Answers.Body: <p><a href="http://pfam.xfam.org/f" rel="nofollow noreferrer">PFam</a> has HMM models for protein domains, this is almost certainly what you're after. You can download all PFam-A models from <a href="ftp://ftp.ebi.ac.uk/pub/databases/Pfam/current_release/Pfam-A.hmm.gz" rel="nofollow noreferrer">ftp://ftp.ebi.ac.uk/pub/databases/Pfam/current_release/Pfam-A.hmm.gz</a>.</p>
  
  <p>Then, you're looking for the "Pkinase", PF00069 family (I found this simply by searching the PFam website for "kinase"), so extract it from the file:</p>
  
  <pre><code>zcat Pfam-A.hmm.gz | awk -vRS='//' -vORS='//' '/PF00069/' &gt; PF00069.pfam
  </code></pre>
  
  <p>Then, format it for HMMER format (you will need to install <a href="http://hmmer.org/" rel="nofollow noreferrer">HMMER</a>)</p>
  
  <pre><code>hmmpress PF00069.hmm
  </code></pre>
  
  <p>And now you can use it to search your sequences (fasta or flat file, probably others; see the <a href="http://www.csb.yale.edu/userguides/seq/hmmer/docs/" rel="nofollow noreferrer">documentation</a> for details):</p>
  
  <pre><code>hmmscan PF00069.hmm prots.pep 
  </code></pre>
  
  <p>I tried this on a fasta file with the sequences of <a href="http://www.uniprot.org/uniprot/P53894.fasta" rel="nofollow noreferrer">CBK1_YEAST</a>, <a href="http://www.uniprot.org/uniprot/P15790.fasta" rel="nofollow noreferrer">CSK21_YEAST</a> (kinases) and <a href="http://www.uniprot.org/uniprot/P21333.fasta" rel="nofollow noreferrer">FLNA_HUMAN</a> (non-kinase control) and got:</p>
  
  <pre><code># hmmscan :: search sequence(s) against a profile database
  # HMMER 3.1b2 (February 2015); http://hmmer.org/
  # Copyright (C) 2015 Howard Hughes Medical Institute.
  # Freely distributed under the GNU General Public License (GPLv3).
  # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
  # query sequence file:             prots.pep
  # target HMM database:             PF00069.hmm
  # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
  
  Query:       sp|P53894|CBK1_YEAST  [L=756]
  Description: Serine/threonine-protein kinase CBK1 OS=Saccharomyces cerevisiae (strain ATCC 204508 / S288c) GN=CBK1 PE=1 SV=1
  Scores for complete sequence (score includes all domains):
     --- full sequence ---   --- best 1 domain ---    -#dom-
      E-value  score  bias    E-value  score  bias    exp  N  Model    Description
      ------- ------ -----    ------- ------ -----   ---- --  -------- -----------
      2.7e-64  203.2   9.0    3.5e-46  143.8   0.2    3.1  3  Pkinase   Protein kinase domain
  
  
  Domain annotation for each model (and alignments):
  &gt;&gt; Pkinase  Protein kinase domain
     #    score  bias  c-Evalue  i-Evalue hmmfrom  hmm to    alifrom  ali to    envfrom  env to     acc
   ---   ------ ----- --------- --------- ------- -------    ------- -------    ------- -------    ----
     1 ?   -2.9   3.2      0.19      0.19     198     226 ..     222     243 ..     191     277 .. 0.57
     2 !  143.8   0.2   3.5e-46   3.5e-46       1     153 [.     352     505 ..     352     522 .. 0.95
     3 !   63.6   0.0   9.8e-22   9.8e-22     154     264 .]     568     672 ..     551     672 .. 0.83
  
    Alignments for each domain:
    == domain 1  score: -2.9 bits;  conditional E-value: 0.19
                             TTSSCHHHHHHHHHTHHHHHHHCTSHH.. CS
                 Pkinase 198 sgekgkekvekeldqlekilkilgetkek 226
                             + +++++++++      + ++i ++++++
    sp|P53894|CBK1_YEAST 222 Q-QQQQQQQQQ------QHMQIQQQQQQQ 243
                             1.111111111......122222221222 PP
  
