Compute the descriptors#
The present implementation offers a particular advantage over the original Retip
application (that was based on R) in terms of speed and reliability. In jp²rt
,
molecular descriptors are
computed directly in Java, using parallel streams (exploiting all the
available CPUs).
In order to compute the descriptors you must prepare a tab-separated file containing the SMILES of the compounds you want to analyze. The file must not contain any header, but can contain any (possibly different) number of field per line, as long as the SMILES is the last one (of every line). This is particularly convenient if you want to include additional information about the compounds, such as the name, the InChiKey, or any other property (that can occupy the first fields of every line).
The computation being done in parallel does not guarantee that the order of the lines in the output file will be the same as the input file, so adding an unique identifier (such as a progressive number, or an InChIKey, as an additional field) can be required to be able to sort the file back to the original order.
To compute the descriptors, you can use the jp2rt
command line tool, as
$ jp2rt compute-descriptors input_file.tsv output_file.tsv
where input_file.tsv
is the name of the file containing the SMILES (as the
last column), and output_file.tsv
is the name of the produced file.
Observe that you will compute the descriptors both for the (usually small) training dataset (containing experimental retention times) and for the (possibly very large) dataset you want to predict the retention time.
Example data#
In the following we’ll use the PlaSMA dataset (follow
Get some example data to obtain it); we assume that the file plasma.tsv
contains the following four columns:
(experimental) retention time (in minutes),
InChiKey,
molecule name, and
SMILES
hence, by running
$ jp2rt compute-descriptors plasma.tsv plasma+descriptors.tsv
Show code cell outputs
Computing 0% │ │ 0/799 (0:00:00 / ?)
Computing 0% │ │ 1/799 (0:00:02 / 0:26:37)
Computing 0% │ │ 3/799 (0:00:03 / 0:13:17)
Computing 0% │▏ │ 6/799 (0:00:04 / 0:08:48)
Computing 1% │▍ │ 10/799 (0:00:05 / 0:06:34)
Computing 1% │▌ │ 13/799 (0:00:06 / 0:06:02)
Computing 2% │▋ │ 16/799 (0:00:07 / 0:05:42)
Computing 2% │▊ │ 21/799 (0:00:08 / 0:04:56)
Computing 3% │█ │ 26/799 (0:00:09 / 0:04:27)
Computing 3% │█▏ │ 30/799 (0:00:10 / 0:04:16)
107409 not found
Computing 4% │█▎ │ 32/799 (0:00:11 / 0:04:23)
Computing 4% │█▌ │ 37/799 (0:00:12 / 0:04:07)
Computing 5% │█▊ │ 45/799 (0:00:13 / 0:03:37)
Computing 6% │██ │ 50/799 (0:00:14 / 0:03:29)
Computing 6% │██▏ │ 53/799 (0:00:15 / 0:03:31)
Computing 7% │██▍ │ 59/799 (0:00:16 / 0:03:20)
Computing 8% │██▋ │ 64/799 (0:00:17 / 0:03:15)
Computing 9% │██▉ │ 72/799 (0:00:18 / 0:03:01)
