Align Phenylacetate-coenzyme A ligase; Phenylacetyl-CoA ligase; PA-CoA ligase; EC 6.2.1.30 (characterized)
to candidate Dsui_1441 Dsui_1441 phenylacetate-CoA ligase
Query= SwissProt::Q9L9C1 (440 letters) >lcl|FitnessBrowser__PS:Dsui_1441 Dsui_1441 phenylacetate-CoA ligase Length = 434 Score = 641 bits (1654), Expect = 0.0 Identities = 308/429 (71%), Positives = 364/429 (84%), Gaps = 2/429 (0%) Query: 11 LEPIEKASQDELRALQLERLKWSVRHAYENVPHYRKAFDAKGVHPDDLKSLADLAKFPFT 70 L+ IE AS+DE+ ALQ+ERL+W+++HAY+NVPHYR FDA+GVHPDD SL DL KFPFT Sbjct: 8 LDAIENASRDEITALQVERLRWTLKHAYDNVPHYRAKFDAQGVHPDDFHSLDDLRKFPFT 67 Query: 71 AKGDLRDNYPFGMFAVPREKVARVHASSGTTGKPTVVGYTLKDIDTWATVVARSIRASGG 130 K DLRDNYPF MFA PRE+V RVHASSGTTGKPTVVGYT KDIDTWA ++ARSI A+GG Sbjct: 68 TKQDLRDNYPFKMFATPREEVVRVHASSGTTGKPTVVGYTQKDIDTWAHLMARSIYAAGG 127 Query: 131 RAGDMVHIAYGYGLFTGGLGAHYGAEKLGCTVVPMSGGQTEKQIQLIQDFKPDIIMVTPS 190 R GD++H+AYGYGLFTGGLGAHYGAE LGCTV+PMSGGQTEKQ+QLI DF P IIM TPS Sbjct: 128 RRGDIIHVAYGYGLFTGGLGAHYGAEALGCTVIPMSGGQTEKQVQLIADFAPRIIMCTPS 187 Query: 191 YMLTVLDEMERMGIDPHQTSLKVGIFGAEPWTQAMRAAMEARAGIDAVDIYGLSEVMGPG 250 YML + DE +R G+DP TSL++GI GAEPWT MR +E GIDAVDIYGLSEVMGPG Sbjct: 188 YMLNIADEFKRQGMDPRGTSLRIGIHGAEPWTDGMRQEIENLLGIDAVDIYGLSEVMGPG 247 Query: 251 VANECIEAKDGPVIWEDHFYPEIIDPHTGEVLPDGSEGELVFTTLTKEAMPVIRYRTRDL 310 VANECIE+KDGPVIWEDHFYPEIIDP+TGEVLP+GS+GELVFT+L+KEA+PV+RYRTRDL Sbjct: 248 VANECIESKDGPVIWEDHFYPEIIDPNTGEVLPEGSQGELVFTSLSKEALPVVRYRTRDL 307 Query: 311 TRLLPPTARSMRRMAKITGRSDDMLIIRGVNLFPTQVEELICKNPKLAPQYLLEVDKDGH 370 TRLL PT+RS RR+ KITGRSDDMLIIRGVN+FP+Q+EELI K KL+ YLLEV +DGH Sbjct: 308 TRLLTPTSRSFRRIGKITGRSDDMLIIRGVNVFPSQIEELILKQAKLSGHYLLEVARDGH 367 Query: 371 MDTLTVKVEINPEANVGRHPEQKEALAKELQHDIKTFIGVSAKVHVCEPFAIERVTIGKA 430 +D++TV VE+ PE + E KE +A ELQH IK++IG+S +V + E IER ++GKA Sbjct: 368 LDSITVNVEMKPEFGIATAAE-KEYVAHELQHHIKSYIGISTQVRIVEVGGIER-SVGKA 425 Query: 431 KRVVDRRPK 439 KRV+D+RP+ Sbjct: 426 KRVIDKRPR 434 Lambda K H 0.318 0.137 0.406 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: 696 Number of extensions: 18 Number of successful extensions: 3 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: 440 Length of database: 434 Length adjustment: 32 Effective length of query: 408 Effective length of database: 402 Effective search space: 164016 Effective search space used: 164016 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 (21.7 bits) S2: 51 (24.3 bits)
Align candidate Dsui_1441 Dsui_1441 (phenylacetate-CoA ligase)
to HMM TIGR02155 (paaF: phenylacetate-CoA ligase (EC 6.2.1.30))
# 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/TIGR02155.hmm # target sequence database: /tmp/gapView.7380.genome.faa # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - Query: TIGR02155 [M=422] Accession: TIGR02155 Description: PA_CoA_ligase: phenylacetate-CoA ligase 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-229 746.9 0.0 2.7e-229 746.8 0.0 1.0 1 lcl|FitnessBrowser__PS:Dsui_1441 Dsui_1441 phenylacetate-CoA liga Domain annotation for each sequence (and alignments): >> lcl|FitnessBrowser__PS:Dsui_1441 Dsui_1441 phenylacetate-CoA ligase # score bias c-Evalue i-Evalue hmmfrom hmm to alifrom ali to envfrom env to acc --- ------ ----- --------- --------- ------- ------- ------- ------- ------- ------- ---- 1 ! 