Alignments for a candidate for dapE in Caulobacter crescentus NA1000

GapMind for Amino acid biosynthesis

Alignments for a candidate for dapE in Caulobacter crescentus NA1000

Align Succinyl-diaminopimelate desuccinylase; SDAP desuccinylase; N-succinyl-LL-2,6-diaminoheptanedioate amidohydrolase; EC 3.5.1.18 (characterized)
to candidate CCNA_00277 CCNA_00277 succinyl-diaminopimelate desuccinylase

Query= SwissProt::Q9JYL2
         (381 letters)



>FitnessBrowser__Caulo:CCNA_00277
          Length = 386

 Score =  321 bits (822), Expect = 2e-92
 Identities = 173/378 (45%), Positives = 231/378 (61%), Gaps = 9/378 (2%)

Query: 7   LELAKELISRPSVTPDDRDCQKLLAERLHKIGFAAEELHFGDTKNIWLRRGTKAPVVCFA 66
           +ELA+ LI RPSVTP D      L  +L  +GFA   + FG+ +N++ RRGT  P +CFA
Sbjct: 14  VELAQALIRRPSVTPADAGAMDTLQRQLEALGFACRRMKFGEIENLYARRGTARPNLCFA 73

Query: 67  GHTDVVPTGPVEKWDSPPFEPAERDGRLYGRGAADMKTSIACFVTACERFVAKHPNHQGS 126
           GHTDVVP G    W + PFE   ++G LYGRGA DMK++IA FV A    VA  P+H GS
Sbjct: 74  GHTDVVPVGDDAAWTAGPFEAEIKEGVLYGRGAVDMKSAIAAFVAA----VANVPDHPGS 129

Query: 127 IALLITSDEEGDALDGTTKVVDVLKARDELIDYCIVGEPTAVDKLGDMIKNGRRGSLSGN 186
           I+ LIT DEEG A DGT KVV+ L A  E+ID+CIVGEPT+ + LGDM+K GRRGS++  
Sbjct: 130 ISFLITGDEEGVAEDGTVKVVEALAAEGEIIDHCIVGEPTSANLLGDMVKIGRRGSINAW 189

Query: 187 LTVKGKQGHIAYPHLAINPVHTFAPALLELTQEVWDEGNEYFPPTSFQISNINGGTGATN 246
           +TV+G+QGH+AYPH A NPV      L  L   V D+G   F P++ +I+ I+ G  ATN
Sbjct: 190 ITVEGRQGHVAYPHRAANPVPVLVDILSALKARVLDDGYTGFQPSNLEITTIDVGNTATN 249

Query: 247 VIPGELNVKFNFRFSTESTEAGLKQRVHAILDKHGVQYD----LQWSCSGQPFLTQAGKL 302
           VIP     + N RF+       L   +     K    +D         SG+ FLT+ G  
Sbjct: 250 VIPAAAKARVNIRFNPAHKGKDLAAWIEGECAKAAEGFDGAATALCKISGEAFLTEPGDF 309

Query: 303 TDVARAAIAETCGIEAELSTTGGTSDGRFIKAIAQELIELGPSNATIHQINENVRLNDIP 362
           TDV  AA+ +  G   ELSTTGGTSD RFI+A+   ++E G   +T+HQ++E V + ++ 
Sbjct: 310 TDVIVAAVTDATGRAPELSTTGGTSDARFIRALC-PVVEFGLVGSTMHQVDERVPVEEVR 368

Query: 363 KLSAVYEGILARLLAGNA 380
           +L+  YE ++ R  A  A
Sbjct: 369 QLAGAYEALIRRYFAAFA 386


Lambda     K      H
   0.317    0.135    0.400 

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: 434
Number of extensions: 15
Number of successful extensions: 4
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: 381
Length of database: 386
Length adjustment: 30
Effective length of query: 351
Effective length of database: 356
Effective search space:   124956
Effective search space used:   124956
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 (21.6 bits)
S2: 50 (23.9 bits)

Align candidate CCNA_00277 CCNA_00277 (succinyl-diaminopimelate desuccinylase)
to HMM TIGR01246 (dapE: succinyl-diaminopimelate desuccinylase (EC 3.5.1.18))

# 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/TIGR01246.hmm
# target sequence database:        /tmp/gapView.30853.genome.faa
# - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -

Query:       TIGR01246  [M=370]
Accession:   TIGR01246
Description: dapE_proteo: succinyl-diaminopimelate desuccinylase
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
    ------- ------ -----    ------- ------ -----   ---- --  --------                             -----------
     4e-135  436.5   0.0   4.6e-135  436.3   0.0    1.0  1  lcl|FitnessBrowser__Caulo:CCNA_00277  CCNA_00277 succinyl-diaminopimel


Domain annotation for each sequence (and alignments):
>> lcl|FitnessBrowser__Caulo:CCNA_00277  CCNA_00277 succinyl-diaminopimelate desuccinylase
   #    score  bias  c-Evalue  i-Evalue hmmfrom  hmm to    alifrom  ali to    envfrom  env to     acc
 ---   ------ ----- --------- --------- ------- -------    ------- -------    ------- -------    ----
   1 !  436.3   0.0  4.6e-135  4.6e-135       2     369 ..      14     380 ..      13     381 .. 0.97

  Alignments for each domain:
  == domain 1  score: 436.3 bits;  conditional E-value: 4.6e-135
                             TIGR01246   2 lelakeLisrksvtPndagaqeliaerLkklgfeieilefedtknlwatrgteepvlvfaGhtDvvPaGelek 74 
                                           +ela+ Li+r+svtP+daga++ ++++L++lgf++++++f++++nl+a+rgt +p+l+faGhtDvvP+G++ +
  lcl|FitnessBrowser__Caulo:CCNA_00277  14 VELAQALIRRPSVTPADAGAMDTLQRQLEALGFACRRMKFGEIENLYARRGTARPNLCFAGHTDVVPVGDDAA 86 
                                           589********************************************************************** PP

                             TIGR01246  75 WssdpfepeerdGklygrGaaDmkgslaafvvaaerfvkknadhkGslsllitsDeegeaidGtkkvvetlke 147
                                           W++ pfe+e+++G+lygrGa+Dmk+++aafv+a+     + +dh Gs+s+lit Deeg a dGt+kvve l +
  lcl|FitnessBrowser__Caulo:CCNA_00277  87 WTAGPFEAEIKEGVLYGRGAVDMKSAIAAFVAAVA----NVPDHPGSISFLITGDEEGVAEDGTVKVVEALAA 155
                                           ********************************977....89******************************** PP

                             TIGR01246 148 rdelidyavvgePssvkklGDvikiGrrGsitgklkikGiqGhvaYPhkaenPvhkavpvlkeliaiklDeGn 220
                                             e id+++vgeP+s++ lGD++kiGrrGsi++ ++++G qGhvaYPh+a nPv+ +v +l +l a+ lD+G 
  lcl|FitnessBrowser__Caulo:CCNA_00277 156 EGEIIDHCIVGEPTSANLLGDMVKIGRRGSINAWITVEGRQGHVAYPHRAANPVPVLVDILSALKARVLDDGY 228
                                           ************************************************************************* PP

                             TIGR01246 221 effppsslqianieagtgasnviPgelkvkfnlrfssevseeelkskvekildkh....kldYelewklsgep 289
                                             f+ps+l+i+ i++g+ a+nviP+++k++ n+rf++ ++ ++l   +e  + k     +   +   k+sge+
  lcl|FitnessBrowser__Caulo:CCNA_00277 229 TGFQPSNLEITTIDVGNTATNVIPAAAKARVNIRFNPAHKGKDLAAWIEGECAKAaegfDGAATALCKISGEA 301
                                           ********************************************9999988877644224444566899**** PP

                             TIGR01246 290 fltkegklikkvaeaieevlkkkpelstsGGtsDarfiaklgaevvelGlvndtihkvneavkiedleklsev 362
                                           flt+ g+ ++++++a++  ++++pelst+GGtsDarfi++l + vve+Glv +t+h+v+e+v +e++++l+  
  lcl|FitnessBrowser__Caulo:CCNA_00277 302 FLTEPGDFTDVIVAAVTDATGRAPELSTTGGTSDARFIRAL-CPVVEFGLVGSTMHQVDERVPVEEVRQLAGA 373
                                           *****************************************.******************************* PP

                             TIGR01246 363 yekllee 369
                                           ye l+++
  lcl|FitnessBrowser__Caulo:CCNA_00277 374 YEALIRR 380
                                           **99975 PP



Internal pipeline statistics summary:
-------------------------------------
Query model(s):                            1  (370 nodes)
Target sequences:                          1  (386 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: 00:00:00.01
# Mc/sec: 10.54
//
[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