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Reliable complex prediction starts with the correct biological construct, not with deleting every low-confidence or disordered-looking segment. Define the molecule you intend to model, freeze and document its source sequence, normalize the amino-acid text, encode chain stoichiometry explicitly, validate MSAs and templates, and retain a complete manifest of every input and software version. The workflow below covers AlphaFold 3 and ColabFold-style runs, including signal peptides, affinity tags, homomeric copies, paired MSAs, and template mappings.
What “cleaning” a protein sequence actually means
Sequence cleaning is the controlled preparation of an input molecule. It is not an instruction to shorten a sequence until a predictor gives a better-looking model. A residue may be biologically essential even when it is expected to be flexible or receive a low confidence score.
Before editing anything, decide which molecule the prediction should represent:
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- The full translated precursor, including signal peptide or transit peptide.
- A mature, proteolytically processed chain.
- The experimentally expressed construct, including an affinity tag or linker.
- A membrane or organelle-targeted form.
- A designed truncation or mutant used for a specific experiment.
Those choices alter residue numbering, interfaces, domain context and the interpretation of confidence scores. UniProt annotations can identify signal peptides, propeptides and other processing regions, but an annotation is evidence about biology, not an automatic command to trim the sequence.
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1. Define the biological construct before editing residues
Record the identity and boundaries
Create a construct record containing the organism, gene or protein accession, isoform, residue boundaries, mutations, tags, linkers, known post-translational modifications and expected assembly. State whether numbering follows the source precursor or a mature-chain convention. Preserve both the original boundaries and any remapped boundaries after processing.
A practical record might distinguish “precursor residues 1–312,” “mature chain after cleavage of residues 1–23,” and “expression construct with an N-terminal six-residue tag and a flexible linker.” These are three different molecules and should not share an unlabeled FASTA file.
Decide whether processing occurs in the modeled sample
Signal peptides, transit peptides, propeptides and initiator methionines should be handled according to the biological state you want to model. If the experiment measures the secreted mature protein, remove the annotated precursor segment and document the mature start. If the prediction is intended to explain folding during expression or targeting, retain the precursor. If a construct was purified with a tag still attached, include the tag and linker rather than silently removing them.
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Do not trim solely for predicted disorder
Low complexity or apparently disordered residues can contribute to oligomerization, regulation, accessibility or crystal contacts. Remove them only when the construct, processing event or modeling question justifies removal. If you create a truncation to test a domain, label it as a new construct and retain a mapping to the full-length sequence.
2. Choose and freeze the source sequence
Prefer a reviewed record that matches the target
Use a reviewed UniProtKB/Swiss-Prot entry when it corresponds to the organism and isoform. If no reviewed record matches, record the alternative database, accession, release or version, organism and evidence used to select it. Do not rely on a sequence copied from a web page without an accession and version.
Keep an immutable original and a derivative
- Download the exact FASTA record and save it as the original source file.
- Do not edit that file in place. Create a separate cleaned FASTA or construct file.
- Compute a checksum for both files; for example, run
sha256sum source.fastaand record the result. - Store the accession, database release, download date, organism, isoform and construct-edit history beside the files.
The checksum proves which bytes were used, while the construct record explains why the derivative differs from the source. This distinction is essential when a database updates an entry or when another researcher needs to reproduce a run.
3. Normalize and validate the amino-acid text
Separate FASTA metadata from the sequence
The FASTA header is metadata. Remove spaces, tabs, carriage returns and residue numbering that may have been copied from a paper or alignment. Concatenate sequence lines into one continuous string. Keep the original header in your manifest even if you replace it with a local construct identifier.
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Check the alphabet explicitly
AlphaFold 3 defines a protein sequence as a one-letter string using the standard amino-acid alphabet. Validate every character against the alphabet expected by the selected tool. Ambiguous or nonstandard symbols must be resolved manually from the biological record or represented according to the tool’s documented modification mechanism; never silently convert an unknown character into another residue.
