Metadata-Version: 2.5
Name: sabr-kit
Version: 0.4.5
Summary: Structure-based Antibody Renumbering
Project-URL: Homepage, https://github.com/delalamo/sabr
Project-URL: Issues, https://github.com/delalamo/sabr/issues
Author: Diego del Alamo
License: MIT License
        
        Copyright (c) 2025 Diego del Alamo
        
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License-File: LICENSE
Requires-Python: >=3.11
Requires-Dist: biopython<2,>=1.87
Requires-Dist: click<9,>=8.4.2
Requires-Dist: dm-haiku<0.1,>=0.0.16
Requires-Dist: jax<0.11,>=0.10.2
Requires-Dist: jaxlib<0.11,>=0.10.2
Requires-Dist: numpy<3,>=2.4.6
Provides-Extra: test
Requires-Dist: coverage<8,>=7.15.0; extra == 'test'
Requires-Dist: pre-commit<5,>=4.6.0; extra == 'test'
Requires-Dist: pytest-cov<8,>=7.1.0; extra == 'test'
Requires-Dist: pytest<10,>=9.1.1; extra == 'test'
Description-Content-Type: text/markdown

# SAbR

SAbR (Structure-based Antibody Renumbering) assigns antibody residue numbers
from backbone coordinates. It combines the original trained Haiku encoder with
the original affine Smith–Waterman alignment and ANARCI numbering rules.

SAbR is intentionally small and feature-complete. It provides one Python API
and one command-line program.

The complete usage guide is available in the
[SAbR documentation](https://sabr.readthedocs.io/).

## Installation

SAbR requires Python 3.11 or newer.

```bash
pip install sabr-kit
```

## Command line

```bash
sabr -i antibody.pdb -c H -o numbered.pdb
```

The complete interface is:

```text
sabr -i INPUT -c CHAIN -o OUTPUT
     [-n imgt|chothia|kabat|martin|aho|wolfguy]
     [-t auto|TYPES]
     [--noise-level 0.0|0.2|0.5|1.0|2.0]
     [-m sabr|softalign]
     [--residue-range START END]
     [--scfv]
     [--no-mmcif]
     [--overwrite] [-v]
```

Defaults are IMGT numbering, automatic H/K/L selection, noise level `0.0`,
`sabr` mode, and the entire selected chain. `--chain-type` accepts a
comma-separated set of candidates. Each candidate is a sequence of `H`, `K`,
and `L` domains: `H,K` tries heavy and kappa single domains, `HK,HL` tries
heavy-kappa and heavy-lambda two-domain chains, and `HHK,HHL` tries the
corresponding three-domain chains. Existing outputs are never replaced unless
`--overwrite` is given. Normal output contains only warnings and errors; `-v`
reports reference scores and pipeline decisions.

Use `--mode softalign` to select the original SoftAlign encoder weights,
reference embeddings, and affine gap penalties together. SoftAlign references
do not vary with `--noise-level`, so that option is ignored in this mode.

Use `--scfv` to search only the scFv candidate set. It is equivalent to
`--chain-type HK,HL,KH,LH` and still requires the default automatic chain type
when used as a flag. Multi-domain results place successive domains in separate
1000-number residue blocks: `1–128`, `1001–1128`, `2001–2128`, and so on.
Linker residues continue sequentially from the preceding domain's last number.
Multi-domain references use the selected parameter mode, so either form can be
combined with `--mode softalign`.

Input and output may be PDB (`.pdb`) or mmCIF (`.cif` or `.mmcif`). When a
requested PDB output needs multi-character insertion codes, SAbR warns and
automatically writes it to the corresponding `.cif` path instead. Pass
`--no-mmcif` to forbid this conversion and fail. Other values that exceed PDB
field limits still require an explicitly named mmCIF output. Writes are atomic,
so a failed run does not leave a partial output.

CLI conversion guarantees preservation of atomic structure content, not
arbitrary non-atomic mmCIF categories. It warns for every mmCIF input.

## Python API

```python
from Bio.PDB import PDBParser
from sabr import renumber_structure

structure = PDBParser(QUIET=True).get_structure("antibody", "antibody.pdb")
numbered = renumber_structure(structure, chain="H")
```

`renumber_structure` accepts a Biopython `Structure`, never mutates its input,
and returns a new Biopython `Structure`. Non-target chains, hetero residues,
waters, and residues outside an inclusive `residue_range` are preserved. SAbR
rejects multi-model structures rather than silently modifying only one model.
If a partial range would create duplicate residue IDs with unchanged residues,
the operation fails with an explanation.