746.8 0.0 2.7e-229 2.7e-229 1 422 [] 12 432 .. 12 432 .. 0.99 Alignments for each domain: == domain 1 score: 746.8 bits; conditional E-value: 2.7e-229 TIGR02155 1 eklsldelralqlerlkvsvkrayenvpayrkafdaagvkpddlkelsdlakfpltaksdlrdnypfdllavprekv 77 e++s+de++alq+erl++++k+ay+nvp+yr++fda+gv+pdd+++l+dl+kfp+t+k+dlrdnypf+++a+pre+v lcl|FitnessBrowser__PS:Dsui_1441 12 ENASRDEITALQVERLRWTLKHAYDNVPHYRAKFDAQGVHPDDFHSLDDLRKFPFTTKQDLRDNYPFKMFATPREEV 88 789************************************************************************** PP TIGR02155 78 vrvhassGttGkptvvaytqkdldtwsevvarslraaGGrkgdllhnayGyGlftGGlGvhyGaeklGatvvpisGG 154 vrvhassGttGkptvv+ytqkd+dtw++++ars++aaGGr+gd++h+ayGyGlftGGlG+hyGae lG+tv+p+sGG lcl|FitnessBrowser__PS:Dsui_1441 89 VRVHASSGTTGKPTVVGYTQKDIDTWAHLMARSIYAAGGRRGDIIHVAYGYGLFTGGLGAHYGAEALGCTVIPMSGG 165 ***************************************************************************** PP TIGR02155 155 qtekqvqliqdfkpdiiavtpsyilalleelkrlgidpedislkvailGaepwteamrkelearlgikaldiyGlse 231 qtekqvqli df p+ii++tpsy+l++++e+kr+g+dp+ +sl+++i Gaepwt+ mr+e+e+ lgi+a+diyGlse lcl|FitnessBrowser__PS:Dsui_1441 166 QTEKQVQLIADFAPRIIMCTPSYMLNIADEFKRQGMDPRGTSLRIGIHGAEPWTDGMRQEIENLLGIDAVDIYGLSE 242 ***************************************************************************** PP TIGR02155 232 viGpGvanecvetkdGlviwedhfypeiidpetgevlpdGeeGelvfttltkealpviryrtrdltrllpgtartmr 308 v+GpGvanec+e+kdG+viwedhfypeiidp+tgevlp+G++Gelvft+l+kealpv+ryrtrdltrll +t+r+ r lcl|FitnessBrowser__PS:Dsui_1441 243 VMGPGVANECIESKDGPVIWEDHFYPEIIDPNTGEVLPEGSQGELVFTSLSKEALPVVRYRTRDLTRLLTPTSRSFR 319 ***************************************************************************** PP TIGR02155 309 rmdkikGrsddllilrGvnvfptqleevllkldklsphyqleltreGaldeltlkvelkdesaalrlleqksllakk 385 r+ ki+Grsdd+li+rGvnvfp+q+ee++lk+ kls+hy le+ r+G+ld++t++ve+k+e ++ +k+ +a++ lcl|FitnessBrowser__PS:Dsui_1441 320 RIGKITGRSDDMLIIRGVNVFPSQIEELILKQAKLSGHYLLEVARDGHLDSITVNVEMKPEFGIAT-AAEKEYVAHE 395 *************************************************************98877.667779**** PP TIGR02155 386 iekkikaevgvsvdvelvepgslerseGkakrvvdkr 422 ++++ik+ +g+s++v++ve g +ers Gkakrv+dkr lcl|FitnessBrowser__PS:Dsui_1441 396 LQHHIKSYIGISTQVRIVEVGGIERSVGKAKRVIDKR 432 ************************************8 PP Internal pipeline statistics summary: ------------------------------------- Query model(s): 1 (422 nodes) Target sequences: 1 (434 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: 10.77 // [ok]
This GapMind analysis is from Sep 17 2021. The underlying query database was built on Sep 17 2021.
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:
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 paper from 2022 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