Alignments for a candidate for serB in Shewanella amazonensis SB2B

GapMind for Amino acid biosynthesis

Alignments for a candidate for serB in Shewanella amazonensis SB2B

Align Phosphoserine phosphatase; PSP; PSPase; O-phosphoserine phosphohydrolase; EC 3.1.3.3 (characterized)
to candidate 6936796 Sama_0978 phosphoserine phosphatase (RefSeq)

Query= SwissProt::Q5QXU4
         (220 letters)



>FitnessBrowser__SB2B:6936796
          Length = 316

 Score =  170 bits (431), Expect = 2e-47
 Identities = 90/198 (45%), Positives = 127/198 (64%)

Query: 6   GLIVFDMDSTLIHIECIDEIARLNNRYTKVSAITEAAMRGEIDFAESLTQRVACLEGIKE 65
           GL+V DMDST I IECIDE+A +      V+ +TE AM+GE+DF +SL QRVA L G   
Sbjct: 110 GLLVMDMDSTAIKIECIDELAAMAGVGEAVAEVTERAMQGELDFKQSLRQRVAKLAGADA 169

Query: 66  SDLESLFSPIPFNPGAKELIQALQAAGWKTALVSGGFTWFANRVQAALNLDAVVANQLEV 125
             +++L + +P   G  E++  L+  GWK  + SGGFT F   ++A L LDA  AN+L +
Sbjct: 170 GIIDTLCARLPLMDGLTEMLAELKGHGWKLVVASGGFTPFVGHLKATLGLDAAFANELVI 229

Query: 126 ADGCLTGKVLGDIVDAQVKAEQLQQLAGHWNIPPDRTVAVGDGANDGLMLKAAAVGIAFN 185
           ADG L G+V G +VDA  KA+ + +L   + I   + +A+GDGAND  M++ A  GIAF+
Sbjct: 230 ADGKLVGEVTGTVVDANFKADVVSRLGDEYGIKDGQRLAIGDGANDIPMVQRADFGIAFH 289

Query: 186 AKPALQAIADYSVNSNNL 203
           AKP L A AD  +++ +L
Sbjct: 290 AKPKLAAAADARIHTLDL 307


Lambda     K      H
   0.318    0.134    0.384 

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: 187
Number of extensions: 7
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: 220
Length of database: 316
Length adjustment: 25
Effective length of query: 195
Effective length of database: 291
Effective search space:    56745
Effective search space used:    56745
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: 47 (22.7 bits)

Align candidate 6936796 Sama_0978 (phosphoserine phosphatase (RefSeq))
to HMM TIGR00338 (serB: phosphoserine phosphatase SerB (EC 3.1.3.3))

# 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/TIGR00338.hmm
# target sequence database:        /tmp/gapView.29599.genome.faa
# - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -

Query:       TIGR00338  [M=219]
Accession:   TIGR00338
Description: serB: phosphoserine phosphatase SerB
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
    ------- ------ -----    ------- ------ -----   ---- --  --------                         -----------
    1.6e-81  259.1   0.0    2.1e-81  258.7   0.0    1.1  1  lcl|FitnessBrowser__SB2B:6936796  Sama_0978 phosphoserine phosphat


Domain annotation for each sequence (and alignments):
>> lcl|FitnessBrowser__SB2B:6936796  Sama_0978 phosphoserine phosphatase (RefSeq)
   #    score  bias  c-Evalue  i-Evalue hmmfrom  hmm to    alifrom  ali to    envfrom  env to     acc
 ---   ------ ----- --------- --------- ------- -------    ------- -------    ------- -------    ----
   1 !  258.7   0.0   2.1e-81   2.1e-81       9     215 ..     104     310 ..      97     314 .. 0.97

  Alignments for each domain:
  == domain 1  score: 258.7 bits;  conditional E-value: 2.1e-81
                         TIGR00338   9 kllkkkklvvfDlDstlieeEvIdeiaklaGveeeVseiTerAmrgeldFkeslreRvkllkglpvellkkveekle 85 
                                       + l++ +l+v+D+Dst+i++E+Ide+a++aGv+e+V+e+TerAm+geldFk+slr+Rv++l g+++ +++  + +l+
  lcl|FitnessBrowser__SB2B:6936796 104 PSLRHPGLLVMDMDSTAIKIECIDELAAMAGVGEAVAEVTERAMQGELDFKQSLRQRVAKLAGADAGIIDTLCARLP 180
                                       5678899********************************************************************** PP

                         TIGR00338  86 lteGveelvkkLkekgykvaviSGgFdlvaeklkekLgldavfaNrLevedgkltGkvegeivdesakaktllklle 162
                                       l++G++e+  +Lk +g+k++v+SGgF+ ++++lk+ Lglda+faN+L + dgkl G+v+g++vd++ ka+++ +l  
  lcl|FitnessBrowser__SB2B:6936796 181 LMDGLTEMLAELKGHGWKLVVASGGFTPFVGHLKATLGLDAAFANELVIADGKLVGEVTGTVVDANFKADVVSRLGD 257
                                       ***************************************************************************** PP

                         TIGR00338 163 kegislektvavGDGanDlsmikaAglgiafnakpvlkekadiviekkdltdi 215
                                       ++gi+  + +a+GDGanD++m+++A++giaf+akp+l  +ad+ i++ dl+ +
  lcl|FitnessBrowser__SB2B:6936796 258 EYGIKDGQRLAIGDGANDIPMVQRADFGIAFHAKPKLAAAADARIHTLDLRVL 310
                                       ************************************************99866 PP



Internal pipeline statistics summary:
-------------------------------------
Query model(s):                            1  (219 nodes)
Target sequences:                          1  (316 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 0.01s 00:00:00.01 Elapsed: 00:00:00.00
# Mc/sec: 12.35
//
[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