Meetup Pytalks prezentacija 13.10

1. some other API
Mario Lovrić

2. Outline
• Kemoinformatika
• QSAR
• MOPAC
• RDkit
1

3. Stara škola:
MeetupChemtalk
Kemoinformatika
Struktura
-pretpostavljena
aktivnost
Dizajn
-sintetski put
Početni materijali
Aktivnost
-in vitro
-in vivo
Prodaja?

4. MeetupChemtalk
Kemoinformatika
Struktura
-prijedlog prema
aktivnosti
X molekula
Dizajn
-simulacija reakcije
Aktivnost
-in silico

5. Kemoinformatika
• Kemoinformatika = korištenje računalnih alata za rješavanje kemijskih
problema
• molekularna mehanika (molekula je oscilator)
• (semi-)empirijske metode
• ab initio kvantna kemija
• Schrödinger
4

6. MeetupChemtalk
QSARmodeliranje
• Aktivnosti: toksičnost, topljivost, biološka
aktivnosti
• Struktura: molekulska težina, vrelište,
naboji, orbitale

7. MeetupChemtalk
QSAR-deskriptori
Glavne grupe molekularnih deskriptora:
 Fizikalno-kemijski (log P, log D, molarna
refraktivnost, pKa, topljivost ...)
 Veličina/oblik (molekularne težine, momenti
inercije ...)
 Topološki (indeksi povezanosti ...)
 Vodikove veze (broj vodikovih donora i akceptora)
 Elektrostatski (formalni naboj, parcijalni naboji
atoma, dipolni momenti i vektori, HOMO i LUMO
energija ...)
 Deskriptori temeljeni na prebrojavanju atoma
strukturnih fragmenata

8. MeetupChemtalk
QSARmodeliranje(Toksičnost)

9. MeetupChemtalk
QSARmodeliranje(Toksičnost)

10. MeetupChemtalk
QSARmodeliranje
Zašto Python?
 Automatizacija
 Konverzija
 Generiranje deskriptora
 Ispitivanje korelacije
 Obrada rezultata

11. MeetupChemtalk
TOOLS-FORMATI
• Razni formati zapisa molekula (input)
struktura:
CC(=O)OC1=CC=CC=C1C(O)=O
SMILES .smi
.mol .mop - CARTESIAN
C 1,37169 1 -0,15132 1 -0,34959 1
C 2,76445 1 0,40647 1 -0,35851 1
O 3,10565 1 1,43188 1 0,21058 1
O 3,58382 1 -0,45421 1 -1,09985 1
C 4,97372 1 -0,22679 1 -1,24483 1
C 5,48511 1 1,06344 1 -1,41149 1
C 6,86118 1 1,25315 1 -1,55109 1
C 7,72426 1 0,15903 1 -1,55109 1
C 7,21133 1 -1,13261 1 -1,42353 1
C 5,83049 1 -1,33986 1 -1,27999 1
C 5,37219 1 -2,74860 1 -1,14834 1
O 6,09811 1 -3,63982 1 -0,73331 1
O 4,11925 1 -2,98371 1 -1,58894 1
H 0,69836 1 0,55992 1 0,13731 1
H 1,35569 1 -1,09121 1 0,20772 1
H 1,02557 1 -0,30601 1 -1,37472 1
H 4,83518 1 1,93435 1 -1,42367 1
H 7,26137 1 2,25976 1 -1,65239 1
H 8,79703 1 0,31053 1 -1,64998 1
H 7,89460 1 -1,98132 1 -1,43564 1
H 3,66871 1 -2,19109 1 -1,93641 1

12. MeetupChemtalk
TOOLS-MOPAC
• FINAL HEAT OF FORMATION = 185.21555 KCAL/MOL
• TOTAL ENERGY = -2420.73389 EV
• ELECTRONIC ENERGY = -9044.42051 EV
• CORE-CORE REPULSION = 6623.68661 EV
•
• GRADIENT NORM = 0.74904
• IONIZATION POTENTIAL = 9.968638 EV
• HOMO LUMO ENERGIES (EV) = -9.969 -2.713
• NO. OF FILLED LEVELS = 30
• MOLECULAR WEIGHT = 172.097
• MOLECULAR DIMENSIONS (Angstroms)
• Atom Atom Distance
• O 13 O 3 9.07979
• O 12 C 7 6.68925
• C 5 C 7 0.08515
• JEDNA PO JEDNA!! KONVERZIJA??

