An effective tool for homogeneous assays using a simple robot arm with Stackers-TRISTAN.

The Twister & RapidPlate Integrated System by TANabe, or TRISTAN, consists of a 96-channel dispenser (RapidPlate 96), a plate reader (V-MAX), and a simple robot arm (Twister). We developed TRISTAN for effectively conducting a homogeneous assay. Although this system accommodates fewer than 20 microplates, it has several advantages over conventional robotic systems for high-throughput screening in the following aspects: parameter setting, running time, hardware errors, manpower, and cost-effectiveness. The system proved to be effective and efficient for homogeneous assays.

A Practical Estimation Method for Analyzing Adverse Drug Reactions Using Data Mining.

This study aimed to determine the potentially severe chemical properties of drugs that can cause adverse drug reactions (ADRs) such as erythema multiforme (EM), Stevens-Johnson syndrome (SJS), and toxic epidermal necrolysis (TEN) by using a data mining method. The study data were extracted from the Adverse Event Reporting System database of the FDA. EM was considered a mild reaction, and SJS and TEN were considered severe reactions. In this study, a new concept termed the "risk of aggravation" (ROA) was defined as whether a certain drug is more likely to cause severe adverse reactions than mild ones. Partial least squares and logistic regression analysis were applied using binary response variable ROAs. These analyses correctly predicted 50 of the 72 drugs associated with SJS and/or TEN and 28 of the 38 drugs associated with EM using binary chemical descriptors that are the same as those using the metric chemical descriptors.

Ordinal classification using Comparative Molecular Field Analysis.

Comparative Molecular Field Analysis (CoMFA) is most widely used as one of the 3-dimensional QSAR (3D-QSAR) methods to identify the relationship between chemical structure and biological activity. Conventional CoMFA requires at least 3 orders of experimental data, such as IC50 and Ki, to obtain a good model, although practically there are many screening assays where biological activity is measured only by a rating scale. Hence, rating classification-oriented CoMFA coupled with ordinal logistic regression has been developed, and its predictive ability and 3D graphical analysis ability have been investigated. As a result, this novel CoMFA (Logistic CoMFA) has been found to be more robust than conventional CoMFAs in both predictive and 3D graphical analysis abilities. Furthermore, Logistic CoMFA is useful since it can provide the probability of each rank.

Enhancement of ordinal CoMFA by ridge logistic partial least squares.

Conventional comparative molecular field analysis (CoMFA) requires at least 3 orders of experimental data, such as IC 50 and K i, to obtain a good model, although practically there are many screening assays where biological activity is measured only by rating scale. To improve three-dimensional quantitative structure-activity relationship (3D-QSAR) analysis, we developed in this study a modified ordinal classification-oriented CoMFA using partial-least-squares generalized linear regression and ridge estimation. The modified Logistic CoMFA was validated using a corticosteroid binding globulin receptor binding data set, a benchmark for 3D-QSAR, and an acetylcholine esterase inhibitor data set. Our results show that modification of Logistic CoMFA enhanced both prediction accuracy and 3D graphical analysis. In addition, the 3D graphical analysis of the modified Logistic CoMFA was much improved. This improvement resulted in more accurate information on the binding mode between proteins and ligands than in the case of conventional CoMFA.