“compound”的搜索结果

通过公开数据库查询化合物活性、分子性质和药物相互作用，整理候选口服药物的分子特征及基因与疾病的关联，为药物研发的前期调研提供支持。

• 查找针对特定靶点的活性化合物
• 评估候选口服药物的分子性质
• 调查相互作用和不良事件报告

Process molecular datasets in Python through a simpler interface to RDKit, a chemistry toolkit. Convert and standardize structures, calculate molecular properties, compare and cluster compounds, generate 3D conformations, and visualize results for drug discovery workflows.

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• Load and standardize molecular datasets
• Calculate molecular properties and similarities
• Cluster compounds and select diverse subsets

Audit saved project learnings against the current codebase to find outdated explanations, overlapping documents, and contradictions. Maintain the documentation with evidence-based updates, consolidation, replacement, or deletion, and deliver a per-document report with committed changes when applicable.

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• Checking saved learnings against current code
• Consolidating overlapping knowledge documents
• Correcting outdated paths and links

Search Rhea, a biochemical reaction database, using reaction IDs, compound names, enzyme classification numbers, or reaction terms. Get concise summaries of focused search results, with raw JSON available when you need machine-readable output.

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• Looking up a reaction by its Rhea ID
• Finding reactions associated with a compound
• Searching reactions by enzyme classification number

Look up compound–target binding data in BindingDB using PDB or UniProt identifiers, or search for similar chemical structures. Receive concise summaries of matching records, with full API responses saved to a file when requested.

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• Find ligands linked to a PDB identifier
• Look up binding data for a UniProt entry
• Search for compounds with similar structures

Generate new small molecules intended to bind a target protein with Boltz. The workflow covers cost estimation, job submission, result downloads, and ranking candidates by binding confidence or a score for improving promising molecules.

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• Generate binding candidates without an existing compound library
• Rank generated molecules by binding confidence
• Review solubility and permeability of promising candidates

Find the appropriate plugin for supported DeFi services, blockchain-based financial applications, using service names or native tokens. Guide installation with user confirmation, then pass the original request to the plugin, or show the available services.

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• Find the plugin for a specific DeFi service
• Identify a service from its native token
• Browse supported DApps

Refactor React components that have accumulated many boolean options. Apply component composition, meaning building interfaces from cooperating parts, and shared state patterns to design reusable component libraries and clearer APIs, with guidance specific to React 19.

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• Refactoring components with too many boolean props
• Designing reusable component library APIs
• Reviewing shared state and provider responsibilities

Use Pint to convert measurements, calculate with units, and check whether units describe compatible physical quantities. It also breaks quantities into values and units, simplifies compound units, and returns calculation results as JSON.

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• Converting measurements between unit systems
• Calculating with mixed units
• Checking the dimensional consistency of formulas

Review saved session learnings to find recurring successes, failures, and decisions. Consolidates similar patterns, proposes reusable skills, rules, event-triggered actions, or agent updates, and creates approved changes with references to the source sessions.

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• Finding recurring lessons in recent work
• Turning repeated procedures into skills
• Saving lessons from failures as rules

Use RDKit in Python to read molecular structures, calculate properties such as molecular weight, find similar compounds or specific structural features, and generate molecular drawings and 3D coordinates for chemistry research.

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• Calculating properties for a list of molecules
• Finding compounds similar to a reference molecule
• Filtering molecules by a specific structural feature

Search NIH Metabolomics Workbench for metabolite structures, study details, and experimental data. Standardize metabolite names with RefMet, find candidate compounds from mass spectrometry measurements, and filter studies by disease, sample source, or analytical method.

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• Finding studies that measure a specific metabolite
• Standardizing metabolite names with RefMet
• Finding compound candidates from mass spectrometry measurements

Standardizes molecular structures using the ChEMBL structure pipeline for normalization and parent selection plus RDKit rdMolStandardize for explicit custom steps such as tautomer canonicalization, salt/solvent stripping, charge handling, stereochemistry handling, mixture selection, and isotope normalization. Explicitly compares ChEMBL, canSARchem, RDKit, and PubChem standardization choices. Use when preparing libraries for QSAR training, joining datasets across sources, deduplicating compound collections, or building canonical compound registries.

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Transform session learnings into permanent capabilities (skills, rules, agents). Use when asked to "improve setup", "learn from sessions", "compound learnings", or "what patterns should become skills".

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Query ChEMBL (2M+ compounds, 19M+ bioactivity measurements, 13K+ targets) via the public REST/JSON API with plain `requests` — no SDK install required. Search compounds, retrieve IC50/Ki/EC50 bioactivities, find target inhibitors, run SAR, access drug mechanism/indication data.

