mlx-examples/esm/notebooks/embeddings.ipynb
Vincent Amato 8e293bbc51 Add ESM
2025-08-16 15:59:51 -04:00

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{
"cells": [
{
"cell_type": "markdown",
"id": "acfe011d",
"metadata": {},
"source": [
"## Exploring Protein Relationships Through ESM-2 Embeddings\n",
"\n",
"Proteins are molecular machines with unique structures that determine their functions. ESM-2 treats protein sequences as a language, learning representations that capture evolutionary and functional relationships without relying on traditional sequence alignment.\n",
"\n",
"In this notebook, we'll explore how ESM-2 embeddings reveal relationships between six human proteins:\n",
"\n",
"**Oxygen Transport & Storage:**\n",
"- **Hemoglobin Beta**: The oxygen-carrying protein in red blood cells, part of the tetrameric hemoglobin complex\n",
"- **Myoglobin**: The oxygen storage protein in muscle tissue, structurally similar to individual hemoglobin subunits\n",
"\n",
"**Antimicrobial Defense:**\n",
"- **Cathelicidin (LL-37)**: An antimicrobial peptide that disrupts bacterial membranes and modulates immune responses\n",
"- **Defensin Beta 4A**: A small cysteine-rich antimicrobial peptide that directly kills bacteria and other pathogens\n",
"\n",
"**Structural Support:**\n",
"- **Erythroid Alpha-Spectrin**: Forms the flexible scaffolding that gives red blood cells their shape and helps them squeeze through tiny blood vessels\n",
"- **Dystrophin**: A massive protein that connects the muscle cell's internal framework to its surroundings, preventing damage during muscle contraction"
]
},
{
"cell_type": "markdown",
"id": "20f98f7f",
"metadata": {},
"source": [
"### Setup\n",
"\n",
"Here we import all neccessary libraries."
]
},
{
"cell_type": "code",
"execution_count": 32,
"id": "2bacd1ff",
"metadata": {},
"outputs": [],
"source": [
"import mlx.core as mx\n",
"import numpy as np\n",
"import matplotlib.pyplot as plt\n",
"import seaborn as sns\n",
"from sklearn.decomposition import PCA\n",
