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Pharmaclaw Catalyst Design

Organometallic catalyst recommendation and novel ligand design for drug synthesis reactions. Recommends catalysts (Pd, Ru, Rh, Ir, Ni, Cu, Zr, Fe) for reacti...
为药物合成反应提供有机金属催化剂(Pd、Ru、Rh、Ir、Ni、Cu、Zr、Fe)推荐及新型配体设计。
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AI智能 clawhub v1.0.0 1 版本 100000 Key: 无需
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概述

Catalyst Design Agent v1.0.0

Overview

Recommends organometallic catalysts for drug synthesis steps and designs novel ligand modifications. Two core workflows: recommend (find the right catalyst) and design (create novel ligand variants).

Quick Start

# Recommend catalysts for a Suzuki coupling
python scripts/catalyst_recommend.py --reaction suzuki

# Recommend with constraints (prefer cheap, earth-abundant)
python scripts/catalyst_recommend.py --reaction "C-N coupling" --constraints '{"prefer_earth_abundant": true, "max_cost": "medium"}'

# Design novel ligand variants from PPh3
python scripts/ligand_designer.py --scaffold PPh3 --strategy all --draw

# Full chain: reaction → catalyst → ligand optimization
python scripts/chain_entry.py --input-json '{"reaction": "suzuki", "context": "retrosynthesis"}'

Scripts

scripts/catalyst_recommend.py

Scores and ranks catalysts from curated database (12 catalysts, 28 reaction types).

--reaction <type>              Required. e.g., suzuki, metathesis, C-N coupling, hydrogenation
--substrate <SMILES>           Optional. Substrate context
--constraints <JSON>           Optional. {prefer_metal, max_cost, prefer_earth_abundant}
--enantioselective             Flag. Prioritize chiral catalysts

Scoring (0-100): reaction match (50), cost (15), metal preference (10), enantioselectivity (10), loading efficiency (5), advantages (5), earth-abundance (5).

scripts/ligand_designer.py

Generates novel ligand variants via three strategies:

StrategyMethodOutput
--------------------------
stericAdd methyl/iPr/tBu to aromatic ringsModified SMILES + properties
electronicAdd OMe/F/CF3 substituentsModified SMILES + properties
bioisostericP→NHC, phenyl→pyridyl, phosphine→phosphiteConceptual suggestions + rationale
--scaffold <SMILES|name>       Required. PPh3, NHC_IMes, NHC_IPr, PCy3, dppe, dppp, or raw SMILES
--strategy <type>              steric|electronic|bioisosteric|all (default: all)
--draw                         Generate 2D grid PNG of variants
--output <path>                Save JSON results to file

scripts/chain_entry.py

Standard PharmaClaw chain interface. Accepts JSON, routes to recommend/design/both.

Input keys: reaction, scaffold/ligand, substrate/smiles, constraints, enantioselective, strategy, draw, context

If only reaction is given, also auto-runs ligand optimization on the top recommended catalyst's ligand.

Chaining

FromInputToOutput
-------------------------
Chemistry Query / RetrosynthesisReaction type needed for a synthesis stepCatalyst DesignRanked catalysts + conditions
Catalyst DesignTop catalyst ligand SMILESLigand DesignerNovel ligand variants
Catalyst DesignNovel ligand SMILESIP ExpansionPatent landscape check
Catalyst DesignRecommended conditionsChemistry QueryForward reaction simulation

Database

references/catalyst_database.json — 12 catalysts, 8 metals, 28 reaction types. Includes SMILES, conditions, loading ranges, cost ratings, advantages/limitations, and literature DOIs.

Expandable: add entries following the existing schema.

Ligand Aliases

PPh3, PCy3, dppe, dppp, NHC_IMes, NHC_IPr — resolved automatically to SMILES.

版本历史

共 1 个版本

  • v1.0.0 当前
    2026-03-29 22:59 安全 安全

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腾讯云安全 (Keen)

安全,无风险
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腾讯云安全 (Sanbu)

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