Tutorial 8: Automatic Alignment Generation

[1]:

import homelette as hm

Introduction

Welcome to the eighth tutorial for homelette, in which we will explore homelette’s tool for automated alignment generation.

The alignment is a central step in homology modelling, and the quality of the alignment used for modelling has a lot of influence on the final models. In general, the challenge of creating solid sequence alignments is mainly dependent how closely the target and template are. If they share a high sequence identity, the alignments are easy to construct and the modelling process will most likely be successful.

Note

As a rule of thumb, it is said that everything above 50-60% sequence identity is well approachable, while everything below 30% sequence identity is very challenging to model.

homelette has methods that can automatically generate an alignment given a query sequence. However, these methods hide some of the complexity of generating good alignments. Use them at your own discretion, especially for target sequences with low sequence identity to any template.

Note

Be careful with automatically generated alignments if your protein of interest has no closely related templates

After these words of caution, let’s look at the implemented methods:

  • alignment.AlignmentGenerator_pdb: Query the PDB and local alignment with Clustal Omega

  • alignment.AlignmentGenerator_hhblits: Local database search against PDB70 database.

  • alignment.AlignmentGenerator_from_aln: For if you already have an alignment ready, but want to make use of homelette’s processing of templates and alignments.

Method 1: Querying RCSB and Realignment of template sequences with Clusta Omega

This class performs a three step process:

  • Template Identification: Query the RCSB using a sequence (interally, MMseq2 is used by RCSB) [1, 2] (get_suggestion)

  • Then the sequences of identified templates are aligned locally using Clustal Omega [3, 4]. (get_suggesion)

  • Finally, the template structures are downloaded and processed together with the alignment (get_pdbs)

Afterwards, the templates schould be ready for performing homology modelling.

For a practical demonstration, let’s find some templates for ARAF:

[2]:

gen = hm.alignment.AlignmentGenerator_pdb.from_fasta('data/alignments/ARAF.fa')
# gen = hm.alignment.AlignmentGenerator_pdb(
#     sequence = 'GTVKVYLPNKQRTVVTVRDGMSVYDSLDKALKVRGLNQDCCVVYRLIKGRKTVTAWDTAIAPLDGEELIVEVL',
#     target = 'ARAF')

There are two ways how AlignmentGenerator can be initialized: either with a sequence, or from a fasta file. Both ways are shown above.

In the next step we use this sequence to generate an initial alignment:

[3]:

gen.get_suggestion()

Querying PDB...
Query successful, 16 found!

Retrieving sequences...
Sequences succefully retrieved!

Generating alignment...
Alignment generated!

As we can see from the output, we are querying the PDB and extracting potential templates. Then, an alignment is generated.

We can have a first look at the suggested templates as such:

[4]:

gen.show_suggestion()

[4]:
template coverage identity
0 1C1Y_2 100.0 60.27
1 1GUA_2 100.0 60.27
2 4G0N_2 100.0 60.27
3 4G3X_2 100.0 60.27
4 6VJJ_2 100.0 60.27
5 6XGU_2 100.0 60.27
6 6XGV_2 100.0 60.27
7 6XHA_2 100.0 60.27
8 6XHB_2 100.0 60.27
9 6XI7_2 100.0 60.27
10 7JHP_2 100.0 60.27
11 3KUC_2 100.0 58.90
12 3KUD_2 100.0 58.90
13 3NY5_1 100.0 58.90
14 6NTD_2 100.0 53.42
15 6NTC_2 100.0 52.05 
[5]:

gen.alignment.print_clustal(70)

