Literature DB >> 16797909

Integration of a rapid automated solubility classification into early validation of hits obtained by high throughput screening.

Thilo A Fligge1, Andrea Schuler.   

Abstract

Besides the structural verification of hits generated by high throughput screening also the determination of physicochemical properties is essential for an efficient lead identification. Especially solubility is fundamental for the correct planning and interpretation of experiments. We describe the set up of a fast automated solubility test within our existing workflow for hit validation to assure compound identity and purity. 384-Well plates with hit validation compound solution are used for analysis employing liquid chromatography and mass spectrometry (LC/MS). The remaining compound solution was used for a fast automated solubility classification employing a nephelometer integrated into a Tecan robotic workstation. Thereby 9000 compounds were classified as poorly- and well-soluble. This rapid and simple test does not require any additional amount of sample or sample processing than before but provides additional information on the hits at an early stage of lead identification. Validated by a more detailed nephelometric analysis for 500 out of the 9000 compounds in different buffer systems this simple test has shown to produce relevant data.

Mesh:

Substances:

Year:  2006        PMID: 16797909     DOI: 10.1016/j.jpba.2006.05.004

Source DB:  PubMed          Journal:  J Pharm Biomed Anal        ISSN: 0731-7085            Impact factor:   3.935


  5 in total

1.  The impact of data integrity on decision making in early lead discovery.

Authors:  Bernd Beck; Daniel Seeliger; Jan M Kriegl
Journal:  J Comput Aided Mol Des       Date:  2015-09-26       Impact factor: 3.686

2.  Interpreting physicochemical experimental data sets.

Authors:  Nicola Colclough; Mark C Wenlock
Journal:  J Comput Aided Mol Des       Date:  2015-06-09       Impact factor: 3.686

3.  Structure-activity studies of divin: an inhibitor of bacterial cell division.

Authors:  Maoquan Zhou; Ye-Jin Eun; Ilia A Guzei; Douglas B Weibel
Journal:  ACS Med Chem Lett       Date:  2013-09-12       Impact factor: 4.345

Review 4.  Applications of Deep-Learning in Exploiting Large-Scale and Heterogeneous Compound Data in Industrial Pharmaceutical Research.

Authors:  Laurianne David; Josep Arús-Pous; Johan Karlsson; Ola Engkvist; Esben Jannik Bjerrum; Thierry Kogej; Jan M Kriegl; Bernd Beck; Hongming Chen
Journal:  Front Pharmacol       Date:  2019-11-05       Impact factor: 5.810

5.  Hyperthermia Improves Solubility of Intravesical Chemotherapeutic Agents.

Authors:  Dominic C Grimberg; Ankeet Shah; Wei Phin Tan; Wiguins Etienne; Ivan Spasojevic; Brant A Inman
Journal:  Bladder Cancer       Date:  2020-12-14
  5 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.