Alignments for a candidate for hisG in Methylomonas methanica MC09

GapMind for Amino acid biosynthesis

Alignments for a candidate for hisG in Methylomonas methanica MC09

Align ATP phosphoribosyltransferase (EC 2.4.2.17) (characterized)
to candidate WP_013817408.1 METME_RS03480 ATP phosphoribosyltransferase

Query= reanno::psRCH2:GFF3236
         (210 letters)



>NCBI__GCF_000214665.1:WP_013817408.1
          Length = 208

 Score =  295 bits (756), Expect = 3e-85
 Identities = 147/199 (73%), Positives = 176/199 (88%)

Query: 1   MLTIALSKGRILDDTLPLLAAAGIVPTENPDKSRKLIIPTTQDDVRLLIVRATDVPTYVE 60
           MLTIA+SKGRI ++ LP L  AGI PT++PDKSRKLI+ TT+ DV+L+I+RATDVPT+VE
Sbjct: 1   MLTIAVSKGRIYEEALPFLQQAGITPTDDPDKSRKLILQTTRPDVQLVIIRATDVPTFVE 60

Query: 61  HGAADLGVAGKDVLMEYGGQGLYEPLDLRIANCKLMTAGKVGAPEPKGRLRVATKFVNVA 120
           +GAADLG+AGKDVL+E+G + LYEPLDL IA C+LMTAG V APE KGRLRVATK+V  A
Sbjct: 61  YGAADLGIAGKDVLLEHGAESLYEPLDLGIAGCRLMTAGPVNAPEVKGRLRVATKYVKTA 120

Query: 121 KRYYAEQGRQVDIIKLYGSMELAPLVGLADKIIDVVDTGNTLRANGLEPQELIAHISSRL 180
           +RYYA+ G Q +IIKLYGSMELAPLVGLAD I+D+VDTGNTL+ANGLEP+ELIA+I+SRL
Sbjct: 121 QRYYADLGIQAEIIKLYGSMELAPLVGLADCIVDLVDTGNTLKANGLEPRELIANITSRL 180

Query: 181 VVNKASMKMQHARIQALID 199
           VVNKA+MKM+H  IQALID
Sbjct: 181 VVNKAAMKMKHQAIQALID 199


Lambda     K      H
   0.319    0.137    0.383 

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: 214
Number of extensions: 3
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: 210
Length of database: 208
Length adjustment: 21
Effective length of query: 189
Effective length of database: 187
Effective search space:    35343
Effective search space used:    35343
Neighboring words threshold: 11
Window for multiple hits: 40
X1: 16 ( 7.4 bits)
X2: 38 (14.6 bits)
X3: 64 (24.7 bits)
S1: 41 (21.8 bits)
S2: 45 (21.9 bits)

Align candidate WP_013817408.1 METME_RS03480 (ATP phosphoribosyltransferase)
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.22941.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
    ------- ------ -----    ------- ------ -----   ---- --  --------                                 -----------
    1.3e-59  187.2   0.0    1.6e-59  187.0   0.0    1.0  1  lcl|NCBI__GCF_000214665.1:WP_013817408.1  METME_RS03480 ATP phosphoribosyl


Domain annotation for each sequence (and alignments):
>> lcl|NCBI__GCF_000214665.1:WP_013817408.1  METME_RS03480 ATP phosphoribosyltransferase
   #    score  bias  c-Evalue  i-Evalue hmmfrom  hmm to    alifrom  ali to    envfrom  env to     acc
 ---   ------ ----- --------- --------- ------- -------    ------- -------    ------- -------    ----
   1 !  187.0   0.0   1.6e-59   1.6e-59       1     183 []       2     182 ..       2     182 .. 0.95

  Alignments for each domain:
  == domain 1  score: 187.0 bits;  conditional E-value: 1.6e-59
                                 TIGR00070   1 lriAlpKGrleeetlkllekaglklskke..erkliasaedeevevlllrakdiptyvekgaadlGitG 67 
                                               l+iA+ KGr+ ee+l +l++ag++ ++    +rkli ++++++v+++++ra+d+pt+ve+gaadlGi G
  lcl|NCBI__GCF_000214665.1:WP_013817408.1   2 LTIAVSKGRIYEEALPFLQQAGITPTDDPdkSRKLILQTTRPDVQLVIIRATDVPTFVEYGAADLGIAG 70 
                                               79*********************988766689************************************* PP

                                 TIGR00070  68 kDlleEsead.vvelldlgfgkcklvlAvpees.dvesledlkegk.riATkypnltreylekkgvkve 133
                                               kD+l E++a+ ++e ldlg+  c+l+ A p +  +v+       g+ r+ATky++++++y+++ g+++e
  lcl|NCBI__GCF_000214665.1:WP_013817408.1  71 KDVLLEHGAEsLYEPLDLGIAGCRLMTAGPVNApEVK-------GRlRVATKYVKTAQRYYADLGIQAE 132
                                               ******98887*********************94443.......445********************** PP

                                 TIGR00070 134 ivkleGavElapllgladaIvDivetGttLrengLkiieeilessarlia 183
                                               i+kl+G++Elapl+glad+IvD+v tG+tL++ngL+  e i ++++rl++
  lcl|NCBI__GCF_000214665.1:WP_013817408.1 133 IIKLYGSMELAPLVGLADCIVDLVDTGNTLKANGLEPRELIANITSRLVV 182
                                               ***********************************************985 PP



Internal pipeline statistics summary:
-------------------------------------
Query model(s):                            1  (183 nodes)
Target sequences:                          1  (208 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: 8.58
//
[ok]

This GapMind analysis is from Apr 10 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