拡張代謝パスウェイデータベース「M-path」の構築
小川哲平1, 牧口大旭1, 荒木通啓2,3
1三井情報株式会社
2京都大学大学院 医学研究科
3神戸大学大学院 科学技術イノベーション研究科

AbstractConcept

Recent developments in synthetic biology and metabolic engineering have led to theconstruction of synthetic metabolic pathways for efficient production of various natural andE4

non-natural chemicals. We introduce the M-path database and viewer to explore latentsynthetic metabolic pathways of putative compounds and reactions. In the current version of
M-path, the set of reaction is increased up to 20,000 by using a manually curated BRENDA
database and compound data from PubChem are regularly updated, which will increase achance to find unknown metabolic pathways with diverse chemical and enzymatic
information.

C1known routeE5C5E0C2E2E1C3E3C4E6E7
CX

predicted route

The concept of M-path is predicting“unknown” route (ex. C1 -> CX -> C3)from start compound (C1) to lastcompound (C3) based on “known” enzyme
reactions (E6 and E7).
It can also be possible to predict thesynthetic route that has not been found tosynthesize yet.

Method & Result
1. Glutamate

2. Acetyl group

3. N-acetyl glutamate

Compound_DB

Mol_CodeGlutamate

Acetylation

N-acetyl glutamate（1 1 0 0 ‥0 0 1）
（2 3 0 0 ‥ 1 2 0）

（3 4 0 0 ‥1 2 1）

（Chemical feature）（-1 -1 0 0 ‥0 0 -1）（Chemical feature）
Deacetylation（Reaction feature）

Calculate pathway feature

Step 1

Output pathway candidates

Solve linear problem.

Step 2

Step 3Make random subset from reaction feature

Step 4

Step 5

Rearrange reactions assign intermediates
4-Hydoroxybutanal

1, 4-BDO

Similarity???
ButanalReaction_DBRandom SelectOptimization

Butanol0.72

1.1.1.202
Reaction feature

Methodology of M-path making:M-path makes use of chemical structure
information and enzymatic reaction rules, and isperformed as shown scheme.

Performance of solving pathway:
Seq : extending pathways step by step until
reaching target.
Opt : solving pathways by using the solution to alinear programming problem.

Chemical feature

M-pathSample reaction: D-glucose -> L-2-Methylserine
Path List:
The predicted route is shown in Path
List. Each step is scored based on thesimilarity to the known reaction.
Score 1 shows that predicted route is
the same reaction as known reaction,and score < 1 shows the similar to it.
Similarity is calculated based on
Tanimoto score of Substrate/Product.

Reaction List:
The reaction which has same substrate-product pairas predicted reaction is scored 1, then similar
reaction is scored based on the similarity of chemical
structure of its substrate and product.

Compound viewer:
Compound viewer shows chemical feature of each compounds andthe score of the pathway candidate with highest score.

Pathway viewer:
Pathway viewer shows potential metabolic pathways including reaction data and thetransition of chemical structures and reaction orders from top to bottom for each pathway.

Compound List:
The predicted compound is shown in Path View
and its similar compounds were shown inCompound List.

Network viewer:
Network Viewer is an integrated network using known amino acid network data,
compounds and reactions from the pathway candidates with M-score > 0.8 for all data.

References(1) M. Araki, R. S. Cox III, H. Makiguchi, T. Ogawa,T. Taniguchi, K. Miyaoku, M. Nakatsui, K. Y. Hara and A. Kondo, Bioinformatics 2015, 31, 905-911.
(2) http://bp.scitec.kobe-u.ac.jp/m-path/aa/(3) http://bp.scitec.kobe-u.ac.jp/m-path/db/
Licensed under a Creative Commons表示4.0国際ライセンス(c)2017 小川哲平

Network Viewer Information:
The core L-amino acid biosynthetic network
annotated by KEGG (grey). Naturally reachable(PATH_0) compounds are shown as pink
circles. Blue edges are putative reaction steps
predicted by M-path. The green squares show
putative L-amino acids not found in KEGG,
with blue squares as their intermediates suchas keto acids.