31:T4d6,# Androgen Activity Database Welcome! This is an interactive notebook that lets the user explore the ${tb`[Androgen Activity Database (AADB)](https://aadb.cloud.edelweissconnect.com/)`} that was assembled and curated by the ${tb`[U.S. FDA](https://www.fda.gov/)`}. The notebook should aid the assessors and researchers to better evaluate the androgen disruption potential of a given compound based on the *in vitro* outcomes of chemically similar compounds. *More text on AADB to create the context around the notebook* **How to use the notebook?** The notebook helps the user to explore androgen activity for their target compound by listing all chemically similar compounds from the AADB and their *in vitro* outcomes. The workflow consists of three steps: 1. **Enter a target compound** structure as SMILES and define the chemical similarity threshold (Tanimoto). 2. **Select the assays you are interested in.** You are returned a diverse set of assays where chemically similar compounds were tested. Based on the assay properties (format, species, etc) you may want to narrow down this set. 3. **View the results from AADB.** After viewing the results you may want to return to Step 2 to refine or change your selection of assays.32:T423,plot_compounds = { var shtml var chembl_html var pubchem_html shtml = "" if (unique_compounds_svg.length > 0) { var i; for (i = 0; i < unique_compounds_svg.length; i++) { var this_svg = unique_compounds_svg[i]; var this_name = unique_compounds[i].Name; var chembl_url = unique_compounds[i]['CHEMBL URL'] var pubchem_url = unique_compounds[i]['Pubchem URL'] var chemblid = unique_compounds[i]['CHEMBLID'] var cid = unique_compounds[i]['CID'] if (chembl_url !== null) {chembl_html = " | " + chemblid + ""} else {chembl_html = ""} if (pubchem_url !== null) {pubchem_html = " | Pubchem CID " + cid + ""} else {pubchem_html= ""} shtml = shtml + "

" + this_name + "" + chembl_html + pubchem_html + " | Tanimoto similarity: " + similarities[i].toFixed(2) + "
" + this_svg + "

"; } } else { return "No similar compounds found"; } return html`${shtml}`; }33:[] 2f:{"title":"Androgen Activity Database","cells":[{"id":0,"value":"$31","pinned":false,"hidden":false,"mode":"md"},{"id":260,"value":"---\n## Step 1: Enter a target compound\nProvide the structure of the target compound as ${tb`[SMILES formula](https://en.wikipedia.org/wiki/Simplified_molecular-input_line-entry_system)`}.\n","pinned":false,"hidden":false,"mode":"md"},{"id":207,"value":"viewof smiles = textarea({placeholder: \"Enter SMILES\", submit: \"Confirm SMILES\", value: \"c2ccc(c1ccccc1)cc2\"})","pinned":false,"hidden":false,"mode":"ojs"},{"id":773,"value":"**This is the target compound molecular structure:**","pinned":false,"hidden":false,"mode":"md"},{"id":209,"value":"compound_figure = html`${svg}`","pinned":false,"hidden":false,"mode":"ojs"},{"id":775,"value":"**Set the Tanimoto chemical similarity threshold.** Compounds in the AADB exceeding this similarity threshold to the target compound will be displayed below.","pinned":false,"hidden":false,"mode":"md"},{"id":219,"value":"viewof tanimoto_threshold = slider({\n min: 0,\n max: 1,\n step: 0.05,\n value: 0.7,\n format: \",\",\n description: \"Tanimoto chemical similarity threshold\"\n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":780,"value":"**List of chemically similar compounds from AADB:**","pinned":false,"hidden":false,"mode":"md"},{"id":245,"value":"$32","pinned":false,"hidden":false,"mode":"ojs"},{"id":274,"value":"---\n## Step 2: Select the assays that you are interested in\nBelow you are given a table with the assays where similar compounds were tested. You may want to narrow down this set of assays based on their properties (such as assay format, group, type, endpoint or species) and by checking which assays will be actually displayed in the results. By default the top 5 assays are selected but feel free to make your own selection. The results will be displayed in Step 3.","pinned":false,"hidden":false,"mode":"md"},{"id":374,"value":"viewof selected_assays = {\n const preselected = unique_assays.slice(0, 5)\n return