GapMind for Amino acid biosynthesis

 

Alignments for a candidate for argB in Pseudomonas fluorescens FW300-N2C3

Align acetylglutamate kinase (EC 2.7.2.8) (characterized)
to candidate AO356_12525 AO356_12525 acetylglutamate kinase

Query= BRENDA::Q9HTN2
         (301 letters)



>FitnessBrowser__pseudo5_N2C3_1:AO356_12525
          Length = 301

 Score =  535 bits (1379), Expect = e-157
 Identities = 274/300 (91%), Positives = 288/300 (96%)

Query: 1   MTLSRDDAAQVAKVLSEALPYIRRFVGKTLVIKYGGNAMESEELKAGFARDVVLMKAVGI 60
           MTL R+ AA  AKVLSEALPYIRR+VGKTLVIKYGGNAMESEELK GFARD+VLMKAVGI
Sbjct: 1   MTLEREAAANTAKVLSEALPYIRRYVGKTLVIKYGGNAMESEELKTGFARDIVLMKAVGI 60

Query: 61  NPVVVHGGGPQIGDLLKRLSIESHFIDGMRVTDAATMDVVEMVLGGQVNKDIVNLINRHG 120
           NPVVVHGGGPQIGDLLKRLSIESHFIDGMRVTDA TMDVVEMVLGGQVNKDIVNLINRHG
Sbjct: 61  NPVVVHGGGPQIGDLLKRLSIESHFIDGMRVTDAQTMDVVEMVLGGQVNKDIVNLINRHG 120

Query: 121 GSAIGLTGKDAELIRAKKLTVTRQTPEMTKPEIIDIGHVGEVTGVNVGLLNMLVKGDFIP 180
           GSAIGLTGKDAELIRAKKLTVTRQTPEMT+PEIIDIGHVGEV G+N  LLN+LVKGDFIP
Sbjct: 121 GSAIGLTGKDAELIRAKKLTVTRQTPEMTQPEIIDIGHVGEVVGINTDLLNLLVKGDFIP 180

Query: 181 VIAPIGVGSNGESYNINADLVAGKVAEALKAEKLMLLTNIAGLMDKQGQVLTGLSTEQVN 240
           VIAPIGVG+NGESYNINADLVAGKVAEALKAEKLMLLTNIAGLMDK G+VLTGLST+QV+
Sbjct: 181 VIAPIGVGANGESYNINADLVAGKVAEALKAEKLMLLTNIAGLMDKTGKVLTGLSTQQVD 240

Query: 241 ELIADGTIYGGMLPKIRCALEAVQGGVTSAHIIDGRVPNAVLLEIFTDSGVGTLISNRKR 300
           +LIADGTIYGGMLPKIRCALEAVQGGV S+ IIDGRVPNA+LLEIFTD+GVGTLISNRKR
Sbjct: 241 DLIADGTIYGGMLPKIRCALEAVQGGVGSSLIIDGRVPNAILLEIFTDTGVGTLISNRKR 300


Lambda     K      H
   0.318    0.138    0.381 

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: 471
Number of extensions: 13
Number of successful extensions: 1
Number of sequences better than 1.0e-02: 1
Number of HSP's gapped: 1
Number of HSP's successfully gapped: 1
Length of query: 301
Length of database: 301
Length adjustment: 27
Effective length of query: 274
Effective length of database: 274
Effective search space:    75076
Effective search space used:    75076
Neighboring words threshold: 11
Window for multiple hits: 40
X1: 16 ( 7.3 bits)
X2: 38 (14.6 bits)
X3: 64 (24.7 bits)
S1: 41 (21.7 bits)
S2: 48 (23.1 bits)

Align candidate AO356_12525 AO356_12525 (acetylglutamate kinase)
to HMM TIGR00761 (argB: acetylglutamate kinase (EC 2.7.2.8))

# hmmsearch :: search profile(s) against a sequence database
# HMMER 3.3.1 (Jul 2020); http://hmmer.org/
# Copyright (C) 2020 Howard Hughes Medical Institute.
# Freely distributed under the BSD open source license.
# - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
# query HMM file:                  ../tmp/path.aa/TIGR00761.hmm
# target sequence database:        /tmp/gapView.768.genome.faa
# - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -

Query:       TIGR00761  [M=231]
Accession:   TIGR00761
Description: argB: acetylglutamate kinase
Scores for complete sequences (score includes all domains):
   --- full sequence ---   --- best 1 domain ---    -#dom-
    E-value  score  bias    E-value  score  bias    exp  N  Sequence                                       Description
    ------- ------ -----    ------- ------ -----   ---- --  --------                                       -----------
    7.9e-82  260.2   6.9    9.4e-82  260.0   6.9    1.0  1  lcl|FitnessBrowser__pseudo5_N2C3_1:AO356_12525  AO356_12525 acetylglutamate kina


Domain annotation for each sequence (and alignments):
>> lcl|FitnessBrowser__pseudo5_N2C3_1:AO356_12525  AO356_12525 acetylglutamate kinase
   #    score  bias  c-Evalue  i-Evalue hmmfrom  hmm to    alifrom  ali to    envfrom  env to     acc
 ---   ------ ----- --------- --------- ------- -------    ------- -------    ------- -------    ----
   1 !  260.0   6.9   9.4e-82   9.4e-82       1     231 []      29     272 ..      29     272 .. 0.98

  Alignments for each domain:
  == domain 1  score: 260.0 bits;  conditional E-value: 9.4e-82
                                       TIGR00761   1 tiViKiGGaais..elleelakdiaklrkegiklvivHGGgpeinelleklgievefvnglRv 61 
                                                     t+ViK+GG+a++  el++ +a+di+ ++++gi++v+vHGGgp+i  ll++l ie +f++g+Rv
  lcl|FitnessBrowser__pseudo5_N2C3_1:AO356_12525  29 TLVIKYGGNAMEseELKTGFARDIVLMKAVGINPVVVHGGGPQIGDLLKRLSIESHFIDGMRV 91 
                                                     68*********9999************************************************ PP

                                       TIGR00761  62 TdketlevvemvligkvnkelvallekhgikavGltgkDgqlltaekldke............ 112
                                                     Td++t++vvemvl g+vnk +v+l+++hg +a+GltgkD++l+ a+kl++             
  lcl|FitnessBrowser__pseudo5_N2C3_1:AO356_12525  92 TDAQTMDVVEMVLGGQVNKDIVNLINRHGGSAIGLTGKDAELIRAKKLTVTrqtpemtqpeii 154
                                                     **********************************************888888899******** PP

                                       TIGR00761 113 dlgyvGeikkvnkelleallkagiipviaslaldeegqllNvnaDtaAaelAaaleAekLvlL 175
                                                     d+g+vGe+  +n++ll+ l+k ++ipvia++++ ++g+ +N+naD +A+++A+al+AekL+lL
  lcl|FitnessBrowser__pseudo5_N2C3_1:AO356_12525 155 DIGHVGEVVGINTDLLNLLVKGDFIPVIAPIGVGANGESYNINADLVAGKVAEALKAEKLMLL 217
                                                     *************************************************************** PP

                                       TIGR00761 176 tdvaGilegdkksliseleleeieqlikqavikgGmipKveaalealesgvkkvvi 231
                                                     t++aG++++ + ++++ l+++++++li  + i+gGm pK+++alea+++gv ++ i
  lcl|FitnessBrowser__pseudo5_N2C3_1:AO356_12525 218 TNIAGLMDK-TGKVLTGLSTQQVDDLIADGTIYGGMLPKIRCALEAVQGGVGSSLI 272
                                                     *********.777**************************************98866 PP



Internal pipeline statistics summary:
-------------------------------------
Query model(s):                            1  (231 nodes)
Target sequences:                          1  (301 residues searched)
Passed MSV filter:                         1  (1); expected 0.0 (0.02)
Passed bias filter:                        1  (1); expected 0.0 (0.02)
Passed Vit filter:                         1  (1); expected 0.0 (0.001)
Passed Fwd filter:                         1  (1); expected 0.0 (1e-05)
Initial search space (Z):                  1  [actual number of targets]
Domain search space  (domZ):               1  [number of targets reported over threshold]
# CPU time: 0.01u 0.01s 00:00:00.02 Elapsed: 00:00:00.00
# Mc/sec: 10.26
//
[ok]

This GapMind analysis is from Aug 03 2021. The underlying query database was built on Aug 03 2021.

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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:

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:

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:

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, or view the source code, or see changes to Amino acid biosynthesis since the publication.

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