Alignments for a candidate for trpED in Azospirillum brasilense Sp245

GapMind for Amino acid biosynthesis

Alignments for a candidate for trpED in Azospirillum brasilense Sp245

Align candidate AZOBR_RS06415 AZOBR_RS06415 (anthranilate synthase subunit I)
to HMM TIGR01815 (anthranilate synthase (EC 4.1.3.27))

# 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/TIGR01815.hmm
# target sequence database:        /tmp/gapView.24040.genome.faa
# - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -

Query:       TIGR01815  [M=717]
Accession:   TIGR01815
Description: TrpE-clade3: anthranilate synthase
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
    ------- ------ -----    ------- ------ -----   ---- --  --------                                 -----------
          0 1298.3   0.0          0 1298.1   0.0    1.0  1  lcl|FitnessBrowser__azobra:AZOBR_RS06415  AZOBR_RS06415 anthranilate synth


Domain annotation for each sequence (and alignments):
>> lcl|FitnessBrowser__azobra:AZOBR_RS06415  AZOBR_RS06415 anthranilate synthase subunit I
   #    score  bias  c-Evalue  i-Evalue hmmfrom  hmm to    alifrom  ali to    envfrom  env to     acc
 ---   ------ ----- --------- --------- ------- -------    ------- -------    ------- -------    ----
   1 ! 1298.1   0.0         0         0       1     717 []      18     736 ..      18     736 .. 0.99

  Alignments for each domain:
  == domain 1  score: 1298.1 bits;  conditional E-value: 0
                                 TIGR01815   1 yrtkGgvvvtrratevkletaleevvdalderrGallsssyeypGrykrwalgfvdppvalsasGrtlr 69 
                                               ++t+Ggv vtr at+++++ al++v+dald+rrG+llss++e+pGry+r+algf+dpp+a++a+Grtlr
  lcl|FitnessBrowser__azobra:AZOBR_RS06415  18 FQTRGGVAVTRCATALDPQGALDPVIDALDRRRGLLLSSGVEAPGRYRRHALGFTDPPLAVTARGRTLR 86 
                                               89******************************************************************* PP

                                 TIGR01815  70 iealnerGevllpviaealkkvedlakleeaarrvtasvkspdevlaeeerskqpsvftvlravldlfa 138
                                               i+aln rG+vllp++aeal+++e+la+leea++rvta+v++p+++++eeers+qps f+vlravl+lfa
  lcl|FitnessBrowser__azobra:AZOBR_RS06415  87 IDALNARGRVLLPAVAEALRGLEALAGLEEAPSRVTALVRKPQHPFPEEERSRQPSLFSVLRAVLNLFA 155
                                               ********************************************************************* PP

                                 TIGR01815 139 seedellGlyGafgydlafqfeaieqklerpddqrdlvlylpdelvvvdyyaakaflveydfitaagst 207
                                               +++d+llGlyGaf+ydlafqfe+i+++lerpddqrdlvlylpd+lvv+d++a+ a+lvey+f+taagst
  lcl|FitnessBrowser__azobra:AZOBR_RS06415 156 APDDPLLGLYGAFAYDLAFQFEPIRLRLERPDDQRDLVLYLPDRLVVLDPVAGLARLVEYEFATAAGST 224
                                               ********************************************************************* PP

                                 TIGR01815 208 egleadgedepyrsdtsiepqadhkpGeyaklvekakeafrrGdlfevvpgqkffeaceaapsevferl 276
                                               egle+ g+d+pyr+dt++e ++dh+pG y+++ve+ak+afrrGdlfevvpgq+f+e+c++aps vf+rl
  lcl|FitnessBrowser__azobra:AZOBR_RS06415 225 EGLERAGRDHPYRPDTNAEGGCDHAPGAYQRVVETAKAAFRRGDLFEVVPGQTFAEPCADAPSAVFRRL 293
                                               ********************************************************************* PP

