Every peptide SAR Slide is built on an alignment — the position-by-position frame that lets Ideation compare peptides of different lengths and compositions. Ideation gives you three ways to get one: import it from a file, or compute it with one of two aligners, center-star and PepSeA. This page explains what an alignment decides, how the three differ, and which one to reach for.
For the step-by-step instructions, see How to Align Peptides.
Why alignment is a choice, not a calculation
Peptides in a series differ in length and composition, so comparing them position-by-position means deciding which monomers "belong" in the same column. There is no single correct answer: pushing two residues into one column asserts they are equivalent, and inserting a gap asserts one peptide is missing something the other has. Every alignment method is a set of trade-offs about which of those assertions to prefer.
The trade-off that matters most in practice is columns versus honesty. A narrow frame is easy to read but forces unrelated residues to share positions; a scrupulous frame keeps residues honest but spreads the series across a wide, mostly-empty grid. The three sources below strike that balance differently — and since an alignment belongs to the dataset, you can keep several and compare them.
The three sources at a glance
| Imported | Center-star | PepSeA | |
|---|---|---|---|
| Who decides the columns | You, in a CSV or Excel file | Ideation's own aligner | MAFFT, through the PepSeA service |
| Created at import | No | Yes — Center-star alignment | Yes — PepSeA alignment |
| How monomers are scored | — | By natural analog and physicochemical family | By the structural similarity of the monomers, from your organisation's monomer similarity matrix |
| Settings you can change | — | None | Alignment strategy and gap penalty |
| Branches | One Excel sheet per branch | Aligned automatically | Aligned automatically |
| Limits | Peptides are matched on their primary identifier | Up to 5,000 peptides, with HELM sequences | Up to 208 distinct non-natural monomers by default |
| Time to get it | Immediate | Quick | Longer: it may wait for the similarity matrix to be rebuilt, and the strategy sets the run time |
| Best for | A curated alignment you already trust | A quick, predictable frame that is easy to reason about | A tighter frame on series rich in non-natural monomers |
Each source shows as a badge on its row in the alignment list — Imported, Center-star or PepSeA — so you always know where an alignment came from.
The method behind each computed source has its own page:
- Understanding Center-Star Alignment — how the centre is chosen, how substitutions are scored, how gap costs are derived.
- Understanding PepSeA Alignment — the similarity matrix, the monomer limit, and the strategy and gap settings it asks for.
What you get at import
A peptide dataset is ready to browse as soon as its sequences are parsed. Its alignments are computed after that, in the background: every import queues one center-star and one PepSeA alignment, which appear in the dataset's alignment list and complete on their own. The center-star one usually finishes first; the PepSeA one can take longer, especially when the import brought monomers the similarity matrix has to be rebuilt for.
Both are best-effort. An alignment that cannot run ends as a Failed row with its reason, and the dataset itself is never affected. If both fail, import an alignment from a file.
Which one should I use?
- Start with what the import gave you. Both computed alignments are there for free; open each in the alignment editor and keep the one that reads better for your series.
- Prefer PepSeA when the series carries many non-natural monomers, or when center-star stacks residues you consider unrelated into one column. It compares the monomers' structures rather than only their natural analog.
- Prefer center-star when you want a frame you can predict and explain, when PepSeA is unavailable, or when the dataset exceeds PepSeA's monomer limit.
- Import a file when your team already maintains a curated alignment, or when neither computed frame is right and correcting it by hand would take longer than writing it.
A computed alignment is a starting point, not a verdict: whichever you pick, you can correct it in the alignment editor and save it as a new alignment.
How branches are aligned
Both aligners treat branches the same way. The backbone is aligned first. Each branch's attachment point is then translated into the aligned backbone column it hangs off, and the branches attached at the same column are aligned together, as a group of their own.
Branches at different columns are never mixed — a branch hanging off position 5 is never compared with one hanging off position 12, because they are not the same feature of the molecule. This is what the x/y branches-aligned count on an alignment row refers to.
An imported alignment takes its branches from the Excel sheets you map to them instead.
The life of a computed alignment
A computed alignment is queued, then run by a worker in the background, so its row appears in the list before it is ready:
| Row shows | Meaning |
|---|---|
| In progress | Queued or running. Click its progress icon to follow the steps. |
| (no status) | Completed: the alignment can be selected for a SAR Slide and opened in the editor. |
| Failed | It did not run to the end. Click the red icon to read why, then delete the row and run a new one. |
| Replaced | A PepSeA request that never started: either a newer request on the same dataset took its place — its arrow icon takes you there — or its parameters were never submitted. |
Only a completed alignment can carry a SAR Slide. When you create a SAR Report, the newest completed alignment is preselected; pick another one in the list if you prefer.
Computing an alignment always adds one — it never overwrites an existing alignment, and imported alignments are never touched.
Where to go next
- How to Align Peptides — creating, importing, reviewing and repairing an alignment
- Understanding Center-Star Alignment
- Understanding PepSeA Alignment
- Understanding Peptides in Ideation — the wider concepts: HELM and monomers, backbone and branches, hotspots, synergies and clustering
- How to Create a Peptide SAR Report