    == domain 2  score: 143.8 bits;  conditional E-value: 3.5e-46
                             EEEEEEEEEESSEEEEEEEETTTTEEEEEEEEEHHCCCHHHH.HHHHHHHHHHHHHSSTTB--EEEEEEESSEEEEEEE--TTEBHHHH CS
                 Pkinase   1 yekleklGeGsfGkVykaveketgkivAvKkikkekakkkke.kkvlrEikilkklkhpnivrlyevfeekdelylvleyveggeladl 88 
                             +++++ +G+G+fG+V  + +k+tgki+A+K++ k+++ kk++  +v +E  +l+ +++p +v ly++f++ ++lyl++e+++gg+l+++
    sp|P53894|CBK1_YEAST 352 FHTVKVIGKGAFGEVRLVQKKDTGKIYAMKTLLKSEMYKKDQlAHVKAERDVLAGSDSPWVVSLYYSFQDAQYLYLIMEFLPGGDLMTM 440
                             67899********************************999999********************************************** PP
  
                             HHHHSS--HHHHHHHHHHHHHHHHHHHHTTEE-SS-SGGGEEEETTTEEEE-SGTTSEECCSSCS CS
                 Pkinase  89 lsrkgslseeeakkiakqilegleylHskgiiHrDlKpeNiLidekgelKitDFGlakelesssk 153
                             l r + ++e+ +++++++ + ++e +H+ g+iHrD+Kp+NiLid +g++K++DFGl++ ++++++
    sp|P53894|CBK1_YEAST 441 LIRWQLFTEDVTRFYMAECILAIETIHKLGFIHRDIKPDNILIDIRGHIKLSDFGLSTGFHKTHD 505
                             **999*****************************************************9999876 PP
  
    == domain 3  score: 63.6 bits;  conditional E-value: 9.8e-22
                             BCTCCSCGGGS-HHHHTTSTCSHHHHHHHHHHHHHHHHHSS-STTTSSCHHHHHHHHHTHHHHHHHCTSHH......TTS-HHHHHHHH CS
                 Pkinase 154 ltsfvgtreYlAPEvlkeneyskkvDvWslGvilyelltgkppfsgekgkekvekeldqlekilkilgetkeklpeaselseeakdllk 242
                             + s vgt++Y+APE+  +++y++++D+WslG i+ye l g ppf +e+ +e+++k+++          e+++++p + ++s ea dl++
    sp|P53894|CBK1_YEAST 568 AYSTVGTPDYIAPEIFLYQGYGQECDWWSLGAIMYECLIGWPPFCSETPQETYRKIMNF---------EQTLQFPDDIHISYEAEDLIR 647
                             6789*****************************************66665533333333.........557799*************** PP
  
                             HHT-SSGCCSTT....HHHHHTSGGG CS
                 Pkinase 243 kllkkdpkkRlt....aeellqhpyl 264
                             +ll+    +Rl+    a+e+++hp++
    sp|P53894|CBK1_YEAST 648 RLLTHA-DQRLGrhggADEIKSHPFF 672
                             ***875.678877779********98 PP
  
  
  
  Internal pipeline statistics summary:
  -------------------------------------
  Query sequence(s):                         1  (756 residues searched)
  Target model(s):                           1  (264 nodes)
  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: inf
  //
  Query:       sp|P15790|CSK21_YEAST  [L=372]
  Description: Casein kinase II subunit alpha OS=Saccharomyces cerevisiae (strain ATCC 204508 / S288c) GN=CKA1 PE=1 SV=1
  Scores for complete sequence (score includes all domains):
     --- full sequence ---   --- best 1 domain ---    -#dom-
      E-value  score  bias    E-value  score  bias    exp  N  Model    Description
      ------- ------ -----    ------- ------ -----   ---- --  -------- -----------
      7.5e-62  195.1   7.2    3.2e-55  173.4   0.7    2.1  2  Pkinase   Protein kinase domain
  
  
  Domain annotation for each model (and alignments):
  &gt;&gt; Pkinase  Protein kinase domain
     #    score  bias  c-Evalue  i-Evalue hmmfrom  hmm to    alifrom  ali to    envfrom  env to     acc
   ---   ------ ----- --------- --------- ------- -------    ------- -------    ------- -------    ----
     1 !   25.5   1.1   4.3e-10   4.3e-10       1      60 [.      40      94 ..      40     115 .. 0.87
     2 !  173.4   0.7   3.2e-55   3.2e-55      56     264 .]     128     363 ..     101     363 .. 0.92
  
