{ "cells": [ { "cell_type": "markdown", "id": "bad6ebe2", "metadata": { "language": "markdown" }, "source": [ "# Ranking peptides for a fixed receptor \u2014 combinatorial peptide libraries\n", "\n", "Which peptides does *this* receptor read? The other ranking task, and the one where nothing at all is\n", "fitted: the read-out is `peptide_score`, the poly-alanine-referenced recognition energy summed over the\n", "two peptide-bearing interfaces, sign-flipped so higher is better.\n", "\n", "$$\\texttt{peptide\\_score} = -\\bigl(\\Delta\\Phi_{\\mathrm{TCR:pep}} + \\Delta\\Phi_{\\mathrm{pep:MHC}}\\bigr),\n", "\\qquad \\Delta\\Phi = \\Phi(\\text{sequence}) - \\Phi(\\text{poly-alanine})$$\n", "\n", "$\\Phi$ is the sum of a residue-pair statistical potential over the observed contacts of one interface\n", "\u2014 TCRen on TCR:peptide, Miyazawa\u2013Jernigan on peptide:MHC. The `d` in $\\Delta\\Phi$ is the **reference\n", "difference**, never a derivative. Both interfaces enter because the assay reads T-cell activation,\n", "which needs the peptide presented as well as the receptor engaged. The third interface, TCR:MHC, is\n", "identically unchanged when only the peptide varies and cancels exactly.\n", "\n", "The benchmark is the deposited combinatorial-peptide-library set: **7 T-cell clones, 2,103 TCRmodel2\n", "peptide-swap models**, each clone's library split into the measured best and worst halves by a\n", "positional-scanning activation assay.\n", "\n", "**Needs**: the MHC allele reference (`tcren build-mhc-ref`, once). The featurisation asks for the\n", "`energetics` family only, which is the cheap one." ] }, { "cell_type": "code", "execution_count": 1, "id": "854a847c", "metadata": { "execution": { "iopub.execute_input": "2026-09-02T02:52:33.813980Z", "iopub.status.busy": "2026-09-02T02:52:33.813595Z", "iopub.status.idle": "2026-09-02T02:52:34.558061Z", "shell.execute_reply": "2026-09-02T02:52:34.557619Z" }, "language": "python" }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "python 3.12.13\n", "tcren 3.0.0\n", "numpy 2.5.1\n", "polars 1.43.0\n", "scipy 1.18.0\n", "scikit 1.9.0\n" ] } ], "source": [ "# Environment. No score in this notebook samples; the only randomness is the plot's\n", "# jitter, drawn from a seeded generator so the figure is reproducible.\n", "import platform, sys\n", "\n", "import numpy as np\n", "import polars as pl\n", "import scipy\n", "import sklearn\n", "\n", "import tcren\n", "\n", "print(f\"python {platform.python_version()}\")\n", "print(f\"tcren {tcren.__version__}\")\n", "print(f\"numpy {np.__version__}\")\n", "print(f\"polars {pl.__version__}\")\n", "print(f\"scipy {scipy.__version__}\")\n", "print(f\"scikit {sklearn.__version__}\")\n" ] }, { "cell_type": "markdown", "id": "b0155cc0", "metadata": { "language": "markdown" }, "source": [ "## 1 \u00b7 Bootstrap the library\n", "\n", "The set is `cpl/` on the Hugging Face dataset\n", "[`isalgo/tcren_structures`](https://huggingface.co/datasets/isalgo/tcren_structures): one archive of\n", "2,103 models laid out as `_{best,worst}/.pdb`, plus the assay table\n", "`CPL_stats/cpl_data_stats_new_struct.tsv` carrying the graded activation score `cpl_score` for 2,102\n", "(clone, peptide) pairs.\n", "\n", "The archive holds one structure the assay table does not: clone `sb27`'s own cognate 13-mer\n", "`LPEPLPQGQLTAY`, modelled after the library deposit. It joins to nothing, and any count of structures\n", "per clone has to say so.\n", "\n", "**The best/worst label comes from the directory, not from the assay table's `cpl_status` column.** The\n", "directories label all 2,103 models; `cpl_status` labels 1,654 and leaves 448 null." ] }, { "cell_type": "code", "execution_count": 2, "id": "fc91dcf8", "metadata": { "execution": { "iopub.execute_input": "2026-09-02T02:52:34.559253Z", "iopub.status.busy": "2026-09-02T02:52:34.559145Z", "iopub.status.idle": "2026-09-02T02:52:34.568071Z", "shell.execute_reply": "2026-09-02T02:52:34.567706Z" }, "language": "python" }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "clones ['1e6', '4c6', '868', 'ila1', 'mel5', 'mel8', 'sb27']\n", "clone x half dirs 14\n", "structures 2103\n", "assay rows 2102 (graded activation `cpl_score` per clone x peptide)\n" ] } ], "source": [ "# Fetch and unpack the library. Idempotent.