probability table from which an additional library is directly generated.

The PDA.TM. technology, viewed broadly, has three components that may be varied to alter the output (e.g. the primary library): the scoring functions used in the process; the filtering technique, and the sampling technique.

In a preferred embodiment, the scoring functions may be altered. In a preferred embodiment, the scoring functions outlined above may be biased or weighted in a variety of ways. For example, a bias towards or away from a reference sequence or family of sequences can be done; for example, a bias towards wild type or homologue residues may be used. Similarly, the entire protein or a fragment of it may be biased; for example, the active site may be biased towards wild type residues, or domain residues towards a particular desired physical property can be done. Furthermore, a bias towards or against increased energy can be generated. Additional scoring function biases include, but are not limited to applying electrostatic potential gradients or hydrophobicity gradients, adding a substrate or binding partner to the calculation, or biasing towards a desired charge or hydrophobicity.

In addition, in an alternative embodiment, there are a variety of additional scoring functions that may be used. Additional scoring functions include, but are not limited to torsional potentials, or residue pair potentials, or residue entropy potentials. Such additional scoring functions can be used alone, or as functions for processing the library after it is scored initially. For example, a variety of functions derived from data on binding of peptides to MHC (Major Histocompatibility Complex) may be used to rescore a library in order to eliminate proteins containing sequences, which can potentially bind to MHC, i.e. potentially immunogenic sequences. See, for example, U.S. Ser. Nos. 60/217,661; 09/903,378; 10/039,170; 60/360,843; 60/384,197; PCT 01/21,823; and PCT 02/00165.

In addition, it should be noted that the preferred methods of the invention result in a rank-ordered or a filtered list of sequences; that is, the sequences are ranked on the basis of some objective criteria. However, as outlined herein, it is possible to create a set of non-ordered sequences, for example by generating a probability table directly (for example using SCMF analysis or sequence alignment techniques) that lists sequences without ranking them. The sampling techniques outlined herein can be used in either situation.

In a preferred embodiment, Boltzmann sampling is done. As will be appreciated by those in the art, the temperature criteria for Boltzmann sampling can be altered to allow broad searches at high temperature and narrow searches close to local optima at low temperatures (see e.g., Metropolis et al., J. Chem. Phys. 21:1087, 1953).

In a preferred embodiment, the sampling technique utilizes genetic algorithms, e.g., such as those described by Holland (Adaptation in Natural and Artificial Systems, 1975, Ann Arbor, U. Michigan Press). Genetic algorithm analysis generally takes generated sequences and recombines them computationally, similar to a nucleic acid recombination event, in a manner similar to "gene shuffling". Thus the "jumps" of genetic algorithm analysis generally are multiple position jumps. In addition, as outlined below, correlated multiple jumps may also be done. Such jumps may occur with different crossover positions and more than one recombination at a time, and may involve recombination of two or more sequences. Furthermore, deletions or insertions (random or biased) can be done. In addition, as outlined below, genetic algorithm analysis may also be used after the secondary library has been generated.

In a preferred embodiment, the sampling technique utilizes simulated annealing, e.g., such as described by Kirkpatrick et al. [Science, 220:671 680 (1983)]. Simulated annealing alters the cutoff for accepting good or bad jumps by altering the temperature. That is, the stringency of the cutoff is altered by altering the temperature. This allows broad searches at high temperature to new areas of sequence space, altering with narrow searches at low temperature to explore regions in detail.

In addition, as outlined below, these sampling methods may be used to further process a first set to generate additional sets of variant TNF-receptor proteins.

As used herein variant TNF-receptor proteins include TNF-R1 (also referred to herein as p55, p55 TNF-R1, p55 TNFR) monomers and TNF-R2 (also referred to herein as p75, p75 TNF-R2) monomers. In addition, these monomers may be dimerized and/or fused to the constant region of an immunoglobulin (or Fc region). Such fusion conjugates may be a fragment or an entire region. See, for example, U.S. Pat. Nos. 5,155,027; 5,567,584; 5,750,375; 5,610,279; 5,843,725; 5,750,375; 5,712,155; 6,018,026; 6,121,022; 6,194,551; 6,277,375; 6,365,161; 6,291,212; 6,291,646; 6,300,099; 6,323,323; U.S. Patent Publication No. 2001/0036459; WO 97/41895; WO 00/42072; and Shields et al. (2001) J. Biol. Chem., 276: 6591 6604; all incorporated by reference.