Computing 9% │███▏ │ 77/799 (0:00:19 / 0:02:58)
Computing 10% │███▎ │ 81/799 (0:00:20 / 0:02:57)
Computing 10% │███▌ │ 87/799 (0:00:21 / 0:02:51)
Computing 11% │███▊ │ 92/799 (0:00:22 / 0:02:49)
Computing 12% │████ │ 98/799 (0:00:23 / 0:02:44)
Computing 12% │████▏ │ 100/799 (0:00:24 / 0:02:47)
Computing 13% │████▍ │ 106/799 (0:00:25 / 0:02:43)
Computing 13% │████▌ │ 111/799 (0:00:26 / 0:02:41)
Computing 14% │████▊ │ 117/799 (0:00:27 / 0:02:37)
Computing 15% │█████ │ 124/799 (0:00:28 / 0:02:32)
Computing 16% │█████▍ │ 132/799 (0:00:29 / 0:02:26)
Computing 16% │█████▌ │ 135/799 (0:00:30 / 0:02:27)
Computing 17% │█████▊ │ 140/799 (0:00:31 / 0:02:25)
Computing 18% │██████ │ 146/799 (0:00:32 / 0:02:23)
Computing 18% │██████▏ │ 150/799 (0:00:33 / 0:02:22)
Computing 19% │██████▍ │ 155/799 (0:00:34 / 0:02:21)
Computing 20% │██████▌ │ 160/799 (0:00:35 / 0:02:19)
Computing 20% │██████▊ │ 164/799 (0:00:36 / 0:02:19)
Computing 20% │██████▉ │ 167/799 (0:00:37 / 0:02:20)
Computing 21% │███████▏ │ 174/799 (0:00:38 / 0:02:16)
Computing 22% │███████▎ │ 178/799 (0:00:39 / 0:02:16)
Computing 22% │███████▍ │ 180/799 (0:00:40 / 0:02:17)
Computing 23% │███████▌ │ 184/799 (0:00:41 / 0:02:17)
Computing 23% │███████▊ │ 189/799 (0:00:42 / 0:02:15)
Computing 24% │███████▉ │ 192/799 (0:00:43 / 0:02:15)
Computing 24% │████████ │ 195/799 (0:00:44 / 0:02:16)
Computing 25% │████████▎ │ 201/799 (0:00:45 / 0:02:13)
Computing 25% │████████▌ │ 207/799 (0:00:46 / 0:02:11)
Computing 26% │████████▊ │ 214/799 (0:00:47 / 0:02:08)
Computing 27% │████████▉ │ 217/799 (0:00:48 / 0:02:08)
Computing 27% │█████████▏ │ 222/799 (0:00:49 / 0:02:07)
Computing 28% │█████████▍ │ 227/799 (0:00:50 / 0:02:05)
Computing 29% │█████████▌ │ 233/799 (0:00:51 / 0:02:03)
Computing 29% │█████████▊ │ 239/799 (0:00:52 / 0:02:01)
Computing 30% │█████████▉ │ 242/799 (0:00:53 / 0:02:01)
Computing 30% │██████████▏ │ 246/799 (0:00:55 / 0:02:03)
Computing 31% │██████████▏ │ 248/799 (0:00:56 / 0:02:04)
Computing 31% │██████████▍ │ 252/799 (0:00:57 / 0:02:03)
Computing 32% │██████████▌ │ 256/799 (0:00:58 / 0:02:03)
Computing 32% │██████████▋ │ 260/799 (0:00:59 / 0:02:02)
Computing 33% │███████████ │ 267/799 (0:01:00 / 0:01:59)
Computing 34% │███████████▎ │ 274/799 (0:01:01 / 0:01:56)
Computing 34% │███████████▌ │ 279/799 (0:01:02 / 0:01:55)
Computing 35% │███████████▌ │ 280/799 (0:01:03 / 0:01:56)
Computing 35% │███████████▋ │ 284/799 (0:01:04 / 0:01:56)
Computing 36% │███████████▉ │ 288/799 (0:01:05 / 0:01:55)
Computing 36% │████████████▏ │ 294/799 (0:01:06 / 0:01:53)
Computing 37% │████████████▎ │ 299/799 (0:01:07 / 0:01:52)
Computing 38% │████████████▌ │ 305/799 (0:01:08 / 0:01:50)
Computing 38% │████████████▊ │ 310/799 (0:01:09 / 0:01:48)
Computing 38% │████████████▊ │ 311/799 (0:01:10 / 0:01:49)