\n", "import os, tarfile, time\n", "from pathlib import Path\n", "\n", "from tcren.paper.bootstrap import fetch_hf_structures\n", "\n", "DATA = Path(os.environ.get(\"TCREN_NB_DATA\", \"data\"))\n", "SET = DATA / \"cpl\"\n", "\n", "if not (SET / \"mel5_best\").is_dir():\n", " fetch_hf_structures(DATA, folders=(\"cpl\",))\n", " with tarfile.open(SET / \"cpl_structures.tar.gz\") as tar:\n", " tar.extractall(SET)\n", "\n", "halves = sorted(p for p in SET.iterdir() if p.is_dir() and p.name.endswith((\"_best\", \"_worst\")))\n", "clones = sorted({p.name.rsplit(\"_\", 1)[0] for p in halves})\n", "print(f\"clones {clones}\")\n", "print(f\"clone x half dirs {len(halves)}\")\n", "print(f\"structures {sum(len(list(p.glob('*.pdb'))) for p in halves)}\")\n", "\n", "# The assay table ships under CPL_stats/ in the deposit; find it wherever the fetch put it.\n", "stats = next(SET.rglob(\"cpl_data_stats_new_struct.tsv\"))\n", "assay = pl.read_csv(stats, separator=\"\\t\",\n", " infer_schema_length=None).rename({\"tcr\": \"clone\", \"peptide\": \"complex.id\"})\n", "print(f\"assay rows {assay.height} (graded activation `cpl_score` per clone x peptide)\")\n" ] }, { "cell_type": "markdown", "id": "aff3b0b0", "metadata": { "language": "markdown" }, "source": [ "## 2 \u00b7 Featurise, one clone-half at a time\n", "\n", "`peptide_score` needs two descriptors, `dPhi_tcr_pep` and `dPhi_pep_mhc`, so only the `energetics`\n", "family is asked for. The exact command per directory:\n", "\n", "```bash\n", "tcren features -s \"data/cpl/mel5_best/*.pdb\" -i energetics -t 0 -o data/cpl/mel5_best.tsv\n", "```\n", "\n", "One call per directory rather than one over the whole set, for a reason worth knowing: a structure's id\n", "is its file stem, which here is the **peptide**, and the same peptide can occur in more than one\n", "clone's library. A single pass would produce a table whose key is not unique. Featurising per directory\n", "lets the clone and the half be recorded as columns.\n", "\n", "Measured here: **2,103 structures in 279 s over 14 calls on 16 cores**. The cached table is used when\n", "it is already on disk." ] }, { "cell_type": "code", "execution_count": 3, "id": "d0a191a5", "metadata": { "execution": { "iopub.execute_input": "2026-09-02T02:52:34.569154Z", "iopub.status.busy": "2026-09-02T02:52:34.569083Z", "iopub.status.idle": "2026-09-02T02:57:13.851527Z", "shell.execute_reply": "2026-09-02T02:57:13.851017Z" }, "language": "python" }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "featurised 2103 structures in 279 s\n", "2103 rows x 15 descriptors\n", "shape: (14, 3)\n", "\u250c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u252c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u252c\u2500\u2500\u2500\u2500\u2500\u2510\n", "\u2502 clone \u2506 half \u2506 len \u2502\n", "\u2502 --- \u2506 --- \u2506 --- \u2502\n", "\u2502 str \u2506 str \u2506 u32 \u2502\n", "\u255e\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u256a\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u256a\u2550\u2550\u2550\u2550\u2550\u2561\n", "\u2502 1e6 \u2506 best \u2506 161 \u2502\n", "\u2502 1e6 \u2506 worst \u2506 164 \u2502\n", "\u2502 4c6 \u2506 best \u2506 161 \u2502\n", "\u2502 4c6 \u2506 worst \u2506 160 \u2502\n", "\u2502 868 \u2506 best \u2506 161 \u2502\n", "\u2502 \u2026 \u2506 \u2026 \u2506 \u2026 \u2502\n", "\u2502 mel5 \u2506 worst \u2506 164 \u2502\n", "\u2502 mel8 \u2506 best \u2506 164 \u2502\n", "\u2502 mel8 \u2506 worst \u2506 96 \u2502\n", "\u2502 sb27 \u2506 best \u2506 162 \u2502\n", "\u2502 sb27 \u2506 worst \u2506 64 \u2502\n", "\u2514\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2534\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2534\u2500\u2500\u2500\u2500\u2500\u2518\n" ] } ], "source": [ "# Descriptors for every clone-half, tagged with the clone and the measured half.