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Rajeshwar P.  Verma 

Corwin  Hansch

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Development of QSAR models using C-QSAR program: a regression program that has dual databases of over 21,000 QSAR models

The interest in the application of quantitative structure-activity relationships has steadily increased in recent decades because it has repeatedly proven itself to be a low-cost, high-return investment. Potential use of QSAR models for screening of chemical databases or virtual libraries before their synthesis appears equally attractive to chemical manufacturers, pharmaceutical companies and government agencies. In the present protocol, we describe the use of C-QSAR program, a regression program used in the development of QSAR models for drug designers \(especially for those who do not have extensive experience in statistics), which handles linear, parabolic and bi-linear equations with various transformation of variables, and has &#x2018;jack-knifing&#x2019; capability on all types of equations. The program has a very user-friendly method of data entry as well as of verification of structures and parameters. Auto-loading of preferred parameters is a time-saving feature of C-QSAR program. C-QSAR also produces a variety of 2-D graphs as output.





C-QSAR<sup>1</sup> is a regression program used in the development of QSAR models for drug designers \(especially for those who do not have extensive experience in statistics), which handles linear, parabolic and bi-linear equations with various transformation of variables, and has &#x2018;jack-knifing&#x2019; capability on all types of equations. The program has a very user-friendly method of data entry as well as of verification of structures and parameters. Auto-loading of preferred parameters is a time-saving feature of C-QSAR program. It also produces a variety of 2-D graphs as output. The C-QSAR program has dual databases of over 21,000 QSAR equations relating bio- and physico-chemical activities to structural parameters. Presently, BIO contains 12,950+ and PHYS 8,900+ equations. This is valuable for the users to validate new QSAR equations as they are being developed that is to see if the emerging structure-activity relationship bears a resemblance to others with known mechanisms. There are a number of commercial and free software programs available, which may be used to calculate descriptors and/or develop a QSAR model and are listed in **Table 1**. In C-QSAR program, the information associated with each data set, which is either in biological \(BIO) or physical \(PHYS) database, has been shown in **Table 2**.

&#x25A0; Modern personal computer \(Operating system should be Windows or Macintosh)


&#x25A0; Reflection for ReGIS Graphics \(It is a terminal emulation program for Windows that allows any PC user to access a Unix or OpenVMS system, emulating terminals ranging from VT52 to VT400, WYSE to UNISYS).


&#x25A0; Versa Term Pro \(It is for text and color graphics program for Macintosh, emulating DEC VT220 and Tektronix terminals, with automatic switching between them.


&#x25A0; C-QSAR Program \(see EQUIPMENT SETUP)





**Equipment Setup**





&#x25A0; C-QSAR Program: The details about the C-QSAR package are available at "http://www.biobyte.com/bb/prod/cqsar.html":http://www.biobyte.com/bb/prod/cqsar.html and their installation instructions at


"http://www.biobyte.com/bb/prod/qsarinstall.pdf":http://www.biobyte.com/bb/prod/qsarinstall.pdf. 


&#x25A0; For Table 1-4, the classification of C-QSAR program, and the details about the physicochemical parameters, please see the attached pdf \(pages 44-58).

1. C-QSAR Program, BioByte Corp., 201W. 4th st., Suit 204, Claremont, CA 91711, USA. www.biobyte.com
  2. Hansch, C., Hoekman, D., Leo, A., Weininger, D. &amp; Selassie, C.D. Chem-bioinformatics: Comparative QSAR at the interface between chemistry and biology. _Chem. Rev._ **102**, 783-812 \(2002). 
  3. Hansch, C. Hoekman, D. &amp; Gao, H. Comparative QSAR: Toward a deeper understanding of chemicobiological interactions. _Chem. Rev._ **96**, 1045-1075 \(1996).
  4. Hansch, C. &amp; Leo, A. Exploring QSAR: Fundamentals and Applications in Chemistry and Biology, American Chemical Society, Washington, D.C. \(1995).
  5. Hansch, C. Leo, A. &amp; Taft, R.W. A survey of Hammett substituent constants and resonance and field parameters. _Chem. Rev._ **91**, 165-195 \(1991).
  6. Schultz, T.W. &amp; Cronin, M.T.D.   Response-Surface Analyses for Toxicity to Tetrahymena pyriformis: Reactive Carbonyl-Containing Aliphatic Chemicals. _J. Chem. Inf. Comput. Sci._  **39**, 304-309 \(1999). 
  7. Zhang, L., Gao, H., Hansch, C. &amp; Selassie, C.D. Molecular orbital parameters and comparative QSAR in the analysis of phenol toxicity to leukemia cells. _J. Chem. Soc. Perkin Trans_ **2**,  2553-2556 \(1998). 
  8. Hu, J. Eriksson, L., Bergman, A., Jakobsson, E., Kolehmainen, E., Knuutinen, J., Suontamo, R. &amp; Wei, X. Molecular orbital studies on brominated diphenyl ethers. Part II-reactivity and quantitative structure-activity \(property) relationships.  _Chemosphere_ **59**,1043-1057\(2005).
  9. Hansch, C., Maloney, P.P., Fujita, T. &amp; Muir, R.M. Correlation of biological activity of phenoxyacetic acids with Hammett substituent constants and partition coefficients. _Nature_ **194**, 178-180 \(1962).
  10. Leo, A.J.  Calculating log Poct from structures.  _Chem. Rev._ **93**, 1281-306 \(1993).
  11. Leo, A.J. &amp; Hansch, C. Role of hydrophobic effects in mechanistic QSAR.   _Perspect. Drug Discovery Des._ **17**, 1-25 \(1999)
  12. Cramer III, R.D., Bunce, J.D., Patterson, D.E. &amp; Frank, I.E. Cross validation, Bootstrapping and partial least squares compared with multiple regression in conventional QSAR studies.  _Quant. Struct.-Act. Relat._ **7**, 18-25 \(1988). 
  13. Weininger, D. SMILES, a chemical language and information system.1. Introduction to methodology and encoding rules.  _J. Chem. Inf. Comput. Sci._  **28**, 31-36 \(1988).
  14. Golbraikh, A. &amp; Tropsha, A.  Beware of q2\! _J. Mol. Graph. Modl._ **20**, 269-276 \(2002).
  15. Wold, S. Validation of QSAR&#x2019;s. _Quant. Struct.-Act. Relat._ **10**, 191-193 \(1991).

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Computational biology and bioinformatics

Method Article

Development of QSAR models using C-QSAR program: a regression program that has dual databases of over 21,000 QSAR models

Rajeshwar P. Verma , Corwin Hansch

Rajeshwar P. Verma

Department of Chemistry, Pomona College, California 91711, USA.

Corresponding Author

Corwin Hansch

Department of Chemistry, Pomona College, California 91711, USA.

DOI:

10.1038/nprot.2007.125

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Development of QSAR models using C-QSAR program: a regression program that has dual databases of over 21,000 QSAR models

Rajeshwar P. Verma , Corwin Hansch

Rajeshwar P. Verma

Department of Chemistry, Pomona College, California 91711, USA.

Corresponding Author

Corwin Hansch

Department of Chemistry, Pomona College, California 91711, USA.

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