"from sklearn.manifold import TSNE\n",
"import pandas as pd"
]
},
{
"cell_type": "markdown",
"id": "5563c495",
"metadata": {},
"source": [
"These are our protein sequences, obtained from [UniProt](https://www.uniprot.org/)."
]
},
{
"cell_type": "code",
"execution_count": 33,
"id": "b8e9d6d2",
"metadata": {},
"outputs": [],
"source": [
"proteins = [\n",
" # Oxygen Transport & Storage\n",
" (\"Hemoglobin Beta\", \"MVHLTPEEKSAVTALWGKVNVDEVGGEALGRLLVVYPWTQRFFESFGDLSTPDAVMGNPKVKAHGKKVLGAFSDGLAHLDNLKGTFATLSELHCDKLHVDPENFRLLGNVLVCVLAHHFGKEFTPPVQAAYQKVVAGVANALAHKYH\"),\n",
" (\"Myoglobin\", \"MGLSDGEWQLVLNVWGKVEADIPGHGQEVLIRLFKGHPETLEKFDKFKHLKSEDEMKASEDLKKHGATVLTALGGILKKKGHHEAEIKPLAQSHATKHKIPVKYLEFISECIIQVLQSKHPGDFGADAQGAMNKALELFRKDMASNYKELGFQG\"),\n",
"\n",
" # Antimicrobial Defense\n",
" (\"Cathelicidin (LL-37)\", \"MKTQRDGHSLGRWSLVLLLLGLVMPLAIIAQVLSYKEAVLRAIDGINQRSSDANLYRLLDLDPRPTMDGDPDTPKPVSFTVKETVCPRTTQQSPEDCDFKKDGLVKRCMGTVTLNQARGSFDISCDKDNKRFALLGDFFRKSKEKIGKEFKRIVQRIKDFLRNLVPRTES\"),\n",
" (\"Defensin Beta 4A\", \"MRVLYLLFSFLFIFLMPLPGVFGGIGDPVTCLKSGAICHPVFCPRRYKQIGTCGLPGTKCCKKP\"),\n",
"\n",
" # Structural Support\n",
" (\"Erythroid Alpha-Spectrin\", \"MEQFPKETVVESSGPKVLETAEEIQERRQEVLTRYQSFKERVAERGQKLEDSYHLQVFKRDADDLGKWIMEKVNILTDKSYEDPTNIQGKYQKHQSLEAEVQTKSRLMSELEKTREERFTMGHSAHEETKAHIEELRHLWDLLLELTLEKGDQLLRALKFQQYVQECADILEWIGDKEAIATSVELGEDWERTEVLHKKFEDFQVELVAKEGRVVEVNQYANECAEENHPDLPLIQSKQNEVNAAWERLRGLALQRQKALSNAANLQRFKRDVTEAIQWIKEKEPVLTSEDYGKDLVASEGLFHSHKGLERNLAVMSDKVKELCAKAEKLTLSHPSDAPQIQEMKEDLVSSWEHIRALATSRYEKLQATYWYHRFSSDFDELSGWMNEKTAAINADELPTDVAGGEVLLDRHQQHKHEIDSYDDRFQSADETGQDLVNANHEASDEVREKMEILDNNWTALLELWDERHRQYEQCLDFHLFYRDSEQVDSWMSRQEAFLENEDLGNSLGSAEALLQKHEDFEEAFTAQEEKIITVDKTATKLIGDDHYDSENIKAIRDGLLARRDALREKAATRRRLLKESLLLQKLYEDSDDLKNWINKKKKLADDEDYKDIQNLKSRVQKQQVFEKELAVNKTQLENIQKTGQEMIEGGHYASDNVTTRLSEVASLWEELLEATKQKGTQLHEANQQLQFENNAEDLQRWLEDVEWQVTSEDYGKGLAEVQNRLRKHGLLESAVAARQDQVDILTDLAAYFEEIGHPDSKDIRARQESLVCRFEALKEPLATRKKKLLDLLHLQLICRDTEDEEAWIQETEPSATSTYLGKDLIASKKLLNRHRVILENIASHEPRIQEITERGNKMVEEGHFAAEDVASRVKSLNQNMESLRARAARRQNDLEANVQFQQYLADLHEAETWIREKEPIVDNTNYGADEEAAGALLKKHEAFLLDLNSFGDSMKALRNQANACQQQQAAPVEGVAGEQRVMALYDFQARSPREVTMKKGDVLTLLSSINKDWWKVEAADHQGIVPAVYVRRLAHDEFPMLPQRRREEPGNITQRQEQIENQYRSLLDRAEERRRRLLQRYNEFLLAYEAGDMLEWIQEKKAENTGVELDDVWELQKKFDEFQKDLNTNEPRLRDINKVADDLLFEGLLTPEGAQIRQELNSRWGSLQRLADEQRQLLGSAHAVEVFHREADDTKEQIEKKCQALSAADPGSDLFSVQALQRRHEGFERDLVPLGDKVTILGETAERLSESHPDATEDLQRQKMELNEAWEDLQGRTKDRKESLNEAQKFYLFLSKARDLQNWISSIGGMVSSQELAEDLTGIEILLERHQEHRADMEAEAPTFQALEDFSAELIDSGHHASPEIEKKLQAVKLERDDLEKAWEKRKKILDQCLELQMFQGNCDQVESWMVARENSLRSDDKSSLDSLEALMKKRDDLDKAITAQEGKITDLEHFAESLIADEHYAKEEIATRLQRVLDRWKALKAQLIDERTKLGDYANLKQFYRDLEELEEWISEMLPTACDESYKDATNIQRKYLKHQTFAHEVDGRSEQVHGVINLGNSLIECSACDGNEEAMKEQLEQLKEHWDHLLERTNDKGKKLNEASRQQRFNTSIRDFEFWLSEAETLLAMKDQARDLASAGNLLKKHQLLEREMLAREDALKDLNTLAEDLLSSGTFNVDQIVKKKDNVNKRFLNVQELAAAHHEKLKEAYALFQFFQDLDDEESWIEEKLIRVSSQDYGRDLQGVQNLLKKHKRLEGELVAHEPAIQNVLDMAEKLKDKAAVGQEEIQLRLAQFVEHWEKLKELAKARGLKLEESLEYLQFMQNAEEEEAWINEKNALAVRGDCGDTLAATQSLLMKHEALENDFAVHETRVQNVCAQGEDILNKVLQEESQNKEISSKIEALNEKTPSLAKAIAAWKLQLEDDYAFQEFNWKADVVEAWIADKETSLKTNGNGADLGDFLTLLAKQDTLDASLQSFQQERLPEITDLKDKLISAQHNQSKAIEERYAALLKRWEQLLEASAVHRQKLLEKQLPLQKAEDLFVEFAHKASALNNWCEKMEENLSEPVHCVSLNEIRQLQKDHEDFLASLARAQADFKCLLELDQQIKALGVPSSPYTWLTVEVLERTWKHLSDIIEEREQELQKEEARQVKNFEMCQEFEQNASTFLQWILETRAYFLDGSLLKETGTLESQLEANKRKQKEIQAMKRQLTKIVDLGDNLEDALILDIKYSTIGLAQQWDQLYQLGLRMQHNLEQQIQAKDIKGVSEETLKEFSTIYKHFDENLTGRLTHKEFRSCLRGLNYYLPMVEEDEHEPKFEKFLDAVDPGRKGYVSLEDYTAFLIDKESENIKSSDEIENAFQALAEGKSYITKEDMKQALTPEQVSFCATHMQQYMDPRGRSHLSGYDYVGFTNSYFGN\"),\n",
" (\"Dystrophin\", \"MLWWEEVEDCYEREDVQKKTFTKWVNAQFSKFGKQHIENLFSDLQDGRRLLDLLEGLTGQKLPKEKGSTRVHALNNVNKALRVLQNNNVDLVNIGSTDIVDGNHKLTLGLIWNIILHWQVKNVMKNIMAGLQQTNSEKILLSWVRQSTRNYPQVNVINFTTSWSDGLALNALIHSHRPDLFDWNSVVCQQSATQRLEHAFNIARYQLGIEKLLDPEDVDTTYPDKKSILMYITSLFQVLPQQVSIEAIQEVEMLPRPPKVTKEEHFQLHHQMHYSQQITVSLAQGYERTSSPKPRFKSYAYTQAAYVTTSDPTRSPFPSQHLEAPEDKSFGSSLMESEVNLDRYQTALEEVLSWLLSAEDTLQAQGEISNDVEVVKDQFHTHEGYMMDLTAHQGRVGNILQLGSKLIGTGKLSEDEETEVQEQMNLLNSRWECLRVASMEKQSNLHRVLMDLQNQKLKELNDWLTKTEERTRKMEEEPLGPDLEDLKRQVQQHKVLQEDLEQEQVRVNSLTHMVVVVDESSGDHATAALEEQLKVLGDRWANICRWTEDRWVLLQDILLKWQRLTEEQCLFSAWLSEKEDAVNKIHTTGFKDQNEMLSSLQKLAVLKADLEKKKQSMGKLYSLKQDLLSTLKNKSVTQKTEAWLDNFARCWDNLVQKLEKSTAQISQAVTTTQPSLTQTTVMETVTTVTTREQILVKHAQEELPPPPPQKKRQITVDSEIRKRLDVDITELHSWITRSEAVLQSPEFAIFRKEGNFSDLKEKVNAIEREKAEKFRKLQDASRSAQALVEQMVNEGVNADSIKQASEQLNSRWIEFCQLLSERLNWLEYQNNIIAFYNQLQQLEQMTTTAENWLKIQPTTPSEPTAIKSQLKICKDEVNRLSDLQPQIERLKIQSIALKEKGQGPMFLDADFVAFTNHFKQVFSDVQAREKELQTIFDTLPPMRYQETMSAIRTWVQQSETKLSIPQLSVTDYEIMEQRLGELQALQSSLQEQQSGLYYLSTTVKEMSKKAPSEISRKYQSEFEEIEGRWKKLSSQLVEHCQKLEEQMNKLRKIQNHIQTLKKWMAEVDVFLKEEWPALGDSEILKKQLKQCRLLVSDIQTIQPSLNSVNEGGQKIKNEAEPEFASRLETELKELNTQWDHMCQQVYARKEALKGGLEKTVSLQKDLSEMHEWMTQAEEEYLERDFEYKTPDELQKAVEEMKRAKEEAQQKEAKVKLLTESVNSVIAQAPPVAQEALKKELETLTTNYQWLCTRLNGKCKTLEEVWACWHELLSYLEKANKWLNEVEFKLKTTENIPGGAEEISEVLDSLENLMRHSEDNPNQIRILAQTLTDGGVMDELINEELETFNSRWRELHEEAVRRQKLLEQSIQSAQETEKSLHLIQESLTFIDKQLAAYIADKVDAAQMPQEAQKIQSDLTSHEISLEEMKKHNQGKEAAQRVLSQIDVAQKKLQDVSMKFRLFQKPANFEQRLQESKMILDEVKMHLPALETKSVEQEVVQSQLNHCVNLYKSLSEVKSEVEMVIKTGRQIVQKKQTENPKELDERVTALKLHYNELGAKVTERKQQLEKCLKLSRKMRKEMNVLTEWLAATDMELTKRSAVEGMPSNLDSEVAWGKATQKEIEKQKVHLKSITEVGEALKTVLGKKETLVEDKLSLLNSNWIAVTSRAEEWLNLLLEYQKHMETFDQNVDHITKWIIQADTLLDESEKKKPQQKEDVLKRLKAELNDIRPKVDSTRDQAANLMANRGDHCRKLVEPQISELNHRFAAISHRIKTGKASIPLKELEQFNSDIQKLLEPLEAEIQQGVNLKEEDFNKDMNEDNEGTVKELLQRGDNLQQRITDERKREEIKIKQQLLQTKHNALKDLRSQRRKKALEISHQWYQYKRQADDLLKCLDDIEKKLASLPEPRDERKIKEIDRELQKKKEELNAVRRQAEGLSEDGAAMAVEPTQIQLSKRWREIESKFAQFRRLNFAQIHTVREETMMVMTEDMPLEISYVPSTYLTEITHVSQALLEVEQLLNAPDLCAKDFEDLFKQEESLKNIKDSLQQSSGRIDIIHSKKTAALQSATPVERVKLQEALSQLDFQWEKVNKMYKDRQGRFDRSVEKWRRFHYDIKIFNQWLTEAEQFLRKTQIPENWEHAKYKWYLKELQDGIGQRQTVVRTLNATGEEIIQQSSKTDASILQEKLGSLNLRWQEVCKQLSDRKKRLEEQKNILSEFQRDLNEFVLWLEEADNIASIPLEPGKEQQLKEKLEQVKLLVEELPLRQGILKQLNETGGPVLVSAPISPEEQDKLENKLKQTNLQWIKVSRALPEKQGEIEAQIKDLGQLEKKLEDLEEQLNHLLLWLSPIRNQLEIYNQPNQEGPFDVKETEIAVQAKQPDVEEILSKGQHLYKEKPATQPVKRKLEDLSSEWKAVNRLLQELRAKQPDLAPGLTTIGASPTQTVTLVTQPVVTKETAISKLEMPSSLMLEVPALADFNRAWTELTDWLSLLDQVIKSQRVMVGDLEDINEMIIKQKATMQDLEQRRPQLEELITAAQNLKNKTSNQEARTIITDRIERIQNQWDEVQEHLQNRRQQLNEMLKDSTQWLEAKEEAEQVLGQARAKLESWKEGPYTVDAIQKKITETKQLAKDLRQWQTNVDVANDLALKLLRDYSADDTRKVHMITENINASWRSIHKRVSEREAALEETHRLLQQFPLDLEKFLAWLTEAETTANVLQDATRKERLLEDSKGVKELMKQWQDLQGEIEAHTDVYHNLDENSQKILRSLEGSDDAVLLQRRLDNMNFKWSELRKKSLNIRSHLEASSDQWKRLHLSLQELLVWLQLKDDELSRQAPIGGDFPAVQKQNDVHRAFKRELKTKEPVIMSTLETVRIFLTEQPLEGLEKLYQEPRELPPEERAQNVTRLLRKQAEEVNTEWEKLNLHSADWQRKIDETLERLRELQEATDELDLKLRQAEVIKGSWQPVGDLLIDSLQDHLEKVKALRGEIAPLKENVSHVNDLARQLTTLGIQLSPYNLSTLEDLNTRWKLLQVAVEDRVRQLHEAHRDFGPASQHFLSTSVQGPWERAISPNKVPYYINHETQTTCWDHPKMTELYQSLADLNNVRFSAYRTAMKLRRLQKALCLDLLSLSAACDALDQHNLKQNDQPMDILQIINCLTTIYDRLEQEHNNLVNVPLCVDMCLNWLLNVYDTGRTGRIRVLSFKTGIISLCKAHLEDKYRYLFKQVASSTGFCDQRRLGLLLHDSIQIPRQLGEVASFGGSNIEPSVRSCFQFANNKPEIEAALFLDWMRLEPQSMVWLPVLHRVAAAETAKHQAKCNICKECPIIGFRYRSLKHFNYDICQSCFFSGRVAKGHKMHYPMVEYCTPTTSGEDVRDFAKVLKNKFRTKRYFAKHPRMGYLPVQTVLEGDNMETPVTLINFWPVDSAPASSPQLSHDDTHSRIEHYASRLAEMENSNGSYLNDSISPNESIDDEHLLIQHYCQSLNQDSPLSQPRSPAQILISLESEERGELERILADLEEENRNLQAEYDRLKQQHEHKGLSPLPSPPEMMPTSPQSPRDAELIAEAKLLRQHKGRLEARMQILEDHNKQLESQLHRLRQLLEQPQAEAKVNGTTVSSPSTSLQRSDSSQPMLLRVVGSQTSDSMGEEDLLSPPQDTSTGLEEVMEQLNNSFPSSRGRNTPGKPMREDTM\"),\n",
"]"
]
},
{
"cell_type": "markdown",
"id": "c9621578",
"metadata": {},
"source": [
"### Loading the model and tokenizing a sequence\n",
"\n",
"Load the ESM-2 model. Here we will use the 650M parameter version. Change the path below to point to your converted checkpoint.\n",
"\n"
]
},
{
"cell_type": "code",
"execution_count": 34,
"id": "05696400",
"metadata": {},
"outputs": [],
"source": [
"import sys\n",
"sys.path.append(\"..\")\n",
"\n",
"from esm import ESM2\n",
"\n",
"esm_checkpoint = \"../checkpoints/mlx-esm2_t33_650M_UR50D\"\n",
"tokenizer, model = ESM2.from_pretrained(esm_checkpoint)"
]
},
{
"cell_type": "markdown",
"id": "2916adbb",
"metadata": {},
"source": [
"Here, we tokenize and decode the protein sequence for human Insulin."