\n", "import subprocess\n", "\n", "FEATURES = SET / \"features_energetics.tsv\"\n", "\n", "if not FEATURES.exists():\n", " t0, frames = time.time(), []\n", " for d in halves:\n", " clone, half = d.name.rsplit(\"_\", 1)\n", " out = SET / f\"{d.name}.tsv\"\n", " subprocess.run([sys.executable, \"-m\", \"tcren\", \"features\", \"-s\", f\"{d}/*.pdb\",\n", " \"-i\", \"energetics\", \"-t\", \"0\", \"-o\", str(out)],\n", " check=True, capture_output=True, text=True)\n", " frames.append(pl.read_csv(out, separator=\"\\t\", infer_schema_length=None)\n", " .with_columns(pl.lit(clone).alias(\"clone\"), pl.lit(half).alias(\"half\")))\n", " pl.concat(frames, how=\"vertical_relaxed\").write_csv(FEATURES, separator=\"\\t\")\n", " print(f\"featurised {sum(f.height for f in frames)} structures in {time.time() - t0:.0f} s\")\n", "\n", "feats = pl.read_csv(FEATURES, separator=\"\\t\", infer_schema_length=None)\n", "print(f\"{feats.height} rows x {len(feats.columns) - 3} descriptors\")\n", "print(feats.group_by(\"clone\", \"half\").len().sort(\"clone\", \"half\"))\n" ] }, { "cell_type": "markdown", "id": "0b691796", "metadata": { "language": "markdown" }, "source": [ "## 3 \u00b7 The score, and nothing is fitted in it\n", "\n", "`tcren.score.peptide_score` is tier 0: no transform, no covariance, no hold-out, no coefficient. The\n", "direction is fixed by the potential, and the potential is Boltzmann-inverted from crystal contact\n", "statistics.\n", "\n", "This is the instrument for peptide ranking against a fixed receptor, and it is **not** the instrument\n", "for receptor ranking: on a receptor benchmark it reads below chance, which is a property of the\n", "reference frame rather than a defect. `score_vdjdb_panel.ipynb` is the receptor task." ] }, { "cell_type": "code", "execution_count": 4, "id": "6c7dfd37", "metadata": { "execution": { "iopub.execute_input": "2026-09-02T02:57:13.853092Z", "iopub.status.busy": "2026-09-02T02:57:13.852990Z", "iopub.status.idle": "2026-09-02T02:57:13.858399Z", "shell.execute_reply": "2026-09-02T02:57:13.857996Z" }, "language": "python" }, "outputs": [ { "data": { "text/html": [ "
\n", "shape: (5, 6)
complex.idclonehalfdPhi_tcr_pepdPhi_pep_mhcpeptide_score
strstrstrf64f64f64
"ALWGPDPAAA""1e6""best"-0.450486-4.985.430486
"CIFGPDFKVV""1e6""best"1.007804-7.936.922196
"CIFGPDFPVI""1e6""best"2.865593-10.417.544407
"CIFGPDWKVI""1e6""best"1.389202-8.236.840798
"CIFGPDWKVV""1e6""best"1.389202-7.676.280798
" ], "text/plain": [ "shape: (5, 6)\n", "\u250c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u252c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u252c\u2500\u2500\u2500\u2500\u2500\u2500\u252c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u252c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u252c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2510\n", "\u2502 complex.id \u2506 clone \u2506 half \u2506 dPhi_tcr_pep \u2506 dPhi_pep_mhc \u2506 peptide_score \u2502\n", "\u2502 --- \u2506 --- \u2506 --- \u2506 --- \u2506 --- \u2506 --- \u2502\n", "\u2502 str \u2506 str \u2506 str \u2506 f64 \u2506 f64 \u2506 f64 \u2502\n", "\u255e\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u256a\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u256a\u2550\u2550\u2550\u2550\u2550\u2550\u256a\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u256a\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u256a\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2561\n", "\u2502 ALWGPDPAAA \u2506 1e6 \u2506 best \u2506 -0.450486 \u2506 -4.98 \u2506 5.430486 \u2502\n", "\u2502 CIFGPDFKVV \u2506 1e6 \u2506 best \u2506 1.007804 \u2506 -7.93 \u2506 6.922196 \u2502\n", "\u2502 CIFGPDFPVI \u2506 1e6 \u2506 best \u2506 2.865593 \u2506 -10.41 \u2506 7.544407 \u2502\n", "\u2502 CIFGPDWKVI \u2506 1e6 \u2506 best \u2506 1.389202 \u2506 -8.23 \u2506 6.840798 \u2502\n", "\u2502 CIFGPDWKVV \u2506 1e6 \u2506 best \u2506 1.389202 \u2506 -7.67 \u2506 6.280798 \u2502\n", "\u2514\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2534\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2534\u2500\u2500\u2500\u2500\u2500\u2500\u2534\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2534\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2534\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2518" ] }, "execution_count": 4, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# Tier 0: the poly-alanine-referenced recognition energy over both peptide-bearing interfaces.\n", "from tcren.score import peptide_score\n", "\n", "lib = feats.with_columns(pl.Series(\"peptide_score\", peptide_score(feats)))\n", "lib = lib.with_columns((pl.col(\"half\") == \"best\").cast(pl.Int8).alias(\"y\"))\n", "lib.select(\"complex.id\", \"clone\", \"half\", \"dPhi_tcr_pep\", \"dPhi_pep_mhc\", \"peptide_score\").head(5)\n" ] }, { "cell_type": "markdown", "id": "cfc836fe", "metadata": { "language": "markdown" }, "source": [ "### Why the reference, and why two interfaces\n", "\n", "Each of these 2,103 models carries its **own** generated pose: the peptide was swapped and the complex\n", "re-folded, so neither the receptor nor the groove is held fixed across a clone's library. Measured\n", "below, the TCR:MHC energy $\\Phi_{\\mathrm{TCR:MHC}}$ spans several statistical-potential units *within*\n", "a single clone even though no clone changes its receptor or its allele.