Azaadamantane benzamide 5-HT4 agonists: gastrointestinal prokinetic SC-54750

Azaadamantanone 1 was converted to a series of aminoazaadamantane benzamides 9a-d, which were profiled for serotonin receptor activity. Aminomethylazaadamantane SC-54750 is a potent 5-HT(4) agonist and 5-HT(3) antagonist with in vivo efficacy in gastroparesis models and also inhibits cisplatin-induced emesis.     

Design and synthesis of conformationally constrained 3-(N-alkylamino)propylphosphonic acids as potent agonists of sphingosine-1-phosphate (S1P) receptors

A series of conformationally constrained 3-(N-alkylamino)propylphosphonic acids were systematically synthesized and their activities as S1P receptor agonists were evaluated. Several pyrrolidine and cyclohexane analogs had S1P receptor profiles comparable to the acyclic lead compound, 3-(N-tetradecylamino)propylphosphonic acid (3), lowered circulating lymphocytes in mice after iv administration and were thus identified as being suitable for further investigations.     

The discovery of 3-(N-alkyl)aminopropylphosphonic acids as potent S1P receptor agonists

3-(N-Alkyl)aminopropylphosphonic acids are potent agonists of four of the five known sphingosine-1-phosphate (S1P) receptor subtypes.     

Synthesis and activity of 1-aryl-1'-imidazolyl methyl ethers as non-thiol farnesyltransferase inhibitors

A series of imidazole-containing methyl ethers (4-5) have been designed and synthesized as potent and selective farnesyltransferase inhibitors (FTIs) by transposition of the D-ring to the methyl group on the imidazole of the previously reported FTIs 3. Several compounds such as 4h and 5b demonstrate superior enzymatic activity to the current benchmark compound tipifarnib (1) with IC(50) values in the lower subnanomolar range, while maintaining excellent cellular activity comparable to tipifarnib. The compounds are characterized as being simple, easier to make, and possess no chiral center involved.     

Synthesis and GABA receptor potency of 3-thiomethyl-4-(hetero)aryl-5-amino-1-phenylpyrazoles

A convenient synthetic route to novel 4-arylpyrazoles is described. The potential for insecticidal activity through GABA channel blockage by this series of compounds, as well as their selectivity for insect versus mammalian receptors, are explored through in vitro and in vivo assays.     

A graph theoretical approach for predicting common RNA secondary structure motifs including pseudoknots in unaligned sequences

MOTIVATION: RNA structure motifs contained in mRNAs have been found to play important roles in regulating gene expression. However, identification of novel RNA regulatory motifs using computational methods has not been widely explored. Effective tools for predicting novel RNA regulatory motifs based on genomic sequences are needed. RESULTS: We present a new method for predicting common RNA secondary structure motifs in a set of functionally or evolutionarily related RNA sequences. This method is based on comparison of stems (palindromic helices) between sequences and is implemented by applying graph-theoretical approaches. It first finds all possible stable stems in each sequence and compares stems pairwise between sequences by some defined features to find stems conserved across any two sequences. Then by applying a maximum clique finding algorithm, it finds all significant stems conserved across at least k sequences. Finally, it assembles in topological order all possible compatible conserved stems shared by at least k sequences and reports a number of the best assembled stem sets as the best candidate common structure motifs. This method does not require prior structural alignment of the sequences and is able to detect pseudoknot structures. We have tested this approach on some RNA sequences with known secondary structures, in which it is capable of detecting the real structures completely or partially correctly and outperforms other existing programs for similar purposes. AVAILABILITY: The algorithm has been implemented in C++ in a program called comRNA, which is available at http://ural.wustl.edu/softwares.html     

The gene ontology categorizer

The Gene Ontology Categorizer, developed jointly by the Los Alamos National Laboratory and Procter & Gamble Corp., provides a capability for the categorization task in the Gene Ontology (GO): given a list of genes of interest, what are the best nodes of the GO to summarize or categorize that list? The motivating question is from a drug discovery process, where after some gene expression analysis experiment, we wish to understand the overall effect of some cell treatment or condition by identifying 'where' in the GO the differentially expressed genes fall: 'clustered' together in one place? in two places? uniformly spread throughout the GO? 'high', or 'low'? In order to address this need, we view bio-ontologies more as combinatorially structured databases than facilities for logical inference, and draw on the discrete mathematics of finite partially ordered sets (posets) to develop data representation and algorithms appropriate for the GO. In doing so, we have laid the foundations for a general set of methods to address not just the categorization task, but also other tasks (e.g. distances in ontologies and ontology merger and exchange) in both the GO and other bio-ontologies (such as the Enzyme Commission database or the MEdical Subject Headings) cast as hierarchically structured taxonomic knowledge systems.