UPDATE in english too :DCX proudly announce about a new advisor.
DCX is growing and supported by Advisor for helping the project.
Andrey Voronkov -
Co-founder of SONM Andre Voronkov is a Scientific researcher, working in the field of computational chemistry, chemoinformatics and medicinal chemistry. \
– PhD degree in bioorganic chemistry and biochemistry
– The completed projects include full-scale drug development of preclinical anti-cancer drug candidates in collaboration with Novo Nordisk and Genentech companies.
Areas of competence include preclinical drug discovery, ADME/Tox optimization, molecular modeling and medicinal chemistry. Expertise in all aspects of chemoinformatics, molecular modeling and drug design. Expertise with virtual screening, library design, QSAR, data mining methods, and modeling tools development, computer-aided drug design, fragment-based approaches, molecular modeling, chemo- and bioinformatics, medicinal chemistry, and target analysis and selection. Optimization of physico-chemical parameters for ADME/Tox and DMPK.
Experienced user of the following software packages: MOE from CCG, Sybyl from Certara, Accelyrs Insight and Discovery studio, OpenEye, Schrödinger suite, Vortex / PipelinePilot. Solid background in chemistry, biology, IT, statistics, and mathematics. Expertise in using HPLC, NMR and MS for organic chemistry applications.
The next fields of research are in scope of the interests:
– Applications development for chemoinformatics and modeling methods and tools.
– Collaboration and research in the interdisciplinary teams of chemists, medicinal chemists, biologists and software developers for the analysis and visualization of scientific data
– Processing and evaluation of commercial and virtual libraries for their suitability for HT screening against targets of interest
– Ligand-based and structure-based models construction for improvement of the compounds potency (using pharmacaphore models/QSAR/multivariate approaches)
– Virtual screening and high-throughput screening methodologies optimization
