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.
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 identified. These studies have been carried out by more than 50 separate research groups. Novel enzyme inhibitors agonists and antagonists to specific receptors, antimicrobial, antifungal and antiviral compounds, and B and T cell epitopes have been identified from such libraries, and have been extensively reviewed.
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 with experimental groups in synthetic chemistry and biology, computational methods help to create models that in turn are used to generate hypothesis and make predictions. A major goal is to help make decisions in drug design and discovery projects.
The research areas of Drs. Medina-Franco and Martinez-Mayorga include, but are not limited to:
- Computer-Aided Drug Design (CAAD)
- Molecular Modeling
- Quantum Chemistry
- Virtual Screening
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 assay or assays (drug or biochemical tests) that are most relevant to the end goal. A key advantage to TPIMS' unique drug discovery tools comes from the fact they can be used effectively in conjunction with a large range of assays, from ultra high throughput screening centers through to multi end-point in vivo models.
Additionally the TPIMS platform accommodates a high degree of flexibility in the drug discovery process maximizing any level of knowledge related to the biological system under study. The figure below illustrates that TPIMS' goal is to discover clinically viable candidates by following a path that is flexible, iterative and state of the art.
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 with prior knowledge of the target(s) and/or additional leads is used to optimize the current leads.
When specific information is known about the target from crystallography or NMR studies, three dimensional models can be used to optimize leads. For example, leads derived from our libraries and other compound collections can be "docked" into the model targets to both identify putative binding modes as well as identify opportunities for increasing activity. As an example, in previous studies using docking models obtained with small molecules and protein kinases specific modifications to leads were identified. These structural modifications were designed to improve activity by including nitrogen atoms at specific positions in order to make hydrogen bonds with the target.
Another use of docking approaches is the virtual or in silico screening of synthetic combinatorial libraries and other compound collections. Using this approach we have identified novel protein kinase B and DNA metiltransferase inhibitors as potential therapeutic agents for the treatment of cancer. The outcome of such calculation is to predict what molecules within a library or collection are most and least likely to be active with a given receptor. Docking different combinatorial libraries that differ in the core scaffold with the same target enables the prediction of what library is the most likely to have activity. This process can be seen as a docking-based scaffold ranking and can be used to complement our traditional approach.
Whether the leads and structural analogs are derived solely from the screening of Torrey Pines Institute' libraries or additional information is known from others sources, the information can be used to identify and optimize the leads from a ligand perspective. For example, active leads can be overlayed on top of each other to identify key common features (Figure below). This information can be used to aid in scaffold hopping and in in silico screening of other TPMIS libraries as well as other compound collections.
Additionally novel computational strategies are in constant development to speed up in silico screening of compound libraries. Figure below shows how after applying a dynamic clustering protocol a reduced number of conformers is obtained while maintaining a biologically relevant ensemble.
Individual Compounds Synthesis
Torrey Pines Institute possesses the capability to rapidly synthesize, purify and characterize (by LCMS and NMR) any individual compound contained in the libraries as well as structural analogs in quantities needed for any secondary lead confirmation assays. This capability is due to the fact that the synthetic schemes have already been developed and optimized when the library was developed. Thus, this ability facilitates the opportunity to execute necessary experiments before entering clinical trials.