[Difficulties in the differential diagnosis of proteinuria during pregnancy].

Even during normal pregnancy, significant morphological, functional and hemodynamic changes take place in the kidneys, resulting in a slightly increased proteinuria. However, an abnormal increase, especially if accompanied by hypertension or impaired renal function, requires close maternal and fetal follow-up, as it may predict severe perina-tal complications. Differential diagnosis of proteinuria is diverse, and the primary consideration in clarifying the etiol-ogy is to differentiate between preeclampsia and other possible primary kidney disease.

Enhanced hit-to-lead process using bioanalogous lead evolution and chemogenomics: application in designing selective matrix metalloprotease inhibitors.

The authors describe an innovative approach for designing novel inhibitors. This approach effectively integrates the emerging chemogenomics concept of target-family-based drug discovery with bioanalogous design strategies, including privileged structures, molecular frameworks as well as bioisosteric and bioanalogous/isofunctional modifications. The authors applied this method in the design of selective inhibitors of matrix metalloproteases (MMPs), also referred to as matrixins, on the basis of a unique analysis of the ligand-target knowledge base, the 'matrixinome'.

Explicit Diversity Index (EDI): a novel measure for assessing the diversity of compound databases.

A novel diversity assessment method, the Explicit Diversity Index (EDI), is introduced for druglike molecules. EDI combines structural and synthesis-related dissimilarity values and expresses them as a single number. As an easily interpretable measure, it facilitates the decision making in the design of combinatorial libraries, and it might assist in the comparison of compound sets provided by different manufacturers.

A neural network based classification scheme for cytotoxicity predictions:Validation on 30,000 compounds.

Elimination of cytotoxic compounds in the early phases of drug discovery can save substantial amounts of research and development costs. An artificial neural network based approach using atomic fragmental descriptors has been developed to categorize compounds according to their in vitro human cytotoxicity. Fragmental descriptors were obtained from the Atomic7 linear logP calculation method implemented in Pallas PrologP program.

A neural network based prediction of octanol-water partition coefficients using atomic5 fragmental descriptors.

An artificial neural network based approach using Atomic5 fragmental descriptors has been developed to predict the octanol-water partition coefficient (logP). We used a pre-selected set of organic molecules from PHYSPROP database as training and test sets for a feedforward neural network. Results demonstrate the superiority of our non-linear model over the traditional linear method.