ARAF        -------------GTVKVYLPNKQRTVVTVRDGMSVYDSLDKALKVRGLNQDCCVVYRLI---KGRKTVT
1C1Y_2      ------------SNTIRVFLPNKQRTVVNVRNGMSLHDCLMKALKVRGLQPECCAVFRLLHEHKGKKARL
1GUA_2      --------PSKTSNTIRVFLPNKQRTVVNVRNGMSLHDCLMKALKVRGLQPECCAVFRLLHEHKGKKARL
3KUC_2      --------PSKTSNTIRVFLPNKQRTVVRVRNGMSLHDCLMKKLKVRGLQPECCAVFRLLHEHKGKKARL
3KUD_2      --------PSKTSNTIRVFLPNKQRTVVNVRNGMSLHDCLMKKLKVRGLQPECCAVFRLLHEHKGKKARL
3NY5_1      MGHHHHHHSHMQKPIVRVFLPNKQRTVVPARCGVTVRDSLKKALMMRGLIPECCAVYRIQ---DGEKKPI
4G0N_2      -----------TSNTIRVFLPNKQRTVVNVRNGMSLHDCLMKALKVRGLQPECCAVFRLLHEHKGKKARL
4G3X_2      ------------SNTIRVFLPNKQRTVVNVRNGMSLHDCLMKALKVRGLQPECCAVFRLLHEHKGKKARL
6NTC_2      --------GAMDSNTIRVLLPNQEWTVVKVRNGMSLHDSLMKALKRHGLQPESSAVFRLLHEHKGKKARL
6NTD_2      --------GAMDSNTIRVLLPNHERTVVKVRNGMSLHDSLMKALKRHGLQPESSAVFRLLHEHKGKKARL
6VJJ_2      ---------SKTSNTIRVFLPNKQRTVVNVRNGMSLHDCLMKALKVRGLQPECCAVFRLLHEHKGKKARL
6XGU_2      ---------SKTSNTIRVFLPNKQRTVVNVRNGMSLHDCLMKALKVRGLQPECCAVFRLLHEHKGKKARL
6XGV_2      ---------SKTSNTIRVFLPNKQRTVVNVRNGMSLHDCLMKALKVRGLQPECCAVFRLLHEHKGKKARL
6XHA_2      ---------SKTSNTIRVFLPNKQRTVVNVRNGMSLHDCLMKALKVRGLQPECCAVFRLLHEHKGKKARL
6XHB_2      ---------SKTSNTIRVFLPNKQRTVVNVRNGMSLHDCLMKALKVRGLQPECCAVFRLLHEHKGKKARL
6XI7_2      ---------SKTSNTIRVFLPNKQRTVVNVRNGMSLHDCLMKALKVRGLQPECCAVFRLLHEHKGKKARL
7JHP_2      ------------SNTIRVFLPNKQRTVVNVRNGMSLHDCLMKALKVRGLQPECCAVFRLLHEHKGKKARL


ARAF        AWDTAIAPLDGEELIVEVL---------------------------------------------------
1C1Y_2      DWNTDAASLIGEELQVDFL---------------------------------------------------
1GUA_2      DWNTDAASLIGEELQVDFL---------------------------------------------------
3KUC_2      DWNTDAASLIGEELQVDFL---------------------------------------------------
3KUD_2      DWNTDAASLIGEELQVDFL---------------------------------------------------
3NY5_1      GWDTDISWLTGEELHVEVLENVPLTTHNF-----------------------------------------
4G0N_2      DWNTDAASLIGEELQVDFL---------------------------------------------------
4G3X_2      DWNTDAASLIGEELQVDFL---------------------------------------------------
6NTC_2      DWNTDAASLIGEELQVDFL---------------------------------------------------
6NTD_2      DWNTDAASLIGEELQVDFL---------------------------------------------------
6VJJ_2      DWNTDAASLIGEELQVDFL---------------------------------------------------
6XGU_2      DWNTDAASLIGEELQVDFLDHVPLTTHNFARKTFLKLAFCDICQKFLLNGFRCQTCGYKFHEHCSTKVPT
6XGV_2      DWNTDAASLIGEELQVDFLDHVPLTTHNFARKTFLKLAFCDICQKFLLNGFRCQTCGYKFHEHCSTKVPT
6XHA_2      DWNTDAASLIGEELQVDFLDHVPLTTHNFARKTFLKLAFCDICQKFLLNGFRCQTCGYKFHEHCSTKVPT
6XHB_2      DWNTDAASLIGEELQVDFLDHVPLTTHNFARKTFLKLAFCDICQKFLLNGFRCQTCGYKFHEHCSTKVPT
6XI7_2      DWNTDAASLIGEELQVDFLDHVPLTTHNFARKTFLKLAFCDICQKFLLNGFRCQTCGYKFHEHCSTKVPT
7JHP_2      DWNTDAASLIGEELQVDFLDHVPLTTHNFARKTFLKLAFCDICQKFLLNGFRCQTCGYKFHEHCSTKVPT


ARAF        ------
1C1Y_2      ------
1GUA_2      ------
3KUC_2      ------
3KUD_2      ------
3NY5_1      ------
4G0N_2      ------
4G3X_2      ------
6NTC_2      ------
6NTD_2      ------
6VJJ_2      ------
6XGU_2      MCVDWS
6XGV_2      MCVDWS
6XHA_2      MCVDWS
6XHB_2      MCVDWS
6XI7_2      MCVDWS
7JHP_2      MCVDW-

After potentially filtering out some sequences, we can proceed with the next step: downloading the structures for our templates, comparing the sequences of the templates with the residues present in the template structure and make adjustments to both the structure and the alignment if necessary.

