OptimumAntigen^TM Design Tool

1. Sequence length: The typical length of the peptide antigen for generating anti-peptide antibodies is in the range of 10-20 residues. Shorter sequence can offer greater specificity, but at the risk of being less likely to be exposed on the native protein. Longer sequences, by contrast, might be slightly less specific, but offer a higher probability of recognizing the native protein. Peptide sequences with length of 10-20 residues minimize synthesis problems since they are reasonably soluble in aqueous solution and may have some degree of secondary structure.

2. Hydrophilic, surface-oriented, and flexible: When examining a protein sequence for potential antigenic epitopes, it is important to choose sequences that are hydrophilic, surface-oriented, and flexible. Most naturally occurring proteins in aqueous solutions have their hydrophilic residues on the protein surface and hydrophobic residues buried in the interior. This optimization is based on the fact that antibodies tend to bind to epitopes on the protein surface. Additionally, it has been shown that epitopes have a high degree of mobility

3. Targeting the N-terminus or C-terminus: Because the C-termini of proteins are often exposed and have a high degree of flexibility, they are usually good choices for generating anti-peptide antibodies directed against the intact protein. If the protein is an integral membrane protein and the C-terminus is part of the transmembrane segment, this sequence will be too hydrophobic to be a good candidate. Like the C-terminus, the N-terminus is also frequently exposed to the surface of the protein making it an ideal candidate for antibody generation. If a protein sequence is derived from the cDNA sequence, the leader sequence should not be included in the sequence selected for antibody generation.

4. Continuous versus Discontinuous Epitopes: Epitopes Sequence in proteins generally consists of 6-12 amino acids and can be classified as continuous and discontinuous. Continuous epitopes consists of a contiguous sequence of amino acids in a protein. Anti-peptide antibodies will bind to continuous epitopes in native protein when the epitope sequence is not buried in the interior of the protein. Discontinuous epitopes consist of sequences of amino acids that are not contiguous but are brought together by the foldings of the peptide chain or by the juxtaposition of two separate polypeptide chains. Anti-peptide antibodies may or may not recognize discontinuous epitope depending on whether the peptide used for the antisera generation has a secondary structure similar to the epitope and/or if the protein epitope has enough continuous sequence for the antibody to bind with a lower affinity.

5. Algorithms: Algorithms for predicting protein characteristics such as hydrophilicity/hydrophobicity and secondary structure regions including alpha-helix, beta-sheet and beta-turn aid the selection process of a potentially exposed, immunogenic internal sequence for antibody generation. Hydrophilicity plots as described by Hopp and Woods assign an average hydrophilicity value for each residue in the sequence. The highest point of average hydrophilicity for a series of contiguous residues is usually at or near an antigenic determinant. A slightly different algorithm described by Kyte and Doolittle evaluates the hydrophilic and hydrophobic tendencies of the sequence. This profile is useful for predicting exterior versus interior regions of the native protein. Secondary structure can be identified by the algorithms developed by Chou and Fasman or Lim. Surface region or regions of high accessibility often border helical or extended secondary structure regions. In addition, sequence regions with beta-turn or amphipthic helix character have been found to be antigenic.

We avoid common sequence motifs such as the RGD motif, the helix-loop-helix sequence, GTP binding sites, and SH2 domains which may cause cross-reactivity. We also avoid sequences associated with certain biological activities, such as autolytic cleavage hormonal activity, and undesired post- translational modifications.

Many commercial software packages such as MacVector^TM, DNAStar^TM, and PC-Gene^TM incorporate these algorithms. Aiming for best optimization, none of the algorithms should be used alone. Combined use of the predictive methods may result in a success rate as high as 86% in predicting antigenic determinants.

6. Coupling Strategy: A factor that is often over-looked when designing a synthetic peptide is the method of coupling the peptide to the carrier protein. For example, N-terminal sequences should be coupled through the C-terminal amino acid and vice versa. Internal sequences can be coupled to either end. Another consideration for internal sequences is to acetlyate or amidate the unconjugated ends as the sequence in the native protein molecule would not contain a charged terminus.

Unless the customer requests otherwise, N-terminal residues are usually acetylated, and C-terminal residues are amidated. Peptide sequences from internal portions of their original proteins are capped on one terminus and conjugated on the other. This ensures the peptide antigens do not show charges as they are in the case of native protein since such extra electrostatic charges may affect proper peptide folding and potentially alter antibody specificity.

7. Experience: Many of our scientists have over twenty years of experience in peptide design and antibody production. Thousands of antibodies with high ELISA titer have been sent to clients which peptide antigens were designed, synthesized, and conjugated by GenScript.

8. Mechanism learning algorithms: Of all the antibody production steps, peptide antigen design has been the most thoroughly studied, using a combination of biochemicals, genetic, and bioinformatic approaches. Increased understanding of the mechanism of peptide antigen has led directly to improvements in scientists’ ability to produce antibodies. In particular, design algorithms for peptide antigen that are used to artificially induce the peptide antigen in antibody production have been significantly improved through research on the mechanism of peptide antigen design.