]
},
{
"cell_type": "code",
"execution_count": 35,
"id": "47178dcd",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Sequence: MALWMRLLPLLALLALWGPDPAAAFVNQHLCGSHLVEALYLVCGERGFFYTPKTRREAEDLQVGQVELGGGPGAGSLQPLALEGSLQKRGIVEQCCTSICSLYQLENYCN\n",
"Tokens: [20, 5, 4, 22, 20, 10, 4, 4, 14, 4, 4, 5, 4, 4, 5, 4, 22, 6, 14, 13, 14, 5, 5, 5, 18, 7, 17, 16, 21, 4, 23, 6, 8, 21, 4, 7, 9, 5, 4, 19, 4, 7, 23, 6, 9, 10, 6, 18, 18, 19, 11, 14, 15, 11, 10, 10, 9, 5, 9, 13, 4, 16, 7, 6, 16, 7, 9, 4, 6, 6, 6, 14, 6, 5, 6, 8, 4, 16, 14, 4, 5, 4, 9, 6, 8, 4, 16, 15, 10, 6, 12, 7, 9, 16, 23, 23, 11, 8, 12, 23, 8, 4, 19, 16, 4, 9, 17, 19, 23, 17]\n",
"Decoded: MALWMRLLPLLALLALWGPDPAAAFVNQHLCGSHLVEALYLVCGERGFFYTPKTRREAEDLQVGQVELGGGPGAGSLQPLALEGSLQKRGIVEQCCTSICSLYQLENYCN\n"
]
}
],
"source": [
"human_insulin_sequence = \"MALWMRLLPLLALLALWGPDPAAAFVNQHLCGSHLVEALYLVCGERGFFYTPKTRREAEDLQVGQVELGGGPGAGSLQPLALEGSLQKRGIVEQCCTSICSLYQLENYCN\"\n",
"tokens = tokenizer.encode(human_insulin_sequence, add_special_tokens=False)\n",
"print(f\"Sequence: {human_insulin_sequence}\")\n",
"print(f\"Tokens: {tokens.tolist()}\")\n",
"print(f\"Decoded: {tokenizer.decode(tokens)}\")"
]
},
{
"cell_type": "markdown",
"id": "c1b73ded",
"metadata": {},
"source": [
"### Embedding sequences\n",
"\n",
"To compute the embeddings of our proteins, we pass each protein sequence through ESM-2's tokenizer to convert amino acids into token IDs, then extract the final layer representations using `get_sequence_representations()`. This process gives us a vector for each protein that captures its learned functional and evolutionary features."
]
},
{
"cell_type": "code",
"execution_count": 36,
"id": "cb470957",
"metadata": {},
"outputs": [],
"source": [
"def extract_embeddings_batch(model, protein_list):\n",
" \"\"\"Extract embeddings by processing all sequences in a batch.\"\"\"\n",
" sequences = [seq for _, seq in protein_list]\n",
" names = [name for name, _ in protein_list]\n",
" \n",
" tokens = model.tokenizer.batch_encode(sequences, add_special_tokens=True)\n",
" embeddings = model.get_sequence_representations(tokens, layer=-1)\n",
" \n",
" return embeddings, names"
]
},
{
"cell_type": "code",
"execution_count": 37,
"id": "38e83142",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"\n",
"Embedding shape: (6, 1280)\n",
"Each protein represented by 1280 features\n"
]
}
],
"source": [
"embeddings, protein_names = extract_embeddings_batch(model, proteins)\n",
"print(f\"\\nEmbedding shape: {embeddings.shape}\")\n",
"print(f\"Each protein represented by {embeddings.shape[1]} features\")"
]
},
{
"cell_type": "markdown",
"id": "fccd2a99",
"metadata": {},
"source": [
"### Protein embedding similarity matrix\n",
"\n",
"We can measure how similar the protein embeddings are by calculating a similarity matrix. We normalize each embedding to unit length and compute cosine similarities between all pairs, producing a matrix where values close to 1 indicate highly similar proteins and values close to 0 indicate dissimilar ones."