[6]:

gen.get_pdbs()

Guessing template naming format...
Template naming format guessed: polymer_entity!

Checking template dir...
Template dir found!

Processing templates:

1C1Y downloading from PDB...
1C1Y downloaded!
1C1Y_B: Chain extracted!
1C1Y_B: Alignment updated!
1C1Y_B: PDB processed!
1GUA downloading from PDB...
1GUA downloaded!
1GUA_B: Chain extracted!
1GUA_B: Alignment updated!
1GUA_B: PDB processed!
3KUC downloading from PDB...
3KUC downloaded!
3KUC_B: Chain extracted!
3KUC_B: Alignment updated!
3KUC_B: PDB processed!
3KUD downloading from PDB...
3KUD downloaded!
3KUD_B: Chain extracted!
3KUD_B: Alignment updated!
3KUD_B: PDB processed!
3NY5 downloading from PDB...
3NY5 downloaded!
3NY5_A: Chain extracted!
3NY5_A: Alignment updated!
3NY5_A: PDB processed!
3NY5_B: Chain extracted!
3NY5_B: Alignment updated!
3NY5_B: PDB processed!
3NY5_C: Chain extracted!
3NY5_C: Alignment updated!
3NY5_C: PDB processed!
3NY5_D: Chain extracted!
3NY5_D: Alignment updated!
3NY5_D: PDB processed!
4G0N downloading from PDB...
4G0N downloaded!
4G0N_B: Chain extracted!
4G0N_B: Alignment updated!
4G0N_B: PDB processed!
4G3X downloading from PDB...
4G3X downloaded!
4G3X_B: Chain extracted!
4G3X_B: Alignment updated!
4G3X_B: PDB processed!
6NTC downloading from PDB...
6NTC downloaded!
6NTC_B: Chain extracted!
6NTC_B: Alignment updated!
6NTC_B: PDB processed!
6NTD downloading from PDB...
6NTD downloaded!
6NTD_B: Chain extracted!
6NTD_B: Alignment updated!
6NTD_B: PDB processed!
6VJJ downloading from PDB...
6VJJ downloaded!
6VJJ_B: Chain extracted!
6VJJ_B: Alignment updated!
6VJJ_B: PDB processed!
6XGU downloading from PDB...
6XGU downloaded!
6XGU_B: Chain extracted!
6XGU_B: Alignment updated!
6XGU_B: PDB processed!
6XGV downloading from PDB...
6XGV downloaded!
6XGV_B: Chain extracted!
6XGV_B: Alignment updated!
6XGV_B: PDB processed!
6XHA downloading from PDB...
6XHA downloaded!
6XHA_B: Chain extracted!
6XHA_B: Alignment updated!
6XHA_B: PDB processed!
6XHB downloading from PDB...
6XHB downloaded!
6XHB_B: Chain extracted!
6XHB_B: Alignment updated!
6XHB_B: PDB processed!
6XI7 downloading from PDB...
6XI7 downloaded!
6XI7_B: Chain extracted!
6XI7_B: Alignment updated!
6XI7_B: PDB processed!
7JHP downloading from PDB...
7JHP downloaded!
7JHP_C: Chain extracted!
7JHP_C: Alignment updated!
7JHP_C: PDB processed!

Finishing... All templates successfully
downloaded and processed!
Templates can be found in
"/home/homelette/workdir/templates".

get_pdbs will check all chains of a template and download those with the correct sequence.