- Reject digits, punctuation, whitespace and alignment gaps in the final query sequence.
- Check that the reported length equals the number of amino-acid characters.
- Confirm that a copied stop symbol or hidden Unicode character has not entered the file.
- Preserve an audit note for every substitution, deletion or insertion.
Handle initiator methionine deliberately
The initiator methionine may be removed biologically, retained in a recombinant construct or represented differently in a mature-chain record. Choose the state relevant to the sample and document the decision. Do not remove the first residue simply because a database or structure begins at the second position.
4. Handle signal peptides, propeptides, tags and linkers
Signal peptides and transit peptides
If the target is the mature secreted or organelle-localized chain, remove the annotated targeting segment and remap residue numbers to the mature sequence. If the target is the precursor or a membrane-insertion intermediate, retain it. A signal peptide can influence topology and oligomerization in a precursor model, while it may be absent from the purified mature protein.
Propeptides and cleavage products
Some proteins fold or assemble only after a propeptide is cleaved. Model the uncleaved precursor when studying maturation; model the cleaved chains when studying the final complex. Record the cleavage site, the source annotation and the numbering relationship between precursor and product.
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Include tags and linkers when they remain in the expressed or purified material being modeled. A tag can create contacts, alter flexibility or occupy a binding site. If it was removed enzymatically before the experiment, omit it and record the cleavage. Linkers should remain exactly as expressed, including their length and composition, unless the modeling question intentionally abstracts them away.
Modifications and nonstandard chemistry
AlphaFold 3 inputs can include optional modifications in addition to the protein sequence. Use the version-specific modification fields for a chemically defined residue or covalent change rather than encoding an invented one-letter amino-acid symbol. If the chosen workflow cannot represent the modification, state that limitation and treat the model as an unmodified approximation.
5. Encode the complex and its stoichiometry
Assign unique chain IDs
Give each distinct protein sequence a unique chain identifier. The chain ID is not merely a label for the FASTA header: it defines which physical copy the predictor should treat as a separate chain. Record the intended assembly in a human-readable form such as A:B, A2 or A2B2.
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Represent repeated copies intentionally
For a homomer, repeat the same sequence only when multiple copies are biologically intended. AlphaFold 3 documents an ID list such as ["A", "B", "C"] for three copies of one protein sequence. Do not duplicate a sequence merely to test whether a monomer forms an interface; that changes the modeling hypothesis.
| Biological hypothesis | Input representation | Common mistake |
|---|---|---|
| One monomer | One sequence and one chain ID | Adding a second copy to “see what happens” |
| Homodimer | Same sequence assigned to two intentional chain IDs, such as A and B | Using one chain and expecting a dimeric interface |
| Heterodimer | Distinct sequences with distinct IDs, such as A and B | Merging both proteins into one FASTA record |
| A2B2 | Two copies of A and two copies of B, with four chain IDs | Providing one A and one B and assuming stoichiometry is inferred |
Check that the number of chains, copy counts and chain order in the input match the experimental or biological hypothesis. A correctly cleaned sequence cannot rescue an incorrectly specified assembly.
6. Prepare custom MSAs correctly
Use valid A3M conventions
Custom multiple-sequence alignments should use A3M syntax when the selected workflow expects A3M. The first sequence must be exactly the ungapped query sequence. Lowercase letters represent insertions relative to the query; hyphens represent alignment gaps.
After conceptually removing lowercase insertion characters, every alignment row must have the same aligned length as the query. This rectangularity check catches shifted rows, copied numbering and malformed manual edits before a prediction starts.
Verify the query row
- Compare the first A3M sequence character-for-character with the cleaned query.
- Confirm that the query has no gaps, lowercase insertions or unexpected symbols.
- Check that the query header identifies the intended chain and construct.
- Verify row lengths after insertion removal, not just the visible text length.
ColabFold also documents the query-first convention. If you generate an MSA externally, keep the exact A3M artifact used by the run rather than regenerating it later from a database that may have changed.
