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N.B.! These descriptors can be only used for model development on OCHEM web site and cannot be exported.

ADRIANA.Code comprises a unique combination of methods for calculating molecular descriptors on a sound geometric and physicochemical basis. These descriptors can be used for a wide range of applications in all areas of chemistry, in particular in QSAR/QSPR.
ADRIANA.Code contains a series of methods for the generation of 3D structures and the calculation of physicochemical descriptors and molecular properties based on rapid empirical models. In addition, it contains a hierarchy of increasing levels of sophistication in representing chemical compounds from the constitution to the 3D structure of a molecule. At each level, a wide range of physicochemical effects are included in the molecular descriptors. 

Available descriptors

The following tables list the descriptors that are calculated by the OCHEM web service of ADRIANA.Code.
For further details about the descriptors availaible in ADRIANA.Code, their scientific and technical background and units, please refer to the ADRIANA.Code program manual

Global molecular descriptors

Global molecular descriptors represent a chemical structure by a structural, chemical or physicochemical feature or property of the molecule expressed by a single value.
The total number of global molecular descriptors is 19.

DescriptorShort name in header line of csv descriptor fileUnitReferences
Molecular weightWeight[u], [Da][1]
Number of hydrogen bonding acceptorsHAcc-[2]
Number of oxygen atom-based hydrogen bonding acceptorsHAcc_O-[2]
Number of nitrogen atom-based hydrogen bonding acceptorsHAcc_N-[2]
Number of hydrogen bonding donorsHDon-[2]
Number of oxygen atom-based hydrogen bonding donorsHDon_O-[2]
Number of nitrogen atom-based hydrogen bonding donorsHDon_N-[2]
Octanol/water partition coefficient (logP)XlogP[log units][3]
Topological polar surface areaTPSA2][4]
Mean molecular polarizabilityPolariz3][5-8]
Molecular dipole momentDipole[Debey][9-15]
Aqueous solubility (logS)LogS[log units][16]
Number of rotatable bondsNRotBond-[17]
Number of Ro5 violationsNViolationsRo5-[2]
Number of extended Ro5 violationsNViolationsExtRo5-[2]
Number of atomsNAtoms--
Number of tetrahedral stereocentersNStereo--
Molecular complexityComplexity-[18]
Ring complexityRComplexity-[19]

Shape and size descriptors

Shape and size descriptors characterize the size and the 3D shape of a molecule, e.g., if a molecule has a more enlongated or a spherical shape. These descriptors represent a molecule by a single value.
The total number of shape- and size-related molecular descriptors is 8.

DescriptorShort name in header line of csv descriptor fileUnitReferences
Molecular diameterDiameter[Å][20]
Principal moment of inertia of 1st principal axisInertiaX[Da·Å2][21]
Principal moment of inertia of 2nd principal axisInertiaX[Da·Å2][21]
Principal moment of inertia of 3rd principal axisInertiaX[Da·Å2][21]
Molecular spanSpan[Å][22]
Molecular radius of gyrationRgyr[Å][22-23]
Molecular eccentricityEccentric[Å][21]
Molecular asphericityAspheric[Å][21]

Topological or 2D property-weighted autocorrelation descriptors

Topological or 2D property-weighted autocorrelation descriptors [24-25] are calculated from 0 - 10 topological distances (i.e., the number of bonds on the shortest path between two atoms), and sampled for each topological distance (11 distance bins). Thus, for each atom pair property a vector of 11 values (n) results.
The total number of 2D property-weighted autocorrelation descriptors is 88. The following table lists all 2D property-weighted autocorrelation descriptors.

Atom pair propertyShort name in header line of csv descriptor fileReferences
Identity, i.e., "1" for an atom2DACorr_Ident_n-
σ charge2DACorr_SigChg_n[10-11]
π charge2DACorr_PiChg_n[12-14]
Total charge2DACorr_TotChg_n[10-14]
σ electronegativity2DACorr_SigEN_n[10-11]
π electronegativity2DACorr_PiEN_n[12-14]
Lone-pair electronegativity2DACorr_LpEN_n[12-14]
Effective atom polarizability2DACorr_Polariz_n[5-8]

Spatial or 3D property-weighted autocorrelation descriptors

Spatial or 3D property-weighted autocorrelation descriptors [26-27] are calculated from 1 - 13 Å and sampled in steps of 1 Å (12 distance bins). Thus, for each atom pair property a vector of 12 values (n) results.
The total number of 3D property-weighted autocorrelation descriptors is 96. The following table lists all 3D property-weighted autocorrelation descriptors.