Computing 39% │█████████████ │ 315/799 (0:01:11 / 0:01:49)
208203 not found
Computing 40% │█████████████▎ │ 323/799 (0:01:12 / 0:01:46)
Computing 40% │█████████████▌ │ 327/799 (0:01:13 / 0:01:45)
Computing 41% │█████████████▋ │ 332/799 (0:01:14 / 0:01:44)
Computing 42% │█████████████▉ │ 337/799 (0:01:15 / 0:01:42)
Computing 42% │██████████████ │ 340/799 (0:01:16 / 0:01:42)
Computing 43% │██████████████▏ │ 344/799 (0:01:17 / 0:01:41)
Computing 43% │██████████████▍ │ 350/799 (0:01:19 / 0:01:41)
Computing 44% │██████████████▋ │ 355/799 (0:01:20 / 0:01:40)
Computing 44% │██████████████▊ │ 359/799 (0:01:21 / 0:01:39)
Computing 45% │███████████████ │ 365/799 (0:01:22 / 0:01:37)
Computing 46% │███████████████▏ │ 369/799 (0:01:23 / 0:01:36)
Computing 46% │███████████████▎ │ 371/799 (0:01:24 / 0:01:36)
Computing 47% │███████████████▌ │ 378/799 (0:01:25 / 0:01:34)
Computing 47% │███████████████▋ │ 380/799 (0:01:26 / 0:01:34)
Computing 48% │███████████████▉ │ 385/799 (0:01:27 / 0:01:33)
Computing 49% │████████████████▏ │ 392/799 (0:01:28 / 0:01:31)
Computing 49% │████████████████▍ │ 397/799 (0:01:29 / 0:01:30)
Computing 50% │████████████████▌ │ 400/799 (0:01:30 / 0:01:29)
Computing 50% │████████████████▋ │ 405/799 (0:01:31 / 0:01:28)
Computing 51% │████████████████▉ │ 411/799 (0:01:32 / 0:01:26)
Computing 52% │█████████████████▏ │ 416/799 (0:01:33 / 0:01:25)
Computing 52% │█████████████████▍ │ 423/799 (0:01:34 / 0:01:23)
Computing 53% │█████████████████▌ │ 425/799 (0:01:35 / 0:01:23)
Computing 53% │█████████████████▋ │ 428/799 (0:01:36 / 0:01:23)
Computing 54% │█████████████████▉ │ 435/799 (0:01:37 / 0:01:21)
Computing 54% │██████████████████▏ │ 439/799 (0:01:38 / 0:01:20)
Computing 56% │██████████████████▌ │ 448/799 (0:01:39 / 0:01:17)
Computing 56% │██████████████████▊ │ 455/799 (0:01:40 / 0:01:15)
Computing 58% │███████████████████▏ │ 464/799 (0:01:41 / 0:01:12)
Computing 59% │███████████████████▋ │ 478/799 (0:01:42 / 0:01:08)
Computing 61% │████████████████████▍ │ 494/799 (0:01:43 / 0:01:03)
Computing 63% │████████████████████▊ │ 505/799 (0:01:44 / 0:01:00)
Computing 64% │█████████████████████▎ │ 516/799 (0:01:45 / 0:00:57)
7205 not found
Computing 65% │█████████████████████▋ │ 526/799 (0:01:46 / 0:00:55)
Computing 67% │██████████████████████▎ │ 539/799 (0:01:47 / 0:00:51)
Computing 68% │██████████████████████▋ │ 550/799 (0:01:48 / 0:00:48)
Computing 71% │███████████████████████▋ │ 574/799 (0:01:49 / 0:00:42)
Computing 74% │████████████████████████▋ │ 599/799 (0:01:50 / 0:00:36)
Computing 77% │█████████████████████████▌ │ 619/799 (0:01:51 / 0:00:32)
Computing 80% │██████████████████████████▌ │ 644/799 (0:01:52 / 0:00:26)
Computing 83% │███████████████████████████▌ │ 668/799 (0:01:53 / 0:00:22)
Computing 89% │█████████████████████████████▌ │ 716/799 (0:01:54 / 0:00:13)
