Nonnucleoside reverse transcriptase inhibitors (NNRTIs) are potent inhibitors of human immunodeficiency virus type 1 (HIV-1); however, currently marketed NNRTIs rapidly select resistant virus, and cross-resistance within the class is extensive. A parallel screening strategy was applied to test candidates from a series of diarylpyrimidines against wild-type and resistant HIV strains carrying clinically relevant mutations. Serum protein binding and metabolic stability were addressed early in the selection process. The emerging clinical candidate, TMC125, was highly active against wild-type HIV-1 (50% effective concentration [EC 50 ] ‫؍‬ 1.4 to 4.8 nM) and showed some activity against HIV-2 (EC 50 ‫؍‬ 3.5 M). TMC125 also inhibited a series of HIV-1 group M subtypes and circulating recombinant forms and a group O virus. Incubation of TMC125 with human liver microsomal fractions suggested good metabolic stability (15% decrease in drug concentration and 7% decrease in antiviral activity after 120 min). Although TMC125 is highly protein bound, its antiviral effect was not reduced by the presence of 45 mg of human serum albumin/ml, 1 mg of ␣ 1 -acid glycoprotein/ml, or 50% human serum. In an initial screen for activity against a panel of 25 viruses carrying single and double reverse transcriptase amino acid substitutions associated with NNRTI resistance, the EC 50 of TMC125 was <5 nM for 19 viruses, including the double mutants K101E؉K103N and K103N؉Y181C. TMC125 also retained activity (EC 50 < 100 nM) against 97% of 1,081 recent clinically derived recombinant viruses resistant to at least one of the currently marketed NNRTIs. TMC125 is a potent next generation NNRTI, with the potential for use in individuals infected with NNRTI-resistant virus.Successful long-term treatment of human immunodeficiency virus type 1 (HIV-1) by antiretrovirals is often hindered by incomplete viral suppression and the resulting emergence of drug resistance. There is now widespread resistance to all available classes of antiretrovirals, and cross-resistance within classes is extensive, often severely limiting the treatment options available (17,20). Although currently marketed nonnucleoside reverse transcriptase inhibitors (NNRTIs) are highly selective and extremely potent, they rapidly select for resistant virus. Moreover, single mutations can lead to dramatic reductions in susceptibility, often to all available inhibitors within the class (2, 11). This broad cross-resistance prevents the consecutive use of currently marketed NNRTIs in treatment regimens (1). Next-generation agents with activity against NNRTI-resistant isolates would therefore offer new treatment options.To increase the likelihood of identifying new compounds active against NNRTI-resistant strains and that have interesting drug-like properties, we developed the following strategies. The structure-activity relationship, traditionally limited to activity against the wild-type virus, was expanded to include concurrent evaluation of several NNRTI-resistant strains. To facilitate...

BACKGROUND & AIMS-Irritable bowel syndrome (IBS) has been associated with mucosal dysfunction,, mild inflammation, and altered colonic bacteria. We used microarray expression profiling of sigmoid colon mucosa to assess whether there are stably expressed sets of genes that suggest there are objective molecular biomarkers associated with IBS.

This paper describes the general design and application of CerBeruS, a computer-based system for supporting the process of sequential screening. CerBeruS stands for cluster-based selection, with cluster analysis forming the pivotal part of the system. CerBeruS uses the Ward's clustering method for partitioning the data set to be screened into smaller, more homogeneous subsets. One representative is picked from each subset and suggested as a screening candidate. Although the number of compounds submitted to screening is most often driven by the capacity of the assay, CerBeruS provides a statistical measure that computes the optimal number of clusters in the data set. This measure forms a point of reference for all screening experiments. Different hierarchies of subsets are stored in an Oracle database. Information about the size and content of a cluster can be retrieved from this database via a Visual Basic application. How these components work together in the CerBeruS system is demonstrated on a large data set. In addition, we show that, using the statistical measure, one can find an optimal trade-off between screening effort and number of hits.

REALISIS is a software system for reagent selection, library design, and profiling, developed to fit the workflow of bench chemists and medicinal chemists. Designed to be portable, the software offers a comprehensive graphical user interface and rapid, integrated functionalities required for reagent retrieval and filtering, product enumeration, and library profiling. REALISIS is component-based, consisting of four main modules: reagent searching; reagent filtering; library enumeration; and library profiling. Each module allows the chemist to access specific functionalities and diverse filtering and profiling mechanisms. By implementing the entire process of reagent selection, library design, and profiling and by integrating all the necessary functionalities for this process, REALISIS cuts the time required to design combinatorial and noncombinatorial libraries from several days to a few hours.