Alignments for a candidate for liuB in Derxia gummosa DSM 723

GapMind for catabolism of small carbon sources

Alignments for a candidate for liuB in Derxia gummosa DSM 723

Align methylcrotonoyl-CoA carboxylase (subunit 2/2) (EC 6.4.1.4) (characterized)
to candidate WP_084545146.1 H566_RS0115200 pyruvate carboxylase

Query= BRENDA::Q9I299
         (655 letters)



>NCBI__GCF_000482785.1:WP_084545146.1
          Length = 1187

 Score =  395 bits (1014), Expect = e-114
 Identities = 218/462 (47%), Positives = 299/462 (64%), Gaps = 17/462 (3%)

Query: 3   PDYRSIQRLLVANRGEIACRVMRSARALGIGSVAVHSDIDRHARHVAEADIAVDLG-GAK 61
           P  R IQ +LVANR EIA RVMR+A  L I +VA++S  DR A H  +AD +  +G G K
Sbjct: 25  PQTRRIQSILVANRSEIAIRVMRAAAELNIRTVAIYSHEDRFALHRFKADQSYLVGEGKK 84

Query: 62  PADSYLRGDRIIAAALASGAQAIHPGYGFLSENADFARACEEAGLLFLGPPAAAIDAMGS 121
           P  +YL  D II  A  +   AIHPGYGFLSEN DFARAC EAGL+F+GP    +  +G+
Sbjct: 85  PLAAYLDIDDIIRIAKLAKVDAIHPGYGFLSENPDFARACAEAGLIFIGPTPEVMTTLGN 144

Query: 122 KSAAKALMEEAGVPLVPGYHGEAQDLETFRREAGRIGYPVLLKAAAGGGGKGMKVVEREA 181
           K AA+     AGVP++P       D+E  +  A  +GYPV+LKA+ GGGG+GM+V+E EA
Sbjct: 145 KVAARNAAVAAGVPVMPATDPLPLDIEGAKAAALTVGYPVMLKASWGGGGRGMRVIETEA 204

Query: 182 ELAEALSSAQREAKAAFGDARMLVEKYLLKPRHVEIQVFADRHGHCLYLNERDCSIQRRH 241
           +L   L  A+REA  AFG+  + +EK + + RHVE+Q+  D+HG+ ++L ERDCS+QRR+
Sbjct: 205 DLEAQLPVARREAAGAFGNDEVYLEKLVRRARHVEVQLLGDKHGNLVHLFERDCSVQRRN 264

Query: 242 QKVVEEAPAPGLGAELRRAMGEAAVRAAQAIGYVGAGTVEFLLD-ERGQFFFMEMNTRLQ 300
           QKVVE APAP L  E R+ + EAA++  +A+GY  AGTVEFL+D + G F+F+E+N R+Q
Sbjct: 265 QKVVERAPAPYLTEEQRQGLCEAALKLGRAVGYTHAGTVEFLMDADTGAFYFIEVNPRVQ 324

Query: 301 VEHPVTEAITGLDLVAWQIRVARGEAL------------PL-TQEQVPLNGHAIEVRLYA 347
           VEH VTE +TG+D+V  QIRV+ G  +            P+  QE + LNGHA++ R+  
Sbjct: 325 VEHTVTEEVTGIDIVQSQIRVSEGAMIGDLVGTEGRPPCPVPKQEDIRLNGHALQCRVTT 384

Query: 348 EDPEGDFLPASGRLMLYREAAAGPGRRVDSGVR-EGDEVSPFYDPMLAKLIAWGETREEA 406
           EDPE  F P  GR+  YR +AAG G R+D G    G  ++P+YD +L K+ AW  +  EA
Sbjct: 385 EDPENGFTPDYGRITAYR-SAAGFGLRLDGGTAYPGAVITPYYDSLLVKVTAWAPSVREA 443

Query: 407 RQRLLAMLAETSVGGLRTNLAFLRRILGHPAFAAAELDTGFI 448
             R+   L E  + G+ TNL F+  ++ HP F + ++ T FI
Sbjct: 444 ITRMDRALREFRIRGVATNLQFVENVINHPDFVSGQVITRFI 485



 Score = 65.1 bits (157), Expect = 2e-14
 Identities = 45/123 (36%), Positives = 60/123 (48%), Gaps = 7/123 (5%)

