Hi David,
Thanks for the tip! I just found it in the documentation; the syntax is
[r{12-20}]. See
http://rdkit.org/docs_temp/RDKit_Book.html#smarts-support-and-extensions
Note that this doesn't suffer from the hard-coded limitation I mentioned,
and you can even specify open ranges such as [r{12-}].
Ivan
On Wed, Oct 9, 2019 at 12:35 PM David Cosgrove <davidacosgrov...@gmail.com>
wrote:
> Hi Ivan,
> There is an RDKit extension to SMARTS that allows something like [r12-20].
> I can’t check the exact syntax at the moment. You might want to check that
> atoms are not in smaller rings as well, so as not to pull up things like
> anthracene which might not be something you’d want to class as a macrocycle.
> Cheers,
> Dave
>
> On Wed, 9 Oct 2019 at 14:39, Ivan Tubert-Brohman <
> ivan.tubert-broh...@schrodinger.com> wrote:
>
>> Hi Thomas,
>>
>> I don't know of an RDKit function that directly recognizes macrocycles,
>> but you could find the size of the largest ring this way:
>>
>> ri = mol.GetRingInfo()
>> largest_ring_size = max((len(r) for r in ri.AtomRings()), default=0)
>> if largest_ring_size > 12:
>> ...
>>
>> You can also find if a molecule has a ring of a certain size using
>> SMARTS, but only for rings up to size 20 at the moment (this is an
>> RDKit-specific limit). For example, if you are happy with finding rings of
>> size 12-20, you could use SMARTS [r12,r13,r14,r15,r16,r17,r18,r19,r20].
>> It's ugly but can be handy if you already have SMARTS-based tools to reuse.
>>
>> Ivan
>>
>> On Wed, Oct 9, 2019 at 7:25 AM Thomas Evangelidis <teva...@gmail.com>
>> wrote:
>>
>>> Greetings,
>>>
>>> Is there an automatic way to distinguish the macrocyclic molecules
>>> within a large chemical library using RDKit? For example, according to this
>>> definition: Macrocycles are ring structures composed of at least twelve
>>> atoms in the central cyclic framework [1,2,3]. Maybe someone here has a
>>> better definition. Could anyone give me some hints on how to program this?
>>>
>>> I thank you in advance.
>>> Thomas
>>>
>>> 1. Yudin AK (2015) Macrocycles: lessons from the distant past, recent
>>> developments, and future directions. Chem Sci 6:30–49.
>>> 2. Marsault E, Peterson ML (2011) Macrocycles are great cycles:
>>> applications, opportunities, and challenges of synthetic macrocycles in
>>> drug discovery. J Med Chem 54:1961–2004.
>>> 3. Heinis C (2014) Drug discovery: tools and rules for macrocycles. Nat
>>> Chem Biol 10:696–698.
>>>
>>>
>>> --
>>>
>>> ======================================================================
>>>
>>> Dr. Thomas Evangelidis
>>>
>>> Research Scientist
>>>
>>> IOCB - Institute of Organic Chemistry and Biochemistry of the Czech
>>> Academy of Sciences <https://www.uochb.cz/web/structure/31.html?lang=en>
>>> , Prague, Czech Republic
>>> &
>>> CEITEC - Central European Institute of Technology
>>> <https://www.ceitec.eu/>, Brno, Czech Republic
>>>
>>> email: teva...@gmail.com, Twitter: tevangelidis
>>> <https://twitter.com/tevangelidis>, LinkedIn: Thomas Evangelidis
>>> <https://www.linkedin.com/in/thomas-evangelidis-495b45125/>
>>>
>>> website: https://sites.google.com/site/thomasevangelidishomepage/
>>>
>>>
>>>
>>> _______________________________________________
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>>>
>> _______________________________________________
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> --
> David Cosgrove
> Freelance computational chemistry and chemoinformatics developer
> http://cozchemix.co.uk
>
>
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