\n", "\n", "That spread is the reason the score is built on $\\Delta\\Phi$ and not on $\\Phi$. A raw interface energy\n", "read off an independently generated complex partly reports the pose the generator chose rather than the\n", "peptide it was asked about; the poly-alanine reference subtracts what the placement contributes and\n", "leaves the sequence's. The two peptide-bearing interfaces are the two that the reference difference is\n", "non-zero on \u2014 the third cancels identically when the peptide is threaded on a **fixed** contact map,\n", "which is what section 7 does.\n" ] }, { "cell_type": "code", "execution_count": 5, "id": "81b6de25", "metadata": { "execution": { "iopub.execute_input": "2026-09-02T02:57:13.859570Z", "iopub.status.busy": "2026-09-02T02:57:13.859491Z", "iopub.status.idle": "2026-09-02T02:57:13.863547Z", "shell.execute_reply": "2026-09-02T02:57:13.863210Z" }, "language": "python" }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "1e6 n = 325 Phi_tcr_mhc min -3.650 max +3.030 spread 6.68\n", "4c6 n = 321 Phi_tcr_mhc min -2.410 max +5.130 spread 7.54\n", "868 n = 321 Phi_tcr_mhc min -1.810 max +2.050 spread 3.86\n", "ila1 n = 325 Phi_tcr_mhc min -4.030 max +4.300 spread 8.33\n", "mel5 n = 325 Phi_tcr_mhc min -0.000 max +5.410 spread 5.41\n", "mel8 n = 260 Phi_tcr_mhc min -2.630 max +4.800 spread 7.43\n", "sb27 n = 226 Phi_tcr_mhc min -5.150 max +1.200 spread 6.35\n" ] } ], "source": [ "# Each model carries its own generated pose, so even the receptor-side energy moves within a clone.\n", "# This is what the poly-alanine reference in peptide_score is there to remove.\n", "for (clone,), g in sorted(lib.group_by(\"clone\"), key=lambda kv: kv[0][0]):\n", " v = g[\"Phi_tcr_mhc\"].to_numpy()\n", " print(f\"{clone:5s} n = {len(v):4d} Phi_tcr_mhc min {v.min():+7.3f} max {v.max():+7.3f} \"\n", " f\"spread {v.max() - v.min():.2f}\")\n" ] }, { "cell_type": "markdown", "id": "fa026bf4", "metadata": { "language": "markdown" }, "source": [ "## 4 \u00b7 Per-clone ranking\n", "\n", "Each clone is its own ranking problem: its library's best half against its own worst half, ranked by\n", "`peptide_score`. Nothing is standardised across clones and nothing is pooled \u2014 the receptor differs, so\n", "the absolute energies are not comparable between rows of the table below." ] }, { "cell_type": "code", "execution_count": 6, "id": "bf5ac636", "metadata": { "execution": { "iopub.execute_input": "2026-09-02T02:57:13.864718Z", "iopub.status.busy": "2026-09-02T02:57:13.864645Z", "iopub.status.idle": "2026-09-02T02:57:13.973214Z", "shell.execute_reply": "2026-09-02T02:57:13.972835Z" }, "language": "python" }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "median per-clone ROC-AUC 0.999\n", "clones above chance 7 of 7\n", "clones above 0.90 6 of 7\n" ] }, { "data": { "text/html": [ "
\n", "shape: (7, 5)
clonenn_bestroc_aucpr_auc
stri64i64f64f64
"1e6"3251610.9995080.99951
"4c6"3211610.9877330.987205
"868"3211610.7045030.592189
"ila1"3251611.01.0
"mel5"3251611.01.0
"mel8"2601640.9528070.973744
"sb27"2261620.9988430.999552
" ], "text/plain": [ "shape: (7, 5)\n", "\u250c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u252c\u2500\u2500\u2500\u2500\u2500\u252c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u252c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u252c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2510\n", "\u2502 clone \u2506 n \u2506 n_best \u2506 roc_auc \u2506 pr_auc \u2502\n", "\u2502 --- \u2506 --- \u2506 --- \u2506 --- \u2506 --- \u2502\n", "\u2502 str \u2506 i64 \u2506 i64 \u2506 f64 \u2506 f64 \u2502\n", "\u255e\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u256a\u2550\u2550\u2550\u2550\u2550\u256a\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u256a\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u256a\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2561\n", "\u2502 1e6 \u2506 325 \u2506 161 \u2506 0.999508 \u2506 0.99951 \u2502\n", "\u2502 4c6 \u2506 321 \u2506 