Computing 93% │██████████████████████████████▉ │ 749/799 (0:01:55 / 0:00:07)
Computing 96% │███████████████████████████████▋ │ 768/799 (0:01:56 / 0:00:04)
Computing 97% │████████████████████████████████▏│ 780/799 (0:01:57 / 0:00:02)
Computing 98% │████████████████████████████████▍│ 784/799 (0:01:58 / 0:00:02)
Computing 98% │████████████████████████████████▍│ 785/799 (0:01:59 / 0:00:02)
Computing 98% │████████████████████████████████▍│ 786/799 (0:02:01 / 0:00:02)
Computing 98% │████████████████████████████████▌│ 787/799 (0:02:03 / 0:00:01)
Computing 98% │████████████████████████████████▌│ 788/799 (0:02:05 / 0:00:01)
Computing 98% │████████████████████████████████▌│ 789/799 (0:02:06 / 0:00:01)
Computing 98% │████████████████████████████████▋│ 790/799 (0:02:08 / 0:00:01)
Computing 98% │████████████████████████████████▋│ 791/799 (0:02:10 / 0:00:01)
Computing 99% │████████████████████████████████▋│ 792/799 (0:02:12 / 0:00:01)
Computing 99% │████████████████████████████████▊│ 793/799 (0:02:15 / 0:00:01)
Computing 99% │████████████████████████████████▊│ 794/799 (0:02:17 / 0:00:00)
Computing 99% │████████████████████████████████▊│ 795/799 (0:02:19 / 0:00:00)
Computing 99% │████████████████████████████████▉│ 796/799 (0:02:22 / 0:00:00)
Computing 99% │████████████████████████████████▉│ 797/799 (0:02:25 / 0:00:00)
Computing 100% │█████████████████████████████████│ 799/799 (0:02:27 / 0:00:00)
Computing 100% │█████████████████████████████████│ 799/799 (0:02:27 / 0:00:00)
we will obtain the file plasma+descriptors.tsv
that contains the same
four columns, followed by the columns related to the computed molecular
descriptors.
Computing the descriptors for a single molecule#
The above approach is the one of choice for bulk operations on large datasets. It is although desirable to be able to compute the descriptor values for a single molecule and to know every value to exactly what descriptor it refers to.
Albeit in a much slower way, one can compute the descriptors for a single
molecule given its SMILES; take for example
O=C(O)C(N)CC1=CC=C(O)C=C1
:
from jp2rt import compute_descriptors
smiles = 'O=C(O)C(N)CC1=CC=C(O)C=C1'
descriptors_values = compute_descriptors(smiles)
To understand the meaning of the computed values, you can use the function descriptors()
to get the list of the descriptors computed.
from jp2rt import descriptors
descriptors_names = descriptors()
Putting together the information returned by the two calls, you can get a better understanding of the meaning of the computed values.
from tabulate import tabulate
print(tabulate(
[(*dn, v) for dn, v in zip(
[(d, n) for d in descriptors_names for n in descriptors_names[d]],
descriptors_values)
], headers=['Descriptor', 'Name', 'Value']
))
Descriptor Name Value
--------------------------------------- ---------------- ------------