The copy preserves metadata represented by the input Biopython object.
Alternate conformers are normalized deterministically: a complete blank-altloc
backbone is preferred, then the complete conformer with the greatest summed
occupancy, with altloc name as the final tie-breaker. Selections above 1,024
polymer residues are rejected before quadratic model work; use
`residue_range` to select the antibody domain.

Modified peptide residues are translated only for sequence generation. Their
original names and atoms remain unchanged. The committed mapping was generated
from the wwPDB Chemical Component Dictionary snapshot dated 2026-07-11
(`components.cif.gz` SHA-256
`0b3323123ec10b997afe1c530b4cad30306e60b451b2b062c59bc9bb5cbe0679`) and
contains only peptide-linking components with exactly one canonical amino-acid
parent. Unsupported or ambiguous polymer chemistry fails explicitly; no
runtime network access occurs.

For unusually long loops that need extended insertion codes, use mmCIF output.

## Scientific behavior

- The default `sabr` mode preserves the trained SAbR encoder weights,
  references, and gap penalties unchanged.
- The optional `softalign` mode uses `softalign_encoder.npz`,
  `softalign_embeddings.npz`, and the exact penalties in
  `softalign_gap.npz` as one parameter set.
- Alignment uses the original differentiable affine Smith–Waterman method.
- In `sabr` mode, gap extension is `-0.175027` and gap opening is `-2.525591`.
  In `softalign` mode, they are `0.1942468136548996` and
  `-2.5441808700561523`, respectively, as stored in the repository asset.
- Deterministic CDR gap distribution and DE-loop correction are always
  applied. Between IMGT anchors 79 and 85, DE-loop residues fill 80 first,
  then 84 back through 81; additional residues are inserted after 82.
- No deterministic C-terminal correction is applied.
- Automatic chain selection aligns against H, K, and L references and uses
  the highest score, with deterministic H/K/L tie order.
- `chain_type` candidate order is deterministic and resolves score ties.
- scFv mode searches only the `HK,HL,KH,LH` candidate list in that order.
- Multi-domain candidates do not apply gap-open or gap-extension costs to
  query linker residues aligned at any boundary between domain references.
- Multi-domain candidates receive normal affine gap-open and gap-extension
  costs for unaligned query and reference termini when their selection scores
  are compared; the underlying alignments and raw alignment scores are
  unchanged.

A structural gap is detected when the C–N distance between consecutive
residues exceeds 2.66 Å. A gap skips only the affected CDR or DE-loop
correction and emits a warning; other regions continue normally.

T-cell receptors are not an officially supported SAbR target. For
experimental low-level use, align a TCR against the K reference because that
reference includes IMGT position 10, as TCRs do. Pass the actual TCR chain
type (`A`, `B`, `G`, or `D`) only to the ANARCI conversion step, together with
`ref_type="K"`. This workaround is limited to IMGT and AHo numbering; the
other bundled schemes are antibody-specific.

## Development

```bash
pip install -c constraints.txt -e '.[test]'
JAX_PLATFORMS=cpu pytest
pre-commit run --all-files
```

`constraints.txt` records the exact canonical development and CI environment.
Package metadata remains ranged for normal installation. SAbR does not force a
JAX backend; CPU is simply the canonical CI regression baseline.

The committed tests are self-contained and never download data. They verify
the fixed asset hashes, encoder and alignment baselines, all numbering schemes,
H/K/L selection, regional corrections, structure-object behavior, and CLI
failure handling.

## Deferred full benchmark

The historical pre-2021 SAbDab manifest contains approximately 1,012 chains.
The current method scores about 90% on that set, not 100%. The full corpus is
not bundled or downloaded by CI.

Future benchmark work should create a checksum-pinned corpus, verify residue
IDs, insertion codes, and coordinate parity, and compare a lossless archive
with Foldcomp before adding a separate manual or nightly workflow. This is a
benchmarking TODO, not a unit-test or release requirement.

## License and attribution

SAbR is distributed under the repository license. The vendored ANARCI
numbering code retains its original license in `src/sabr/_anarci/LICENSE`.
