Stacey Hoge Product - Management MilliporeSigma, A business of Merck KGaA, Darmstadt, Germany
Kevin Long, Ph.D. - Scientific Content Management MilliporeSigma, A business of Merck KGaA, Darmstadt, Germany
Successful drug discovery often involves protein studies, because most drugs are designed either to interact with specific target proteins, or to alter target protein-protein interactions. Current approaches toward a successful lead development and drug discovery require high throughput screening (HTS), that is, a fast and efficient screening of large numbers of compounds in a parallel manner. HTS is made possible because of advances in genomics, proteomics, combinatorial peptide synthesis, software programming and robotics. The result is peptide-based drug discovery, an effective approach but one with several challenging steps to consider.
An overview of the challenges involved
Proteins are large molecules and are usually ineffective as drugs due to delivery and stability issues. To make a peptide drug, a specific region of the protein that represents the active site or epitope needs to be identified. The first challenging step in drug development is to “map” these active regions of a protein in a process called epitope mapping. This involves the use of large numbers of peptide libraries, which are then synthesized and assayed in a parallel, high-throughput manner. Once the epitope is identified, the next challenging steps are to optimize the peptide sequence and then to stabilize it into a final drug product.
Challenge #1: Design of libraries for epitope mapping
Designing peptide libraries is a critical consideration in ensuring the success of the project. While the bottom line is the eventual selection of a set of overlapping peptide sequences of specific lengths and of specific offset number, in reality it is a delicate balance between the cost of the entire experiment versus the potential usefulness of the data obtained. The offset number is the number of residues that the peptide sequence is shifted along the native protein sequence. While ideally one would choose longer sequences and a shorter offset, synthesizing long peptides can result in a lower peptide quality. While shorter peptide length leads to more peptide sequences to synthesize, shorter peptides typically result in higher peptide quality. The number of peptides in the library will depend on the length of the protein sequence. The obvious goal is to select the minimum number of peptides that can yield the best results. The common practice is to use 8 to 20 residues, preferably in the 12- to 16-residue range, and an offset number that is roughly a third of the peptide length.
Challenge #2: Sequence optimization
Once an epitope is identified, the next step is to perform studies to demonstrate structure and function relationships. These studies are usually composed of two phases: peptide sequence optimization, followed by structure stabilization. Ideally, sequence optimization should be performed by synthesizing all possible sequence combinations for a given number of residues that constitute an epitope. Unfortunately, this is impractical because the number of peptide sequence permutations increase exponentially with the length of the peptide and it would be impossible to individually synthesize (at least for now) all the sequences in the peptide library. Instead, there are four practical strategies used to generate alternative combinatorial libraries.
- Alanine scanning library – Alanine is systematically substituted into each amino acid position in the previously identified epitope and peptide activity shifts observed.
- Truncation library – This is a series of peptide sequences representing the systematic truncation of the flanking residues to determine the minimum length required for optimum peptide activity.
- Random library – This is a shotgun approach where selected residues in the peptide sequence (called the wobble sequence) are simultaneously substituted with a mixture of all 20 amino acids, or a mixture of pre-determined amino acids.
- Positional scanning library – A selected position or positions in a peptide sequence are systematically replaced with different amino acids to determine the preferred amino acid residues, as manifested by corresponding increases in activity.
Challenge #3: Sequence stabilization
The optimum peptide sequence usually does not constitute the final drug candidate. Peptide drugs are typically chemically and conformationally unstable in circulation and, therefore, their structures must be stabilized to maintain their potency over time. The most common strategy to stabilize peptide structures is to substitute selected amino acids with non-standard amino acids. Some examples of non-standard amino acids are either homologs of natural amino acids such as ornithine, homolysine, norleucine, and norvaline, or the chiral analogs (D-forms) of the naturally occurring amino acids (L-forms). Incorporation of these non-standard amino acids can lock a preferred structural conformation and make the peptide resistant to degradation, oxidation, and PTM. Additional stabilization strategies include the formation of cyclic structures via disulfide or lactam bridges or chemically modifying the peptide termini by acetylation or addition of bulky groups.
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