AcidicGroupCountDescriptor nAcid 1
ALOGPDescriptor ALogP -0.0742
ALOGPDescriptor ALogp2 0.00550564
ALOGPDescriptor AMR 50.9351
AminoAcidCountDescriptor nA 1
AminoAcidCountDescriptor nR 0
AminoAcidCountDescriptor nN 0
AminoAcidCountDescriptor nD 0
AminoAcidCountDescriptor nC 0
AminoAcidCountDescriptor nF 0
AminoAcidCountDescriptor nQ 0
AminoAcidCountDescriptor nE 0
AminoAcidCountDescriptor nG 1
AminoAcidCountDescriptor nH 0
AminoAcidCountDescriptor nI 0
AminoAcidCountDescriptor nP 0
AminoAcidCountDescriptor nL 0
AminoAcidCountDescriptor nK 0
AminoAcidCountDescriptor nM 0
AminoAcidCountDescriptor nS 0
AminoAcidCountDescriptor nT 0
AminoAcidCountDescriptor nY 0
AminoAcidCountDescriptor nV 0
AminoAcidCountDescriptor nW 0
APolDescriptor apol 26.6807
AromaticAtomsCountDescriptor naAromAtom 0
AromaticBondsCountDescriptor nAromBond 0
AtomCountDescriptor nAtom 24
AutocorrelationDescriptorCharge ATSc1 0.299003
AutocorrelationDescriptorCharge ATSc2 -0.102402
AutocorrelationDescriptorCharge ATSc3 -0.0800436
AutocorrelationDescriptorCharge ATSc4 0.0233263
AutocorrelationDescriptorCharge ATSc5 0.0286145
AutocorrelationDescriptorMass ATSm1 15.6834
AutocorrelationDescriptorMass ATSm2 14.1625
AutocorrelationDescriptorMass ATSm3 19.4352
AutocorrelationDescriptorMass ATSm4 17.6015
AutocorrelationDescriptorMass ATSm5 11.3286
AutocorrelationDescriptorPolarizability ATSp1 617.503
AutocorrelationDescriptorPolarizability ATSp2 675.55
AutocorrelationDescriptorPolarizability ATSp3 839.431
AutocorrelationDescriptorPolarizability ATSp4 718.318
AutocorrelationDescriptorPolarizability ATSp5 479.111
BasicGroupCountDescriptor nBase 1
BCUTDescriptor BCUTw-1l 11.6937
BCUTDescriptor BCUTw-1h 16.01
BCUTDescriptor BCUTc-1l -0.400234
BCUTDescriptor BCUTc-1h 0.399237
BCUTDescriptor BCUTp-1l 4.05829
BCUTDescriptor BCUTp-1h 8.93048
BondCountDescriptor nB 13
BPolDescriptor bpol 12.3233
CarbonTypesDescriptor C1SP1 0
CarbonTypesDescriptor C2SP1 0
CarbonTypesDescriptor C1SP2 1
CarbonTypesDescriptor C2SP2 5
CarbonTypesDescriptor C3SP2 1
CarbonTypesDescriptor C1SP3 0
CarbonTypesDescriptor C2SP3 2
CarbonTypesDescriptor C3SP3 0
CarbonTypesDescriptor C4SP3 0
ChiChainDescriptor SCH-3 0
ChiChainDescriptor SCH-4 0
ChiChainDescriptor SCH-5 0
ChiChainDescriptor SCH-6 0.0833333
ChiChainDescriptor SCH-7 0.142259
ChiChainDescriptor VCH-3 0
ChiChainDescriptor VCH-4 0
ChiChainDescriptor VCH-5 0
ChiChainDescriptor VCH-6 0.0277778
ChiChainDescriptor VCH-7 0.0320645
ChiClusterDescriptor SC-3 1.06183
ChiClusterDescriptor SC-4 0
ChiClusterDescriptor SC-5 0.235702
ChiClusterDescriptor SC-6 0
ChiClusterDescriptor VC-3 0.362942
ChiClusterDescriptor VC-4 0
ChiClusterDescriptor VC-5 0.0215166
ChiClusterDescriptor VC-6 0
ChiPathClusterDescriptor SPC-4 1.9913
ChiPathClusterDescriptor SPC-5 1.60203