    Alignments for each domain:
    == domain 1  score: 25.5 bits;  conditional E-value: 4.3e-10
                             EEEEEEEEEESSEEEEEEEETTTTEEEEEEEEEHHCCCHHHHHHHHHHHHHHHHHSSTTB CS
                  Pkinase  1 yekleklGeGsfGkVykaveketgkivAvKkikkekakkkkekkvlrEikilkklkhpni 60
                             ye ++k+G+G++++V+++v+ +++ ++++K++k  k+kk k     rEikil  l+ +++
    sp|P15790|CSK21_YEAST 40 YEIENKVGRGKYSEVFQGVKLDSKVKIVIKMLKPVKKKKIK-----REIKILTDLSNEKV 94
                             78999****************************99888855.....7******9998877 PP
  
    == domain 2  score: 173.4 bits;  conditional E-value: 3.2e-55
                              S.STTB--EEEEEEE..SSEEEEEEE--TTEBHHHHHHHHSS--HHHHHHHHHHHHHHHHHHHHTTEE-SS-SGGGEEEE.TTTEEEE CS
                  Pkinase  56 k.hpnivrlyevfee..kdelylvleyveggeladllsrkgslseeeakkiakqilegleylHskgiiHrDlKpeNiLid.ekgelKi 139
                              + h ni++l++++++  +++  lv+eyv++ ++  l+    +l++ e+++++ ++l++l+y+Hs+gi+HrD+Kp+N++id ++++l++
    sp|P15790|CSK21_YEAST 128 NgHANIIHLFDIIKDpiSKTPALVFEYVDNVDFRILYP---KLTDLEIRFYMFELLKALDYCHSMGIMHRDVKPHNVMIDhKNKKLRL 212
                              35*************8878888*********9988887...5**************************************66677*** PP
  
                              -SGTTSEECCSSCSBCTCCSCGGGS-HHHH.TTSTCSHHHHHHHHHHHHHHHHHSS-STTTSSCHHHHHHHHHTHHHHHHHCTSHH.. CS
                  Pkinase 140 tDFGlakelessskltsfvgtreYlAPEvl.keneyskkvDvWslGvilyelltgkppfsgekgkekvekeldqlekilkilgetkek 226
                              +D+Gla+ ++ + +++ +v++r +  PE+l ++++y+ + D+Ws G +l++++++++pf   +g++    ++dql+ki+k+lg+++++
    sp|P15790|CSK21_YEAST 213 IDWGLAEFYHVNMEYNVRVASRFFKGPELLvDYRMYDYSLDLWSFGTMLASMIFKREPFF--HGTS----NTDQLVKIVKVLGTSDFE 294
                              ******************************999***************************..3443....789**********77766 PP
  
                              ....TTS...............................-HHHHHHHHHHT-SSGCCSTTHHHHHTSGGG CS
                  Pkinase 227 lpeasel...............................seeakdllkkllkkdpkkRltaeellqhpyl 264
                                  +                                 ++e++dl+++ll++d+++Rlta+e++ hp++
    sp|P15790|CSK21_YEAST 295 KYLLKYEitlprefydmdqyirkpwhrfindgnkhlsgNDEIIDLIDNLLRYDHQERLTAKEAMGHPWF 363
                              5554444588999999****************************************************9 PP
  
  
  
  Internal pipeline statistics summary:
  -------------------------------------
  Query sequence(s):                         1  (372 residues searched)
  Target model(s):                           1  (264 nodes)
  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: 00:00:00.02
  # Mc/sec: 4.91
  //
  Query:       sp|P21333|FLNA_HUMAN  [L=2647]
  Description: Filamin-A OS=Homo sapiens GN=FLNA PE=1 SV=4
  Scores for complete sequence (score includes all domains):
     --- full sequence ---   --- best 1 domain ---    -#dom-
      E-value  score  bias    E-value  score  bias    exp  N  Model    Description
      ------- ------ -----    ------- ------ -----   ---- --  -------- -----------
  
     [No hits detected that satisfy reporting thresholds]
  
  
  Domain annotation for each model (and alignments):
  
     [No targets detected that satisfy reporting thresholds]
  
  
  Internal pipeline statistics summary:
  -------------------------------------
  Query sequence(s):                         1  (2647 residues searched)
  Target model(s):                           1  (264 nodes)
  Passed MSV filter:                         0  (0); expected 0.0 (0.02)
  Passed bias filter:                        0  (0); expected 0.0 (0.02)
  Passed Vit filter:                         0  (0); expected 0.0 (0.001)
  Passed Fwd filter:                         0  (0); expected 0.0 (1e-05)
  Initial search space (Z):                  1  [actual number of targets]
  Domain search space  (domZ):               0  [number of targets reported over threshold]
  # CPU time: 0.00u 0.00s 00:00:00.00 Elapsed: 00:00:00.00
  # Mc/sec: inf
  //
  </code></pre>
  
