Alignments for a candidate for hisG in Dinoroseobacter shibae DFL-12

GapMind for Amino acid biosynthesis

Alignments for a candidate for hisG in Dinoroseobacter shibae DFL-12

Align ATP phosphoribosyltransferase (EC 2.4.2.17) (characterized)
to candidate 3609569 Dshi_2953 ATP phosphoribosyltransferase (RefSeq)

Query= reanno::Phaeo:GFF2940
         (230 letters)



>FitnessBrowser__Dino:3609569
          Length = 239

 Score =  328 bits (842), Expect = 4e-95
 Identities = 164/221 (74%), Positives = 188/221 (85%)

Query: 1   MSLKLGVPSKGRLMEKTFEWFAKRGITLSRTGSDREYAGAVAGIDGIDLVLLSAGEMPRE 60
           M+LKLGVPSKGRLM+KTF+WF + GITL RTGS+REYAG+V G+DG+ LVLLSAGE+PRE
Sbjct: 1   MTLKLGVPSKGRLMDKTFDWFGRHGITLQRTGSEREYAGSVDGVDGVALVLLSAGEIPRE 60

Query: 61  LAAGRIHLGVTGTDLVQEKLPLWEQQVEEIAGLGFGHADLILAVPQIWVDVETIDDLDAV 120
           LAAGRIHLGVTGTDLVQEKLP W +QV  IA LGFGHADLILAVP+ W+DVET+DDLDAV
Sbjct: 61  LAAGRIHLGVTGTDLVQEKLPDWMRQVRSIAPLGFGHADLILAVPKCWIDVETLDDLDAV 120

Query: 121 AAAFRAKHGHRLRIATKYHRLVREYLMDAGVADYQLVDSQGATEGTVKNETAEMVADITS 180
           AA FRA HG RLRIATKYHRLV  +L   GVADYQLVDSQGATEGTV N TAE +ADITS
Sbjct: 121 AAQFRANHGFRLRIATKYHRLVHSHLSAHGVADYQLVDSQGATEGTVANLTAEAIADITS 180

Query: 181 TGETLRANHLKLMSDGLILRSQATLWRSRVAKYSAKEKATL 221
           TGETLRANHLK++    +L+SQATL+ SR+A +    +A +
Sbjct: 181 TGETLRANHLKILKGEPVLKSQATLFASRMADWDPTARAAM 221


Lambda     K      H
   0.318    0.134    0.385 

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: 260
Number of extensions: 9
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: 230
Length of database: 239
Length adjustment: 23
Effective length of query: 207
Effective length of database: 216
Effective search space:    44712
Effective search space used:    44712
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: 46 (22.3 bits)

Align candidate 3609569 Dshi_2953 (ATP phosphoribosyltransferase (RefSeq))
to HMM TIGR00070 (hisG: ATP phosphoribosyltransferase (EC 2.4.2.17))

# 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/TIGR00070.hmm
# target sequence database:        /tmp/gapView.4690.genome.faa
# - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -

Query:       TIGR00070  [M=183]
Accession:   TIGR00070
Description: hisG: ATP phosphoribosyltransferase
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
    ------- ------ -----    ------- ------ -----   ---- --  --------                         -----------
    7.7e-54  168.4   0.0    8.9e-54  168.2   0.0    1.0  1  lcl|FitnessBrowser__Dino:3609569  Dshi_2953 ATP phosphoribosyltran


Domain annotation for each sequence (and alignments):
>> lcl|FitnessBrowser__Dino:3609569  Dshi_2953 ATP phosphoribosyltransferase (RefSeq)
   #    score  bias  c-Evalue  i-Evalue hmmfrom  hmm to    alifrom  ali to    envfrom  env to     acc
 ---   ------ ----- --------- --------- ------- -------    ------- -------    ------- -------    ----
   1 !  168.2   0.0   8.9e-54   8.9e-54       1     182 [.       3     206 ..       3     207 .. 0.94

  Alignments for each domain:
  == domain 1  score: 168.2 bits;  conditional E-value: 8.9e-54
                         TIGR00070   1 lriAlp.KGrleeetlkllekaglklskke.erkliasaed.eevevlllrakdiptyvekgaadlGitGkDlleE. 73 
                                       l++++p KGrl+++t++++ ++g++l+++  er++  s++  ++v ++ll+a +ip++++ g+++lG+tG+Dl++E 
  lcl|FitnessBrowser__Dino:3609569   3 LKLGVPsKGRLMDKTFDWFGRHGITLQRTGsEREYAGSVDGvDGVALVLLSAGEIPRELAAGRIHLGVTGTDLVQEk 79 
                                       79***************************999999998887357********************************6 PP

                         TIGR00070  74 ...seadvvelldlgfgkcklvlAvpees.dvesledlke...........gkriATkypnltreylekkg.vkvei 134
                                          + ++v  ++ lgfg+++l+lAvp+ + dve+l+dl++           + riATky++l++++l+ +g +++++
  lcl|FitnessBrowser__Dino:3609569  80 lpdWMRQVRSIAPLGFGHADLILAVPKCWiDVETLDDLDAvaaqfranhgfRLRIATKYHRLVHSHLSAHGvADYQL 156
                                       6655666***************************************9976445******************889*** PP

                         TIGR00070 135 vkleGavElapllgladaIvDivetGttLrengLkiie..eilessarli 182
                                       v+++Ga+E +++  +a+aI+Di++tG+tLr+n+Lki++   +l+s+a+l+
  lcl|FitnessBrowser__Dino:3609569 157 VDSQGATEGTVANLTAEAIADITSTGETLRANHLKILKgePVLKSQATLF 206
                                       *************************************7658*******97 PP



Internal pipeline statistics summary:
-------------------------------------
Query model(s):                            1  (183 nodes)
Target sequences:                          1  (239 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: 0.00u 0.00s 00:00:00.00 Elapsed: 00:00:00.00
# Mc/sec: 6.73
//
[ok]

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

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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