brenda_database

Name: brenda_database
Author: ai4protein

244stars35forks

How to install brenda_database?

ai4protein/venusfactory2/brenda_database

$npx -y skills add ai4protein/VenusFactory2 --skill brenda_database

Installs into the current project.

Summary

Access BRENDA enzyme database via SOAP API. Retrieve kinetic parameters (Km, kcat), reaction equations, organism data, and substrate-specific enzyme information for biochemical research and metabolic pathway analysis.

Files · 1

View on GitHub

SKILL.md

1	# BRENDA Database
2
3	## Overview
4
5	BRENDA (BRaunschweig ENzyme DAtabase) is the world's most comprehensive enzyme information system, containing detailed enzyme data from scientific literature. In this project the agent exposes only download tools: save Km values, reactions, enzyme-by-substrate results, organism comparison, environmental parameters, kinetic data export, and pathway reports to files; each returns JSON `{success, file_path[, error]}`. For programmatic use, the package also provides query-style APIs (see Project Modules). Access over 45,000 enzymes with millions of kinetic data points for biochemical research, metabolic engineering, and enzyme discovery.
6
7	## When to Use This Skill
8
9	This skill should be used when:
10	- Searching for enzyme kinetic parameters (Km, kcat, Vmax)
11	- Retrieving reaction equations and stoichiometry
12	- Finding enzymes for specific substrates or reactions
13	- Comparing enzyme properties across different organisms
14	- Investigating optimal pH, temperature, and conditions
15	- Accessing enzyme inhibition and activation data
16	- Supporting metabolic pathway reconstruction and retrosynthesis
17	- Performing enzyme engineering and optimization studies
18	- Analyzing substrate specificity and cofactor requirements
19
20	## Quick Start
21
22	The skill provides:
23	1. Agent tools (download only) in `src/tools/search/tools_agent.py`: the agent exposes only download operations; each returns JSON `{success, file_path[, error]}`. See table below.
24	2. Project modules in `src/tools/database/brenda/`: `brenda_client.py` (SOAP), `brenda_queries.py`, `enzyme_pathway_builder.py`, `brenda_operations.py`; all re-exported via package. For programmatic use (including query-style APIs), import e.g. `from src.tools.database.brenda import download_brenda_km_values_by_ec_number, query_brenda_km_values_by_ec_number, ...`.
25	3. Reference: `references/api_reference.md`
26
27	### Agent Tools (Download Only)
28
29	\| Tool name \| Arguments \| Purpose \|
30	\|-----------\|-----------\|---------\|
31	\| `download_brenda_km_values_by_ec_number` \| `ec_number`, `out_path`, `organism` (optional), `substrate` (optional) \| Download Km values by EC number to .json or .txt \|
32	\| `download_brenda_reactions_by_ec_number` \| `ec_number`, `out_path`, `organism` (optional) \| Download reaction equations by EC number to file \|
33	\| `download_brenda_enzymes_by_substrate` \| `substrate`, `out_path`, `limit` (optional) \| Download enzyme-by-substrate search results to JSON \|
34	\| `download_brenda_compare_organisms_by_ec_number` \| `ec_number`, `organisms`, `out_path` \| Download organism comparison by EC number to JSON \|
35	\| `download_brenda_environmental_parameters_by_ec_number` \| `ec_number`, `out_path` \| Download environmental parameters (pH, temperature) by EC number to JSON \|
36	\| `download_brenda_kinetic_data_by_ec_number` \| `ec_number`, `out_path`, `format` (optional: json/csv) \| Download kinetic data export by EC number to file \|
37	\| `download_brenda_pathway_report` \| `pathway` (dict), `out_path` \| Generate and save pathway report from pathway data to file \|
38
39	All require `BRENDA_EMAIL` and `BRENDA_PASSWORD` in the environment.
40
41	### Project Modules (Programmatic Use)
42
43	\| Capability \| Function \| Module \| Purpose \|
44	\|------------\|----------\|--------\|---------\|
45	\| SOAP Km \| `get_km_values(ec_number, organism=, substrate=)` \| brenda_client.py \| Raw Km entries from BRENDA \|
46	\| SOAP reactions \| `get_reactions(ec_number, organism=, reaction=)` \| brenda_client.py \| Raw reaction entries \|
47	\| Parse Km \| `parse_km_entry(entry)` \| brenda_queries.py \| Parse Km string to dict \|
48	\| Parse reaction \| `parse_reaction_entry(entry)`, `extract_substrate_products(entry)` \| brenda_queries.py \| Parse reaction / get substrates & products \|
49	\| Organism data \| `extract_organism_data(entry)` \| brenda_queries.py \| Extract organism info from entry \|
50	\| Search by substrate \| `search_enzymes_by_substrate(substrate, limit)` \| brenda_queries.py \| Find enzymes for substrate \|
51	\| Search by product \| `search_enzymes_by_product(product, limit)` \| brenda_queries.py \| Find enzymes producing product \|
52	\| Search by pattern \| `search_by_pattern(pattern, limit)` \| brenda_queries.py \| Find enzymes by reaction pattern \|
53	\| Compare organisms \| `compare_across_organisms(ec_number, organisms)` \| brenda_queries.py \| Compare enzyme data across organisms \|
54	\| Organisms for enzyme \| `get_organisms_for_enzyme(ec_number)` \| brenda_queries.py \| List organisms with enzyme \|
55	\| Environmental params \| `get_environmental_parameters(ec_number)` \| brenda_queries.py \| pH, temperature, stability \|
56	\| Cofactors \| `get_cofactor_requirements(ec_number)` \| brenda_queries.py \| Cofactor requirements \|
57	\| Substrate specificity \| `get_substrate_

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brenda_database

244stars35forks

View on GitHub

How to install brenda_database?

ai4protein/venusfactory2/brenda_database

$npx -y skills add ai4protein/VenusFactory2 --skill brenda_database

Installs into the current project.