  <hr>
  
  <p>HMMER is a great tool and can also analyse multiple sequence alignments to build the hmms if that's what you need. I strongly urge you to reads <a href="http://www.csb.yale.edu/userguides/seq/hmmer/docs/" rel="nofollow noreferrer">its documentation</a> which is both informative and a surpisingly fun read (it includes such phrases as "<em>Their format is “proprietary”, which is an open source term of art that means both “I haven’t found time
  to document them yet” and “I still might decide to change them arbitrarily without telling you”</em>").</p>
  
Answers.ContentLicense: CC BY-SA 3.0
Answers.CreationDate: 2018-01-26T15:22:15.703Z
Answers.Text: I was sure that with pfam and hmmer it could be possible to find a specific protein motif. But given that the OP has a consensus it might be hard to use it to search in pfam.
Answers.UserDisplayName: llrs
Answers.ContentLicense: CC BY-SA 3.0
Answers.CreationDate: 2018-01-26T15:58:39.483Z
Answers.Text: @Llopis pfam has HMM models which are essentially PWMs. And this isn't a way of searching PFam, it's a way of using PFam to search protein sequences. The OP says: "*I am trying to identify proteins that carry a consensus target sequence for a kinase.*", so I assume Ian has a list of proteins and needs to search through them for a kinase domain. I may be wrong, but that's what I got from the question.
Answers.UserDisplayName: terdon
Answers.ContentLicense: CC BY-SA 3.0
Answers.CreationDate: 2018-01-26T16:02:20.480Z
Answers.Text: I need to review my notes on HMM. Thanks for the answer!
Answers.UserDisplayName: llrs
Answers.ContentLicense: CC BY-SA 3.0
Answers.CreationDate: 2018-01-27T07:35:01.633Z
Answers.Text: Thanks, but its the pwm for the kinase targets rather than the kinase domain i was looking for.
Answers.UserDisplayName: Ian Sudbery
Answers.ContentLicense: CC BY-SA 3.0
Answers.CreationDate: 2018-01-26T14:27:45.727Z
Answers.LastActivityDate: 2018-01-26T14:27:45.727Z
Answers.UserDisplayName: terdon
Body: <p>I am trying to identify proteins that carry a consensus target sequence for a kinase. Usually if I am working with, for e.g. transcription factors binding to DNA I would use position weight matrices (PWMs) from one of a number of databases of PWMs to search the sequences with something like FIMO.</p>
  
  <p>However, I don't know of any databases that contain protein motif PWMs. Specially I am looking for one for yeast Cdc28, but it seems like it would be a generally useful resource that I can't believe doesn't exist. For example, while the MEME suite was originally developed to identify protein motifs, and ouputs PWMs, all of its databases refer to DNA or RNA. </p>
  
Comments.ContentLicense: CC BY-SA 3.0
Comments.CreationDate: 2018-01-25T14:32:02.850Z
Comments.Text: As the sequence of a protein usually is set on the DNA level, why should there be one specific for proteins? Given a DNA sequence you can find the amino acids, but not the other way around, so it is usually done with DNA (AFAIK)
Comments.UserDisplayName: llrs
Comments.ContentLicense: CC BY-SA 3.0
Comments.CreationDate: 2018-01-25T17:07:05.800Z
Comments.Text: Thats true, but usually DNA/RNA PWMs encode the binding sites of proteins on DNA/RNA. I am looking for the binding sites of proteins on other proteins. A DNA PWM is probably not suitable for this because, for example  Cdc28 binds the amino acid consensus S/T-P-X-K/R and there are many many ways of encoding this in DNA because each amino acid can be coded for by many codons. I doubt that a PWM built on the DNA sequences of the genes with this consensus would return a sensible PWM.
Comments.UserDisplayName: Ian Sudbery
Comments.ContentLicense: CC BY-SA 3.0
Comments.CreationDate: 2018-01-25T21:25:54.823Z
Comments.Text: I think it easy enough to do it yourself with the sequences you want. You can use Biopython to build the PWM once you have the sequences (which could be downloaded from Uniprot).
Comments.UserDisplayName: llrs
Comments.ContentLicense: CC BY-SA 3.0
Comments.CreationDate: 2018-01-26T00:57:24.087Z
Comments.Text: My problem is I don't know the PWM - I only know the consensus sequence, not the frequency variation about that. That is why I was hopeing someone could point me to a database that might contain the full PWM. (e.g. The first amino acid of the target site can be Serine or Threonine, but I have no idea if one is favoured over the other)
Comments.UserDisplayName: Ian Sudbery
Comments.ContentLicense: CC BY-SA 3.0
Comments.CreationDate: 2018-01-26T07:27:35.173Z
Comments.Text: And how has you built the consensus sequence? If it is consensus you have a MSA, so you can use it to calculate the PWM.
Comments.UserDisplayName: llrs
Comments.ContentLicense: CC BY-SA 3.0
Comments.CreationDate: 2018-01-27T07:38:46.090Z
Comments.Text: I just pulled it out of a paper. Actually, not true. My collaborator did or at least its something they just know and i assume they could look out the reference for if necessary...
Comments.UserDisplayName: Ian Sudbery
Tags: <public-databases><motifs>
Title: Database of position weight matrices for protein motifs?
ThreadText: # Database of position weight matrices for protein motifs?
  
