Align L-tyrosine transporter (characterized)
to candidate PP_4495 PP_4495 aromatic amino acid transport protein
Query= reanno::pseudo5_N2C3_1:AO356_18530 (471 letters) >FitnessBrowser__Putida:PP_4495 Length = 472 Score = 806 bits (2082), Expect = 0.0 Identities = 392/467 (83%), Positives = 435/467 (93%) Query: 1 MSGQNSHSGELKRGLKNRHIQLIALGGAIGTGLFLGSAGVLKSAGPSMILGYAICGFIAF 60 MSGQN HSGELKRGLKNRHIQLIALGGAIGTGLFLGSAGV+KSAGPSMILGYAICGFIAF Sbjct: 1 MSGQNMHSGELKRGLKNRHIQLIALGGAIGTGLFLGSAGVMKSAGPSMILGYAICGFIAF 60 Query: 61 MIMRQLGEMIVEEPVAGSFSHFAHKYWGGFAGFLSGWNCWILYILVGMSELTAVGKYIHY 120 MIMRQLGEMIVEEPVAGSFSHFAH YWGGFAGFLSGWNCW+LYILVGMSEL+AVGKY+HY Sbjct: 61 MIMRQLGEMIVEEPVAGSFSHFAHTYWGGFAGFLSGWNCWVLYILVGMSELSAVGKYVHY 120 Query: 121 WAPDIPTWVSAAAFFILINAINLANVKVFGEAEFWFAIIKVVAIVGMIALGSYLLVSGHG 180 W P+IPTWV+AAAFF+LINAINL NVK FGEAEFWFAIIKVVAIV MI LG+YLL SG G Sbjct: 121 WWPEIPTWVTAAAFFVLINAINLMNVKFFGEAEFWFAIIKVVAIVSMIGLGAYLLTSGSG 180 Query: 181 GPQASVTNLWSHGGFFPNGVSGLVMAMAIIMFSFGGLEMLGFTAAEADKPKTVIPKAINQ 240 GP+A+V NLW+HGGFFPNGVSGLVMA+A IMFSFGGLEMLGFTAAEADKPKTVIPKAINQ Sbjct: 181 GPEATVANLWTHGGFFPNGVSGLVMALAFIMFSFGGLEMLGFTAAEADKPKTVIPKAINQ 240 Query: 241 VIYRILIFYIGALVVLLSLTPWDSLLATLNASGDAYSGSPFVQVFSMLGSNTAAHILNFV 300 VIYRILIFY+GALVVLLSLTPWD+L+A+++ASG +Y SPFVQVFS+LGS+ AA++LNFV Sbjct: 241 VIYRILIFYVGALVVLLSLTPWDNLVASIDASGGSYGSSPFVQVFSLLGSDVAANLLNFV 300 Query: 301 VLTAALSVYNSGTYCNSRMLLGMAEQGDAPKALSRIDKRGVPVRSILASAAVTLVAVLLN 360 VLTAALSVYNSGTYCN+RMLLGMAEQGDAP +L+++DKRGVPVRSIL SAAVT VAVLLN Sbjct: 301 VLTAALSVYNSGTYCNARMLLGMAEQGDAPASLAKVDKRGVPVRSILVSAAVTFVAVLLN 360 Query: 361 YLVPQHALELLMSLVVATLVINWAMISYSHFKFRQHMNQTQQTPLFKALWYPYGNYICLA 420 YL+PQ+ALELLMSLVVATLVINWAMISYSH KFRQH+++T Q PLFKALWYPYGNY+ LA Sbjct: 361 YLMPQNALELLMSLVVATLVINWAMISYSHLKFRQHLDRTGQKPLFKALWYPYGNYVVLA 420 Query: 421 FVVFILGVMLLIPGIQISVYAIPVWVVFMWVCYVIKNKRSARQELAV 467 FVV ILG+ML+IPGIQ+SVYAIPVW++ M V Y++K++R AV Sbjct: 421 FVVLILGIMLMIPGIQVSVYAIPVWLLAMLVVYMVKSRRQVNAGGAV 467 Lambda K H 0.327 0.139 0.432 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: 810 Number of extensions: 32 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: 471 Length of database: 472 Length adjustment: 33 Effective length of query: 438 Effective length of database: 439 Effective search space: 192282 Effective search space used: 192282 Neighboring words threshold: 11 Window for multiple hits: 40 X1: 15 ( 7.1 bits) X2: 38 (14.6 bits) X3: 64 (24.7 bits) S1: 40 (21.7 bits) S2: 51 (24.3 bits)
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