In a preferred embodiment, the variant TNF-receptor proteins are soluble proteins, preferably monomers, that retain the ability to bind TNF. In a preferred embodiment, the variant TNFR proteins are soluble TNF-R1 monomer variants.

The computational processing results in a set of optimized variant TNF-receptor protein sequences. Optimized variant TNF-receptor protein sequences are generally different from the wild type TNF-receptor sequence in structural regions critical for receptor affinity, i.e, p55 or p75 receptor domains. In a preferred embodiment, "receptor domain(s)" refers to the first three cysteine-rich domains of the extra-cellular region of soluble p55 TNF-R1. Preferably, these three domains are C-terminally fused to an epitope tag (triple flag peptide) for purification purposes. The fourth cysteine-rich domain is generally avoided due to its lack of involvement in TNF binding. A 14 amino acid deletion at the N terminus, which corresponds to residues 1 14 of the crystallized structure, was made between the signal peptide and the first cysteine rich domain (LVPHLGDREKRDSV). The TNFR nomenclature used here is consistent with the description of the crystallized form of the receptor.

Preferably, each optimized variant TNF-receptor protein sequence comprises at least about 1 variant amino acid from the starting or wild-type sequence, with 2 15 being preferred. Preferably, variant TNF-receptor protein sequences comprising 2 5 variant amino acids are generated. However, other embodiments may include TNF-receptor protein sequences comprising from 2 7, 3 5, 5 7, 5 10, 10 15, etc, variant amino acids.

Thus, in the broadest sense, the present invention is directed to variant TNF-receptor proteins that neutralize wild type TNF or antagonize the biological properties of TNF by neutralizing its ability to bind receptors. By "variant TNF-receptor" herein is meant TNF-receptor proteins, which have been designed using the computational methods outlined herein to differ from the corresponding wild type protein by at least 1 amino acid.

By "neutralize", "neutralizing" or other grammatical variations means when a molecule blocks or prevents one molecule from interacting with its target molecule thereby preventing what would otherwise result in some biological response or signal (when present in sufficient amounts). Thus the effect of neutralization is to interfere with the biological response or signal that would normally occur when two molecules interact. A common example would be the ability of a "neutralizing" antibody to block some biological activity of the antigen to which it was raised. Another example occurs when the extra-cellular portion of a cell surface receptor is made soluble and it retains its ability to bind to its ligand. If present in sufficient amounts, this soluble receptor can "neutralize" or block the activity of the ligand.

By "protein" herein is meant at least two covalently attached amino acids, which includes proteins, polypeptides, oligopeptides and peptides. The protein may be made up of naturally occurring amino acids and peptide bonds, or synthetic peptidomimetic structures, i.e., "analogs" such as peptoids [see Simon et al., Proc. Natl. Acd. Sci. U.S.A. 89(20:9367 71 (1992)], generally depending on the method of synthesis. Thus "amino acid", or "peptide residue", as used herein means both naturally occurring and synthetic amino acids. For example, homo-phenylalanine, citrulline, and noreleucine are considered amino acids for the purposes of the invention. "Amino acid" also includes imino acid residues such as proline and hydroxyproline. In addition, any amino acid representing a component of the variant TNF-receptor proteins can be replaced by the same amino acid but of the opposite chirality. Thus, any amino acid naturally occurring in the L-configuration (which may also be referred to as the R or S, depending upon the structure of the chemical entity) may be replaced with an amino acid of the same chemical structural type, but of the opposite chirality, generally referred to as the D-amino acid but which can additionally be referred to as the R-- or the S--, depending upon its composition and chemical configuration. Such derivatives have the property of greatly increased stability, and therefore are advantageous in the formulation of compounds which may have longer in vivo half lives, when administered by oral, intravenous, intramuscular, intraperitoneal, topical, rectal, intraocular, or other routes. In the preferred embodiment, the amino acids are in the (S) or L-configuration. If non-naturally occurring side chains are used, non-amino acid substituents may be used, for example to prevent or retard in vivo degradations. Proteins including non-naturally occurring amino acids may be synthesized or in some cases, made recombinantly; see van Hest et al., FEBS Lett 428:(1 2) 68 70 May 22, 1998 and Tang et al., Abstr. Pap Am. Chem. S218:U138-U138 Part 2 Aug. 22, 1999, both of which are expressly incorporated by reference herein.