  (Asked by: username_0 on 2018-01-25)
  
  I am trying to identify proteins that carry a consensus target sequence for a kinase. Usually if I am working with, for e.g. transcription factors binding to DNA I would use position weight matrices (PWMs) from one of a number of databases of PWMs to search the sequences with something like FIMO.
  
  However, I don't know of any databases that contain protein motif PWMs. Specially I am looking for one for yeast Cdc28, but it seems like it would be a generally useful resource that I can't believe doesn't exist. For example, while the MEME suite was originally developed to identify protein motifs, and ouputs PWMs, all of its databases refer to DNA or RNA.
  
  **Tags:** public-databases, motifs
  
  > **Comments:**
  > **username_1**: As the sequence of a protein usually is set on the DNA level, why should there be one specific for proteins? Given a DNA sequence you can find the amino acids, but not the other way around, so it is usually done with DNA (AFAIK)  
  > **username_0**: Thats true, but usually DNA/RNA PWMs encode the binding sites of proteins on DNA/RNA. I am looking for the binding sites of proteins on other proteins. A DNA PWM is probably not suitable for this because, for example  Cdc28 binds the amino acid consensus S/T-P-X-K/R and there are many many ways of encoding this in DNA because each amino acid can be coded for by many codons. I doubt that a PWM built on the DNA sequences of the genes with this consensus would return a sensible PWM.  
  > **username_1**: I think it easy enough to do it yourself with the sequences you want. You can use Biopython to build the PWM once you have the sequences (which could be downloaded from Uniprot).  
  > **username_0**: My problem is I don't know the PWM - I only know the consensus sequence, not the frequency variation about that. That is why I was hopeing someone could point me to a database that might contain the full PWM. (e.g. The first amino acid of the target site can be Serine or Threonine, but I have no idea if one is favoured over the other)  
  > **username_1**: And how has you built the consensus sequence? If it is consensus you have a MSA, so you can use it to calculate the PWM.  
  > **username_0**: I just pulled it out of a paper. Actually, not true. My collaborator did or at least its something they just know and i assume they could look out the reference for if necessary...  
  
  ---
  
  ## 1 answers
  
  ### Answer by username_2 on 2018-01-26. Score: 2
  
  [PFam](http://pfam.xfam.org/f) has HMM models for protein domains, this is almost certainly what you're after. You can download all PFam-A models from <ftp://ftp.ebi.ac.uk/pub/databases/Pfam/current_release/Pfam-A.hmm.gz>.
  
  Then, you're looking for the "Pkinase", PF00069 family (I found this simply by searching the PFam website for "kinase"), so extract it from the file:
  
  ```
  zcat Pfam-A.hmm.gz | awk -vRS='//' -vORS='//' '/PF00069/' > PF00069.pfam
  
  ```
  
  Then, format it for HMMER format (you will need to install [HMMER](http://hmmer.org/))
  
  ```
  hmmpress PF00069.hmm
  
  ```
  
  And now you can use it to search your sequences (fasta or flat file, probably others; see the [documentation](http://www.csb.yale.edu/userguides/seq/hmmer/docs/) for details):
  