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Query PubChem (110M+ compounds) directly via the PUG-REST/JSON API with plain `requests` — no SDK install required. Search by name/CID/SMILES/InChIKey/formula, retrieve properties (MW, XLogP, TPSA, H-bond counts), do similarity/substructure searches with async ListKey polling, fetch synonyms, descriptions, assay summaries, and download SDF/PNG. For local cheminformatics use rdkit; for bioactivity-centric workflows use chembl-database-bioactivity.

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Cross-reference compound IDs across 20+ databases (ChEMBL, DrugBank, PubChem, ChEBI, PDB, SureChEMBL, HMDB, DrugCentral, BindingDB) via UniChem REST API. Resolve InChIKeys to source IDs, translate between source-specific IDs, find structurally related compounds by connectivity. POST with a JSON body for all cross-reference queries; only /sources is GET. No auth required.

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Query the ZINC22 virtual compound library (CartBlanche API, billions of make-on-demand + purchasable molecules). Look up substances by ZINC ID, resolve a SMILES to its ZINC ID (exact match), inspect purchasability/catalogs, and assemble compound sets for docking. Property (MW/logP) filtering is done locally with RDKit. For bioactivity use chembl-database-bioactivity; for approved drugs use drugbank-database-access.

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Parse local DrugBank XML for drug info, interactions, targets, and properties. Search by ID/name/CAS, extract DDIs with severity, map targets/enzymes/transporters, compute SMILES similarity. Primary via local XML; REST API rate-limited (3k/month dev). For live bioactivity use chembl-database-bioactivity; for compound properties use pubchem-compound-search.

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World-class growth strategy expertise combining Andrew Chen's marketplace and network effects wisdom, Brian Balfour's growth frameworks, Casey Winters' Pinterest/Grubhub playbooks, and the best of Silicon Valley growth thinking. Growth is not marketing. Growth is the systematic application of product, engineering, and data to create compounding user acquisition, activation, and retention. It's a mindset, not a department. Use when "growth strategy, how do we grow, acquisition strategy, retention strategy, viral growth, network effects, growth loops, product-led growth, plg, ltv cac, unit economics, growth model, flywheel, compound growth, channel strategy, referral program, activation rate, magic moment, aha moment, growth experimentation, growth, strategy, acquisition, retention, viral, network-effects, plg, loops, experimentation" mentioned.

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用户在做长期投资/储蓄/增长决策，需要理解时间和复利的力量，或被短期波动困扰时。 语言信号:"持有多久合适"/"年化X%十年后会怎样"/"为什么长期持有比频繁交易好"/"小收益怎么变成大财富" 不适用于:短期交易决策、不需要时间维度的分析。

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Bioactivity and small-molecule data-side catalog. Covers ChEMBL search/lookup, MolTrack compound and batch registration, HitTriage / HitDesign / PeptiHit workflows, and Curves dose-response analysis (IC50/EC50 fitting). Open this skill when the user asks about querying ChEMBL, registering or looking up compounds in MolTrack, running a hit-triage campaign, or fitting/inspecting dose-response curves.

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Value investing analysis using Graham (NCAV/net-net/defensive-investor) and Buffett (economic moat/ROE/FCF) methodologies. Covers single-stock diagnostics and batch screening for both Graham cigar-butt and Buffett quality-compounder criteria. Runs cross-statement reconciliation before scoring. Data from Longbridge CLI first, MCP fallback, WebSearch only for genuine gaps. Triggers: "格雷厄姆", "巴菲特", "捡烟蒂", "烟蒂股", "NCAV", "净流动资产", "护城河", "价值投资", "安全边际", "深度价值", "撿煙蒂", "煙蒂股", "淨流動資產", "護城河", "安全邊際", "Graham", "Buffett", "cigar butt", "net-net", "NCAV screen", "moat", "value investing", "margin of safety", "deep value", "quality compounder", "價值投資", "深度價值", "防御型投资者", "防禦型投資者"

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Query the ChEMBL database web services for measured bioactivity data, compound records and calculated properties, targets, assays, mechanisms of action, drug indications and warnings. Use this skill to build curated SAR or QSAR datasets for a target, look compounds up by SMILES, InChIKey, name, or ChEMBL id, run similarity and substructure searches, and check what chemistry is already known against a protein. Also trigger when a query mentions ChEMBL ids (CHEMBL...), pChEMBL values, IC50/Ki/Kd/EC50 retrieval, assay confidence scores, or ebi.ac.uk/chembl.

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