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ADMET PK/PD Predict

ADMET and pharmacokinetic/pharmacodynamic property prediction workflows using ADMET Predictor, AOMP, OBA, Graph-pKa, DeepEsol, and Molecular Descriptors thro...
利用ADMET Predictor、AOMP、OBA、Graph‑pKa、DeepEsol和分子描述符等工具进行ADMET及药代动力学/药效动力学属性预测的工作流程。
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概述

ADMET & PKPD Skill

This skill groups property prediction workflows for assessing the pharmacokinetic and pharmacodynamic profile of small molecules, including:

  • comprehensive ADMET property prediction (absorption, distribution, metabolism, excretion, toxicity) with ADMET Predictor
  • AOX-mediated oxidative metabolism and site-of-metabolism prediction with AOMP
  • oral bioavailability prediction with OBA
  • pKa calculation for ionizable groups with Graph-pKa
  • aqueous solvation free-energy prediction with DeepEsol
  • physicochemical molecular descriptor calculation with Molecular Descriptors

When to use this skill

  • Predict ADMET properties (hERG, CYP, BBB, Caco-2, AMES, etc.) for a set of molecules
  • Identify AOX metabolic substrates and their sites of oxidative metabolism
  • Estimate oral bioavailability at a given dose
  • Calculate pKa values of ionizable functional groups
  • Predict aqueous solvation free energy (ΔG_solv)
  • Calculate physicochemical descriptors (MW, LogP, TPSA, etc.) for a molecule or a library

Method selection rule

  • For full ADMET profiling, use ADMET Predictor. Select specific features to narrow the output (e.g., T for toxicity only, M_CYP450 3A4 Inhibitor for a single endpoint).
  • For AOX-specific metabolism and site-of-metabolism (SOM) prediction, use AOMP.
  • For oral bioavailability at a specific dose, use OBA (requires both SMILES and dose in mg).
  • For pKa of ionizable groups, use Graph-pKa.
  • For aqueous solvation free energy, use DeepEsol.
  • For bulk physicochemical descriptors supporting PKPD modelling or Lipinski/Veber filtering, use Molecular Descriptors.
  • When input is a single SMILES or a small set, prefer the SMILES-input interface. When a file is provided or the library is large, prefer the file-upload interface.

Prerequisites

  1. Obtain a free SciMiner API key from https://sciminer.tech/utility.
  2. Store it outside this repository at ~/.config/sciminer/credentials.json with JSON shaped as {"api_key":"your_api_key_here"}.
  3. For SciMiner calls, read the API key from ~/.config/sciminer/credentials.json and send it as the X-Auth-Token header.
  4. Never print, persist, or store the API key in prompts, logs, or repository files. Agents should remember only the credential file path.

If ~/.config/sciminer/credentials.json is not available or does not contain an api_key field, stop and tell the user to obtain a free SciMiner API key from https://sciminer.tech/utility and store it in that file. Do not try to complete the task by switching to other tools or services.

Authoritative tool-doc source (required)

The published Markdown files under https://sciminer.tech/tool_api_files/ are

the single source of truth for provider_name, tool_name, allowed

parameters, file-upload behavior, request encoding, and the example

submission flow for this skill's included tools.

Use these SciMiner Markdown docs:

  • ADMET Predictor -> ADMET Predictor_api_doc.md
  • AOMP -> AOMP_api_doc.md
  • OBA -> OBA_api_doc.md
  • Graph-pKa -> Graph-pKa_api_doc.md
  • DeepEsol -> DeepEsol_api_doc.md
  • Molecular Descriptors -> Molecular Descriptors_api_doc.md

The agent MUST:

  1. Resolve the selected tool's Markdown file and read it before every

invocation.

  1. Never invent provider_name, tool_name, parameter names, enum values,

upload-field names, content type, or submission flow from memory.

  1. Extract and follow the selected doc section's exact:
    • Base URL
    • API endpoint
    • Content-Type
    • Authentication header
    • Tool Name
    • Method
    • Parameter table, including required fields and enum values
    • File-upload instructions and example code
  2. Choose the correct section if the selected doc contains multiple tool

variants, such as SMILES input vs file upload.

  1. Cite the selected Markdown doc as the payload source in summaries.

If a user-provided parameter is not present in the selected Markdown doc

section, ask for correction or drop it with an explanation.

Required workflow

  1. Determine which included tool matches the user's request.
  2. Read the corresponding Markdown file from

https://sciminer.tech/tool_api_files/.

  1. Choose the doc section that matches the user's input shape.
  2. Collect any missing required parameters from the user.
  3. Upload required file inputs exactly as described by the selected Markdown

doc and replace local paths with returned file_id values.

  1. Write or run the invocation code directly from the selected Markdown doc's

base-information block, parameter table, file-upload instructions, and

example code. Do not apply a shared invocation template or local registry

abstraction in this skill.

  1. Poll for the task result and return the share_url in the final user-facing

summary.

File upload rules

  • Upload every required file parameter described by the selected Markdown doc

before invocation.

  • Replace local paths in parameters with the returned file_id strings.
  • Use the upload form field documented by the selected Markdown doc. If the doc

only shows the generic SciMiner upload example and does not override the

field name, follow that example's default file field.

  • Skip optional file parameters that the user did not provide.

Expected result format

{
  "status": "SUCCESS",
  "result": {...},
  "task_id": "xxx",
   "share_url": "https://sciminer.tech/share?id=<task_id>&type=API_TOOL"
}

Workflow guidance

  • General ADMET or drug-likeness assessment, and endpoint-specific questions such as CYP inhibition, BBB penetration, hERG liability, AMES mutagenicity, or Caco-2 permeability -> ADMET Predictor
  • AOX-mediated metabolism or site-of-metabolism prediction -> AOMP
  • Oral bioavailability prediction -> OBA
  • pKa or ionization-state prediction -> Graph-pKa
  • Solubility or solvation free-energy prediction -> DeepEsol
  • Molecular weight, LogP, TPSA, rotatable bonds, H-bond donor/acceptor counts, or related descriptor requests -> Molecular Descriptors
  • Combined ADMET + descriptor + pKa panels -> chain ADMET Predictor, Molecular Descriptors, and Graph-pKa

Notes

  • Use the selected Markdown doc under

https://sciminer.tech/tool_api_files/ as the authoritative source for

payload construction and invoke-method details.

  • Read the SciMiner API key from ~/.config/sciminer/credentials.json and send it as the X-Auth-Token header. Do not print or persist the API key in prompts, logs, or repository files.
  • If ~/.config/sciminer/credentials.json is missing or does not contain an api_key field, stop and tell the user to obtain a free SciMiner API key from https://sciminer.tech/utility and store it in that file.
  • provider_name must exactly match the selected Markdown doc.
  • The features parameter for ADMET Predictor is optional; omitting it returns all endpoints. Passing category letters (A, D, M, E, T) returns all endpoints within that category.
  • Use the selected Markdown doc to determine request encoding, file-upload

field names, and any tool-specific submission details.

  • Important: When summarizing results to users, attach the share_url links of every successful task at the end so that users can view the online results of each invoked tool, rather than showing the file download links.
  • For long-running tasks without a fixed ETA, poll for no more than 600 seconds; if the task is still running, stop polling and return the current task_id and share_url so the user can check later.

版本历史

共 3 个版本

  • v1.0.4 当前
    2026-06-01 12:27
  • v1.0.3
    2026-05-07 04:00 安全 安全
  • v1.0.1
    2026-05-03 10:15 安全 安全

安全检测

腾讯云安全 (Keen)

队列中

腾讯云安全 (Sanbu)

队列中

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