  ```
  hmmscan PF00069.hmm prots.pep 
  
  ```
  
  I tried this on a fasta file with the sequences of [CBK1\_YEAST](http://www.uniprot.org/uniprot/P53894.fasta), [CSK21\_YEAST](http://www.uniprot.org/uniprot/P15790.fasta) (kinases) and [FLNA\_HUMAN](http://www.uniprot.org/uniprot/P21333.fasta) (non-kinase control) and got:
  
  ```
  # hmmscan :: search sequence(s) against a profile database
  # HMMER 3.1b2 (February 2015); http://hmmer.org/
  # Copyright (C) 2015 Howard Hughes Medical Institute.
  # Freely distributed under the GNU General Public License (GPLv3).
  # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
  # query sequence file:             prots.pep
  # target HMM database:             PF00069.hmm
  # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
  
  Query:       sp|P53894|CBK1_YEAST  [L=756]
  Description: Serine/threonine-protein kinase CBK1 OS=Saccharomyces cerevisiae (strain ATCC 204508 / S288c) GN=CBK1 PE=1 SV=1
  Scores for complete sequence (score includes all domains):
     --- full sequence ---   --- best 1 domain ---    -#dom-
      E-value  score  bias    E-value  score  bias    exp  N  Model    Description
      ------- ------ -----    ------- ------ -----   ---- --  -------- -----------
      2.7e-64  203.2   9.0    3.5e-46  143.8   0.2    3.1  3  Pkinase   Protein kinase domain
  
  Domain annotation for each model (and alignments):
  >> Pkinase  Protein kinase domain
     #    score  bias  c-Evalue  i-Evalue hmmfrom  hmm to    alifrom  ali to    envfrom  env to     acc
   ---   ------ ----- --------- --------- ------- -------    ------- -------    ------- -------    ----
     1 ?   -2.9   3.2      0.19      0.19     198     226 ..     222     243 ..     191     277 .. 0.57
     2 !  143.8   0.2   3.5e-46   3.5e-46       1     153 [.     352     505 ..     352     522 .. 0.95
     3 !   63.6   0.0   9.8e-22   9.8e-22     154     264 .]     568     672 ..     551     672 .. 0.83
  
    Alignments for each domain:
    == domain 1  score: -2.9 bits;  conditional E-value: 0.19
                             TTSSCHHHHHHHHHTHHHHHHHCTSHH.. CS
                 Pkinase 198 sgekgkekvekeldqlekilkilgetkek 226
                             + +++++++++      + ++i ++++++
    sp|P53894|CBK1_YEAST 222 Q-QQQQQQQQQ------QHMQIQQQQQQQ 243
                             1.111111111......122222221222 PP
  
    == domain 2  score: 143.8 bits;  conditional E-value: 3.5e-46
                             EEEEEEEEEESSEEEEEEEETTTTEEEEEEEEEHHCCCHHHH.HHHHHHHHHHHHHSSTTB--EEEEEEESSEEEEEEE--TTEBHHHH CS
                 Pkinase   1 yekleklGeGsfGkVykaveketgkivAvKkikkekakkkke.kkvlrEikilkklkhpnivrlyevfeekdelylvleyveggeladl 88 
                             +++++ +G+G+fG+V  + +k+tgki+A+K++ k+++ kk++  +v +E  +l+ +++p +v ly++f++ ++lyl++e+++gg+l+++
    sp|P53894|CBK1_YEAST 352 FHTVKVIGKGAFGEVRLVQKKDTGKIYAMKTLLKSEMYKKDQlAHVKAERDVLAGSDSPWVVSLYYSFQDAQYLYLIMEFLPGGDLMTM 440
                             67899********************************999999********************************************** PP
  
                             HHHHSS--HHHHHHHHHHHHHHHHHHHHTTEE-SS-SGGGEEEETTTEEEE-SGTTSEECCSSCS CS
                 Pkinase  89 lsrkgslseeeakkiakqilegleylHskgiiHrDlKpeNiLidekgelKitDFGlakelesssk 153
                             l r + ++e+ +++++++ + ++e +H+ g+iHrD+Kp+NiLid +g++K++DFGl++ ++++++
    sp|P53894|CBK1_YEAST 441 LIRWQLFTEDVTRFYMAECILAIETIHKLGFIHRDIKPDNILIDIRGHIKLSDFGLSTGFHKTHD 505
                             **999*****************************************************9999876 PP
  
    == domain 3  score: 63.6 bits;  conditional E-value: 9.8e-22
                             BCTCCSCGGGS-HHHHTTSTCSHHHHHHHHHHHHHHHHHSS-STTTSSCHHHHHHHHHTHHHHHHHCTSHH......TTS-HHHHHHHH CS
