Biomedical subjects

Gisbert Schneider

Publications and source records attributed to Gisbert Schneider.

6 recordsLinked to original sources

PubMed2003

Improved anaerobic use of arginine by Saccharomyces cerevisiae.

Anaerobic arginine catabolism in Saccharomyces cerevisiae was genetically modified to allow assimilation of all four rather than just three of the nitrogen atoms in arginine. This was accomplished by bypassing normal formation of proline, an unusable nitrogen source in the absence of oxygen, and causing formation of glutamate instead. A pro3 ure2 strain expressing a PGK1 promoter-driven PUT2 allele encoding Delta(1)-pyrroline-5-carboxylate dehydrogenase lacking a mitochondrial targeting sequence produced significant cytoplasmic activity, accumulated twice as much intracellular glutamate, and produced twice as much cell mass as the parent when grown anaerobically on limiting arginine as sole nitrogen source.

Anaerobiosis↗

PubMed2002

A virtual screening method for prediction of the HERG potassium channel liability of compound libraries.

A computer-based method has been developed for prediction of the hERG (human ether-à-go-go related gene) K(+)-channel affinity of low molecular weight compounds. hERG channel blockage is a major concern in drug design, as such blocking agents can cause sudden cardiac death. Various techniques were applied to finding appropriate molecular descriptors for modeling structure-activity relationships: substructure analysis, self-organizing maps (SOM), principal component analysis (PCA), partial least squares fitting (PLS), and supervised neural networks. The most accurate prediction system was based on an artificial neural network. In a validation study, 93 % of the nonblocking agents and 71 % of the hERG channel blockers were correctly classified. This virtual screening method can be used for general compound-library shaping and combinatorial library design.

Cation Transport Proteins↗

PubMed2002

Development of a virtual screening method for identification of "frequent hitters" in compound libraries.

A computer-based method was developed for rapid and automatic identification of potential "frequent hitters". These compounds show up as hits in many different biological assays covering a wide range of targets. A scoring scheme was elaborated from substructure analysis, multivariate linear and nonlinear statistical methods applied to several sets of one and two-dimensional molecular descriptors. The final model is based on a three-layered neural network, yielding a predictive Matthews correlation coefficient of 0.81. This system was able to correctly classify 90% of the test set molecules in a 10-times cross-validation study. The method was applied to database filtering, yielding between 8% (compilation of trade drugs) and 35% (Available Chemicals Directory) potential frequent hitters. This filter will be a valuable tool for the prioritization of compounds from large databases, for compound purchase and biological testing, and for building new virtual libraries.

Databases, Factual↗

PubMed2002

Virtual screening and fast automated docking methods.

Recent advances in high-throughput protein structure determination and in computational chemistry have refocused attention on virtual screening and fast automated docking methods. This review provides a brief introduction to the basic ideas and outlines computational tools currently used. We also provide several examples of where virtual screening has proved successful, highlighting the usefulness of the approach.

Combinatorial Chemistry Techniques↗

PubMed2002

Trends in virtual combinatorial library design.

Recent developments in combinatorial molecular design using virtual screening methods are summarised. These include similarity-based compound clustering techniques, structure-based docking and scoring, and fragment-based de novo design. Three major trends have been identified: i) the design of small target-focused compound libraries yielding activity-enriched sets of molecules; ii) advanced prediction methods for "drug-like" molecular properties complement activity predictions in the library design process, forming a multi-dimensional objective function; iii) "cherry picking" of selected products is increasingly used in lead generation and optimisation compared to purely educt-driven library design methods aiming at maximising structural diversity.

Algorithms↗

PubMedDate not supplied

Ligand-based combinatorial design of selective purinergic receptor (A2A) antagonists using self-organizing maps.

A virtual screening procedure based on a topological pharmacophore similarity metric and self-organizing maps (SOM) was developed and applied to optimizing combinatorial products functioning as P(1) purinergic receptor antagonists. The target was the human A(2A) receptor. A SOM was developed using a set of biologically tested molecules to establish a preliminary structure-activity relationship. A combinatorial library design was performed by projecting virtually assembled new molecules onto the SOM. A small focused library of 17 selected combinatorial products was synthesized and tested. On average, the designed structures yielded a 3-fold smaller binding constant ( approximately 33 vs approximately 100 nM) and 3.5-fold higher selectivity (50 vs 14) than the initial library. The most selective compound obtained revealed a 121-fold relative selectivity for A(2A) with K(i) (A(2A)) = 2.4 nM, and K(i) (A(1)) = 292 nM. This result demonstrates that it was possible to design a small, activity-enriched focused library with an improved property profile using the SOM virtual screening approach. The strategy might be particularly useful in projects in which structure-based design cannot be applied because of a lack of receptor structure information, for example, in the many projects aiming at finding new GPCR modulators.

Adenosine A2 Receptor Antagonists↗