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7. Pair MSAs for multimer predictions
Why pairing is different from ordinary MSA search
For a single chain, an MSA primarily supplies evolutionary context for that sequence. For a multimer, rows can contain homologs from different organisms in the same position, falsely suggesting that the proteins co-occur. Pairing attempts to place homologs from the same organism or genomic context on the same row so that coevolutionary information is meaningful.
AlphaFold 3 documentation states that MSA pairing matters only when folding multiple chains. For a controlled result, pair rows manually or use an appropriate pairing program, then provide the paired result through the documented unpaired-MSA field when that is the recommended input for the workflow.
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Audit the pairing process
- Check organism identifiers and the rule used to match them.
- Record how duplicate organisms, paralogs and missing partners were handled.
- Verify chain order in every paired row.
- Record row depth, database release, pairing software and date.
- Inspect a sample of rows manually, especially for proteins with many paralogs.
An intentionally controlled unpaired MSA can be preferable when exact placement is needed or when reliable organism pairing is impossible. State that choice instead of presenting an unpaired alignment as if it were a paired one.
8. Use templates conservatively
Meet the file and mapping requirements
When a template is supplied, use a single-chain mmCIF file and provide correct zero-based query-to-template residue-index mappings. The mapping must account for chain identity, residue numbering, insertions and deletions. Confirm that the template actually represents the relevant protein state and that ligand or cofactor context is appropriate.
When to omit a template
Run template-free when chain identity or residue mapping is uncertain. A wrong template can impose an incorrect fold or interface, making a confident-looking model less useful than one generated without that structural prior. Keep the rejected template and the reason for exclusion in the run record.
9. Choose an input workflow: AlphaFold 3 JSON or ColabFold
The best format depends on the molecules, level of control and infrastructure available. Neither format makes an incorrect construct biologically correct.
| Decision axis | AlphaFold 3 JSON workflow | ColabFold FASTA/CSV workflow |
|---|---|---|
| Molecule and modification support | Structured fields for protein sequences, chain IDs, optional modifications and other supported molecule types; exact fields depend on the installed release. | FASTA or CSV-oriented input with workflow-specific conventions; represent only the molecules and modifications supported by the selected ColabFold mode. |
| Paired versus unpaired MSAs | Explicit MSA fields, including the documented approach for controlled pairing and unpaired input. | MSA generation and pairing follow ColabFold’s supported options; retain the produced A3M files. |
| Templates | Template objects with single-chain mmCIF files and zero-based index mappings. | Template handling depends on the chosen ColabFold interface; export or convert only through documented options. |
| Database searches | Depends on the deployment and configured databases; pin the database release and search environment. | Can use ColabFold-supported local or service-based searches; record which was used and when. |
| Reproducibility | Preserve the JSON, referenced files, software version, database versions and hashes. | Preserve FASTA or CSV, A3M output, template files, command or notebook settings, versions and hashes. |
| Output provenance | Keep the generated structure, confidence outputs and exact input object. | ColabFold produces predicted coordinates and A3M files; the A3M records sequences used by the run. |
ColabFold can export AF3-compatible JSON with its documented --af3-json option when that conversion matches your installed version. Validate the exported object rather than assuming that a conversion preserved chain IDs, MSAs and templates exactly.
10. Build a manifest alongside the input
A manifest turns a one-off prediction into a reproducible experiment. At minimum, store:
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- Original FASTA checksum and cleaned-construct checksum.
- Construct boundaries, processing decisions, mutations, tags, linkers and modifications.
- Chain IDs, sequence-to-chain mapping, stoichiometry and chain order.
- Exact FASTA, JSON or CSV input.
- Every A3M file, its query sequence and pairing method.
- Template mmCIF files, chain identity and zero-based residue mappings.
- Tool, database and template versions, execution environment and run date.
Use stable local identifiers instead of relying on mutable filenames. A manifest should allow another person to determine which biological sequence each chain represents without opening the prediction software.