161 \u2506 0.987733 \u2506 0.987205 \u2502\n", "\u2502 868 \u2506 321 \u2506 161 \u2506 0.704503 \u2506 0.592189 \u2502\n", "\u2502 ila1 \u2506 325 \u2506 161 \u2506 1.0 \u2506 1.0 \u2502\n", "\u2502 mel5 \u2506 325 \u2506 161 \u2506 1.0 \u2506 1.0 \u2502\n", "\u2502 mel8 \u2506 260 \u2506 164 \u2506 0.952807 \u2506 0.973744 \u2502\n", "\u2502 sb27 \u2506 226 \u2506 162 \u2506 0.998843 \u2506 0.999552 \u2502\n", "\u2514\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2534\u2500\u2500\u2500\u2500\u2500\u2534\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2534\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2534\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2518" ] }, "execution_count": 6, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# ROC-AUC of peptide_score, best half against worst half, one row per clone.\n", "from sklearn.metrics import average_precision_score, roc_auc_score\n", "\n", "rows = []\n", "for (clone,), g in sorted(lib.group_by(\"clone\"), key=lambda kv: kv[0][0]):\n", " y, v = g[\"y\"].to_numpy(), g[\"peptide_score\"].to_numpy()\n", " ok = np.isfinite(v)\n", " rows.append({\"clone\": clone, \"n\": len(y), \"n_best\": int(y.sum()),\n", " \"roc_auc\": roc_auc_score(y[ok], v[ok]),\n", " \"pr_auc\": average_precision_score(y[ok], v[ok])})\n", "per_clone = pl.DataFrame(rows)\n", "\n", "roc = per_clone[\"roc_auc\"].to_numpy()\n", "print(f\"median per-clone ROC-AUC {np.median(roc):.3f}\")\n", "print(f\"clones above chance {int((roc > 0.5).sum())} of {len(roc)}\")\n", "print(f\"clones above 0.90 {int((roc > 0.9).sum())} of {len(roc)}\")\n", "per_clone\n" ] }, { "cell_type": "markdown", "id": "48e52dd0", "metadata": { "language": "markdown" }, "source": [ "Six of the seven clones separate their own library halves almost perfectly. The seventh, `868`, does\n", "not, and its cognate epitope is the HIV-1 Gag p17 nonamer `SLYNTVATL`. It is reported here rather than\n", "dropped: a per-clone table shows which receptor the instrument works on, which a pooled AUC over 2,103\n", "models cannot." ] }, { "cell_type": "markdown", "id": "23120c21", "metadata": { "language": "markdown" }, "source": [ "## 5 \u00b7 The graded read-out\n", "\n", "Best-against-worst is a binarisation of a continuous measurement: `cpl_score` is the assayed activation\n", "itself, and the deposited halves are the top and the bottom of that same quantity. Reporting the rank\n", "correlation against it puts the ranking on the assay's own scale rather than on a threshold applied\n", "to it.\n", "\n", "Spearman, because neither the assay's units nor the potential's are on a common interval scale. Within\n", "clone, because pooling across receptors would read a between-receptor offset rather than a within-library\n", "ordering \u2014 the absolute energies in the table above are not comparable between clones." ] }, { "cell_type": "code", "execution_count": 7, "id": "752178a2", "metadata": { "execution": { "iopub.execute_input": "2026-09-02T02:57:13.974465Z", "iopub.status.busy": "2026-09-02T02:57:13.974374Z", "iopub.status.idle": "2026-09-02T02:57:13.982214Z", "shell.execute_reply": "2026-09-02T02:57:13.981833Z" }, "language": "python" }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "joined 2102 of 2103 structures (1 not in the assay table)\n", "\n", "median within-clone Spearman rho 0.708\n" ] }, { "data": { "text/html": [ "
\n", "shape: (7, 4)
clonenspearman_rhop_value
stri64f64f64
"1e6"3250.762325.3644e-63
"4c6"3210.7080713.9326e-50
"868"3210.1898540.000628
"ila1"3250.7654028.6068e-64
"mel5"3250.7905359.2162e-71
"mel8"2600.4647952.4371e-15
"sb27"2250.5826827.4592e-22
" ], "text/plain": [ "shape: (7, 4)\n", "\u250c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u252c\u2500\u2500\u2500\u2500\u2500\u252c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u252c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2510\n", "\u2502 clone \u2506 n \u2506 spearman_rho \u2506 p_value \u2502\n", "\u2502 --- \u2506 --- \u2506 --- \u2506 --- \u2502\n", "\u2502 str \u2506 i64 \u2506 f64 \u2506 f64 \u2502\n", "\u255e\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u256a\u2550\u2550\u2550\u2550\u2550\u256a\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u256a\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2561\n", "\u2502 1e6 \u2506 325 \u2506 0.76232 \u2506 5.3644e-63 \u2502\n", "\u2502 4c6 \u2506 321 \u2506 0.708071 \u2506 3.9326e-50 \u2502\n", "\u2502 868 \u2506 321 \u2506 0.189854 \u2506 0.000628 \u2502\n", "\u2502 ila1 \u2506 325 \u2506 0.765402 \u2506 8.6068e-64 \u2502\n", "\u2502 mel5 \u2506 325 \u2506 0.790535 \u2506 9.2162e-71 \u2502\n", "\u2502 mel8 \u2506 260 \u2506 0.464795 \u2506 2.4371e-15 \u2502\n", "\u2502 sb27 \u2506 225 \u2506 0.582682 \u2506 7.4592e-22 \u2502\n", "\u2514\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2534\u2500\u2500\u2500\u2500\u2500\u2534\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2534\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2518" ] }, "execution_count": 7, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# Spearman rho of peptide_score against the graded activation score, within clone.\n", "from scipy.stats import spearmanr\n", "\n", "graded = lib.join(assay.select(\"complex.id\", \"clone\", \"cpl_score\"),\n", " on=[\"complex.id\", \"clone\"], how=\"inner\")\n", "print(f\"joined {graded.height} of {lib.height} structures \"\n", " f\"({lib.height - graded.height} not in the assay table)\")\n", "\n", "rows = []\n", "for (clone,), g in sorted(graded.group_by(\"clone\"), key=lambda kv: kv[0][0]):\n", " v, a = g[\"peptide_score\"].to_numpy(), g[\"cpl_score\"].to_numpy()\n", " ok = np.isfinite(v) & np.isfinite(a)\n", " rho, p = spearmanr(v[ok], a[ok])\n", " rows.append({\"clone\": clone, \"n\": int(ok.sum()), \"spearman_rho\": rho, \"p_value\": p})\n", "per_clone_rho = pl.DataFrame(rows)\n", "print(f\"\\nmedian within-clone Spearman rho \"\n", " f\"{np.median(per_clone_rho['spearman_rho'].to_numpy()):.3f}\")\n", "per_clone_rho\n" ] }, { "cell_type": "markdown", "id": "b771eead", "metadata": { "language": "markdown" }, "source": [ "## 6 \u00b7 Drawn\n", "\n", "Left: the score distribution per clone, measured best half against measured worst half. Right: the\n", "graded read-out for one clone, `peptide_score` against the assay's activation score." ] }, { "cell_type": "code", "execution_count": 8, "id": "46e5bb4f", "metadata": { "execution": { "iopub.execute_input": "2026-09-02T02:57:13.983257Z", "iopub.status.busy": "2026-09-02T02:57:13.983191Z", "iopub.status.idle": "2026-09-02T02:57:14.440948Z", "shell.execute_reply": "2026-09-02T02:57:14.440510Z" }, "language": "python" }, "outputs": [ { "data": { "image/png": "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", "text/plain": [ "
" ] }, "execution_count": 8, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": "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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "%matplotlib inline\n", "# Per-clone separation and the graded relation for one clone. Okabe-Ito palette.\n", "import matplotlib.pyplot as plt\n", "\n", "BEST, WORST = \"#D55E00\", \"#56B4E9\"\n", "SHOW = \"mel5\"\n", "\n", "plt.rcParams.update({\"font.size\": 8, \"axes.spines.top\": False, \"axes.spines.right\": False,\n", " \"figure.dpi\": 130})\n", "fig, (ax0, ax1) = plt.subplots(1, 2, figsize=(9.0, 3.4),\n", " gridspec_kw={\"width_ratios\": [7, 4], \"wspace\": 0.28})\n", "\n", "order = sorted(set(lib[\"clone\"]))\n", "for i, clone in enumerate(order):\n", " for half, colour, dx in ((\"best\", BEST, -0.16), (\"worst\", WORST, 0.16)):\n", " v = lib.filter((pl.col(\"clone\") == clone) & (pl.col(\"half\") == half))[\"peptide_score\"]\n", " v = v.to_numpy()\n", " ax0.scatter(np.full(len(v), i + dx) + np.random.default_rng(0).normal(0, 0.035, len(v)),\n", " v, s=3, color=colour, alpha=0.45, edgecolor=\"none\", zorder=2)\n", " ax0.hlines(np.median(v), i + dx - 0.13, i + dx + 0.13, color=\"0.15\", lw=1.2, zorder=3)\n", "ax0.set_xticks(range(len(order)))\n", "ax0.set_xticklabels(order)\n", "ax0.set_xlabel(\"T-cell clone\")\n", "ax0.set_ylabel(\"peptide_score (higher = better read)\")\n", "ax0.set_title(\"measured best half against measured worst half\", fontsize=8)\n", "ax0.scatter([], [], s=12, color=BEST, label=\"best half\")\n", "ax0.scatter([], [], s=12, color=WORST, label=\"worst half\")\n", "ax0.legend(frameon=False, loc=\"lower right\")\n", "\n", "g = graded.filter(pl.col(\"clone\") == SHOW)\n", "rho = float(per_clone_rho.filter(pl.col(\"clone\") == SHOW)[\"spearman_rho\"][0])\n", "ax1.scatter(g[\"peptide_score\"].to_numpy(), g[\"cpl_score\"].to_numpy(), s=5,\n", " color=\"#009E73\", alpha=0.55, edgecolor=\"none\")\n", "ax1.set_xlabel(\"peptide_score\")\n", "ax1.set_ylabel(\"assayed