13. PROBLEM – KONVERZIJA??
 import subprocess, os
 bab_adr='C:/Program Files (x86)/OpenBabel-2.3.2/babel.exe'
 for file in os.listdir('Z:/'):
 if file.endswith ('.smiles'):
 smile_file='Z:/'+str(file)
 mop_file='Z:/'+str(file)+'.mop'
 subprocess.call([bab_adr, '-ismi',str(smile_file),'-omopcrt',str(mop_file),'--gen2d', '-xkAM1' ])
MOPAC RUN
 mopac_adr='C:/Program Files/MOPAC/MOPAC2012.exe
 mop_path='M:/2015-05-30/mop
 for pacfile in os.listdir(mop_path):
if pacfile.endswith('.mop'):
mopfile=str(mop_path)+'/'+str(pacfile)
subprocess.call([mopac_adr, str(mopfile)])
MeetupChemtalk
TOOLS–MOPAC-PYTHON

14. MeetupChemtalk

15. To include names in the mol blocks, set the molecule’s “_Name” property:
 m2=Chem.MolFromSmiles('C1CCC1')
 m2.SetProp("_Name","cyclobutane")
 print Chem.MolToMolBlock(m2)
cyclobutane
RDKit
4 4 0 0 0 0 0 0 0 0999 V2000
0.0000 0.0000 0.0000 C 0 0 0 0 0 0 0 0 0 0 0 0
0.0000 0.0000 0.0000 C 0 0 0 0 0 0 0 0 0 0 0 0
0.0000 0.0000 0.0000 C 0 0 0 0 0 0 0 0 0 0 0 0
0.0000 0.0000 0.0000 C 0 0 0 0 0 0 0 0 0 0 0 0
1 2 1 0
2 3 1 0
3 4 1 0
4 1 1 0
M END
MeetupChemtalk
TOOLS–RDkit

16. You can either include 2D coordinates (i.e. a depiction):
 from rdkit.Chem import AllChem
 AllChem.Compute2DCoords(m2)
0
 print Chem.MolToMolBlock(m2)
cyclobutane
RDKit 2D
4 4 0 0 0 0 0 0 0 0999 V2000
1.0607 -0.0000 0.0000 C 0 0 0 0 0 0 0 0 0 0 0 0
-0.0000 -1.0607 0.0000 C 0 0 0 0 0 0 0 0 0 0 0 0
-1.0607 0.0000 0.0000 C 0 0 0 0 0 0 0 0 0 0 0 0
0.0000 1.0607 0.0000 C 0 0 0 0 0 0 0 0 0 0 0 0
1 2 1 0
2 3 1 0
3 4 1 0
4 1 1 0
M END
MeetupChemtalk
TOOLS–RDkit

17.  AllChem.EmbedMolecule(m2)
0
 AllChem.UFFOptimizeMolecule(m2)
0
 print Chem.MolToMolBlock(m2)
cyclobutane
RDKit 3D
4 4 0 0 0 0 0 0 0 0999 V2000
-0.7883 0.5560 -0.2718 C 0 0 0 0 0 0 0 0 0 0 0 0
-0.4153 -0.9091 -0.1911 C 0 0 0 0 0 0 0 0 0 0 0 0
0.7883 -0.5560 0.6568 C 0 0 0 0 0 0 0 0 0 0 0 0
0.4153 0.9091 0.5762 C 0 0 0 0 0 0 0 0 0 0 0 0
1 2 1 0
2 3 1 0
3 4 1 0
4 1 1 0
M END
MeetupChemtalk
TOOLS–RDkit

18. m3 = Chem.AddHs(m2)
m3.GetNumAtoms()
12
m4 = Chem.RemoveHs(m3)
m4.GetNumAtoms()
4
MeetupChemtalk
TOOLS–RDkit

19. Substructure matching can be done using query molecules
built from SMARTS:
m = Chem.MolFromSmiles('c1ccccc1O')
patt = Chem.MolFromSmarts('ccO')
m.HasSubstructMatch(patt)
True
m.GetSubstructMatch(patt)
(0, 5, 6)
MeetupChemtalk
TOOLS–RDkit

20. ps = rxn.RunReactants((Chem.MolFromSmiles('OC=C'),
Chem.MolFromSmiles('C=CC(N)=C')))
Chem.MolToSmiles(ps[0][0])
'NC1=CCCC(O)C1'
MeetupChemtalk
TOOLS–RDkit

21. • http://www.rdkit.org/
• http://openmopac.net/
• https://github.com/mariolovric
• Dale Hoff et al. , Predicting the Toxicities of Chemicals to Aquatic Animal
Species, 2010
MeetupChemtalk
Ref.

22. Hvala na pažnji.
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