mdciao.sites

Tools for reading and manipulating sites.

x2site

Return a site dictionary from a dict or an ascii file

sites_to_res_pairs

Return the pairs of res_idxs needed to compute all the contacts contained in all the input sites.

Sites are user-defined collections of contacts. They can be constructed by hand or read from plain ascii files:

>>> cat site.dat
# contacts to look at :
L394-K270
D381-Q229
Q384-Q229
R385-Q229
D381-K232
Q384-I135

The ascii-files can be annotated if the JSON format is used:

>>> cat site.json
{"name":"interesting contacts",
"pairs": {"AAresSeq": [
        "L394-K270",
        "D381-Q229",
        "Q384-Q229",
        "R385-Q229",
        "D381-K232",
        "Q384-I135"
        ]}}

Sites can also be used inside the Python script/session by using dictionaries, e.g.:

my_site = {"name":"interesting contacts",
           "pairs":{"AAresSeq":[
                     "L394-K270",
                     "D381-Q229",
                     "Q384-Q229",
                     "R385-Q229",
                     "D381-K232",
                     "Q384-I135"
                     ]}}

You can specify the “pairs” as “AAresSeq” (like above) or as zero-indexed residue serial indices using “residx”:

my_site = {"name":"interesting contacts",
           "pairs":{"residx":[
                     "353-972",
                     "340-956",
                     "343-956",
                     "344-956",
                     "340-959",
                     "343-865"
                     ]}}

In this last case, you can also directly use pairs of integers, instead of strings:

my_site = {"name":"interesting contacts",
           "pairs":{"residx":[
                    [353,972],
                    [340,956],
                    [343,956],
                    [344,956],
                    [340,959],
                    [343,865],
                    ]}}

Using “AAresSeq” makes site-definitions portable of across topologies: e.g. “L394” will be picked regardless of the actual residue index. This can be problematic if there’s duplicates (e.g. “ALA150” appears two times in 3SN6). “residx” avoid this, but first the user needs to find out which residue index they are interested in. mdciao offers several ways to do this. From the CLI you can use:

>>> mdc_residue.py ALA150 3SN6.pdb

From the API, you can use:

>>> mdciao.cli.residue_selection("ALA150",geom);
   Using method 'lig_resSeq+' these fragments were found
   fragment      0 with  349 AAs     THR9           (   0) -   LEU394           (348 ) (0)  resSeq jumps
   fragment      1 with  340 AAs     GLN1           ( 349) -   ASN340           (688 ) (1)
   fragment      2 with  217 AAs     ASN5           ( 689) -  ALA1160           (905 ) (2)  resSeq jumps
   fragment      3 with  284 AAs    GLU30           ( 906) -   CYS341           (1189) (3)  resSeq jumps
   fragment      4 with  128 AAs     GLN1           (1190) -   SER128           (1317) (4)
   fragment      5 with    1 AAs  P0G1601           (1318) -  P0G1601           (1318) (5)
   0.0)       ALA150 in fragment 0 with residue index 113
   0.1)       ALA150 in fragment 0 with residue index 1026
   Your selection 'ALA150' yields:
      residue      residx    fragment      resSeq      GPCR        CGN
       ALA150         113           0        150       None       None
       ALA150        1026           0        150       None       None

Check mdciao.cli.residue_selection for more.