activation (cpl_score)\")\n", "ax1.set_title(f\"clone {SHOW}: rho = {rho:.3f}, n = {g.height}\", fontsize=8)\n", "fig\n" ] }, { "cell_type": "markdown", "id": "418e5a62", "metadata": { "language": "markdown" }, "source": [ "## 7 \u00b7 The other direction \u2014 a response matrix from one template\n", "\n", "The library above scores 2,103 models, one per peptide. The same question can be asked of a **single**\n", "structure: thread all twenty residues through each contacting peptide position on the template's own\n", "contact map and re-read the potential. That is `tcren cpl`, and it costs one batched call per interface\n", "rather than one model per peptide.\n", "\n", "Two reference states come out, and a cell means nothing except against one of them. `effect_equimolar`\n", "scores a residue against the 1/20 mixture, which is what a positional-scanning library actually\n", "realises and the right axis against a measured matrix. `effect_wild_type` scores it against the residue\n", "the template carries, which is the mutation-scan and neoantigen question. Positive is favourable on\n", "both." ] }, { "cell_type": "code", "execution_count": 9, "id": "14e04b9d", "metadata": { "execution": { "iopub.execute_input": "2026-09-02T02:57:14.442214Z", "iopub.status.busy": "2026-09-02T02:57:14.442073Z", "iopub.status.idle": "2026-09-02T02:57:14.447914Z", "shell.execute_reply": "2026-09-02T02:57:14.447597Z" }, "language": "python" }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "200 cells = 10 contacting positions x 20 residues\n", "shape: (2, 2)\n", "\u250c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u252c\u2500\u2500\u2500\u2500\u2500\u2510\n", "\u2502 interface_class \u2506 len \u2502\n", "\u2502 --- \u2506 --- \u2502\n", "\u2502 str \u2506 u32 \u2502\n", "\u255e\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u256a\u2550\u2550\u2550\u2550\u2550\u2561\n", "\u2502 anchor \u2506 20 \u2502\n", "\u2502 receptor \u2506 180 \u2502\n", "\u2514\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2534\u2500\u2500\u2500\u2500\u2500\u2518\n" ] }, { "data": { "text/html": [ "
\n", "shape: (8, 6)
poswt_aaaainterface_classeffect_equimolareffect_wild_type
i64strstrstrf64f64
8"L""I""receptor"3.2422781.159913
2"L""F""receptor"2.9619860.30304
2"L""L""receptor"2.6589450.0
5"I""I""receptor"2.5699680.0
1"E""F""receptor"2.5259863.915961
7"I""I""receptor"2.5024460.0
1"E""L""receptor"2.3029453.69292
6"G""I""receptor"2.2368262.295054
" ], "text/plain": [ "shape: (8, 6)\n", "\u250c\u2500\u2500\u2500\u2500\u2500\u252c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u252c\u2500\u2500\u2500\u2500\u2500\u252c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u252c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u252c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2510\n", "\u2502 pos \u2506 wt_aa \u2506 aa \u2506 interface_class \u2506 effect_equimolar \u2506 effect_wild_type \u2502\n", "\u2502 --- \u2506 --- \u2506 --- \u2506 --- \u2506 --- \u2506 --- \u2502\n", "\u2502 i64 \u2506 str \u2506 str \u2506 str \u2506 f64 \u2506 f64 \u2502\n", "\u255e\u2550\u2550\u2550\u2550\u2550\u256a\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u256a\u2550\u2550\u2550\u2550\u2550\u256a\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u256a\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u256a\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2561\n", "\u2502 8 \u2506 L \u2506 I \u2506 receptor \u2506 3.242278 \u2506 1.159913 \u2502\n", "\u2502 2 \u2506 L \u2506 F \u2506 receptor \u2506 2.961986 \u2506 0.30304 \u2502\n", "\u2502 2 \u2506 L \u2506 L \u2506 receptor \u2506 2.658945 \u2506 0.0 \u2502\n", "\u2502 5 \u2506 I \u2506 I \u2506 receptor \u2506 2.569968 \u2506 0.0 \u2502\n", "\u2502 1 \u2506 E \u2506 F \u2506 receptor \u2506 2.525986 \u2506 3.915961 \u2502\n", "\u2502 7 \u2506 I \u2506 I \u2506 receptor \u2506 2.502446 \u2506 0.0 \u2502\n", "\u2502 1 \u2506 E \u2506 L \u2506 receptor \u2506 2.302945 \u2506 3.69292 \u2502\n", "\u2502 6 \u2506 G \u2506 I \u2506 receptor \u2506 2.236826 \u2506 2.295054 \u2502\n", "\u2514\u2500\u2500\u2500\u2500\u2500\u2534\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2534\u2500\u2500\u2500\u2500\u2500\u2534\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2534\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2534\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2518" ] }, "execution_count": 9, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# The predicted response matrix of one template: clone mel5 on its cognate ELAGIGILTV.