Table(unique_assays, {\n value: preselected,\n format: {\n \"PMID\": links => htl.html`${links[0]} `,\n \"PubChem\": links => htl.html`${links[0]} `,\n \"ChEMBL\": links => htl.html`${links[0]} `,\n },\n width: {\n \"Description\": 300\n },\n columns: [\"Assay ID\", \"Name\", \"Format\", \"Group\", \"Type\", \"Species\", \"PMID\", \"PubChem\", \"ChEMBL\"]})\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":63,"value":"viewof assayFormatDropdown = Select(unique_assay_formats, {label: \"Assay format:\", multiple: true, value: unique_assay_formats})","pinned":false,"hidden":false,"mode":"ojs"},{"id":65,"value":"viewof assayGroupDropdown = Select(unique_assay_groups, {label: \"Assay group:\", multiple: true, value: unique_assay_groups})","pinned":false,"hidden":false,"mode":"ojs"},{"id":70,"value":"viewof assayTypeDropdown = Select(unique_assay_types, {label: \"Assay type:\", multiple: true, value: unique_assay_types})","pinned":false,"hidden":false,"mode":"ojs"},{"id":73,"value":"viewof endpointDropdown = Select(unique_endpoints, {label: \"Endpoint:\", multiple: true, value: unique_endpoints})","pinned":false,"hidden":false,"mode":"ojs"},{"id":75,"value":"viewof speciesDropdown = Select(unique_species, {label: \"Species:\", multiple: true, value: unique_species})","pinned":false,"hidden":false,"mode":"ojs"},{"id":810,"value":"---\n## Step 3: View the results from AADB\n\nThe *in vitro* outcomes for chemically similar compounds in the selected assays are displayed on the two heatmaps below. In the first heatmap qualitative activities are shown to give quick insights about activity profiles. In the second heatmap quantitative activities are shown and you may pick a linear or logarithmic color scale.","pinned":false,"hidden":false,"mode":"md"},{"id":832,"value":"vl.markRect().data(selected_data_points)\n.encode(\n vl.x({field: \"Name\", type: \"nominal\", title: null}).scale({domain: unique_compound_names}),\n vl.y().fieldN(\"Assay ID\").scale({domain: selected_assay_ids}),\n vl.color({field: \"Comment\", type: \"nominal\", title: \"Activity\"}).scale({\n domain: [\"inactive\", \"very weak active (not quantified)\", \"active, but no AC50 derived\", \"active\", \"inconclusive/not determined\"],\n range: [\"#59A14F\", \"#EDC948\", \"#F28E2B\", \"#E15759\", \"#BAB0AC\"]}), \n vl.tooltip([\n {field: \"StringValue\", type: \"nominal\", title: \"Value\"},\n {field: \"Comment\", type: \"nominal\", title: \"Activity\"},\n {field: \"Assay Format\", type: \"nominal\", title: \"Format\"},\n {field: \"Assay Group\", type: \"nominal\", title: \"Group\"},\n {field: \"Assay Type\", type: \"nominal\", title: \"Type\"},\n {field: \"Species\", type: \"nominal\", title: \"Species\"},\n ]),\n).width({step: 50}).height({step: 50}).render()","pinned":false,"hidden":false,"mode":"ojs"},{"id":700,"value":"viewof scale_type = Inputs.radio([\"linear\", \"log\"], {label: \"Type of colour scale:\", value: 'linear'})","pinned":false,"hidden":false,"mode":"ojs"},{"id":482,"value":"vl.markRect().data(selected_data_points)\n.encode(\n vl.x({field: \"Name\", type: \"nominal\", title: null}).scale({domain: unique_compound_names}),\n vl.y().fieldN(\"Assay ID\").scale({domain: selected_assay_ids}),\n vl.color({field: \"CleanValue\", type: \"quantitative\", title: \"Value\"}).scale({scheme: 'redyellowgreen', type: scale_type}), \n vl.tooltip([\n {field: \"StringValue\", type: \"nominal\", title: \"Value\"},\n {field: \"Comment\", type: \"nominal\", title: \"Activity\"},\n {field: \"Assay Format\", type: \"nominal\", title: \"Format\"},\n {field: \"Assay Group\", type: \"nominal\", title: \"Group\"},\n {field: \"Assay Type\", type: \"nominal\", title: \"Type\"},\n {field: \"Species\", type: \"nominal\", title: \"Species\"},\n ]),\n).width({step: 50}).height({step: 50}).render()","pinned":false,"hidden":false,"mode":"ojs"},{"id":1004,"value":"---\n## Step 3b: hand-picking the results (optional)\n\nBelow the results from AADB are displayed in a tabular form and results in the heatmaps above will be instantly updated. You can manually pick which results should be displayed in the heatmap above. By