                 Pkinase 154 ltsfvgtreYlAPEvlkeneyskkvDvWslGvilyelltgkppfsgekgkekvekeldqlekilkilgetkeklpeaselseeakdllk 242
                             + s vgt++Y+APE+  +++y++++D+WslG i+ye l g ppf +e+ +e+++k+++          e+++++p + ++s ea dl++
    sp|P53894|CBK1_YEAST 568 AYSTVGTPDYIAPEIFLYQGYGQECDWWSLGAIMYECLIGWPPFCSETPQETYRKIMNF---------EQTLQFPDDIHISYEAEDLIR 647
                             6789*****************************************66665533333333.........557799*************** PP
  
                             HHT-SSGCCSTT....HHHHHTSGGG CS
                 Pkinase 243 kllkkdpkkRlt....aeellqhpyl 264
                             +ll+    +Rl+    a+e+++hp++
    sp|P53894|CBK1_YEAST 648 RLLTHA-DQRLGrhggADEIKSHPFF 672
                             ***875.678877779********98 PP
  
  Internal pipeline statistics summary:
  -------------------------------------
  Query sequence(s):                         1  (756 residues searched)
  Target model(s):                           1  (264 nodes)
  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: inf
  //
  Query:       sp|P15790|CSK21_YEAST  [L=372]
  Description: Casein kinase II subunit alpha OS=Saccharomyces cerevisiae (strain ATCC 204508 / S288c) GN=CKA1 PE=1 SV=1
  Scores for complete sequence (score includes all domains):
     --- full sequence ---   --- best 1 domain ---    -#dom-
      E-value  score  bias    E-value  score  bias    exp  N  Model    Description
      ------- ------ -----    ------- ------ -----   ---- --  -------- -----------
      7.5e-62  195.1   7.2    3.2e-55  173.4   0.7    2.1  2  Pkinase   Protein kinase domain
  
  Domain annotation for each model (and alignments):
  >> Pkinase  Protein kinase domain
     #    score  bias  c-Evalue  i-Evalue hmmfrom  hmm to    alifrom  ali to    envfrom  env to     acc
   ---   ------ ----- --------- --------- ------- -------    ------- -------    ------- -------    ----
     1 !   25.5   1.1   4.3e-10   4.3e-10       1      60 [.      40      94 ..      40     115 .. 0.87
     2 !  173.4   0.7   3.2e-55   3.2e-55      56     264 .]     128     363 ..     101     363 .. 0.92
  
    Alignments for each domain:
    == domain 1  score: 25.5 bits;  conditional E-value: 4.3e-10
                             EEEEEEEEEESSEEEEEEEETTTTEEEEEEEEEHHCCCHHHHHHHHHHHHHHHHHSSTTB CS
                  Pkinase  1 yekleklGeGsfGkVykaveketgkivAvKkikkekakkkkekkvlrEikilkklkhpni 60
                             ye ++k+G+G++++V+++v+ +++ ++++K++k  k+kk k     rEikil  l+ +++
    sp|P15790|CSK21_YEAST 40 YEIENKVGRGKYSEVFQGVKLDSKVKIVIKMLKPVKKKKIK-----REIKILTDLSNEKV 94
                             78999****************************99888855.....7******9998877 PP
  
    == domain 2  score: 173.4 bits;  conditional E-value: 3.2e-55
                              S.STTB--EEEEEEE..SSEEEEEEE--TTEBHHHHHHHHSS--HHHHHHHHHHHHHHHHHHHHTTEE-SS-SGGGEEEE.TTTEEEE CS
                  Pkinase  56 k.hpnivrlyevfee..kdelylvleyveggeladllsrkgslseeeakkiakqilegleylHskgiiHrDlKpeNiLid.ekgelKi 139
                              + h ni++l++++++  +++  lv+eyv++ ++  l+    +l++ e+++++ ++l++l+y+Hs+gi+HrD+Kp+N++id ++++l++
    sp|P15790|CSK21_YEAST 128 NgHANIIHLFDIIKDpiSKTPALVFEYVDNVDFRILYP---KLTDLEIRFYMFELLKALDYCHSMGIMHRDVKPHNVMIDhKNKKLRL 212
                              35*************8878888*********9988887...5**************************************66677*** PP
  
                              -SGTTSEECCSSCSBCTCCSCGGGS-HHHH.TTSTCSHHHHHHHHHHHHHHHHHSS-STTTSSCHHHHHHHHHTHHHHHHHCTSHH.. CS
                  Pkinase 140 tDFGlakelessskltsfvgtreYlAPEvl.keneyskkvDvWslGvilyelltgkppfsgekgkekvekeldqlekilkilgetkek 226
                              +D+Gla+ ++ + +++ +v++r +  PE+l ++++y+ + D+Ws G +l++++++++pf   +g++    ++dql+ki+k+lg+++++