Atom pair propertyShort name in header line of csv descriptor fileReferences
Identity, i.e., "1" for an atom3DACorr_Ident_n-
σ charge3DACorr_SigChg_n[10-11]
π charge3DACorr_PiChg_n[12-14]
Total charge3DACorr_TotChg_n[10-14]
σ electronegativity3DACorr_SigEN_n[10-11]
π electronegativity3DACorr_PiEN_n[12-14]
Lone-pair electronegativity3DACorr_LpEN_n[12-14]
Effective atom polarizability3DACorr_Polariz_n[5-8]

References

  1. Atomic weights were taken from www.webelements.com and are currently implemented up to the atomic number of 109 (Mt, Meitnerium).
  2. Lipinski, C.A.; Lombardo, F.; Dominy, B.W.; Feeney, P.J. Experimental and Computational Approaches to Estimate Solubility and Permeability in Drug Discovery and Development Settings. Adv. Drug Delivery Rev. 199723, 3-25.
  3. Wang, R.; Gao, Y; Lai, L. Calculating Partition Coefficient by Atom-Additive Method. Perspect. Drug Discovery Des. 200019, 47-66.
  4. Ertl, P; Rohde, B.; Selzer, P. Fast Calculation of Molecular Polar Surface Area as a Sum of Fragment-Based Contributions and Its Application to the Prediction of Drug Tansport Properties. J. Med. Chem. 200043, 3714-3717.
  5. Gasteiger, J.; Hutchings, M.G. Empirical Models of Substituent Polarisability and their Application to Stabilisation Effects in Positively Charged Species. Tetrahedron Lett. 198324, 2537-2540.
  6. Gasteiger, J.; Hutchings, M.G. Quantitative Models of Gas-Phase Proton Transfer Reactions Involving Alcohols, Ethers and their Thio Analogs. Correlation Analyses Based on Residual Electronegativity and Effective Polarizability. J. Am. Chem. Soc. 1984106, 6489-6495.
  7. Kang, Y.K.; Jhon, M.S. Theor. Chim. Acta 198261, 41.
  8. Miller, K.J. Additivity Methods in Molecular Polarizability. J. Am. Chem. Soc. 1990112, 8533-8542.
  9. (a) Sadowski, J.; Gasteiger, J.; Klebe, G. Comparison of Automatic Three-Dimensional Model Builders Using 639 X-Ray Structures. J. Chem. Inf. Comput. Sci. 199434, 1000-1008.
  10. (b) CORINA by Molecular Networks GmbH, Erlangen, Germany.
  11. (a) Hinze, J.; Jaffe, H.H. J. Am. Chem. Soc. 196284, 540. (b) Hinze, J.; Jaffe, H.H. J. Am. Chem. Soc. 196385, 148. (c) Hinze, J.; Jaffe, H.H. J. Phys. Chem. 196367, 1501.
  12. (a) Gasteiger, J.; Marsili, M. A New Model for Calculating Atomic Charges in Molecules. Tetrahedron Lett. 197834, 3181-3184. (b) Gasteiger, J.; Marsili, M. Iterative Partial Equalization of Orbital Electronegativity - A Rapid Access to Atomic Charges. Tetrahedron 198036, 3219-3228. (c) Gasteiger, J.; Guillen, M.D. Extension of the Method of Iterative Partial Equalization of Orbital Electronegativity to Small Ring Systems. Tetrahedron 198339, 1331-1335.
  13. Bauerschmidt, S.; Gasteiger J. Overcoming the Limitations of a Connection Table Description: A Universal Representation of Chemical Species. J. Chem. Inf. Comput. Sci. 199737, 705-714.
  14. Streitwieser, A. Jr. Molecular Orbital Theory for Organic Chemists. John Wiley & Sons, Inc. New York, London: 1961.
  15. (a) Abraham, R.J.; Hudson, B. J. Comp. Chem. 19846, 562-570. (b) Abraham, R.J.; Hudson, B. J. Comp. Chem. 19856, 173-181. (c) Abraham, R.J.; Smith, P.E. J. Comp. Chem. 19879, 288-297.