default all the results are selected except for the cases when multiple values are provided for a single compound in a single assay.","pinned":false,"hidden":false,"mode":"md"},{"id":971,"value":"viewof selected_data_points = Table(double_filtered_data, {value: nonduplicated_data, columns: ['Name', 'Assay ID', 'Endpoint', 'Value', 'Unit']})","pinned":false,"hidden":false,"mode":"ojs"},{"id":1016,"value":"For a reference the compounds and assays where multiple values were provided for the same endpoint are listed below:","pinned":false,"hidden":false,"mode":"md"},{"id":1028,"value":"viewof table = Inputs.table(duplicated_data)","pinned":false,"hidden":false,"mode":"ojs"},{"id":196,"value":"---\n## Supplementary Code","pinned":false,"hidden":false,"mode":"md"},{"id":996,"value":"nonduplicated_data = getNonDuplicatedData(double_filtered_data)","pinned":false,"hidden":false,"mode":"ojs"},{"id":958,"value":"duplicated_data = findDuplicates(double_filtered_data)","pinned":false,"hidden":false,"mode":"ojs"},{"id":991,"value":"getNonDuplicatedData = function(data) {\n var non_duplicated_data = []\n for (var compound of compounds_after_filtering) {\n for (var assay_id of assays_after_filtering) {\n for (var endpoint of endpoints_after_filtering) {\n var data_subset = data.filter(item => (item['Endpoint'] == endpoint) & (item['Name'] == compound) & (item['Assay ID'] == assay_id))\n \n if (data_subset.length == 1) {\n non_duplicated_data.push(...data_subset)\n }\n }\n }\n }\n return non_duplicated_data\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":944,"value":"findDuplicates = function(data) {\n var properties_of_duplicates = []\n for (var compound of compounds_after_filtering) {\n for (var assay_id of assays_after_filtering) {\n for (var endpoint of endpoints_after_filtering) {\n var number_of_duplicates = data.filter(item => (item['Endpoint'] == endpoint) & (item['Name'] == compound) & (item['Assay ID'] == assay_id)).length\n if (number_of_duplicates > 1) {\n properties_of_duplicates.push({'Name': compound, 'Assay ID': assay_id, 'Endpoint': endpoint})\n }\n }\n }\n }\n return properties_of_duplicates\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":941,"value":"assays_after_filtering = Array.from(new Set(double_filtered_data.map(item => item[\"Assay ID\"]))) ","pinned":false,"hidden":false,"mode":"ojs"},{"id":938,"value":"compounds_after_filtering = Array.from(new Set(double_filtered_data.map(item => item[\"Name\"]))) ","pinned":false,"hidden":false,"mode":"ojs"},{"id":934,"value":"endpoints_after_filtering = Array.from(new Set(double_filtered_data.map(item => item[\"Endpoint\"]))) ","pinned":false,"hidden":false,"mode":"ojs"},{"id":485,"value":"double_filtered_data.map(measurement => {\n measurement.Comment = comment(measurement.Value)\n measurement.CleanValue = cleanup(measurement.Value)\n\n if (measurement.Unit === null) {\n measurement.StringValue = measurement.Value\n } else {\n measurement.StringValue = measurement.Value + \" \" + measurement.Unit\n }\n return measurement\n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":491,"value":"cleanup = function(value) {\n if (value == -10000) {\n return null\n } else if (value == -5000) {\n return null\n } else if (value == 1000000) {\n return null\n } else if (value == 99999) {\n return null\n } else if (value == 88888) {\n return null\n } else if (value == 77777) {\n return null\n } else {\n return value\n }\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":497,"value":"comment = function(value) {\n if (value == -10000) {\n return \"inactive\"\n } else if (value == -5000) {\n return \"very weak active (not quantified)\"\n } else if (value == 1000000) {\n return \"inactive\"\n } else if (value == 99999) {\n return \"active, but no AC50 derived\"\n } else if (value == 88888) {\n return \"inactive\"\n } else if (value == 77777) {\n return \"inconclusive/not determined\"\n } else {\n return \"active\"\n }\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":394,"value":"double_filtered_data = filtered_data.filter(item => selected_assay_ids.includes(item['Assay ID']))","pinned":false,"hidden":false,"mode":"ojs"},{"id":410,"value":"selected_assay_ids = selected_assays.map(row => row['Assay ID'])","pinned":false,"hidden":false,"mode":"ojs"},{"id":235,"value":"similarities = unique_compounds.map(compound => compound.SMILES.similarity)","pinned":false,"hidden":false,"mode":"ojs"},{"id":237,"value":"unique_compounds_svg = Promise.all(unique_compounds.map(item => {\n return function_get_svg_from_smiles(item[\"SMILES\"][\"canonical\"])\n}))","pinned":false,"hidden":false,"mode":"ojs"},{"id":214,"value":"svg = function_get_svg_from_smiles(smiles)","pinned":false,"hidden":false,"mode":"ojs"},{"id":184,"value":"calculate_mean = function(arr) {\n var total = 0;\n for(var i = 0; i < arr.length; i++) {\n total += arr[i];\n }\n var avg = total / arr.length;\n return avg\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":174,"value":"aggregate = function(data, compounds) {\n var i;\n var aggregated = [];\n for (i=0; i item[\"Name\"] == compounds[i])\n var values = subset.map(item => item[\"Value\"])\n var average = calculate_mean(values)\n aggregated.push({\n 'Name': subset[0][\"Name\"],\n \"Value\": average\n })\n }\n return aggregated\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":330,"value":"filtered_data = metadata\n .filter(item => assayFormatDropdown.includes(item[\"Assay Format\"]))\n .filter(item => assayGroupDropdown.includes(item[\"Assay Group\"]))\n .filter(item => assayTypeDropdown.includes(item[\"Assay Type\"]))\n .filter(item => endpointDropdown.includes(item[\"Endpoint\"]))\n .filter(item => speciesDropdown.includes(item[\"Species\"]))","pinned":false,"hidden":false,"mode":"ojs"},{"id":361,"value":"unique_assays = {\n var i;\n var arr = [];\n for (i = 0; i < unique_assay_id.length; i++) {\n var assay_id = unique_assay_id[i];\n var row = filtered_data.filter(item => item[\"Assay ID\"] == assay_id)[0]\n var obj = {\n 'Assay ID': row['Assay ID'],\n 'Name': row['Assay Name'],\n 'Format': row['Assay Format'],\n 'Group': row['Assay Group'],\n 'Type': row['Assay Type'],\n 'Description': row['Description'],\n 'Species': row['Species'],\n 'PMID': create_pubmed_field(row['PubMed ID']),\n 'PubChem': create_pubchem_assay_field(row['PubChem Assay ID']),\n 'ChEMBL': create_chembl_assay_field(row['ChEMBL Assay ID']),\n 'Article Title': row['Article Title'],\n 'Journal Name': row['Journal Name']\n }\n arr.push(obj)\n }\n return arr\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":898,"value":"function create_pubmed_field(pubmed_id) {\n if (pubmed_id !== null) {\n if (isNaN(Math.round(pubmed_id))) {\n var pubmed_ids = pubmed_id.split(\"|\")\n return [pubmed_id, \"https://pubmed.ncbi.nlm.nih.gov/\" + Math.round(pubmed_ids[0])]\n } else {\n return [Math.round(pubmed_id), \"https://pubmed.ncbi.nlm.nih.gov/\" + Math.round(pubmed_id)]\n }\n } else {\n return [\"\", \"\"]\n }\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":910,"value":"function create_pubchem_assay_field(pubchem_id) {\n if (pubchem_id !== null) {\n return [Math.round(pubchem_id), \"https://pubchem.ncbi.nlm.nih.gov/bioassay/\" + Math.round(pubchem_id)]\n } else {\n return [\"\", \"\"]\n }\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":912,"value":"function create_chembl_assay_field(chembl_id) {\n if (chembl_id !== null) {\n return [chembl_id, \"https://www.ebi.ac.uk/chembl/assay_report_card/\" + chembl_id]\n } else {\n return [\"\", \"\"]\n }\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":328,"value":"unique_assay_id = Array.from(new Set(filtered_data.map(item => item[\"Assay ID\"]))) ","pinned":false,"hidden":false,"mode":"ojs"},{"id":59,"value":"unique_assay_formats = Array.from(new Set(metadata.map(item => item[\"Assay Format\"]))) ","pinned":false,"hidden":false,"mode":"ojs"},{"id":53,"value":"unique_assay_groups = Array.from(new Set(metadata.map(item => item[\"Assay Group\"]))) ","pinned":false,"hidden":false,"mode":"ojs"},{"id":51,"value":"unique_assay_types = Array.from(new Set(metadata.map(item => item[\"Assay Type\"]))) ","pinned":false,"hidden":false,"mode":"ojs"},{"id":46,"value":"unique_endpoints = Array.from(new Set(metadata.map(item => item[\"Endpoint\"]))) ","pinned":false,"hidden":false,"mode":"ojs"},{"id":42,"value":"unique_species = Array.from(new Set(metadata.map(item => item[\"Species\"]))) ","pinned":false,"hidden":false,"mode":"ojs"},{"id":303,"value":"unique_compounds = {\n var i;\n var arr = [];\n for (i = 0; i < unique_compound_names.length; i++) {\n var compound_name = unique_compound_names[i];\n var row = compounds_dataset.filter(item => item.Name == compound_name)[0]\n var chembl_url = null\n var pubchem_url = null\n var bindingdb_url = null\n if (row['CHEMBLID'] !