[7]:

gen.alignment.print_clustal(70)

ARAF        -------------GTVKVYLPNKQRTVVTVRDGMSVYDSLDKALKVRGLNQDCCVVYRLI---KGRKTVT
1C1Y_B      ------------SNTIRVFLPNKQRTVVNVRNGMSLHDCLMKALKVRGLQPECCAVFRLLHEHKGKKARL
1GUA_B      -------------NTIRVFLPNKQRTVVNVRNGMSLHDCLMKALKVRGLQPECCAVFRLLHEHKGKKARL
3KUC_B      -------------NTIRVFLPNKQRTVVRVRNGMSLHDCLMKKLKVRGLQPECCAVFRLLHEHKGKKARL
3KUD_B      -------------NTIRVFLPNKQRTVVNVRNGMSLHDCLMKKLKVRGLQPECCAVFRLLHEHKGKKARL
3NY5_A      ---------H-QKPIVRVFLPNKQRTVVPARCGVTVRDSLKKAL--RGLIPECCAVYRIQ------KKPI
3NY5_B      --------SH-QKPIVRVFLPNKQRTVVPARCGVTVRDSLKKAL--RGLIPECCAVYRIQ-----EKKPI
3NY5_C      -----------QKPIVRVFLPNKQRTVVPARCGVTVRDSLKKAL--RGLIPECCAVYRIQ------KKPI
3NY5_D      ---------H-QKPIVRVFLPNKQRTVVPARCGVTVRDSLKKAL--RGLIPECCAVYRI-------KKPI
4G0N_B      -----------TSNTIRVFLPNKQRTVVNVRNGMSLHDCLMKALKVRGLQPECCAVFRLLHEHKGKKARL
4G3X_B      ------------SNTIRVFLPNKQRTVVNVRNGMSLHDCLMKALKVRGLQPECCAVFRLLHEHKGKKARL
6NTC_B      -------------NTIRVLLPNQEWTVVKV---MSLHDSLMKALKRHGLQPESSAVF---------KARL
6NTD_B      ------------SNTIRVLLPNHERTVVKVRNGMSLHDSLMKALKRHGLQPESSAVF-----------RL
6VJJ_B      ------------SNTIRVFLPNKQRTVVNVRNGMSLHDCLMKALKVRGLQPECCAVFRLLHEHKGKKARL
6XGU_B      ------------SNTIRVFLPNKQRTVVNVRNGMSLHDCLMKALKVRGLQPE-CAVFRLLHEHKGKKARL
6XGV_B      ------------SNTIRVFLPNKQRTVVNVRNGMSLHDCLMKALKVRGLQPE-CAVFRLLHEHKGKKARL
6XHA_B      ------------SNTIRVFLPNKQRTVVNVRNGMSLHDCLMKALKVRGLQPE-CAVFRLLHEHKGKKARL
6XHB_B      ------------SNTIRVFLPNKQRTVVNVRNGMSLHDCLMKALKVRGLQPE-CAVFRLLHEHKGKKARL
6XI7_B      -------------NTIRVFLPNKQRTVVNVRNGMSLHDCLMKALKVRGLQPECCAVFRLLH----KKARL
7JHP_C      ------------SNTIRVFLPNKQRTVVNVRNGMSLHDCLMKALKVRGLQPECCAVFRLL-----KKARL


ARAF        AWDTAIAPLDGEELIVEVL---------------------------------------------------
1C1Y_B      DWNTDAASLIGEELQVDFL---------------------------------------------------
1GUA_B      DWNTDAASLIGEELQVDFL---------------------------------------------------
3KUC_B      DWNTDAASLIGEELQVDFL---------------------------------------------------
3KUD_B      DWNTDAASLIGEELQVDFL---------------------------------------------------
3NY5_A      GWDTDISWLTGEELHVEVLENVPLT---------------------------------------------
3NY5_B      GWDTDISWLTGEELHVEVLENVPLTTH-------------------------------------------
3NY5_C      GWDTDISWLTGEELHVEVLENVPLTTH-------------------------------------------
3NY5_D      GWDTDISWLTGEELHVEVLENVPL----------------------------------------------
4G0N_B      DWNTDAASLIGEELQVDFL---------------------------------------------------
4G3X_B      DWNTDAASLIGEELQVDFL---------------------------------------------------
6NTC_B      DWNTDAASLIGEELQVDF----------------------------------------------------
6NTD_B      DWNTDAASLIGEELQVD-----------------------------------------------------
6VJJ_B      DWNTDAASLIGEELQVDFL---------------------------------------------------
6XGU_B      DWNTDAASLIGEELQVDFLDHVPLTTHNFARKTFLKLAFCDICQKFLLNGFRCQTCGYKFHEHCSTKVPT
6XGV_B      DWNTDAASLIGEELQVDFLDHVPLTTHNFARKTFLKLAFCDICQKFLLNGFRCQTCGYKFHEHCSTKVPT
6XHA_B      DWNTDAASLIGEELQVDFLDHVPLTTHNFARKTFLKLAFCDICQKFLLNGFRCQTCGYKFHEHCSTKVPT
6XHB_B      DWNTDAASLIGEELQVDFLDHVPLTTHNFARKTFLKLAFCDICQKFLLNGFRCQTCGYKFHEHCSTKVPT
6XI7_B      DWNTDAASLIGEELQVDFLDHVPLTTHNFARKTFLKLAFCDICQKFLLNGFRCQTCGYKFHEHCSTKVPT
7JHP_C      DWNTDAASLIGEELQVDFLDH--LTTHNFARKTFLKLAFCDICQKFLLNGFRCQTCGYKFHEHCSTKVPT