ChiPathClusterDescriptor SPC-6 2.31513
ChiPathClusterDescriptor VPC-4 0.51763
ChiPathClusterDescriptor VPC-5 0.464159
ChiPathClusterDescriptor VPC-6 0.491555
ChiPathDescriptor SP-0 9.84493
ChiPathDescriptor SP-1 6.09222
ChiPathDescriptor SP-2 5.5829
ChiPathDescriptor SP-3 3.97862
ChiPathDescriptor SP-4 2.36277
ChiPathDescriptor SP-5 2.03084
ChiPathDescriptor SP-6 1.00364
ChiPathDescriptor SP-7 0.591607
ChiPathDescriptor VP-0 6.97388
ChiPathDescriptor VP-1 3.85652
ChiPathDescriptor VP-2 2.8153
ChiPathDescriptor VP-3 1.70915
ChiPathDescriptor VP-4 0.973275
ChiPathDescriptor VP-5 0.645913
ChiPathDescriptor VP-6 0.265353
ChiPathDescriptor VP-7 0.126889
EccentricConnectivityIndexDescriptor ECCEN 157
FMFDescriptor FMF 0.461538
FractionalCSP3Descriptor Fsp3 0.222222
FractionalPSADescriptor tpsaEfficiency 0.461414
FragmentComplexityDescriptor fragC 420.04
HBondAcceptorCountDescriptor nHBAcc 4
HBondDonorCountDescriptor nHBDon 3
HybridizationRatioDescriptor HybRatio 0.222222
JPlogPDescriptor JPLogP 0.267646
KappaShapeIndicesDescriptor Kier1 11.0769
KappaShapeIndicesDescriptor Kier2 5.02422
KappaShapeIndicesDescriptor Kier3 3.7037
KierHallSmartsDescriptor khs.sLi 0
KierHallSmartsDescriptor khs.ssBe 0
KierHallSmartsDescriptor khs.ssssBe 0
KierHallSmartsDescriptor khs.ssBH 0
KierHallSmartsDescriptor khs.sssB 0
KierHallSmartsDescriptor khs.ssssB 0
KierHallSmartsDescriptor khs.sCH3 0
KierHallSmartsDescriptor khs.dCH2 0
KierHallSmartsDescriptor khs.ssCH2 1
KierHallSmartsDescriptor khs.tCH 0
KierHallSmartsDescriptor khs.dsCH 0
KierHallSmartsDescriptor khs.aaCH 4
KierHallSmartsDescriptor khs.sssCH 1
KierHallSmartsDescriptor khs.ddC 0
KierHallSmartsDescriptor khs.tsC 0
KierHallSmartsDescriptor khs.dssC 1
KierHallSmartsDescriptor khs.aasC 2
KierHallSmartsDescriptor khs.aaaC 0
KierHallSmartsDescriptor khs.ssssC 0
KierHallSmartsDescriptor khs.sNH3 0
KierHallSmartsDescriptor khs.sNH2 1
KierHallSmartsDescriptor khs.ssNH2 0
KierHallSmartsDescriptor khs.dNH 0
KierHallSmartsDescriptor khs.ssNH 0
KierHallSmartsDescriptor khs.aaNH 0
KierHallSmartsDescriptor khs.tN 0
KierHallSmartsDescriptor khs.sssNH 0
KierHallSmartsDescriptor khs.dsN 0
KierHallSmartsDescriptor khs.aaN 0
KierHallSmartsDescriptor khs.sssN 0
KierHallSmartsDescriptor khs.ddsN 0
KierHallSmartsDescriptor khs.aasN 0
KierHallSmartsDescriptor khs.ssssN 0
KierHallSmartsDescriptor khs.sOH 2
KierHallSmartsDescriptor khs.dO 1
KierHallSmartsDescriptor khs.ssO 0
KierHallSmartsDescriptor khs.aaO 0
KierHallSmartsDescriptor khs.sF 0
KierHallSmartsDescriptor khs.sSiH3 0
KierHallSmartsDescriptor khs.ssSiH2 0
KierHallSmartsDescriptor khs.sssSiH 0
KierHallSmartsDescriptor khs.ssssSi 0
KierHallSmartsDescriptor khs.sPH2 0
KierHallSmartsDescriptor khs.ssPH 0
KierHallSmartsDescriptor khs.sssP 0
KierHallSmartsDescriptor khs.dsssP 0