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11. Run a preflight validation
Perform these checks before submitting a long or expensive run:
- Alphabet and length: every query uses the permitted one-letter amino-acid alphabet, and the recorded length matches the sequence.
- Construct identity: processing, tags, linkers, mutations and boundaries match the stated biological sample.
- Chain count: each intended copy has one chain ID, with no accidental duplicate or split record.
- Stoichiometry: the chain list represents the proposed assembly, such as A:B or A2B2.
- MSA query identity: the first A3M sequence is exactly the corresponding ungapped query.
- MSA rectangularity: after removing lowercase insertions conceptually, all rows align to the query length.
- Pairing: organism matching, duplicate handling and chain order are consistent.
- Templates: each file is a single-chain mmCIF with valid zero-based mappings and appropriate residue context.
- Chain IDs: IDs are unique where required and consistent across sequence, MSA, template and JSON/CSV fields.
- Manifest: files, hashes, versions and dates are present and machine-readable.
Save the validation report with the run. A failed check should stop the run or require an explicit override with a reason.
12. Troubleshoot common failures
The predictor rejects the sequence alphabet
Inspect invisible characters, copied residue numbers, punctuation, stop symbols and nonstandard letters. Compare the cleaned sequence against the source record and resolve each ambiguous character manually. Do not replace it with the most likely amino acid without evidence.
The MSA is rejected or produces odd alignments
Check that the first sequence is the exact query, not a trimmed or gapped version. Remove accidental lowercase characters from the query, preserve hyphens only in aligned rows and verify equal aligned lengths after insertion removal. Recreate the A3M from the cleaned query if a prior construct edit changed its length.
A multimer model separates chains unexpectedly
First verify that the chains are biologically supposed to interact and that the intended stoichiometry was encoded. Then inspect MSA pairing, organism consistency, chain order and duplicate handling. A malformed or independently mixed MSA can remove the evolutionary signal needed for an interface. Do not use a high global confidence score to excuse a wrong construct or a missing chain.
The interface is implausible despite a good monomer fold
Check whether the modeled state includes the correct signal-peptide processing, tag removal, cofactors and oligomeric copy number. Review interface-specific confidence measures available in the selected tool in addition to ranking and pTM-related values. An accurate monomer does not prove that the assembly, chain pairing or biological state is correct.
A template causes an unexpected topology
Recheck single-chain identity, residue numbering, insertion and deletion mapping, and ligand context. If any mapping is uncertain, omit the template and compare a template-free run rather than forcing a questionable alignment.
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Keep the predicted coordinates, confidence outputs and all input artifacts together. ColabFold’s A3M output records the sequences used by that run, so archive it with the coordinates. For complexes, inspect ranking and pTM-related confidence together with interface-specific measures exposed by the chosen tool. These scores help prioritize models; they do not validate a mistaken construct, incorrect stoichiometry or malformed MSA.
There is no universal success rate that applies across proteins, processing states and complex stoichiometries. Report the exact construct and input provenance when sharing a model, and distinguish a confident fold from evidence that the proposed assembly exists in the experimental state.
Quick Recap
Final reproducibility checklist
- Biological state selected: precursor, mature chain, expressed construct or designed truncation.
- Source accession, organism, isoform, release and checksum recorded.
- Original FASTA preserved; cleaned derivative created separately.
- Signal peptides, propeptides, tags, linkers, mutations and modifications documented.
- Standard amino-acid alphabet and exact lengths validated.
- Chain IDs and stoichiometry explicitly encoded.
- A3M query rows exactly match cleaned queries.
- MSA rows are rectangular after lowercase insertion removal.
- Multimer pairing method, organism checks and database release recorded.
- Templates, if used, are single-chain mmCIF files with correct zero-based mappings.
- Input files, A3Ms, templates, software versions, database versions, hashes and run date archived.
- Output confidence and interface evidence interpreted in the context of the construct.
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