I want to show some numbers from a compatible fragmentation scheme to my own
one. Which means generating all the leaves from the hierarchy and then doing
some post processing to merge these fragments. This isn't a problem on some of
the more drug like data sets, however with ChEMBL this is causing me some
stress.
Best,
Nick
Nicholas C. Firth | PhD Student | Cancer Therapeutics
The Institute of Cancer Research | 15 Cotswold Road | Belmont | Sutton | Surrey
| SM2 5NG
T 020 8722 4033 | E [email protected]<mailto:[email protected]> |
W www.icr.ac.uk<http://www.icr.ac.uk/> | Twitter
@ICRnews<https://twitter.com/ICRnews>
Facebook
www.facebook.com/theinstituteofcancerresearch<http://www.facebook.com/theinstituteofcancerresearch>
Making the discoveries that defeat cancer
[cid:[email protected]]
On 11 Jun 2014, at 09:26, Greg Landrum
<[email protected]<mailto:[email protected]>> wrote:
The RECAP code currently generates a hierarchy tree for the molecule. The size
of this tree scales very non-linearly with the number of fragments. That
molecule has a huge number of fragments.
I don't think the RECAP code will work for you as written.
What are you trying to get out of the analysis? There may be another approach
that will work,
-greg
On Wed, Jun 11, 2014 at 3:25 AM, Nicholas Firth
<[email protected]<mailto:[email protected]>> wrote:
I think I have found part of the problem, I tried it on a single processor last
night and didn't get past the second molecule. The script hangs on this
molecule.
>>> from rdkit import Chem
>>> from rdkit.Chem import Recap
>>> mol =
>>> Chem.MolFromSmiles('CC[C@H](C)[C@H](NC(=O)[C@H](CC(C)C)NC(=O)[C@@H](NC(=O)[C@@H](N)CCSC)[C@@H](C)O)C(=O)NCC(=O)N[C@@H](C)C(=O)N[C@@H](C)C(=O)N[C@@H](Cc1c[nH]cn1)C(=O)N[C@@H](CC(=O)N)C(=O)NCC(=O)N[C@@H](C)C(=O)N[C@@H](C)C(=O)N[C@@H](CCC(=O)N)C(=O)N[C@@H](CC(C)C)C(=O)N[C@@H](CC(C)C)C(=O)N[C@@H](CCCN=C(N)N)C(=O)N[C@@H](CCC(=O)N)C(=O)N[C@@H](CC(C)C)C(=O)N[C@@H](CCCN=C(N)N)C(=O)NCC(=O)N[C@@H](CCC(=O)N)C(=O)N[C@@H](CC(C)C)C(=O)NCC(=O)N2CCC[C@H]2C(=O)N3CCC[C@H]3C(=O)NCC(=O)N[C@@H](CO)C(=O)N[C@@H](CCCN=C(N)N)C(=O)N')
>>> hierarch = Recap.RecapDecompose(mol)
>>> ks = hierarch.GetLeaves().keys()
I imagined it would be slow for this molecule, but 8 hours might be an issue
rather than a feature!
Best,
Nick
Nicholas C. Firth | PhD Student | Cancer Therapeutics
The Institute of Cancer Research | 15 Cotswold Road | Belmont | Sutton | Surrey
| SM2 5NG
T 020 8722 4033 | E [email protected]<mailto:[email protected]> |
W www.icr.ac.uk<http://www.icr.ac.uk/> | Twitter
@ICRnews<https://twitter.com/ICRnews>
Facebook
www.facebook.com/theinstituteofcancerresearch<http://www.facebook.com/theinstituteofcancerresearch>
Making the discoveries that defeat cancer
<image001.gif>
On 10 Jun 2014, at 20:53, Dimitri Maziuk
<[email protected]<mailto:[email protected]>> wrote:
On 06/10/2014 01:48 PM, Nicholas Firth wrote:
I still have plenty of CPU's and memory available though, so this
seems odd. Some of the processes have done nothing and the others seem
to have frozen at different times.
Yeah. Parallel processing is often not quite that straightforward.
For instance, since you say they're writing to files, how's your disk i/o?
--
Dimitri Maziuk
Programmer/sysadmin
BioMagResBank, UW-Madison -- http://www.bmrb.wisc.edu<http://www.bmrb.wisc.edu/>
The Institute of Cancer Research: Royal Cancer Hospital, a charitable Company
Limited by Guarantee, Registered in England under Company No. 534147 with its
Registered Office at 123 Old Brompton Road, London SW7 3RP.
This e-mail message is confidential and for use by the addressee only. If the
message is received by anyone other than the addressee, please return the
message to the sender by replying to it and then delete the message from your
computer and network.
------------------------------------------------------------------------------
HPCC Systems Open Source Big Data Platform from LexisNexis Risk Solutions
Find What Matters Most in Your Big Data with HPCC Systems
Open Source. Fast. Scalable. Simple. Ideal for Dirty Data.
Leverages Graph Analysis for Fast Processing & Easy Data Exploration
http://p.sf.net/sfu/hpccsystems
_______________________________________________
Rdkit-discuss mailing list
[email protected]<mailto:[email protected]>
https://lists.sourceforge.net/lists/listinfo/rdkit-discuss
The Institute of Cancer Research: Royal Cancer Hospital, a charitable Company
Limited by Guarantee, Registered in England under Company No. 534147 with its
Registered Office at 123 Old Brompton Road, London SW7 3RP.
This e-mail message is confidential and for use by the addressee only. If the
message is received by anyone other than the addressee, please return the
message to the sender by replying to it and then delete the message from your
computer and network.------------------------------------------------------------------------------
HPCC Systems Open Source Big Data Platform from LexisNexis Risk Solutions
Find What Matters Most in Your Big Data with HPCC Systems
Open Source. Fast. Scalable. Simple. Ideal for Dirty Data.
Leverages Graph Analysis for Fast Processing & Easy Data Exploration
http://p.sf.net/sfu/hpccsystems
_______________________________________________
Rdkit-discuss mailing list
[email protected]
https://lists.sourceforge.net/lists/listinfo/rdkit-discuss
