GapMind for catabolism of small carbon sources

 

Aligments for a candidate for rbsK in Shewanella sp. ANA-3

Align Ribokinase (EC 2.7.1.15) (characterized)
to candidate 7026335 Shewana3_3477 ribokinase (RefSeq)

Query= reanno::Koxy:BWI76_RS00290
         (309 letters)



>lcl|FitnessBrowser__ANA3:7026335 Shewana3_3477 ribokinase (RefSeq)
          Length = 303

 Score =  279 bits (713), Expect = 7e-80
 Identities = 148/298 (49%), Positives = 198/298 (66%), Gaps = 3/298 (1%)

Query: 7   LVVLGSINADHILNLDAFPTPGETVTGHHYQVAFGGKGANQAVAAGR---SGANISFIAC 63
           ++V+GS NADH++N +  P PG+T+    Y++  GGKGANQAVA  R     A ++FI  
Sbjct: 4   ILVIGSANADHVMNFEYLPVPGQTLMSRAYRLEHGGKGANQAVACARLCQGDAEVAFICH 63

Query: 64  TGDDDIGERVRRQLESDNIDVAPVRAVAGESTGVALIFVNAEGENTIGIHAGANAALCVA 123
            G D +G  +R     D I    +  VA  STG ALIFV   GEN+IGI AGANA L  +
Sbjct: 64  LGQDSVGNDMRTSWLKDGIKAEGITQVANMSTGTALIFVGDNGENSIGIAAGANADLTPS 123

Query: 124 QVDAEKERIASAQALLMQLESPLESVLAAAKIAHQNQTSVILNPAPARELPDELLTLVDI 183
           +++      A+AQ LL+QLE+P+E+V  A + A +   + +LNPAPA     + L  VDI
Sbjct: 124 ELEKHYALFANAQFLLIQLETPMETVHHALQTAKRLGITTVLNPAPATSQELDYLKWVDI 183

Query: 184 ITPNETEAEKLTGVRVENDEDAAKAAKVLHDKGIGTVIITLGSRGVWASSEGNGRRVPGF 243
           ITPNETEAE LTG+ V N+EDA  AA+ LH +G+ TV+ITLGS+G + SS G    +P  
Sbjct: 184 ITPNETEAEALTGIEVNNEEDAELAAQWLHQQGVATVVITLGSKGAFISSAGFTGLIPAL 243

Query: 244 KVQAVDTIAAGDTFNGALVTALLEGRELAEAIRFAHAAAAIAVTRKGAQPSVPWRKEI 301
            VQA+DT+AAGDTFNGALV  L EG  +A A+ FA+AA+AI VTR+GAQ ++P+R E+
Sbjct: 244 TVQAIDTVAAGDTFNGALVVGLSEGMSIAAAVGFANAASAITVTREGAQRAIPYRHEV 301


Lambda     K      H
   0.315    0.131    0.366 

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: 287
Number of extensions: 9
Number of successful extensions: 2
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: 309
Length of database: 303
Length adjustment: 27
Effective length of query: 282
Effective length of database: 276
Effective search space:    77832
Effective search space used:    77832
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 (21.5 bits)
S2: 48 (23.1 bits)

Align candidate 7026335 Shewana3_3477 (ribokinase (RefSeq))
to HMM TIGR02152 (rbsK: ribokinase (EC 2.7.1.15))

# 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.carbon/TIGR02152.hmm
# target sequence database:        /tmp/gapView.5056.genome.faa
# - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -

Query:       TIGR02152  [M=298]
Accession:   TIGR02152
Description: D_ribokin_bact: ribokinase
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
    ------- ------ -----    ------- ------ -----   ---- --  --------                         -----------
   1.2e-118  381.7   4.2   1.4e-118  381.6   4.2    1.0  1  lcl|FitnessBrowser__ANA3:7026335  Shewana3_3477 ribokinase (RefSeq


Domain annotation for each sequence (and alignments):
>> lcl|FitnessBrowser__ANA3:7026335  Shewana3_3477 ribokinase (RefSeq)
   #    score  bias  c-Evalue  i-Evalue hmmfrom  hmm to    alifrom  ali to    envfrom  env to     acc
 ---   ------ ----- --------- --------- ------- -------    ------- -------    ------- -------    ----
   1 !  381.6   4.2  1.4e-118  1.4e-118       1     297 [.       4     302 ..       4     303 .] 0.99

  Alignments for each domain:
  == domain 1  score: 381.6 bits;  conditional E-value: 1.4e-118
                         TIGR02152   1 ivvvGSinvDlvlrvkrlpkpGetvkaeefkiaaGGKGANQAvaaarlg...aevsmigkvGkDefgeellenlkke 74 
                                       i+v+GS+n+D+v+++++lp+pG+t+ ++ +++ +GGKGANQAva+arl+   aev++i+++G+D++g++++ ++ k+
  lcl|FitnessBrowser__ANA3:7026335   4 ILVIGSANADHVMNFEYLPVPGQTLMSRAYRLEHGGKGANQAVACARLCqgdAEVAFICHLGQDSVGNDMRTSWLKD 80 
                                       89**********************************************99999************************ PP

                         TIGR02152  75 gidteyvkkvkktstGvAlilvdeegeNsIvvvaGaneeltpedvkaaeekikesdlvllQlEipletveealkiak 151
                                       gi++e +++v+++stG+Ali+v ++geNsI ++aGan++ltp++++++ + +++++++l+QlE+p+etv++al++ak
  lcl|FitnessBrowser__ANA3:7026335  81 GIKAEGITQVANMSTGTALIFVGDNGENSIGIAAGANADLTPSELEKHYALFANAQFLLIQLETPMETVHHALQTAK 157
                                       ***************************************************************************** PP

                         TIGR02152 152 kagvkvllnPAPaekkldeellslvdiivpNetEaeiLtgievedledaekaaekllekgvkaviitlGskGallvs 228
                                       + g++++lnPAPa++ ++ ++l++vdii+pNetEae+Ltgiev+++edae aa++l+++gv +v+itlGskGa+++s
  lcl|FitnessBrowser__ANA3:7026335 158 RLGITTVLNPAPATS-QELDYLKWVDIITPNETEAEALTGIEVNNEEDAELAAQWLHQQGVATVVITLGSKGAFISS 233
                                       *************66.779********************************************************** PP

                         TIGR02152 229 kdekklipalkvkavDttaAGDtFigalavaLaegksledavrfanaaaalsVtrkGaqssiPtkeeve 297
                                       ++ + lipal+v+a+Dt+aAGDtF+gal+v L+eg+s+++av fanaa+a++Vtr+Gaq++iP+++ev+
  lcl|FitnessBrowser__ANA3:7026335 234 AGFTGLIPALTVQAIDTVAAGDTFNGALVVGLSEGMSIAAAVGFANAASAITVTREGAQRAIPYRHEVQ 302
                                       *******************************************************************98 PP



Internal pipeline statistics summary:
-------------------------------------
Query model(s):                            1  (298 nodes)
Target sequences:                          1  (303 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 0.01s 00:00:00.02 Elapsed: 00:00:00.01
# Mc/sec: 6.05
//
[ok]

This GapMind analysis is from Sep 17 2021. The underlying query database was built on Sep 17 2021.

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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:

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:

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:

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 preprint on GapMind for carbon sources, or view the source code.

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