\n", "TEMPLATE = SET / \"mel5_best\" / \"ELAGIGILTV.pdb\"\n", "MATRIX = SET / \"mel5_response_matrix.csv\"\n", "\n", "if not MATRIX.exists():\n", " subprocess.run([sys.executable, \"-m\", \"tcren\", \"cpl\", \"-s\", str(TEMPLATE), \"-o\", str(MATRIX)],\n", " check=True, capture_output=True, text=True)\n", "\n", "rm = pl.read_csv(MATRIX)\n", "print(f\"{rm.height} cells = {rm['pos'].n_unique()} contacting positions x {rm['aa'].n_unique()} residues\")\n", "print(rm.group_by(\"interface_class\").len().sort(\"interface_class\"))\n", "rm.sort(\"effect_equimolar\", descending=True).select(\n", " \"pos\", \"wt_aa\", \"aa\", \"interface_class\", \"effect_equimolar\", \"effect_wild_type\").head(8)\n" ] }, { "cell_type": "code", "execution_count": 10, "id": "9aa8b6c2", "metadata": { "execution": { "iopub.execute_input": "2026-09-02T02:57:14.448937Z", "iopub.status.busy": "2026-09-02T02:57:14.448872Z", "iopub.status.idle": "2026-09-02T02:57:14.596075Z", "shell.execute_reply": "2026-09-02T02:57:14.595680Z" }, "language": "python" }, "outputs": [ { "data": { "image/png": "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", "text/plain": [ "
" ] }, "execution_count": 10, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": "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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# The matrix as a heat map: positions down, residues across, scored against the 1/20 mixture.\n", "AA = list(\"ACDEFGHIKLMNPQRSTVWY\")\n", "positions = sorted(rm[\"pos\"].unique().to_list())\n", "grid = np.full((len(positions), len(AA)), np.nan)\n", "lookup = {(r[\"pos\"], r[\"aa\"]): r[\"effect_equimolar\"] for r in rm.iter_rows(named=True)}\n", "for i, p in enumerate(positions):\n", " for j, a in enumerate(AA):\n", " grid[i, j] = lookup.get((p, a), np.nan)\n", "\n", "wt = {r[\"pos\"]: r[\"wt_aa\"] for r in rm.iter_rows(named=True)}\n", "lim = np.nanmax(np.abs(grid))\n", "\n", "fig, ax = plt.subplots(figsize=(6.4, 3.0))\n", "im = ax.imshow(grid, cmap=\"RdBu_r\", vmin=-lim, vmax=lim, aspect=\"auto\")\n", "ax.set_xticks(range(len(AA)))\n", "ax.set_xticklabels(AA)\n", "ax.set_yticks(range(len(positions)))\n", "ax.set_yticklabels([f\"{p} ({wt[p]})\" for p in positions])\n", "ax.set_xlabel(\"threaded residue\")\n", "ax.set_ylabel(\"peptide position (template residue)\")\n", "ax.set_title(\"mel5 / ELAGIGILTV: predicted effect against the 1/20 mixture\", fontsize=8)\n", "for i, p in enumerate(positions):\n", " ax.add_patch(plt.Rectangle((AA.index(wt[p]) - 0.5, i - 0.5), 1, 1,\n", " fill=False, edgecolor=\"0.1\", lw=1.0))\n", "fig.colorbar(im, ax=ax, shrink=0.85, label=\"effect_equimolar\")\n", "fig\n" ] }, { "cell_type": "markdown", "id": "00840822", "metadata": { "language": "markdown" }, "source": [ "## What this notebook establishes\n", "\n", "- Peptide ranking for a fixed receptor runs end to end from deposited coordinates with **nothing\n", " fitted anywhere**: the direction is the potential's, and no binding label, no hold-out and no\n", " coefficient enters `peptide_score`.\n", "- Reported **per clone**, because that is what says which receptor the instrument works on. Six of the\n", " seven clones separate their own library halves above 0.90 ROC-AUC; the seventh is reported at its\n", " measured value rather than dropped.\n", "- On the assay's own continuous scale the within-clone rank correlation is positive in all seven\n", " clones, with a median Spearman rho of 0.71 over 2,102 assayed models.\n", "- The same question asked of **one** structure is `tcren cpl`, which returns the whole\n", " position x residue matrix against two named reference states.\n", "\n", "**What it does not claim.** Not affinity, and not a rank that transfers between receptors: an absolute\n", "`peptide_score` from one clone's template cannot be compared with another clone's. And this is the\n", "peptide task only -- on a receptor benchmark the same score reads below chance, which is the reference\n", "frame speaking, not a defect.\n" ] } ], "metadata": { "kernelspec": { "display_name": "Python 3", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.12.13" } }, "nbformat": 4, "nbformat_minor": 5 }