Ronan Keegan, Martyn Winn CCP4 group, Daresbury Laboratory

1. MrBUMP – Molecular Replacement with Bulk Model PreparationAutomated search model discovery and preparation for structure solution by molecular replacement Ronan Keegan, Martyn Winn CCP4 group, Daresbury Laboratory Leuven, August 8th 2006

2. The aim of Mr Bump • An automation framework for Molecular Replacement. • Particular emphasis on generating a variety of search models. • Wraps Phaser and/or Molrep. • Also uses a variety of helper applications (e.g. Chainsaw) and bioinformatics tools (e.g. Fasta, Mafft) • Uses on-line databases (e.g. PDB, Scop) • In favourable cases, gives “one-button” solution • In unfavourable cases, will suggest likely search models for manual investigation

3. The pipeline - first steps Target MTZ & Sequence Number of residues & molecular weight Matthews Coefficient. Estimated number of molecules in a.s.u. ` Target Details ` Template Search Generate a list of structures that are possible templates for search models

4. Search for homologous proteins FASTA search of PDB • Sequence based search using sequence of target structure. • Can be run locally if user has fasta34 program installed or remotely using the OCA web-based service hosted by the EBI. • Local search is done against the complete list of PDB sequences derived from ATOM records in the PDB structure files. • All of the resulting PDB id codes are added to a list • Not interested in the alignment to target at this stage.

5. Search for additional similar structures • Additional structure-based search (optional) • Top hit from the FASTA search is used as the template structure for a secondary structure based search. • Uses the SSM webservice provided by the EBI (a.k.a. MSDfold) • Any new structures found are added to the list. • Provides structural variation, not based on direct sequence similarity to target • Manual addition • Can add additional PDB id codes to the list, e.g. from FFAS or psiBLAST searches

6. Multiple Alignment • After the set of PDB ids are collected in the FASTA and SSM searches, their coordinate-based sequences are collected and put through a multiple alignment with the target sequence • Aims: • Extract pairwise alignment between template and target for use in Chainsaw step. Multiple alignment should give a better set of alignments than the original pair-wise FASTA alignments • Score template structures in a consistent manner, in order to prioritise them for subsequent steps

7. Multiple Alignment target model templates pairwise alignment Jalview 2.08.1 Barton group, Dundee currently support ClustalW or MAFFT for multiple alignment

8. Template Model Scoring • Sequence identity: • Ungapped sequence identity i.e. sequence identity of aligned target residues • Alignment quality: • Dependent on the alignment length, the number of gaps created in the template alignment and the extent of each of these gaps. • The penalties given for gaps and the size of the gaps is biased so that alignments that preserve domains of the structure rather than spreading the aligned residues out score higher. The top scoring models are then used for further processing • Alignment Scoring: • score = sequence identity X alignment quality

9. Domains • Suitable templates for individual target domains may exist in isolation in PDB, or in combination with dissimilar domains • In case of relative domain motion, may want to solve domains separately

10. Domains • Domains search: • Top scoring templates from multiple alignment are tested to see if they contain any domains. • Uses the SCOP database. This only lists domains that appear more than once in the PDB. • The database is scanned to to see if domains exist for each of the PDBs in the list of templates • Domains are then extracted from the parent PDB structure file and added to the list of template models as additional search models for MR.

11. Multimers • Multimer search: • Search for quaternary structures that may be used as search models. • Better signal-to-noise ratio than monomer, if assembly is correct for the target. • Multimeric structures based on top templates are retrieved using the PQS service at the EBI, and added to the list of search models • PQS will soon be replaced by the use of the PISA service at the EBI (Eugene Krissinel) 1n5a SPLIT-ASU into 4 Oligomeric files of type TRIMERIC 1n5b SPLIT-ASU into 2 Oligomeric files of type DIMERIC 1n5c SYMMETRY-COMPLEX Oligomeric file of type DIMERIC 1n5d SYMMETRY-COMPLEX Oligomeric file of type DIMERIC

12. ` Target MTZ & Sequence Target Details ` Model Search ` Model Preparation Raw template structures not usually appropriate for MR. Edit to create search model.