Aromatic amino acids may be replaced with D- or L-naphylalanine, D- or L-Phenylglycine, D- or L-2-thieneylalanine, D- or L-1-, 2-, 3- or 4-pyreneylalanine, D- or L-3-thieneylalanine, D- or L-(2-pyridinyl)-alanine, D- or L-(3-pyridinyl)-alanine, D- or L-(2-pyrazinyl)-alanine, D- or L-(4-isopropyl)-phenylglycine, D-(trifluoromethyl)-phenylglycine, D-(trifluoromethyl)-phenylalanine, D-p-fluorophenylalanine, D- or L-p-biphenylphenylalanine, D- or L-p-methoxybiphenylphenylalanine, D- or L-2-indole(alkyl)alanines, and D- or L-alkylainines where alkyl may be substituted or unsubstituted methyl, ethyl, propyl, hexyl, butyl, pentyl, isopropyl, iso-butyl, sec-isotyl, iso-pentyl, non-acidic amino acids, of C1 C20.

Acidic amino acids may be substituted with non-carboxylate amino acids while maintaining a negative charge, and derivatives or analogs thereof, such as the non-limiting examples of (phosphono)alanine, glycine, leucine, isoleucine, threonine, or serine; or sulfated (e.g., --SO.sub.3H) threonine, serine, tyrosine.

Other substitutions may include unnatural hydroxylated amino acids which may made by combining "alkyl" with any natural amino acid. The term "alkyl" as used herein refers to a branched or unbranched saturated hydrocarbon group of 1 to 24 carbon atoms, such as methyl, ethyl, n-propyl, isoptopyl, n-butyl, isobutyl, t-butyl, octyl, decyl, tetradecyl, hexadecyl, eicosyl, tetracisyl and the like. Alkyl includes heteroalkyl, with atoms of nitrogen, oxygen and sulfur. Preferred alkyl groups herein contain 1 to 12 carbon atoms. Basic amino acids may be substituted with alkyl groups at any position of the naturally occurring amino acids lysine, arginine, ornithine, citrulline, or (guanidino)-acetic acid, or other (guanidino)alkyl-acetic acids, where "alkyl" is define as above. Nitrile derivatives (e.g., containing the CN-moiety in place of COOH) may also be substituted for asparagine or glutamine, and methionine sulfoxide may be substituted for methionine. Methods of preparation of such peptide derivatives are well known to one skilled in the art.

In addition, any amide linkage in any of the variant TNF-receptor polypeptides can be replaced by a ketomethylene moiety. Such derivatives are expected to have the property of increased stability to degradation by enzymes, and therefore possess advantages for the formulation of compounds which may have increased in vivo half lives, as administered by oral, intravenous, intramuscular, intraperitoneal, topical, rectal, intraocular, or other routes.

Additional amino acid modifications of amino acids of variant TNF-receptor polypeptides of to the present invention may include the following: Cysteinyl residues may be reacted with receptor-haloacetates (and corresponding amines), such as 2-chloroacetic acid or chloroacetamide, to give carboxymethyl or carboxyamidomethyl derivatives. Cysteinyl residues may also be derivatized by reaction with compounds such as bromotrifluoroacetone, receptor-bromo-beta-(5-imidozoyl)propionic acid, chloroacetyl phosphate, N-alkylmaleimides, 3-nitro-2-pyridyl disulfide, methyl 2-pyridyl disulfide, p-chloromercuribenzoate, 2-chloromercuri-4-nitrophenol, or chloro-7-nitrobenzo-2-oxa-1,3-diazole.

Histidyl residues may be derivatized by reaction with compounds such as diethylprocarbonate e.g., at pH 5.5 7.0 because this agent is relatively specific for the histidyl side chain, and para-bromophenacyl bromide may also be used; e.g., where the reaction is preferably performed in 0.1 M sodium cacodylate at pH 6.0.

Lysinyl and amino terminal residues may be reacted with compounds such as succinic or other carboxylic acid anhydrides. Derivatization with these agents is expected to have the effect of reversing the charge of the lysinyl residues. Other suitable reagents for derivatizing receptor-amino-containing residues include compounds such as imidoesters/e.g., as methyl picolinimidate; pyridoxal phosphate; pyridoxal; chloroborohydride; trinitrobenzenesulfonic acid; O-methylisourea; 2,4 pentanedione; and transaminase-catalyzed reaction with glyoxylate.

Arginyl residues may be modified by reaction with one or several conventional reagents, among them phenylglyoxal, 2,3-butanedione, 1,2-cyclohexanedione, and ninhydrin according to known method steps. Derivatization of arginine residues requires that the reaction be performed in alkaline conditions because of the high pKa of the guanidine functional group. Furthermore, these reagents may react with the groups of lysine as well as the arginine epsilon-amino group.