  16. (a) Saller, H.; Gasteiger, J. Calculation of the Charge Distribution in Conjugated Systems by a Quantification of the Resonance Concept. Angew. Chem. Int. Ed. Engl. 198524, 687-689. (b) Saller, H.; Gasteiger, J. Berechnung der Ladungsverteilung in konjugierten Systemen durch eine Quantifizierung des Mesomeriekonzeptes. Angew. Chem. 198597, 699-701.
  17. (a) Yan, A.; Gasteiger, J. Prediction of Aqueous Solubility of Organic Compounds Based on a 3D Structure Representation. J. Chem. Inf. Comput. Sci. 200343, 429-434. (b) Yan, A.; Gasteiger, J.; Krug, M.; Anzali, S. Linear and Nonlinear Functions on Modeling the Aqueous Solubility of Organic Compounds by Two Structure Representation Methods. J. Comput.-Aided Mol. Design 200418, 75-87. (c) Schmid, B. Deriving a Linear Model for Predicting the Solubility Coefficient for Organic Molecules. Personal Communications 2005.
  18. Veber, D.F.; Johnson, S.R.; Cheng, H.-Y.; Smith, B.R.; Ward, K.W.; Kopple, K.D. Molecular Properties That Influence the Oral Bioavailability of Drug Candidates. J. Med. Chem. 200245 (12), 2615-2623.
  19. Hendrickson, J.B.; Huang, P.; Toczko, A.G. Molecular Complexity: A Simplified Formula Adapted to Individual Atoms. J. Chem. Inf. Comput. Sci. 198727, 63-67.
  20. Gasteiger, J; Jochum, C. An Algorithm for the Perception of Synthetically Important Rings. J. Chem. Inf. Comput. Sci. 197919, 43-48.
  21. Petitjean, M. Applications of the radius-diameter diagram to the classification of topological and geometrical shapes of chemical compounds. J. Chem. Inf. Comput. Sci. 199232, 331-337.
  22. Todeschini, R.; Consonni, V. Handbook of Molecular Descriptors. Wiley-VCH, Weinheim: 2000, Vol. 11.
  23. Volkenstein, M.V. Configurational Statistics of Polymeric Chains. Wiley-Interscience, New York: 1963.
  24. Tanford, C. Physical Chemistry of Macromolecules. Wiley, New York: 1961.
  25. (a) Moreau, G.; Broto, P. Nouv. J. Chim. 19804, 359-360. (b) Broto, P.; Moreau, G.; Vandycke, C. Eur. J. Med. Chem. Chim. Ther. 198419, 66-70.
  26. Bauknecht, H.; Zell, A.; Bayer, H.; Levi, P.; Wagener, M.; Sadowski, J.; Gasteiger, J. Locating Biologically Active Compounds in Medium-Sized Heterogeneous Datasets by Topological Autocorrelation Vectors: Dopamine and Benzodiazepine Agonists. J. Chem. Inf. Comput. Sci. 199636, 1205-1213.
  27. (a) Wagener, M.; Sadowski, J.; Gasteiger, J. Assessing the Similarity and Diversity of Combinatorial Libraries by Spatial Autocorrelation Functions and Neural Networks. Angew. Chem. Int. Ed. Engl.199534, 2674-2677. (b) Wagener, M.; Sadowski, J.; Gasteiger, J. Bewertung der Ähnlichkeit und Vielfalt von Verbindungsbibliotheken mit räumlichen Autokorrelationsvektoren und neuronalen Netzen.Angew. Chem. 1995107, 2892-2895.
  28. Teckentrup, A.; Briem, H.; Gasteiger, J. Mining High-Throughput Screening Data of Combinatorial Libraries: Development of a Filter to Distinguish Hits from Nonhits. J. Chem. Inf. Comput. Sci. 2004,44, 626-634.

Copyright statement

ADRIANA is a registered trademark owned by Molecular Networks GmbH, Erlangen, Germany in the Federal Republic of Germany. Other product names and company names may be trademarks or registered trademarks of their respective owners, in the Federal Republic of Germany and other countries. All rights reserved.

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