]
},
{
"cell_type": "code",
"execution_count": 38,
"id": "93d14fff",
"metadata": {},
"outputs": [],
"source": [
"def compute_similarity_matrix(embeddings):\n",
" \"\"\"Compute cosine similarity matrix for embeddings.\"\"\"\n",
" normalized = embeddings / mx.linalg.norm(embeddings, axis=1, keepdims=True)\n",
" similarity_matrix = normalized @ normalized.T\n",
" return similarity_matrix"
]
},
{
"cell_type": "code",
"execution_count": 39,
"id": "3485f854",
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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",
"text/plain": [
"<Figure size 800x600 with 2 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"similarity_matrix = compute_similarity_matrix(embeddings)\n",
"\n",
"plt.figure(figsize=(8, 6))\n",
"similarity_np = np.array(similarity_matrix)\n",
"\n",
"sim_df = pd.DataFrame(similarity_np, \n",
" index=protein_names, \n",
" columns=protein_names)\n",
"\n",
"sns.heatmap(sim_df, annot=True, cmap='viridis', \n",
" fmt='.3f', square=True, cbar_kws={'label': 'Cosine Similarity'})\n",
"plt.title('Protein Similarity Matrix (ESM-2 Embeddings)', fontsize=14)\n",
"plt.xticks(rotation=45, ha='right')\n",
"plt.yticks(rotation=0)\n",
"plt.tight_layout()\n",
"plt.show()"
]
},
{
"cell_type": "markdown",
"id": "1532dfc5",
"metadata": {},
"source": [
"The similarity matrix highlights clear expected relationships. Erythroid Alpha-Spectrin and Dystrophin are most similar (0.982), reflecting their shared role in cytoskeletal support. Hemoglobin Beta and Myoglobin also show high similarity (0.950), consistent with their oxygen-binding functions. Antimicrobial peptides Cathelicidin and Defensin Beta 4A likewise cluster closely (0.955), reflecting their common role in immunity. Alongside these expected patterns, some unexpected similarities appear, such as between Cathelicidin and Dystrophin (0.948) or Hemoglobin Beta and Alpha-Spectrin (0.931). These likely reflect sequence-level motifs or general structural tendencies that the embeddings capture, rather than direct functional relationships."
]
},
{
"cell_type": "markdown",
"id": "66794597",
"metadata": {},
"source": [
"### PCA visualization\n",
"\n",
"PCA (Principal Component Analysis) reduces high-dimensional data to a lower-dimensional representation by finding the directions of maximum variance in the data. This allows us to visualize our high-dimensional protein embeddings in 2D space while preserving the most important patterns of similarity and difference between proteins."
]
},
{
"cell_type": "code",
"execution_count": 42,
"id": "67afd74e",
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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",
"text/plain": [
"<Figure size 1200x500 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"pca = PCA(n_components=2)\n",
"pca_result = pca.fit_transform(np.array(embeddings))\n",
"\n",
"plt.figure(figsize=(12, 5))\n",
"\n",
"plt.subplot(1, 2, 1)\n",
"plt.scatter(pca_result[:, 0], pca_result[:, 1], s=100, alpha=0.7)\n",
"for i, name in enumerate(protein_names):\n",
" plt.annotate(name, (pca_result[i, 0], pca_result[i, 1]), \n",
" xytext=(5, 5), textcoords='offset points', fontsize=9)\n",
"plt.xlabel(f'PC1 ({pca.explained_variance_ratio_[0]:.1%} variance)')\n",
"plt.ylabel(f'PC2 ({pca.explained_variance_ratio_[1]:.1%} variance)')\n",
"plt.title('PCA of Protein Embeddings')\n",
"plt.grid(True, alpha=0.3)"
]
},
{
"cell_type": "markdown",
"id": "4dd24749",
"metadata": {},
"source": [
"The PCA analysis reveals clear groupings among the proteins, with the first two components capturing the majority of the variance in the embeddings. Hemoglobin Beta and Myoglobin cluster tightly in the upper right, reflecting their shared evolutionary history and common role in oxygen transport. Erythroid Alpha-Spectrin and Dystrophin separate into the lower left quadrant, consistent with their related cytoskeletal functions and structural importance in maintaining cell integrity. Cathelicidin and Defensin Beta 4A form another distinct cluster, aligning with their antimicrobial roles in innate immunity. The spatial separation of these groups highlights how the embeddings capture broad functional and structural distinctions, while also showing within-group proximity that reflects biological similarity."
]
}
],
"metadata": {
"kernelspec": {
"display_name": ".venv",
"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": "3.11.13"
}
},
"nbformat": 4,
"nbformat_minor": 5
}