ARAF        ------
1C1Y_B      ------
1GUA_B      ------
3KUC_B      ------
3KUD_B      ------
3NY5_A      ------
3NY5_B      ------
3NY5_C      ------
3NY5_D      ------
4G0N_B      ------
4G3X_B      ------
6NTC_B      ------
6NTD_B      ------
6VJJ_B      ------
6XGU_B      MCVDWS
6XGV_B      MCVDWS
6XHA_B      MCVDWS
6XHB_B      MCVDWS
6XI7_B      MCV---
7JHP_C      MCVDW-

Now we can directly use these template for homology modelling:

[8]:

# initialize task
t = gen.initialize_task(task_name = 'Tutorial8', overwrite = True)

# create a model per template
templates = [temp for temp in t.alignment.sequences.keys() if temp != 'ARAF']
for template in templates:
    t.execute_routine(
        tag = f'test_{template}',
        routine = hm.routines.Routine_automodel_default,
        templates = [template],
        template_location = './templates/'
    )

[9]:

# inspect models
t.models

[9]:

[<homelette.organization.Model at 0x7f22492f4340>,
 <homelette.organization.Model at 0x7f22492f45b0>,
 <homelette.organization.Model at 0x7f229829a610>,
 <homelette.organization.Model at 0x7f2273b6afa0>,
 <homelette.organization.Model at 0x7f2273b38ee0>,
 <homelette.organization.Model at 0x7f22491c0e50>,
 <homelette.organization.Model at 0x7f22491bf070>,
 <homelette.organization.Model at 0x7f22491bf880>,
 <homelette.organization.Model at 0x7f22491c5760>,
 <homelette.organization.Model at 0x7f22491c5a00>,
 <homelette.organization.Model at 0x7f22491c8310>,
 <homelette.organization.Model at 0x7f22491c8820>,
 <homelette.organization.Model at 0x7f22491b0f10>,
 <homelette.organization.Model at 0x7f22491c96a0>,
 <homelette.organization.Model at 0x7f22491c9b80>,
 <homelette.organization.Model at 0x7f22491c8af0>,
 <homelette.organization.Model at 0x7f22492f49d0>,
 <homelette.organization.Model at 0x7f22491bfbe0>,
 <homelette.organization.Model at 0x7f2273b38040>]

Method 2: HHSuite

This class is build on the hhblits query function of the HHSuite3 [5].

This has the same interface as AlignmentGenerator_pdb, except some different settings for the alignment generation with get_pdbs.

It should also be noted that technically, this approach does not generate a multiple sequence alignment, but rather a combined alignment of lots of pairwise alignments of query to template. These pairwise alignments are combined on the common sequence they are all aligned to.

(This code is commented out since it requires big databases to run, which are not part of the docker container.)

[10]:

# gen = hm.alignment.AlignmentGenerator_hhblits.from_fasta('data/alignments/ARAF.fa')
# gen.get_suggestion(database_dir='/home/philipp/Downloads/hhsuite_dbs/')
# gen.get_pdbs()
# gen.show_suggestion()
# t = gen.initialize_task()

Method 3: Using pre-computed alignments

If you already have an alignment computed, but want to make use of get_pdbs in order to download the templates and process the alignment and the template structures, there is also the possibility to load your alignment into an AlignmentGenerator object:

[11]:

# initialize an alignment generator from a pre-computed alignemnt
gen = hm.alignment.AlignmentGenerator_from_aln(
    alignment_file = 'data/alignments/unprocessed.fasta_aln',
    target = 'ARAF')

gen.show_suggestion()
gen.alignment.print_clustal(70)
gen.get_pdbs()
gen.alignment.print_clustal(70)