Summary

Files · 1

View on GitHub

SKILL.md

1	# BRENDA Database
2
3	## Overview
4
5	BRENDA (BRaunschweig ENzyme DAtabase) is the world's most comprehensive enzyme information system, containing detailed enzyme data from scientific literature. In this project the agent exposes only download tools: save Km values, reactions, enzyme-by-substrate results, organism comparison, environmental parameters, kinetic data export, and pathway reports to files; each returns JSON `{success, file_path[, error]}`. For programmatic use, the package also provides query-style APIs (see Project Modules). Access over 45,000 enzymes with millions of kinetic data points for biochemical research, metabolic engineering, and enzyme discovery.
6
7	## When to Use This Skill
8
9	This skill should be used when:
10	- Searching for enzyme kinetic parameters (Km, kcat, Vmax)
11	- Retrieving reaction equations and stoichiometry
12	- Finding enzymes for specific substrates or reactions
13	- Comparing enzyme properties across different organisms
14	- Investigating optimal pH, temperature, and conditions
15	- Accessing enzyme inhibition and activation data
16	- Supporting metabolic pathway reconstruction and retrosynthesis
17	- Performing enzyme engineering and optimization studies
18	- Analyzing substrate specificity and cofactor requirements
19
20	## Quick Start
21
22	The skill provides:
23	1. Agent tools (download only) in `src/tools/search/tools_agent.py`: the agent exposes only download operations; each returns JSON `{success, file_path[, error]}`. See table below.
24	2. Project modules in `src/tools/database/brenda/`: `brenda_client.py` (SOAP), `brenda_queries.py`, `enzyme_pathway_builder.py`, `brenda_operations.py`; all re-exported via package. For programmatic use (including query-style APIs), import e.g. `from src.tools.database.brenda import download_brenda_km_values_by_ec_number, query_brenda_km_values_by_ec_number, ...`.
25	3. Reference: `references/api_reference.md`
26
27	### Agent Tools (Download Only)
28
29	\| Tool name \| Arguments \| Purpose \|
30	\|-----------\|-----------\|---------\|
31	\| `download_brenda_km_values_by_ec_number` \| `ec_number`, `out_path`, `organism` (optional), `substrate` (optional) \| Download Km values by EC number to .json or .txt \|
32	\| `download_brenda_reactions_by_ec_number` \| `ec_number`, `out_path`, `organism` (optional) \| Download reaction equations by EC number to file \|
33	\| `download_brenda_enzymes_by_substrate` \| `substrate`, `out_path`, `limit` (optional) \| Download enzyme-by-substrate search results to JSON \|
34	\| `download_brenda_compare_organisms_by_ec_number` \| `ec_number`, `organisms`, `out_path` \| Download organism comparison by EC number to JSON \|
35	\| `download_brenda_environmental_parameters_by_ec_number` \| `ec_number`, `out_path` \| Download environmental parameters (pH, temperature) by EC number to JSON \|
36	\| `download_brenda_kinetic_data_by_ec_number` \| `ec_number`, `out_path`, `format` (optional: json/csv) \| Download kinetic data export by EC number to file \|
37	\| `download_brenda_pathway_report` \| `pathway` (dict), `out_path` \| Generate and save pathway report from pathway data to file \|
38
39	All require `BRENDA_EMAIL` and `BRENDA_PASSWORD` in the environment.
40
41	### Project Modules (Programmatic Use)
42
43	\| Capability \| Function \| Module \| Purpose \|
44	\|------------\|----------\|--------\|---------\|
45	\| SOAP Km \| `get_km_values(ec_number, organism=, substrate=)` \| brenda_client.py \| Raw Km entries from BRENDA \|
46	\| SOAP reactions \| `get_reactions(ec_number, organism=, reaction=)` \| brenda_client.py \| Raw reaction entries \|
47	\| Parse Km \| `parse_km_entry(entry)` \| brenda_queries.py \| Parse Km string to dict \|
48	\| Parse reaction \| `parse_reaction_entry(entry)`, `extract_substrate_products(entry)` \| brenda_queries.py \| Parse reaction / get substrates & products \|
49	\| Organism data \| `extract_organism_data(entry)` \| brenda_queries.py \| Extract organism info from entry \|
50	\| Search by substrate \| `search_enzymes_by_substrate(substrate, limit)` \| brenda_queries.py \| Find enzymes for substrate \|
51	\| Search by product \| `search_enzymes_by_product(product, limit)` \| brenda_queries.py \| Find enzymes producing product \|
52	\| Search by pattern \| `search_by_pattern(pattern, limit)` \| brenda_queries.py \| Find enzymes by reaction pattern \|
53	\| Compare organisms \| `compare_across_organisms(ec_number, organisms)` \| brenda_queries.py \| Compare enzyme data across organisms \|
54	\| Organisms for enzyme \| `get_organisms_for_enzyme(ec_number)` \| brenda_queries.py \| List organisms with enzyme \|
55	\| Environmental params \| `get_environmental_parameters(ec_number)` \| brenda_queries.py \| pH, temperature, stability \|
56	\| Cofactors \| `get_cofactor_requirements(ec_number)` \| brenda_queries.py \| Cofactor requirements \|
57	\| Substrate specificity \| `get_substrate_

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