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Disease Drug Development
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Drug Development (New Methods)

Torrey Pines Institute combines a unique set of tools in order to provide a robust and cost effective drug discovery program. These tools which include the Institute's proprietary "high density" combinatorial libraries, ligand and target based computational methods, as well as traditional medicinal chemistry which allows the implementation of drug or biochemical tests that are most relevant to the end goal. A key advantage to Torrey Pines Institute's unique drug discovery tools comes from the fact they can be used effectively in conjunction with a large range of tests, from ultra high throughput screening centers to multi end-point in vivo models.


  • Combinatorial Libraries
    Combinatorial Libraries Torrey Pines Institute's drug discovery program is centered on our proprietary "high density" combinatorial libraries, otherwise known as mixture-based combinatorial libraries. The utility of mixture-based combinatorial libraries has been demonstrated in more than 100 separate studies in which active compounds have been...
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  • Computational Chemistry
    Computational resources are very valuable to integrate chemistry knowledge with experimental biological data. This integration has become crucial in drug discovery and development as demonstrated by the several drugs currently on the market and in clinical trials that have been designed with the aid of computational methods. Working very closely...
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  • Drug Discovery
    Torrey Pines Institute (TPIMS) combines a unique set of tools in order to provide a robust and cost effective drug discovery program. These tools which include TPIMS' proprietary "high density" combinatorial libraries, ligand and target based computational methods, as well as traditional medicinal chemistry which allows the implementation of the...
    Read More...
  • Lead Discovery and Optimization
    The screening and deconvolution of Torrey Pines Institute' libraries leads to the rapid identification of lead individual compounds as well as information on structural analogs. Inherent in the deconvolution of the Torrey Pines Institute libraries is a certain amount of structure activity relationship ("SAR") data. This information alone or in conjunction...
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Extensive Reviews & Cited References

Extensive Reviews

I. Houghten, R. A.; Pinilla, C.; Giulianotti, M. A.; Appel, J. R.; Dooley, C. T.; Nefzi, A.; Ostresh, J. M.; Yu, Y.; Maggiora, G. M.; Medina-Franco, J. L.; Brunner, D.; Schneider, J. J. Comb. Chem 2008, 10, 3-19.
II. Pinilla, C.; Appel, J. R.; Borras, E.; Houghten, R. A. Nat Med 2003, 9, 118-122.
III. Houghten, R. A.; Pinilla, C.; Appel, J. R.; Blondelle, S. E.; Dooley, C. T.; Eichler, J.; Nefzi, A.; Ostresh, J. M. J. Med. Chem. 1999, 42, 3743-3778.

Cited References

1

Houghten, R. A.; Pinilla, C.; Blondelle, S. E.; Appel, J. R.; Dooley, C. T.; Cuervo, J. H. Nature 1991, 354, 84-86.

2

Vidal, A.; Nefzi, A.; Houghten, R. A. J. Org. Chem. 2001, 66, 8268-8272.

3

Apletalina, E.; Appel, J.; Lamango, N. S.; Houghten, R. A.; Lindberg, I. J. Biol. Chem. 1998, 273, 26589-26595.

4

Cameron, A.; Appel, J.; Houghten, R. A.; Lindberg, I. J. Biol. Chem. 2000, 275, 36741-36749.

5

Dooley, C. T. a. R. A. H. Biopolymers (Peptide Science) 2000, 51, 379-390.

6

Blondelle, S. E. a. K. L. Biopolymers (Peptide Sci.) 2000, 55, 85-87.

7

Borras, E.; Martin, R.; Judkowski, V.; Shukaliak, J.; Zhao, Y.; Rubio-Godoy, V.; Valmori, D.; Wilson, D.; Simon, R.; Houghten, R.; Pinilla, C. Journal of Immunological Methods 2002, 267, 79-97.

8

Houghten, R. A.; Pinilla, C.; Appel, J. R.; Blondelle, S. E.; Dooley, C. T.; Eichler, J.; Nefzi, A.; Ostresh, J. M. J. Med. Chem. 1999, 42, 3743-3778.

9

Pinilla, C.; Appel, J. R.; Borras, E.; Houghten, R. A. Nat Med 2003, 9, 118-122.

10

Houghten, R. A.; Pinilla, C.; Giulianotti, M. A.; Appel, J. R.; Dooley, C. T.; Nefzi, A.; Ostresh, J. M.; Yu, Y.; Maggiora, G. M.; Medina-Franco, J. L.; Brunner, D.; Schneider, J. J. Comb. Chem 2008, 10, 3-19.

11

Medina-Franco, J. L.; Martínez-Mayorga, K.; Giulianotti, M. A.; Houghten, R. A.; Pinilla, C. Curr. Comput.- Aided Drug Des. 2008, 4, 322-333.

12

Singh, N.; Guha, R.; Giulianotti, M.; Pinilla, C.; Houghten, R.; Medina-Franco, J. L. J. Chem. Inf. Model. 2009, 49, 1010-1024.

13

Singh, N.; Dueñas-González, A.; Lyko, F.; Medina-Franco, J. L. ChemMedChem 2009, 4, 792-799.

14

Armishaw, C. J.; Singh, N.; Medina-Franco, J. L.; Clark, R. J.; Scott, K. C. M.; Houghten, R. A.; Jensen, A. A. J. Biol. Chem. 2010, 285, 1809-1821.

15

“Hernández-Campos, A.; Velázquez-Martínez, I.; Castillo, R.; López-Vallejo, F.; Jia, P.; Yu, Y.; Giulianotti, M. A.; Medina-Franco, J. L. Chem. Biol. Drug Des. 2010, 76, 269-276.”

16

Medina-Franco, J. L.; Giulianotti, M. A.; Yu, Y.; Shen, L.; Yao, L.; Singh, N. Bioorg. Med. Chem. Lett. 2009, 19, 4634-4638.

17

Kuck, D.; Singh, N.; Lyko, F.; Medina-Franco, J. L. Bioorg. Med. Chem. 2010, 18, 822-829.