== null) {chembl_url= \"https://www.ebi.ac.uk/chembl/compound_report_card/\" + row['CHEMBLID']}\n if (row['CID'] !== null) {pubchem_url = \"https://pubchem.ncbi.nlm.nih.gov/compound/\" + row['CID']}\n row['CHEMBL URL'] = chembl_url\n row['Pubchem URL'] = pubchem_url\n arr.push(row)\n }\n return arr\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":115,"value":"unique_compound_names = Array.from(new Set(compounds_dataset.map(item => item[\"Name\"])))","pinned":false,"hidden":false,"mode":"ojs"},{"id":18,"value":"metadata = fetch_dataset_to_array(dataset_url, {\n method: 'POST',\n body: JSON.stringify({\n columns: [\"Name\", \"Endpoint\", \"Assay ID\", \"Assay Name\", \"Assay Type\", \"Assay Group\", \"Assay Format\", \"Species\", \"SMILES\", \"Description\", \"Value\", \"Unit\", \"Article Title\", \"Journal Name\", \"PubMed ID\", \"ChEMBL Assay ID\", 'PubChem Assay ID'],\n condition: {\n ge: [{tanimotoSimilarity: [smiles, { column: [\"SMILES\"] }]}, tanimoto_threshold]\n },\n orderBy: [\n {expression: {tanimotoSimilarity: [smiles, { column: [\"SMILES\"] }]}, ordering: \"descending\"}\n ]\n }),\n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":16,"value":"function fetch_dataset_to_array(dataset_url, query_options) {\n return fetch(dataset_url, query_options).then(response_dataset => {\n if (!response_dataset.ok) throw new Error(response_dataset.status);\n return response_dataset.json();}).then(json => json.results.map(x => x.data));\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":210,"value":"function_get_svg_from_smiles = function get_svg_from_smiles(smiles) {\n const safeSmiles = encodeURIComponent(smiles);\n const svg_url = \"https://chemidconvert.cloud.douglasconnect.com/v1/asSvg?width=200&height=100&smiles=\" + safeSmiles;\n return fetch(svg_url).then(response => response.text());\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":851,"value":"compounds_dataset = fetch_dataset_to_array(compounds_dataset_url, {\n method: 'POST',\n body: JSON.stringify({\n //columns: [\"Name\", \"SMILES\", \"CHEMBLID\", \"CID\", \"BindingDB_ID\"],\n condition: {\n ge: [{tanimotoSimilarity: [smiles, { column: [\"SMILES\"] }]}, tanimoto_threshold]\n },\n orderBy: [\n {expression: {tanimotoSimilarity: [smiles, { column: [\"SMILES\"] }]}, ordering: \"descending\"}\n ]\n }),\n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":226,"value":"compounds_dataset_url = api_url + compounds_dataset_id + \"/versions/latest/data\"","pinned":false,"hidden":false,"mode":"ojs"},{"id":20,"value":"dataset_url = api_url + main_dataset_id + \"/versions/latest/data\"","pinned":false,"hidden":false,"mode":"ojs"},{"id":7,"value":"main_dataset_id = '2559f7fb-4a84-42aa-ac02-e29fc66c9dcc'//'be8f9ba7-bd8e-4c8d-9c84-260c9c0bf97d'","pinned":false,"hidden":false,"mode":"ojs"},{"id":225,"value":"compounds_dataset_id = '21b033c5-d048-41f5-b8a1-d5d8492f7048'","pinned":false,"hidden":false,"mode":"ojs"},{"id":12,"value":"api_url = 'https://api.aadb.cloud.edelweissconnect.com/datasets/'","pinned":false,"hidden":false,"mode":"ojs"},{"id":5,"value":"import {Select, Range, Toggle, Search, Table, Text} from \"@observablehq/inputs\"","pinned":false,"hidden":false,"mode":"ojs"},{"id":167,"value":"import {select, textarea, text, slider} from \"@jashkenas/inputs\"","pinned":false,"hidden":false,"mode":"ojs"},{"id":4,"value":"import {vl} from \"@vega/vega-lite-api\"","pinned":false,"hidden":false,"mode":"ojs"},{"id":791,"value":"import {tb} from \"@mariodelgadosr/target-blank\"\n","pinned":false,"hidden":false,"mode":"ojs"}],"files":"$W33","stdlib":"1","titling":"auto"}