ARAF        -------------GTVKVYLPNKQRTVVTVRDGMSVYDSLDKALKVRGLNQDCCVVYRLI---KGRKTVT
3NY5        MGHHHHHHSHMQKPIVRVFLPNKQRTVVPARCGVTVRDSLKKALMMRGLIPECCAVYRIQ---DGEKKPI
4G0N        -----------TSNTIRVFLPNKQRTVVNVRNGMSLHDCLMKALKVRGLQPECCAVFRLLHEHKGKKARL


ARAF        AWDTAIAPLDGEELIVEVL----------
3NY5        GWDTDISWLTGEELHVEVLENVPLTTHNF
4G0N        DWNTDAASLIGEELQVDFL----------


Guessing template naming format...
Template naming format guessed: entry!

Checking template dir...
Template dir found!

Processing templates:

3NY5 downloading from PDB...
3NY5 downloaded!
3NY5_A: Chain extracted!
3NY5_A: Alignment updated!
3NY5_A: PDB processed!
3NY5_B: Chain extracted!
3NY5_B: Alignment updated!
3NY5_B: PDB processed!
3NY5_C: Chain extracted!
3NY5_C: Alignment updated!
3NY5_C: PDB processed!
3NY5_D: Chain extracted!
3NY5_D: Alignment updated!
3NY5_D: PDB processed!
4G0N downloading from PDB...
4G0N downloaded!
4G0N_B: Chain extracted!
4G0N_B: Alignment updated!
4G0N_B: PDB processed!

Finishing... All templates successfully
downloaded and processed!
Templates can be found in
"./templates/".
ARAF        -------------GTVKVYLPNKQRTVVTVRDGMSVYDSLDKALKVRGLNQDCCVVYRLI---KGRKTVT
3NY5_A      ---------H-QKPIVRVFLPNKQRTVVPARCGVTVRDSLKKAL--RGLIPECCAVYRIQ------KKPI
3NY5_B      --------SH-QKPIVRVFLPNKQRTVVPARCGVTVRDSLKKAL--RGLIPECCAVYRIQ-----EKKPI
3NY5_C      -----------QKPIVRVFLPNKQRTVVPARCGVTVRDSLKKAL--RGLIPECCAVYRIQ------KKPI
3NY5_D      ---------H-QKPIVRVFLPNKQRTVVPARCGVTVRDSLKKAL--RGLIPECCAVYRI-------KKPI
4G0N_B      -----------TSNTIRVFLPNKQRTVVNVRNGMSLHDCLMKALKVRGLQPECCAVFRLLHEHKGKKARL


ARAF        AWDTAIAPLDGEELIVEVL----------
3NY5_A      GWDTDISWLTGEELHVEVLENVPLT----
3NY5_B      GWDTDISWLTGEELHVEVLENVPLTTH--
3NY5_C      GWDTDISWLTGEELHVEVLENVPLTTH--
3NY5_D      GWDTDISWLTGEELHVEVLENVPL-----
4G0N_B      DWNTDAASLIGEELQVDFL----------

Again, for every template structure, homelette is finding which chains fit to the sequence and then extract all of them.

Of course, if your alignment and template(s) are already processed, it is perfectly fine to use the Alignment class directly as we have done in the previous tutorials.

Implementing own methods

While not discussed in Tutorial 4, AlignmentGenerator object are also building blocks in the homelette framework and custom versions can be implemented. All AlignmentGenerator children classes so far inherit from the AlignmentGenerator abstract base class, which contains some useful functionality for writing your own alignment generations, in particular the get_pdbs function.

Further Reading

Congratulation on finishing the tutorial about alignment generation in homelette.

Please note that there are other tutorials, which will teach you more about how to use homelette.

  • Tutorial 1: Learn about the basics of homelette.

  • Tutorial 2: Learn more about already implemented routines for homology modelling.

  • Tutorial 3: Learn about the evaluation metrics available with homelette.

  • Tutorial 4: Learn about extending homelette’s functionality by defining your own modelling routines and evaluation metrics.

  • Tutorial 5: Learn about how to use parallelization in order to generate and evaluate models more efficiently.

  • Tutorial 6: Learn about modelling protein complexes.

  • Tutorial 7: Learn about assembling custom pipelines.

