Chemoinformatics as a theoretical chemistry discipline
Here, chemoinformatics is considered as a theoretical chemistry discipline complementary
to quantum chemistry and force‐field molecular modeling. These three fields are compared …
to quantum chemistry and force‐field molecular modeling. These three fields are compared …
An analysis of QSAR research based on machine learning concepts
MR Keyvanpour, MB Shirzad - Current Drug Discovery …, 2021 - ingentaconnect.com
Quantitative Structure–Activity Relationship (QSAR) is a popular approach developed to
correlate chemical molecules with their biological activities based on their chemical …
correlate chemical molecules with their biological activities based on their chemical …
Basic validation procedures for regression models in QSAR and QSPR studies: theory and application
R Kiralj, M Ferreira - Journal of the Brazilian Chemical Society, 2009 - SciELO Brasil
Four quantitative structure-activity relationships (QSAR) and quantitative structure-property
relationship (QSPR) data sets were selected from the literature and used to build regression …
relationship (QSPR) data sets were selected from the literature and used to build regression …
Neuraldecipher–reverse-engineering extended-connectivity fingerprints (ECFPs) to their molecular structures
Protecting molecular structures from disclosure against external parties is of great relevance
for industrial and private associations, such as pharmaceutical companies. Within the …
for industrial and private associations, such as pharmaceutical companies. Within the …
Computer-aided molecular design using the Signature molecular descriptor: Application to solvent selection
DC Weis, DP Visco - Computers & Chemical Engineering, 2010 - Elsevier
There is a growing demand to develop more environmentally friendly solvents to reduce
costs and comply with regulation. Researchers at GlaxoSmithKline (GSK) have developed a …
costs and comply with regulation. Researchers at GlaxoSmithKline (GSK) have developed a …
Towards the revival of interpretable QSAR models
W Shoombuatong, P Prathipati, W Owasirikul… - Advances in QSAR …, 2017 - Springer
Quantitative structure-activity relationship (QSAR) has been instrumental in aiding medicinal
chemists and physical scientists in understanding how modification of substituents at …
chemists and physical scientists in understanding how modification of substituents at …
An informatics approach to evaluating combined chemical exposures from consumer products: a case study of asthma-associated chemicals and potential endocrine …
Background: Simultaneous or sequential exposure to multiple environmental stressors can
affect chemical toxicity. Cumulative risk assessments consider multiple stressors but it is …
affect chemical toxicity. Cumulative risk assessments consider multiple stressors but it is …
A constructive approach for discovering new drug leads: Using a kernel methodology for the inverse-QSAR problem
WWL Wong, FJ Burkowski - Journal of cheminformatics, 2009 - Springer
Background The inverse-QSAR problem seeks to find a new molecular descriptor from
which one can recover the structure of a molecule that possess a desired activity or property …
which one can recover the structure of a molecule that possess a desired activity or property …
Bigger data, collaborative tools and the future of predictive drug discovery
Over the past decade we have seen a growth in the provision of chemistry data and
cheminformatics tools as either free websites or software as a service commercial offerings …
cheminformatics tools as either free websites or software as a service commercial offerings …
Shared consensus machine learning models for predicting blood stage malaria inhibition
The development of new antimalarial therapies is essential, and lowering the barrier of entry
for the screening and discovery of new lead compound classes can spur drug development …
for the screening and discovery of new lead compound classes can spur drug development …