mordred 1.2.0

描述符数

>>>frommordredimportCalculator,descriptors>>>n_all=len(Calculator(descriptors,ignore_3D=False).descriptors)>>>n_2D=len(Calculator(descriptors,ignore_3D=True).descriptors)>>>print("2D:    {:5}\n3D:    {:5}\n------------\ntotal: {:5}".format(n_2D,n_all-n_2D,n_all))2D:16133D:213------------total:1826

安装

测试安装

$ python -m mordred.tests

示例

as命令

计算所有描述符

$ python -m mordred example.smi
name,ECIndex,WPath,WPol,Zagreb1, (snip)
benzene,36,27,3,24.0, (snip)
chrolobenzene,45,42,5,30.0, (snip)

保存到文件（显示进度条）

$ python -m mordred example.smi -o example.csv
50%|███████████████████████████████████████▌                                       | 1/2 [00:00<00:00,  7.66it/s]

流读取（内存不足，没有分子信息）

$ python -m mordred example.smi -s -o example.csv
0it [00:00, ?it/s]

仅限ABCIndex

$ python -m mordred example.smi -d ABCIndex
name,ABC,ABCGG
benzene,4.242640687119286,3.9999999999999996
chlorobenzene,5.059137268047012,4.785854275382693

abcindex和酸碱性

$ python -m mordred example.smi -d ABCIndex -d AcidBase
name,ABC,ABCGG,nAcid,nBase
benzene,4.242640687119286,3.9999999999999996,0,0
chlorobenzene,5.059137268047012,4.785854275382693,0,0

多输入

$ python -m mordred example.smi example2.smi -d ABCIndex
name,ABC,ABCGG
benzene,4.242640687119286,3.9999999999999996
chlorobenzene,5.059137268047012,4.785854275382693
pentane,2.8284271247461903,3.1462643699419726

显示帮助

$ python -m mordred --help
usage: python -m mordred [-h] [--version] [-t {auto,sdf,mol,smi}] [-o OUTPUT]
                         [-p PROCESSES] [-q] [-s] [-d DESC] [-3] [-v]
                         INPUT [INPUT ...]

positional arguments:
  INPUT

optional arguments:
  -h, --help            show this help message and exit
  --version             input molecular file
  -t {auto,sdf,mol,smi}, --type {auto,sdf,mol,smi}
                        input filetype (default: auto)
  -o OUTPUT, --output OUTPUT
                        output file path (default: stdout)
  -p PROCESSES, --processes PROCESSES
                        number of processes (default: number of logical
                        processors)
  -q, --quiet           hide progress bar
  -s, --stream          stream read
  -d DESC, --descriptor DESC
                        descriptors to calculate (default: all)
  -3, --3D              use 3D descriptors (require sdf or mol file)
  -v, --verbosity       verbosity

descriptors: ABCIndex AcidBase AdjacencyMatrix Aromatic AtomCount
Autocorrelation BalabanJ BaryszMatrix BCUT BertzCT BondCount CarbonTypes Chi
Constitutional CPSA DetourMatrix DistanceMatrix EccentricConnectivityIndex
EState ExtendedTopochemicalAtom FragmentComplexity Framework GeometricalIndex
GravitationalIndex HydrogenBond InformationContent KappaShapeIndex Lipinski
McGowanVolume MoeType MolecularDistanceEdge MolecularId MomentOfInertia MoRSE
PathCount Polarizability RingCount RotatableBond SLogP TopologicalCharge
TopologicalIndex TopoPSA VdwVolumeABC VertexAdjacencyInformation WalkCount
Weight WienerIndex ZagrebIndex

作为库

>>>fromrdkitimportChem>>>frommordredimportCalculator,descriptors# create descriptor calculator with all descriptors>>>calc=Calculator(descriptors,ignore_3D=True)>>>len(calc.descriptors)1613>>>len(Calculator(descriptors,ignore_3D=True,version="1.0.0"))1612# calculate single molecule>>>mol=Chem.MolFromSmiles('c1ccccc1')>>>calc(mol)[:3][4.242640687119286,3.9999999999999996,0]# calculate multiple molecule>>>mols=[Chem.MolFromSmiles(smi)forsmiin['c1ccccc1Cl','c1ccccc1O','c1ccccc1N']]# as pandas>>>df=calc.pandas(mols)>>>df['SLogP']02.340011.392221.2688Name:SLogP,dtype:float64

见examples

引文

Moriwaki H，Tian Y-S，Kawashita N，Takagi T（2018）Mordred:分子描述符计算器。化学信息学杂志10:4。doi:10.1186/s13321-018-0258-y

文档

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• v1.1.0
• v1.0.0