13. Search Model Preparation Search models prepared in four ways: • PDBclip • original PDB with waters removed, hydrogens removed, most probable conformations for side chains selected and chain ID’s added if missing. • Molrep • Molrep contains a model preparation function which will align the template sequence with the target sequence and prune the non-conserved side chains accordingly. • Chainsaw • Can be given any alignment between the target and template sequences. • Non-conserved residues are pruned back to the gamma atom. • Polyalanine • Created by excluding all of the side chain atoms beyond the CB atom using the Pdbset program

14. Search Model Preparation Ensemble for Phaser: • Top scoring search models are superposed to create a ensemble model. • This may provide a better search model than any of the individual models on their own. • Currently the default is to use the top 5 scoring search models but plan to create dynamically based on MW and RMSDs of constituent search models

15. ` Target MTZ & Sequence Target Details ` Model Search ` Model Preparation ` Molecular Replacement & Refinement

16. Molecular Replacement and Refinement • The search models can be processed with Molrep or Phaser or both. • The resulting models from molecular replacement are passed to Refmac for restrained refinement. • The change in the Rfree value during refinement is used as rough estimate of how good the resulting model is. final Rfree < 0.35 or final Rfree < 0.5 and dropped by 20%  “success”  “marginal” final Rfree < 0.5 and dropped by 5%  otherwise “failure” • MR scores and un-refined models available for later inspection.

17. Serial mode ` Target MTZ & Sequence Target Details ` Model Search ` Model Preparation Check Scores and exit or select the next model ` Molecular Replacement & Refinement

18. Parallel mode ` Target MTZ & Sequence Target Details ` Model Search Start multiple MR jobs and exit when one finds a solution ` Model Preparation ` ` ` ` ` Molecular Replacement & Refinement Molecular Replacement & Refinement Molecular Replacement & Refinement Molecular Replacement & Refinement Molecular Replacement & Refinement

19. MrBUMP on compute clusters • MrBUMP can take advantage of a compute cluster to farm out the Molecular Replacement jobs. • Currently Sun Grid Engine enabled clusters are supported but support will be added for LSF and condor and any other types of queuing system if there is enough demand.

20. Pre-release version of MrBUMP • Pre-release made available in Jan 06 • Simple installation • Currently runs on Linux and OSX. • Windows version almost ready. • Comes with CCP4 GUI . • Can also be run from the command line with keyword input • First citation in Obiero et al., Acta Cryst. (2006). F62, 757-760 • Regular updates (currently version 0.3.1) http://www.ccp4.ac.uk/MrBUMP

21. Example 1 1vlw: aldolase from T. maritima 3 chains of 205aa. Data in C2221 to 2.3Å. Using Molrep. Solutions based on 1fq0: Other models based on 1eun and 1eua Most, but not all, work.

22. Example 2 1k6d: alpha subunit of acetate CoA-transferase from E.Coli Solutions based on 1ope: 1ope - longer chains colinear with bacterial alpha and beta subunits Domain 2 is therefore best model. Whole chain also works because of alignment / model editing.

23. A few observations ... • In difficult cases, success in MrBUMP may depend on particular template, chain and model preparation method • Nevertheless, may get several putative solutions • Ease of subsequent model re-building, model completion may depend on choice of solution • First solution or check everything? • Expectation that quick solution required - in fact, most users seem happy to let MrBUMP run for long time (hours, days) • Worth checking “failed” solutions!

24. Future developments • Windows support (requires installer) • Complexes (in progress) • Processing of multiple target sequences • Improved alignment: • Multiple alignment against larger sequence database • Alignment from profile-based search • User-supplied alignment • Incorporate PISA multimer determining service (in progress) • Model generation: • Identification of flexible loops • Normal mode generated conformations • Develop web-service version to allow CCP4i users to run jobs on CCP4 cluster

25. Acknowledgements • Ronan Keegan, CCP4 @ Daresbury • Thanks to authors of all underlying programs and services • Other suggestions from: • Dave Meredith, Graeme Winter, Daresbury Laboratory. • Eugene Krissinel, EBI, Cambridge. • Eleanor Dobson, YSBL, York University • Geoff Barton, Charlie Bond, University of Dundee • Randy Read, Airlie McCoy, Cambridge • Funding: • BBSRC (e-HTPX, CCP4) • See posters m34.p07 (Keegan, sic), m03.p03 (Vagin), • m32.p06 (Remacle) http://www.ccp4.ac.uk/MrBUMP