TURBOMOLE is a powerful Quantum Chemistry (QC) program package and one of the fastest and most stable codes available for standard quantum chemical applications (HF, DFT, MP2). Unlike many other programs, the main focus in the development of TURBOMOLE has not been to implement all new methods and fu...
Turbomole 7.4 released TURBOMOLE V7.4 has been released (July 2019) New features: NMR: Nuclear coupling constants (Fermi contact term) at HF and DFT level All-electron relativistic NMR shielding constants (one-component DLU-X2C) [url... Source: Turbomole Forum
Bengaluru: July 26, 2019 at 08:05PM
Hall of Fame Winners of the scientific challenges with interesting projects using BioSolveIT - Finest Software for Drug Discovery software solutions like #SeeSAR #HYDE #InfiniSee
Bengaluru: June 29, 2019 at 10:24AM
Drug Discovery Today: Capturing and Applying Knowledge to Guide Compound Optimisation Drug Discovery Today; V24 No.5 May 2019 Matthew Segall, Tamsin Mansley, Peter Hunt, Edmund Champness Successful drug discovery requires knowledge and experience across many disciplines, and no current 'artificial intelligence' (AI) method can replace expert scientists. However, computers can recall more information than any individual or team and facilitate the transfer of knowledge across disciplines. Here, we discuss how knowledge relating to chemistry and the biological and physicochemical properties required for a successful compound can be captured. Furthermore, we illustrate how, by combining and applying this knowledge computationally, a broader range of optimisation strategies can be rigorously explored, and the results presented in an intuitive way for consideration by the experts. #CADD #Drug #Discovery #Zastra #Optibrium #StarDrop
Bengaluru: June 29, 2019 at 10:14AM
Metadata can greatly augment scientific data. In practice, we must ensure that metadata capture does not become a burden to the scientist. Collaborative Drug Discovery set out to design a simple, quick, and efficient method of assay metadata management.
CDD's Q2 Scientific Webinar, had our expert panel of scientists, Dr. Ellen Berg (Eurofins and Alto Predict) and Dr. Isabella Feierberg (AstraZeneca) discuss the importance of metadata and their vision for how assay annotation will shape the future of drug discovery. #CDD #ELN #VAULT #CLOUD #Drug #Discovery
Bengaluru: June 29, 2019 at 09:54AM
AI to Predict Missing Data Points in Compound Data Data where a significant amount of points are missing from the complete sets – or “noisy” data – data where a significant amount of variables could contribute to issues and changes in results – and making predictive models that fill in missing points with degrees of certainty and without having to undergo costly experimentation.
Bengaluru: June 29, 2019 at 09:48AM
Capturing and Applying Knowledge to Guide Compound Optimisation Demonstrated how: > Synthetic strategies from previous projects can be applied to generate relevant compound ideas and propose synthetic routes. > SAR and multi-parameter objectives can prioritise ideas for experts’ consideration. > Supplementing scientists’ experience helps to objectively explore new strategies. #Optibrium #StarDrop #MedChem #CADD
Bengaluru: June 29, 2019 at 09:43AM
#Gaussian #QSAR #Potentials
Bengaluru: April 20, 2019 at 08:39AM