Focused libraries by Vitas-M Laboratory

Solutions

You can download currently obtained data, including: description of virtual screening experiments, structures of protein targets and active ligands.

HIV protease.
Leukotriene A4 hydrolase.
HMG-CoA reductase.
Dihydrofolate reductase.
Dihydroorotate dehydrogenase.
Phospholipase A2.
Beta-lactamase.

Estrogen receptor α.
Estrogen receptor β.
Farnesoid X receptor.
Glucocorticoid receptor.
Liver X receptor α.
Liver X receptor β.
Mineralocorticoid receptor.
PPAR-α.
PPAR-γ.
PPAR-δ.
Thyroid receptor β.
Vitamin D receptor.

Androgen receptor.
Retinoic acid α.
Retinoic acid γ.
Thyroid hormone α.

Acetylcholinesterase.
Retinoic acid β.
Retinoid X α.
Retinoid X β.
Adrenaline β2 receptor.
EGFR.
Factor Xa.
mGluR1 antagonists.
mGluR3 agonists.
NMDA antagonists.
Orotidine-5’-P decarboxylase.
Protein tyrosine phosphatase β.
Thrombin.

Focused libraries by Moltech and Vitas-M Laboratory

MolTech Ltd and Vitas-M Laboratory, one of the world-leading suppliers of compound libraries for drug discovery research, cooperate to produce focused libraries of compounds for major therapeutic targets. Focused libraries represent collections of 4000 compounds each, selected by Lead-Finder from the STK library of 300000 compounds by Vitas-M Laboratory. About 30 focused libraries covering major therapeutic targets including kinases, proteases, phosphatases, phospholipases, various hydrolases and oxidoreductases, nuclear hormone receptors, GPCRs and others are currently available and the work keeps going on. Elaboration of novel focused libraries for particular targets can be performed on demand.

The process of focused library design includes three stages:

Virtual screening of the entire STK library against therapeutic target model using Lead-Finder and rank-ordering of all compounds according to predicted VS-score.
Validation of the screening results by docking and calculating VS-score for a set of active ligands for the particular target (extracted from the public domain). After all compounds (including active ligands and STK library) are rank-ordered according to VS-score, the corresponding scoring function of Lead-Finder is re-optimized to give highest score (enrichment) with respect to active ligands. Re-optimization (or training) procedure implies semi-automatic adjustment of energy scaling coefficients of Lead-Finder VS-scoring function.
Repeat of STK library rank-ordering according to target-optimal scoring function, and selection of top-scored compounds to comprise the desired focused library.

To make focused library construction more robust representative sets (normally counting several tens) of active compounds were extracted from the public domain for each target. In cases where additional convincing information about ligand physicochemical properties or crucial protein-ligand interactions (hydrogen bonds) was available, additional filters were applied along with VS-score rank-ordering; description of such procedures (if relevant) is provided for each target separately.

For each focused library descriptions of the corresponding target, its therapeutic and market significance are supplied along with benchmarking results achieved by Lead-Finder (with respect to known active ligands). Additionally, a «demo» sets of compounds predicted as binders for particular target are provided (along with target structure model) for visualization and further assessment purposes.