s tudy o f t he s econd v irial c oefficients : n ew c hallenge f or qspr

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STUDY OF THE SECOND VIRIAL COEFFICIENTS: NEW CHALLENGE FOR QSPR Elena Mokshyna, Victor E. Kuz’min, Vadim I. Nedostup

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S TUDY O F T HE S ECOND V IRIAL C OEFFICIENTS : N EW C HALLENGE F OR QSPR. Elena Mokshyna , Victor E. Kuz’min , Vadim I. Nedostup. W HY C HALLENGE ?. The compressibility factor is expressed as a series expansion in either density (reciprocal molar volume) or pressure : - PowerPoint PPT Presentation

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Page 1: S TUDY  O F  T HE  S ECOND  V IRIAL  C OEFFICIENTS : N EW  C HALLENGE  F OR  QSPR

STUDY OF THE SECOND VIRIAL COEFFICIENTS:NEW CHALLENGE FOR QSPR

Elena Mokshyna, Victor E. Kuz’min, Vadim I. Nedostup

Page 2: S TUDY  O F  T HE  S ECOND  V IRIAL  C OEFFICIENTS : N EW  C HALLENGE  F OR  QSPR

WHY CHALLENGE?

The compressibility factor is expressed as a series expansion in either density (reciprocal molar volume) or pressure:

Main purposes:

• Development of approach to QSPR of T-dependent properties• Calibration of the descriptors

• Prediction for new complex organic compounds

Page 3: S TUDY  O F  T HE  S ECOND  V IRIAL  C OEFFICIENTS : N EW  C HALLENGE  F OR  QSPR

EXPERIMENTAL DATA

Number of compounds: 262 Number of points: 4787

Range of virial coefficients: -5891 – 391 cm3/mol Range of temperatures: 110 – 773 K

Page 4: S TUDY  O F  T HE  S ECOND  V IRIAL  C OEFFICIENTS : N EW  C HALLENGE  F OR  QSPR

DESCRIPTORS & MODELLING TECHNIQUES

SiRMS descriptors:

Temperature as a single descriptor:

B = f(T)

Two-layer QSPR model:

a = f(descriptors) b = f(descriptors)

B = f(a, b)

Page 5: S TUDY  O F  T HE  S ECOND  V IRIAL  C OEFFICIENTS : N EW  C HALLENGE  F OR  QSPR

STATISTICAL ANALYSIS Various statistical methods:

MLR (Multi-Linear Regression)PLS (Projection on Latent Structures)

RF (Random Forest)SVM (Support Vector Machines) with radial basis function kernel

Rigorous 3x5-fold stratified external cross-validationTraining setTest set! Data on virial coefficient of compound

under all the temperatures are put in the test set

Page 6: S TUDY  O F  T HE  S ECOND  V IRIAL  C OEFFICIENTS : N EW  C HALLENGE  F OR  QSPR

RESULTS for B = f(T)

R2ws = 0.53

R2ts = 0.19

R2ws = 0.71

R2ts = 0.45

R2ws = 0.87

R2ts = 0.68

R2ws = 0.94

R2ts = 0.71

Page 7: S TUDY  O F  T HE  S ECOND  V IRIAL  C OEFFICIENTS : N EW  C HALLENGE  F OR  QSPR

RESULTS for B = f (a,b)a = f(descriptors), b = f(descriptors)

R2ws = 0.88

R2ts = 0.51

R2ws = 0.90

R2ts = 0.72

R2ws = 0.98

R2ts = 0.85

R2ws = 0.95

R2ts = 0.75

Page 8: S TUDY  O F  T HE  S ECOND  V IRIAL  C OEFFICIENTS : N EW  C HALLENGE  F OR  QSPR

EXPERIMENTAL ERRORS VS. ERRORS OF MODELS

Hydro-carbons

Halocarbon compounds

Nitrogen compounds

Oxygen compounds

Silicon compounds

Sulphur compounds

0

40

80

120

160

200

Hydrocarbons; Exper-imental error; 21

Halocarbon com-pounds; Experimental

error; 24

Nitrogen compounds; Experimental error; 58

Oxygen compounds; Experimental error; 59Silicon compounds;

Experimental error; 50Sulphur compounds;

Experimental error; 48

Hydrocarbons; T-model error ; 59Halocarbon

compounds; T-model error ; 43

Nitrogen compounds; T-model error ; 190

Oxygen compounds; T-model error ; 131

Silicon compounds; T-model error ; 100

Sulphur compounds; T-model error ; 134

Hydrocarbons; Coef -ficient model error;

37

Halocarbon com-pounds; Coefficient

model error; 43

Nitrogen compounds; Coefficient model er-

ror; 172

Oxygen compounds; Coefficient model

error; 99Silicon compounds; Coefficient model

error; 75

Sulphur compounds; Coefficient model

error; 87Experimental errorT-model error Coefficient model error

Page 9: S TUDY  O F  T HE  S ECOND  V IRIAL  C OEFFICIENTS : N EW  C HALLENGE  F OR  QSPR

Relative Variable Influence

Van-der-Waals Interactions

Temperature Partial charges Molecular Weight Donor/acceptor of Hydrogen Bond

0

10

20

30

40

Van-der-Waals In-teractions; Series1;

31

Temperature; Series1; 24

Partial charges; Series1; 18 Molecular Weight;

Series1; 16Donor/acceptor of Hydrogen Bond;

Series1; 11

Page 10: S TUDY  O F  T HE  S ECOND  V IRIAL  C OEFFICIENTS : N EW  C HALLENGE  F OR  QSPR

Influential fragments

*

*

*

*

*

Some examples from the generated fragments library :

Page 11: S TUDY  O F  T HE  S ECOND  V IRIAL  C OEFFICIENTS : N EW  C HALLENGE  F OR  QSPR

So….MISSION IS POSSIBLE,

BUT CHALLENGE IS NOT COMPLETED!

Page 12: S TUDY  O F  T HE  S ECOND  V IRIAL  C OEFFICIENTS : N EW  C HALLENGE  F OR  QSPR

Thank you for the attention!