Query: 532  GDDLVSRVDGVTRRSAALRRGRQLFLEWEGE--LLAIEAVDPIAEAEAAHAHQGGLS--- 586
            G  L+ R+ G          G ++F E  G+  +L IE            A  G  +   
Sbjct: 1065 GKTLIIRMQGTAPSEDG--EGTKIFFELNGQARVLKIEKAGAAKANRHVQADPGNAAHVP 1122

Query: 587  APMNGSIVRVLVEPGQTVEAGATLVVLEAMKMEHSIRAPHAGVVKALYCSEGELVEEGTP 646
            APM G +V V V+PGQ V++G  LV +EAMKME  IRA   G VKA++   GE +     
Sbjct: 1123 APMPGMVVMVAVKPGQAVKSGDPLVSIEAMKMETQIRADRDGTVKAVHVKSGETISARDL 1182

Query: 647  LVE 649
            LVE
Sbjct: 1183 LVE 1185


Lambda     K      H
   0.319    0.135    0.397 

Gapped
Lambda     K      H
   0.267   0.0410    0.140 


Matrix: BLOSUM62
Gap Penalties: Existence: 11, Extension: 1
Number of Sequences: 1
Number of Hits to DB: 1635
Number of extensions: 88
Number of successful extensions: 6
Number of sequences better than 1.0e-02: 1
Number of HSP's gapped: 3
Number of HSP's successfully gapped: 2
Length of query: 655
Length of database: 1187
Length adjustment: 43
Effective length of query: 612
Effective length of database: 1144
Effective search space:   700128
Effective search space used:   700128
Neighboring words threshold: 11
Window for multiple hits: 40
X1: 16 ( 7.4 bits)
X2: 38 (14.6 bits)
X3: 64 (24.7 bits)
S1: 41 (21.8 bits)
S2: 56 (26.2 bits)

This GapMind analysis is from Sep 24 2021. The underlying query database was built on Sep 17 2021.

Downloads

Candidates (tab-delimited)
Steps (tab-delimited)
Rules (tab-delimited)
Protein sequences (fasta format)
Organisms (tab-delimited)
SQLite3 databases

Related tools

About GapMind

Each pathway is defined by a set of rules based on individual steps or genes. Candidates for each step are identified by using ublast (a fast alternative to protein BLAST) against a database of manually-curated proteins (most of which are experimentally characterized) or by using HMMer with enzyme models (usually from TIGRFam). Ublast hits may be split across two different proteins.

A candidate for a step is "high confidence" if either:

ublast finds a hit to a characterized protein at above 40% identity and 80% coverage, and bits >= other bits+10.
- (Hits to curated proteins without experimental data as to their function are never considered high confidence.)
HMMer finds a hit with 80% coverage of the model, and either other identity < 40 or other coverage < 0.75.

where "other" refers to the best ublast hit to a sequence that is not annotated as performing this step (and is not "ignored").

Otherwise, a candidate is "medium confidence" if either:

ublast finds a hit at above 40% identity and 70% coverage (ignoring otherBits).
ublast finds a hit at above 30% identity and 80% coverage, and bits >= other bits.
HMMer finds a hit (regardless of coverage or other bits).

Other blast hits with at least 50% coverage are "low confidence."

Steps with no high- or medium-confidence candidates may be considered "gaps." For the typical bacterium that can make all 20 amino acids, there are 1-2 gaps in amino acid biosynthesis pathways. For diverse bacteria and archaea that can utilize a carbon source, there is a complete high-confidence catabolic pathway (including a transporter) just 38% of the time, and there is a complete medium-confidence pathway 63% of the time. Gaps may be due to:

our ignorance of proteins' functions,
omissions in the gene models,
frame-shift errors in the genome sequence, or
the organism lacks the pathway.

GapMind relies on the predicted proteins in the genome and does not search the six-frame translation. In most cases, you can search the six-frame translation by clicking on links to Curated BLAST for each step definition (in the per-step page).

For more information, see:

the paper from 2019 on GapMind for amino acid biosynthesis
the paper from 2022 on GapMind for carbon sources
the source code
instructions for running GapMind on your computer

If you notice any errors or omissions in the step descriptions, or any questionable results, please let us know

by Morgan Price, Arkin group, Lawrence Berkeley National Laboratory

GapMind for catabolism of small carbon sources