References

[1] Rose, Y., Duarte, J. M., Lowe, R., Segura, J., Bi, C., Bhikadiya, C., Chen, L., Rose, A. S., Bittrich, S., Burley, S. K., & Westbrook, J. D. (2021). RCSB Protein Data Bank: Architectural Advances Towards Integrated Searching and Efficient Access to Macromolecular Structure Data from the PDB Archive. Journal of Molecular Biology, 433(11), 166704. https://doi.org/10.1016/J.JMB.2020.11.003

[2] Steinegger, M., & Söding, J. (2017). MMseqs2 enables sensitive protein sequence searching for the analysis of massive data sets. Nature Biotechnology 2017 35:11, 35(11), 1026–1028. https://doi.org/10.1038/nbt.3988

[3] Sievers, F., Wilm, A., Dineen, D., Gibson, T. J., Karplus, K., Li, W., Lopez, R., McWilliam, H., Remmert, M., Söding, J., Thompson, J. D., & Higgins, D. G. (2011). Fast, scalable generation of high-quality protein multiple sequence alignments using Clustal Omega. Molecular Systems Biology, 7(1), 539. https://doi.org/10.1038/MSB.2011.75

[4] Sievers, F., & Higgins, D. G. (2018). Clustal Omega for making accurate alignments of many protein sequences. Protein Science, 27(1), 135–145. https://doi.org/10.1002/PRO.3290

[5] Steinegger, M., Meier, M., Mirdita, M., Vöhringer, H., Haunsberger, S. J., & Söding, J. (2019). HH-suite3 for fast remote homology detection and deep protein annotation. BMC Bioinformatics, 20(1), 1–15. https://doi.org/10.1186/S12859-019-3019-7/FIGURES/7

Session Info

[12]:

# session info
import session_info
session_info.show(html = False, dependencies = True)

-----
homelette           1.4
pandas              1.5.3
session_info        1.0.0
-----
PIL                 7.0.0
altmod              NA
anyio               NA
asttokens           NA
attr                19.3.0
babel               2.12.1
backcall            0.2.0
certifi             2022.12.07
chardet             3.0.4
charset_normalizer  3.1.0
comm                0.1.2
cycler              0.10.0
cython_runtime      NA
dateutil            2.8.2
debugpy             1.6.6
decorator           4.4.2
executing           1.2.0
fastjsonschema      NA
idna                3.4
importlib_metadata  NA
importlib_resources NA
ipykernel           6.21.3
ipython_genutils    0.2.0
jedi                0.18.2
jinja2              3.1.2
json5               NA
jsonschema          4.17.3
jupyter_events      0.6.3
jupyter_server      2.4.0
jupyterlab_server   2.20.0
kiwisolver          1.0.1
markupsafe          2.1.2
matplotlib          3.1.2
modeller            10.4
more_itertools      NA
mpl_toolkits        NA
nbformat            5.7.3
numexpr             2.8.4
numpy               1.24.2
ost                 2.3.1
packaging           20.3
parso               0.8.3
pexpect             4.8.0
pickleshare         0.7.5
pkg_resources       NA
platformdirs        3.1.1
prometheus_client   NA
promod3             3.2.1
prompt_toolkit      3.0.38
psutil              5.5.1
ptyprocess          0.7.0
pure_eval           0.2.2
pydev_ipython       NA
pydevconsole        NA
pydevd              2.9.5
pydevd_file_utils   NA
pydevd_plugins      NA
pydevd_tracing      NA
pygments            2.14.0
pyparsing           2.4.6
pyrsistent          NA
pythonjsonlogger    NA
pytz                2022.7.1
qmean               NA
requests            2.28.2
rfc3339_validator   0.1.4
rfc3986_validator   0.1.1
send2trash          NA
sitecustomize       NA
six                 1.12.0
sniffio             1.3.0
stack_data          0.6.2
swig_runtime_data4  NA
tornado             6.2
traitlets           5.9.0
urllib3             1.26.15
wcwidth             NA
websocket           1.5.1
yaml                6.0
zipp                NA
zmq                 25.0.1
-----
IPython             8.11.0
jupyter_client      8.0.3
jupyter_core        5.2.0
jupyterlab          3.6.1
notebook            6.5.3
-----
Python 3.8.10 (default, Nov 14 2022, 12:59:47) [GCC 9.4.0]
Linux-4.15.0-206-generic-x86_64-with-glibc2.29
-----
Session information updated at 2023-03-15 23:40