The specific modification of tyrosyl residues per se is well-known, such as for introducing spectral labels into tyrosyl residues by reaction with aromatic diazonium compounds or tetranitromethane. N-acetylimidizol and tetranitromethane may be used to form O-acetyl tyrosyl species and 3-nitro derivatives, respectively.

Carboxyl side groups (aspartyl or glutamyl) may be selectively modified by reaction with carbodiimides (R'--N--C--N--R') such as 1-cyclohexyl-3-(2-morpholinyl-(4-ethyl) carbodiimide or 1-ethyl-3-(4-azonia-4,4-dimethylpentyl) carbodiimide. Furthermore aspartyl and glutamyl residues may be converted to asparaginyl and glutaminyl residues by reaction with ammonium ions.

Glutaminyl and asparaginyl residues may be frequently deamidated to the corresponding glutamyl and aspartyl residues. Alternatively, these residues may be deamidated under mildly acidic conditions. Either form of these residues falls within the scope of the present invention.

The TNF-receptor proteins may be from any number of organisms, with TNF-receptor proteins from mammals being particularly preferred. Suitable mammals include, but are not limited to, rodents (rats, mice, hamsters, guinea pigs, etc.), primates, farm animals (including sheep, goats, pigs, cows, horses, etc); and in the most preferred embodiment, from humans. As will be appreciated by those in the art, TNF-receptor proteins based on TNF-receptor proteins from mammals other than humans may find use in animal models of human disease.

The TNF-R proteins of the invention are antagonists of wild type TNF. By "antagonists of wild type TNF" herein is meant that the variant TNF-receptor protein inhibits or significantly decreases the activation of receptor signaling by wild type TNF proteins by at least 10% or more. In a preferred embodiment, the variant TNF-receptor protein interacts with the wild type TNF protein such that the complex comprising the variant TNF-receptor and wild type TNF is incapable of activating TNF receptors, i.e. TNF-R1 or TNF-R2. Preferably, the variant TNF-receptor protein preferentially interacts with wild type TNF such that receptor binding does not occur and/or TNF-receptor signaling is not initiated.

The variant TNF-receptor antagonist proteins of the invention include improved stability, pharmacokinetics, reduced immunogenicity and high affinity for wild type TNF-alpha. Variants with higher affinity, i.e, at least 10% or more, toward wild type TNF-alpha may be generated from variants exhibiting TNF-receptor antagonism as outlined above.

As outlined above, the invention provides variant TNF-receptor nucleic acids encoding variant TNF-receptor polypeptides. The variant TNF-receptor polypeptide preferably has at least one property, i.e., altered property, which is substantially different from the same property of the corresponding naturally occurring TNF polypeptide. The property of the variant TNF-receptor polypeptide is the result the PDA analysis of the present invention.

The term "altered property" or grammatical equivalents thereof in the context of a polypeptide, as used herein, refers to any characteristic or attribute of a polypeptide that can be selected or detected and compared to the corresponding property of a naturally occurring protein. These properties include, but are not limited to cytotoxic activity; oxidative stability, substrate specificity, substrate binding or catalytic activity, thermal stability, alkaline stability, pH activity profile, resistance to proteolytic degradation, kinetic association (K.sub.on) and dissociation (K.sub.off) rate, protein folding, inducing an immune response, ability to bind to a ligand, ability to bind to a receptor, ability to be secreted, ability to be displayed on the surface of a cell, ability to oligomerize, ability to signal, ability to stimulate cell proliferation, ability to inhibit cell proliferation, ability to induce apoptosis, ability to be modified by phosphorylation or glycosylation, a reduction in immunogenicity and the ability to treat disease.

Unless otherwise specified, a substantial change in any of the above-listed properties, when comparing the property of a variant TNF-receptor polypeptide to the property of a naturally occurring TNF-receptor protein is preferably at least a 20%, more preferably, 50%, more preferably at least a 2-fold increase or decrease. Thus, a change in cytotoxic activity is evidenced by at least a 75% or greater decrease in TNF-induced cell death as compared to wild type protein. A change in binding affinity is evidenced by at least a 5% or greater increase or decrease in binding affinity to wild type TNF.

A change in oxidative stability is evidenced by at least about 20%, more preferably at least 50% increase of activity of a variant TNF-receptor protein when exposed to various oxidizing conditions a