                                 TIGR01815 277 kainpspyeffvnlGrgeylvgaspemfvrveGr....rvetcpisGtikrGddaiddaaqilkllnsk 341
                                               +a+np+pye+fvnlGrge+lv+aspem+vrv+G+    rvetcpisGt++rG+da++daaq+l+ll+s+
  lcl|FitnessBrowser__azobra:AZOBR_RS06415 294 RAANPAPYEAFVNLGRGEFLVAASPEMYVRVAGGrmggRVETCPISGTVARGADALGDAAQVLRLLTSA 362
                                               *******************************975222279***************************** PP

                                 TIGR01815 342 kdeaeltmctdvdrndksrvcepGsvkviGrrqielysrlihtvdhveGrlrdeldaldaflshawavt 410
                                               kd+aeltmctdvdrndk+rvcepGsv+viGrr+ielysrlihtvdhveGrlr++ldaldafl+h+wavt
  lcl|FitnessBrowser__azobra:AZOBR_RS06415 363 KDAAELTMCTDVDRNDKARVCEPGSVRVIGRRMIELYSRLIHTVDHVEGRLRPGLDALDAFLTHTWAVT 431
                                               ********************************************************************* PP

                                 TIGR01815 411 vtGapkraalqfiekteksprrwyGGavGrlgfnGdlntGltlrtirlkdgiaevraGatllydsdpea 479
                                               vtGapkr+a+qf+e+te+sprrwyGGa+Grlgf+G+++tGltlrtir+++g+a+vraGatll+dsdp+a
  lcl|FitnessBrowser__azobra:AZOBR_RS06415 432 VTGAPKRWAMQFLEDTEQSPRRWYGGAFGRLGFDGGMDTGLTLRTIRMAEGVAYVRAGATLLSDSDPDA 500
                                               ********************************************************************* PP

                                 TIGR01815 480 eeaetelkaaalieairdakaadaakeesavakvgeGkrillvdhedsfvhtlanylrqtGasvttlrh 548
                                               e+ae++lkaaa+++air + + + a  ++a++++g G+r+llvdh+dsfvhtla+ylrqtGasv tlrh
  lcl|FitnessBrowser__azobra:AZOBR_RS06415 501 EDAECRLKAAAFRDAIR-GVTEGVACALPAAPNGGRGRRVLLVDHDDSFVHTLADYLRQTGASVMTLRH 568
                                               *****************.888999********************************************* PP

                                 TIGR01815 549 svaeelldeerpdlvvlspGpGrpkdfdvketikaalardlpvfGvclGlqglveafGGeldvlaepvh 617
                                               ++a+++l+e+rpdlvvlspGpGrp+df+v++ti+aala++lpvfGvclGlqg+ve+fGG+ldvl+epvh
  lcl|FitnessBrowser__azobra:AZOBR_RS06415 569 GHARAALAERRPDLVVLSPGPGRPADFNVAGTIDAALALGLPVFGVCLGLQGMVERFGGALDVLPEPVH 637
                                               ********************************************************************* PP

                                 TIGR01815 618 GkasrirvlepdvlfaglpeeltvGryhslfarsdrlpkelkvtaesedgvimaiehrklpvaavqfhp 686
                                               Gka+++rvl++ +lfaglpe++ vGryhsl+ar+drlp++l+vtae++dg++ma+ehr+lp+aavqfhp
  lcl|FitnessBrowser__azobra:AZOBR_RS06415 638 GKATEVRVLGG-ALFAGLPERMRVGRYHSLVARRDRLPADLTVTAETADGLVMAVEHRRLPLAAVQFHP 705
                                               *********99.********************************************************* PP

                                 TIGR01815 687 esiltlaGeaGlalienvvdklaksaktkaa 717
                                               esil+l+G+aGlal++nv+d+la++a t+aa
  lcl|FitnessBrowser__azobra:AZOBR_RS06415 706 ESILSLDGGAGLALLGNVMDRLAAGALTDAA 736
                                               ****************************986 PP



Internal pipeline statistics summary:
-------------------------------------
Query model(s):                            1  (717 nodes)
Target sequences:                          1  (737 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: 0.06u 0.01s 00:00:00.06 Elapsed: 00:00:00.06
# Mc/sec: 8.30
//
[ok]

This GapMind analysis is from Apr 09 2024. The underlying query database was built on Apr 09 2024.

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

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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:

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
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

GapMind for Amino acid biosynthesis