    sp|P15790|CSK21_YEAST 213 IDWGLAEFYHVNMEYNVRVASRFFKGPELLvDYRMYDYSLDLWSFGTMLASMIFKREPFF--HGTS----NTDQLVKIVKVLGTSDFE 294
                              ******************************999***************************..3443....789**********77766 PP
  
                              ....TTS...............................-HHHHHHHHHHT-SSGCCSTTHHHHHTSGGG CS
                  Pkinase 227 lpeasel...............................seeakdllkkllkkdpkkRltaeellqhpyl 264
                                  +                                 ++e++dl+++ll++d+++Rlta+e++ hp++
    sp|P15790|CSK21_YEAST 295 KYLLKYEitlprefydmdqyirkpwhrfindgnkhlsgNDEIIDLIDNLLRYDHQERLTAKEAMGHPWF 363
                              5554444588999999****************************************************9 PP
  
  Internal pipeline statistics summary:
  -------------------------------------
  Query sequence(s):                         1  (372 residues searched)
  Target model(s):                           1  (264 nodes)
  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: 00:00:00.02
  # Mc/sec: 4.91
  //
  Query:       sp|P21333|FLNA_HUMAN  [L=2647]
  Description: Filamin-A OS=Homo sapiens GN=FLNA PE=1 SV=4
  Scores for complete sequence (score includes all domains):
     --- full sequence ---   --- best 1 domain ---    -#dom-
      E-value  score  bias    E-value  score  bias    exp  N  Model    Description
      ------- ------ -----    ------- ------ -----   ---- --  -------- -----------
  
     [No hits detected that satisfy reporting thresholds]
  
  Domain annotation for each model (and alignments):
  
     [No targets detected that satisfy reporting thresholds]
  
  Internal pipeline statistics summary:
  -------------------------------------
  Query sequence(s):                         1  (2647 residues searched)
  Target model(s):                           1  (264 nodes)
  Passed MSV filter:                         0  (0); expected 0.0 (0.02)
  Passed bias filter:                        0  (0); expected 0.0 (0.02)
  Passed Vit filter:                         0  (0); expected 0.0 (0.001)
  Passed Fwd filter:                         0  (0); expected 0.0 (1e-05)
  Initial search space (Z):                  1  [actual number of targets]
  Domain search space  (domZ):               0  [number of targets reported over threshold]
  # CPU time: 0.00u 0.00s 00:00:00.00 Elapsed: 00:00:00.00
  # Mc/sec: inf
  //
  
  ```
  
  ---
  
  HMMER is a great tool and can also analyse multiple sequence alignments to build the hmms if that's what you need. I strongly urge you to reads [its documentation](http://www.csb.yale.edu/userguides/seq/hmmer/docs/) which is both informative and a surpisingly fun read (it includes such phrases as "*Their format is “proprietary”, which is an open source term of art that means both “I haven’t found time
  to document them yet” and “I still might decide to change them arbitrarily without telling you”*").
  
  > **Comments:**
  > **username_1**: I was sure that with pfam and hmmer it could be possible to find a specific protein motif. But given that the OP has a consensus it might be hard to use it to search in pfam.  
  > **username_2**: @Llopis pfam has HMM models which are essentially PWMs. And this isn't a way of searching PFam, it's a way of using PFam to search protein sequences. The OP says: "*I am trying to identify proteins that carry a consensus target sequence for a kinase.*", so I assume Ian has a list of proteins and needs to search through them for a kinase domain. I may be wrong, but that's what I got from the question.  
  > **username_1**: I need to review my notes on HMM. Thanks for the answer!  
  > **username_0**: Thanks, but its the pwm for the kinase targets rather than the kinase domain i was looking for.  
  
  ---
  
  