KierHallSmartsDescriptor khs.sssssP 0
KierHallSmartsDescriptor khs.sSH 0
KierHallSmartsDescriptor khs.dS 0
KierHallSmartsDescriptor khs.ssS 0
KierHallSmartsDescriptor khs.aaS 0
KierHallSmartsDescriptor khs.dssS 0
KierHallSmartsDescriptor khs.ddssS 0
KierHallSmartsDescriptor khs.sCl 0
KierHallSmartsDescriptor khs.sGeH3 0
KierHallSmartsDescriptor khs.ssGeH2 0
KierHallSmartsDescriptor khs.sssGeH 0
KierHallSmartsDescriptor khs.ssssGe 0
KierHallSmartsDescriptor khs.sAsH2 0
KierHallSmartsDescriptor khs.ssAsH 0
KierHallSmartsDescriptor khs.sssAs 0
KierHallSmartsDescriptor khs.sssdAs 0
KierHallSmartsDescriptor khs.sssssAs 0
KierHallSmartsDescriptor khs.sSeH 0
KierHallSmartsDescriptor khs.dSe 0
KierHallSmartsDescriptor khs.ssSe 0
KierHallSmartsDescriptor khs.aaSe 0
KierHallSmartsDescriptor khs.dssSe 0
KierHallSmartsDescriptor khs.ddssSe 0
KierHallSmartsDescriptor khs.sBr 0
KierHallSmartsDescriptor khs.sSnH3 0
KierHallSmartsDescriptor khs.ssSnH2 0
KierHallSmartsDescriptor khs.sssSnH 0
KierHallSmartsDescriptor khs.ssssSn 0
KierHallSmartsDescriptor khs.sI 0
KierHallSmartsDescriptor khs.sPbH3 0
KierHallSmartsDescriptor khs.ssPbH2 0
KierHallSmartsDescriptor khs.sssPbH 0
KierHallSmartsDescriptor khs.ssssPb 0
LargestChainDescriptor nAtomLC 9
LargestPiSystemDescriptor nAtomP 7
MannholdLogPDescriptor MLogP 2.01
MDEDescriptor MDEC-11 0
MDEDescriptor MDEC-12 0
MDEDescriptor MDEC-13 0
MDEDescriptor MDEC-14 0
MDEDescriptor MDEC-22 4.88359
MDEDescriptor MDEC-23 9.07086
MDEDescriptor MDEC-24 0
MDEDescriptor MDEC-33 2.10258
MDEDescriptor MDEC-34 0
MDEDescriptor MDEC-44 0
MDEDescriptor MDEO-11 0.595275
MDEDescriptor MDEO-12 0
MDEDescriptor MDEO-22 0
MDEDescriptor MDEN-11 0
MDEDescriptor MDEN-12 0
MDEDescriptor MDEN-13 0
MDEDescriptor MDEN-22 0
MDEDescriptor MDEN-23 0
MDEDescriptor MDEN-33 0
PetitjeanNumberDescriptor PetitjeanNumber 0.5
PetitjeanShapeIndexDescriptor topoShape 1
PetitjeanShapeIndexDescriptor geomShape nan
RotatableBondsCountDescriptor nRotB 3
RuleOfFiveDescriptor LipinskiFailures 0
SmallRingDescriptor nSmallRings 1
SmallRingDescriptor nAromRings 1
SmallRingDescriptor nRingBlocks 1
SmallRingDescriptor nAromBlocks 1
SmallRingDescriptor nRings3 0
SmallRingDescriptor nRings4 0
SmallRingDescriptor nRings5 0
SmallRingDescriptor nRings6 1
SmallRingDescriptor nRings7 0
SmallRingDescriptor nRings8 0
SmallRingDescriptor nRings9 0
SpiroAtomCountDescriptor nSpiroAtoms 0
TPSADescriptor TopoPSA 83.55
VAdjMaDescriptor VAdjMat 4.70044
WeightDescriptor MW 181.189
WeightedPathDescriptor WTPT-1 25.2212
WeightedPathDescriptor WTPT-2 1.94009
WeightedPathDescriptor WTPT-3 9.74438
WeightedPathDescriptor WTPT-4 7.26746
WeightedPathDescriptor WTPT-5 2.47692
WienerNumbersDescriptor WPATH 268
WienerNumbersDescriptor WPOL 15
XLogPDescriptor XLogP -2.711
ZagrebIndexDescriptor Zagreb 60