Torrey Pines Institute for Molecular Studies

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: Antigen & T cell. The organization has 2323 authors who have published 2217 publications receiving 112618 citations.

Identification of two novel, potent, low-liability antinociceptive compounds from the direct in vivo screening of a large mixture-based combinatorial library.

Abstract: Synthetic combinatorial methods now make it practical to readily produce hundreds of thousands of individual compounds, but it is clearly impractical to screen each separately in vivo. We theorized that the direct in vivo testing of mixture-based combinatorial libraries during the discovery phase would enable the identification of novel individual compounds with desirable antinociceptive profiles while simultaneously eliminating many compounds with poor absorption, distribution, metabolism, or pharmacokinetic properties. The TPI 1346 small-molecule combinatorial library is grouped in 120 mixtures derived from 26 functionalities at the first three positions and 42 functionalities at the fourth position of a pyrrolidine bis-cyclic guanidine core scaffold, totaling 738,192 compounds. These 120 mixtures were screened in vivo using the mouse 55°C warm water tail-withdrawal assay to identify mixtures producing antinociception. From these data, two fully defined individual compounds (TPI 1818-101 and TPI 1818-109) were synthesized. These were examined for antinociceptive, respiratory, locomotor, and conditioned place preference effects. The tail-withdrawal assay consistently demonstrated distinctly active mixtures with analgesic activity that was blocked by pretreatment with the non-selective opioid antagonist, naloxone. Based on these results, synthesis and testing of TPI 1818-101 and 1818-109 demonstrated a dose-dependent antinociceptive effect three to five times greater than morphine that was antagonized by mu- or mu- and kappa-opioid receptor selective antagonists, respectively. Neither 1818-101 nor 1818-109 produced significant respiratory depression, hyperlocomotion, or conditioned place preference. Large, highly diverse mixture-based libraries can be screened directly in vivo to identify individual compounds, potentially accelerating the development of promising therapeutics.

Multivariate Analysis of Functional Metagenomes

Abstract: Metagenomics is a primary tool for the description of microbial and viral communities. The sheer magnitude of the data generated in each metagenome makes identifying key differences in the function and taxonomy between communities difficult to elucidate. Here we discuss the application of seven different data mining and statistical analyses by comparing and contrasting the metabolic functions of 212 microbial metagenomes within and between 10 environments. Not all approaches are appropriate for all questions, and researchers should decide which approach addresses their questions. This work demonstrated the use of each approach: for example, random forests provided a robust and enlightening description of both the clustering of metagenomes and the metabolic processes that were important in separating microbial communities from different environments. All analyses identified that the presence of phage genes within the microbial community was a predictor of whether the microbial community was host-associated or free-living. Several analyses identified the subtle differences that occur with environments, such as those seen in different regions of the marine environment.

Electronic tracking tag programming is critical to data collection for behavioral time‐series analysis

Abstract: Electronic tracking tags are major tools of ecological research and management, but programming sophisticated tags can be challenging. We discovered that a common programming scheme can negatively affect the quality of tracks collected by Argos tags. Here we describe the problem and how it occurred. We then simulated a series of tracks with different data collection schemes to investigate how spatial precision and temporal frequency affect the overall quality of tracking data. Tracks were simulated using a two-state composite correlated random walk (CCRW). Tracks were simulated with two spatial scales, using parameters estimated from northern elephant seal (large scale) and California sea lion (small scale) tracking data. Onto each simulated track, observations of varying precision, frequency, and censoring were imposed. We then fit the CCRW in a state-space model (SSM) to the simulated observations in order to assess how data quality and frequency affected recovery of known behavioral state and location. We show that when movement scales are small, regular observations were critical to recover behavior and location. In addition, tracks with frequent regular locations (increasing N) overcame low spatial accuracy (e.g., Argos) to detect small-scale movement patterns, suggesting frequently collected Argos locations may be as good as infrequently collected GPS in some circumstances. From these results and our experience tracking animals generally, we produce a set of guidelines for those manufacturing, programming, and deploying electronic tracking tags to maximize the utility of the data they produce.

A novel class of inhibitors of peptide deformylase discovered through high-throughput screening and virtual ligand screening.

Abstract: Peptide deformylase (PDF) has been identified as a promising antibacterial and herbicide target. A structurally novel class of inhibitors containing a 2-thioxo-thiazolidin-4-one heterocycle substituted by an arylidene group at the 5-position and a hexanoic acid side chain at the 3-position was discovered independently via high-throughput screening and virtual ligand screening. Data mining and analogue synthesis established a structure−activity relationship for the side chain region that is consistent with the docked structure.