Alignments for a candidate for serB in Marinobacter adhaerens HP15

GapMind for Amino acid biosynthesis

Alignments for a candidate for serB in Marinobacter adhaerens HP15

Align Phosphoserine phosphatase ThrH; PSP; PSPase; EC 3.1.3.3 (characterized)
to candidate GFF1895 HP15_1852 homoserine kinase

Query= SwissProt::Q9I2Y2
         (205 letters)



>FitnessBrowser__Marino:GFF1895
          Length = 218

 Score =  314 bits (805), Expect = 7e-91
 Identities = 151/199 (75%), Positives = 174/199 (87%)

Query: 1   MEIACLDLEGVLVPEIWIAFAEKTGIDALKATTRDIPDYDVLMKQRLRILDEHGLKLGDI 60
           +E+ACLDLEGVL+PEIWIAFAEKTGI+ LKATTRDIPDYDVLMKQRL++LD+HG  L  I
Sbjct: 15  VELACLDLEGVLIPEIWIAFAEKTGIEELKATTRDIPDYDVLMKQRLKLLDQHGYGLPQI 74

Query: 61  QEVIATLKPLEGAVEFVDWLRERFQVVILSDTFYEFSQPLMRQLGFPTLLCHKLEIDDSD 120
           QEVI  L PL GA EF+DWLRERFQVVILSDTFYEF+ PLM++LG+P LLCHKLE+ D  
Sbjct: 75  QEVIGELDPLPGAREFLDWLRERFQVVILSDTFYEFAMPLMKKLGYPALLCHKLEVADDG 134

Query: 121 RVVGYQLRQKDPKRQSVIAFKSLYYRVIAAGDSYNDTTMLSEAHAGILFHAPENVIREFP 180
           ++  Y LRQ+DPKRQSV AF+ L YRVIAAGDSYNDTTML +A AGILFHAP+NVI EFP
Sbjct: 135 QITNYLLRQRDPKRQSVRAFQLLNYRVIAAGDSYNDTTMLGQAEAGILFHAPQNVIDEFP 194

Query: 181 QFPAVHTYEDLKREFLKAS 199
           QFPAVH ++DL++EFLKAS
Sbjct: 195 QFPAVHNFDDLRQEFLKAS 213


Lambda     K      H
   0.323    0.140    0.408 

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: 224
Number of extensions: 6
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: 205
Length of database: 218
Length adjustment: 21
Effective length of query: 184
Effective length of database: 197
Effective search space:    36248
Effective search space used:    36248
Neighboring words threshold: 11
Window for multiple hits: 40
X1: 16 ( 7.5 bits)
X2: 38 (14.6 bits)
X3: 64 (24.7 bits)
S1: 41 (22.0 bits)
S2: 45 (21.9 bits)

Align candidate GFF1895 HP15_1852 (homoserine kinase)
to HMM TIGR02137 (thrH: phosphoserine phosphatase/homoserine phosphotransferase bifunctional protein (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/TIGR02137.hmm
# target sequence database:        /tmp/gapView.11144.genome.faa
# - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -

Query:       TIGR02137  [M=203]
Accession:   TIGR02137
Description: HSK-PSP: phosphoserine phosphatase/homoserine phosphotransferase bifunctional protein
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
    ------- ------ -----    ------- ------ -----   ---- --  --------                           -----------
   2.4e-106  339.8   0.0     3e-106  339.4   0.0    1.0  1  lcl|FitnessBrowser__Marino:GFF1895  HP15_1852 homoserine kinase


Domain annotation for each sequence (and alignments):
>> lcl|FitnessBrowser__Marino:GFF1895  HP15_1852 homoserine kinase
   #    score  bias  c-Evalue  i-Evalue hmmfrom  hmm to    alifrom  ali to    envfrom  env to     acc
 ---   ------ ----- --------- --------- ------- -------    ------- -------    ------- -------    ----
   1 !  339.4   0.0    3e-106    3e-106       2     200 ..      16     214 ..      15     216 .. 0.99

  Alignments for each domain:
  == domain 1  score: 339.4 bits;  conditional E-value: 3e-106
                           TIGR02137   2 evvtldlegvlvpeiwiavaektgiddlklttrdipdydvlmkqrlkileeenlklsdiqeviatlkllegavef 76 
                                         e+++ldlegvl+peiwia+aektgi++lk+ttrdipdydvlmkqrlk+l++++  l +iqevi +l++l ga+ef
  lcl|FitnessBrowser__Marino:GFF1895  16 ELACLDLEGVLIPEIWIAFAEKTGIEELKATTRDIPDYDVLMKQRLKLLDQHGYGLPQIQEVIGELDPLPGAREF 90 
                                         789************************************************************************ PP

                           TIGR02137  77 vdtlreeaqvvilsdtfqefaqplmkqlgfptllchklvvedsdrvkgyqlrqkdqkrkvvkalkelyykviaag 151
                                         +d+lre++qvvilsdtf+efa plmk+lg+p+llchkl+v d  ++  y lrq+d+kr++v+a++ l+y+viaag
  lcl|FitnessBrowser__Marino:GFF1895  91 LDWLRERFQVVILSDTFYEFAMPLMKKLGYPALLCHKLEVADDGQITNYLLRQRDPKRQSVRAFQLLNYRVIAAG 165
                                         ******************************************9******************************** PP

                           TIGR02137 152 dsyndttmlkeadkgilfhapesvvaefpqleavktyeelkdkflkasd 200
                                         dsyndttml +a++gilfhap++v+ efpq++av+ +++l+++flkas+
  lcl|FitnessBrowser__Marino:GFF1895 166 DSYNDTTMLGQAEAGILFHAPQNVIDEFPQFPAVHNFDDLRQEFLKASE 214
                                         **********************************************986 PP



Internal pipeline statistics summary:
-------------------------------------
Query model(s):                            1  (203 nodes)
Target sequences:                          1  (218 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 0.00s 00:00:00.01 Elapsed: 00:00:00.00
# Mc/sec: 7.74
//
[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