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Institution

Torrey Pines Institute for Molecular Studies

NonprofitSan Diego, California, United States
About: Torrey Pines Institute for Molecular Studies is a nonprofit organization based out in San Diego, California, United States. It is known for research contribution in the topics: T cell & Antigen. The organization has 2323 authors who have published 2217 publications receiving 112618 citations.


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TL;DR: The power of synthetic mixture-based combinatorial libraries lies in their ability to accelerate the acquisition of information regarding specific functionalities at each variable position in the library that determines the activity of a specific chemical scaffold or pharmacophore.
Abstract: Since its inception more than 20 years ago with highthroughput parallel synthesis for oligonucleotides and peptides, synthetic combinatorial methods have fundamentally advanced the ability to synthesize and screen large numbers of compounds because of improvements made in technology, instrumentation, and library design strategies. This discipline was readily accepted initially and is now an embedded component of the drug discovery process worldwide. While there are a range of combinatorial approaches, the use of mixture-based libraries made up of tens of thousands to billions of compounds is the approach that enables the most rapid and economical acquisition of chemical and biological information. Mixture-based libraries represent powerful tools that can be used for the identification of active individual compounds for a wide range of important targets, as reviewed. In the past decade, such approaches have been expanded to include the synthesis of low molecular weight acyclic and heterocyclic compounds. As with most innovations, synthetic combinatorial methods developed for the synthesis and screening of mixture-based libraries were slow to gain acceptance because of the conceptual distance between these approaches and the traditional methods previously used in the pharmaceutical industry. This was, and is, especially true for mixture-based libraries composed of tens of thousands to billions of different compounds, but such methods are now being used by an increasing number of groups for the identification of highly active, novel compounds in research and drug discovery programs. Mixture-based libraries are systematically arranged mixtures of synthetic compounds having both defined and mixture positions of diversity. This permits information to be gathered regarding both the activity and importance of every functionality at each position of the library. Post synthetic chemical modification of such existing mixturebased libraries using the “libraries from libraries” approach now enables the ever-increasing generation of low molecular weight compounds. Thus, for the last 16 years, we have successfully used this approach for the design and the generation of a range of peptidomimetic and small molecule libraries from resin-bound polyamides. We have also used this approach combining solidand solution-phase synthesis methods for the synthesis of a nitrosamine library and a platinum tetraamine coordination complex library. The power of synthetic mixture-based combinatorial libraries lies in their ability to accelerate the acquisition of information regarding specific functionalities at each variable position in the library that determines the activity of a specific chemical scaffold or pharmacophore. Another advantage of mixture-based libraries resides in the very high densities of compounds that can be synthesized in narrow areas of chemical space. When compared to existing high-throughput screening (HTS) programs, in which tens of thousands of individual compounds are screened against therapeutically important targets, millions of compounds formatted as mixtures can be examined using substantially less material and at much lower time/labor economics than if these same mixture-based diversities were made and screened as individual compounds. This unique combinatorial library approach can be applied to virtually any existing bioassay for the identification of novel ligands. For example, a novel, highly active tetrapeptide agonist for the κ-opioid receptor was identified from a positional scanning library of 6.25 * To whom correspondence should be addressed. Phone: 858-455-3805. Fax: 858-455-3804. E-mail: rhoughten@tpims.org. † Torrey Pines Institute for Molecular Studies. ‡ University of Arizona. § PsychoGenics, Inc. | Carnegie Mellon University. ⊥ Current address: College of Pharmaceutical Science, Zijin Campus, Zhejiang University, Hangzhou 310058, P. R. China. J. Comb. Chem. 2008, 10, 3–19 3

116 citations

Journal ArticleDOI
TL;DR: Time-domain modeling approaches to the sea-surface scattering problem are described and two alternatives are formulated, relatively simple using ray theory and a ray-based formulation of the Helmholtz integral equation with a time-domain Kirchhoff approximation.
Abstract: Solutions to ocean acoustic scattering problems are often formulated in the frequency domain, which implies that the surface is “frozen” in time. This may be reasonable for short duration signals but breaks down if the surface changes appreciably over the transmission time. Frequency domain solutions are also impractical for source-receiver ranges and frequency bands typical for applications such as acoustic communications (e.g. hundreds to thousands of meters, 1–50kHz band). In addition, a driving factor in the performance of certain acoustic systems is the Doppler spread, which is often introduced from sea-surface movement. The time-varying nature of the sea surface adds complexity and often leads to a statistical description for the variations in received signals. A purely statistical description likely limits the insight that modeling generally provides. In this paper, time-domain modeling approaches to the sea-surface scattering problem are described. As a benchmark for comparison, the Helmholtz inte...

116 citations

Journal ArticleDOI
TL;DR: It is found that common sequence variations in a region in and around MECP2 show association with structural brain size measures in 2 independent cohorts, a discovery sample from the Thematic Organized Psychosis research group, and a replication samples from the Alzheimer's Disease Neuroimaging Initiative.
Abstract: The gene MECP2 is a well-known determinant of brain structure. Mutations in the MECP2 protein cause microencephalopathy and are associated with several neurodevelopmental disorders that affect both brain morphology and cognition. Although mutations in MECP2 result in severe neurological phenotypes, the effect of common variation in this genetic region is unknown. We find that common sequence variations in a region in and around MECP2 show association with structural brain size measures in 2 independent cohorts, a discovery sample from the Thematic Organized Psychosis research group, and a replication sample from the Alzheimer's Disease Neuroimaging Initiative. The most statistically significant replicated association (P < 0.025 in both cohorts) involved the minor allele of SNP rs2239464 with reduced cortical surface area, and the finding was specific to male gender in both populations. Variations in the MECP2 region were associated with cortical surface area but not cortical thickness. Secondary analysis showed that this allele was also associated with reduced surface area in specific cortical regions (cuneus, fusiform gyrus, pars triangularis) in both populations.

116 citations

Journal ArticleDOI
TL;DR: A number of new antimicrobial and/or antifungal compounds have been successfully identified from pools of millions of other compounds.

116 citations

Journal ArticleDOI
TL;DR: The results reveal considerable overexpression of IL-1β, IL-10 and IFNγ transcripts in SLE-prone MRL-lprlpr (MRLl) and BXSB male (BXSBm) mice, but with some strain differences, pointing to certain cytokines as potential targets for immunotherapy in lupus.

115 citations


Authors

Showing all 2327 results

NameH-indexPapersCitations
Eric J. Topol1931373151025
John R. Yates1771036129029
George F. Koob171935112521
Ian A. Wilson15897198221
Peter G. Schultz15689389716
Gerald M. Edelman14754569091
Floyd E. Bloom13961672641
Stuart A. Lipton13448871297
Benjamin F. Cravatt13166661932
Chi-Huey Wong129122066349
Klaus Ley12949557964
Nicholas J. Schork12558762131
Michael Andreeff11795954734
Susan L. McElroy11757044992
Peter E. Wright11544455388
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
20235
202210
202153
202060
201950
201842