An updated review of computer‐aided drug design and its application to COVID‐19
The recent outbreak of the deadly coronavirus disease 19 (COVID‐19) pandemic poses
serious health concerns around the world. The lack of approved drugs or vaccines continues …
serious health concerns around the world. The lack of approved drugs or vaccines continues …
Big data and artificial intelligence modeling for drug discovery
H Zhu - Annual review of pharmacology and toxicology, 2020 - annualreviews.org
Due to the massive data sets available for drug candidates, modern drug discovery has
advanced to the big data era. Central to this shift is the development of artificial intelligence …
advanced to the big data era. Central to this shift is the development of artificial intelligence …
A review on machine learning algorithms for the ionic liquid chemical space
There are thousands of papers published every year investigating the properties and
possible applications of ionic liquids. Industrial use of these exceptional fluids requires …
possible applications of ionic liquids. Industrial use of these exceptional fluids requires …
[图书][B] Understanding the basics of QSAR for applications in pharmaceutical sciences and risk assessment
Understanding the Basics of QSAR for Applications in Pharmaceutical Sciences and Risk
Assessment describes the historical evolution of quantitative structure-activity relationship …
Assessment describes the historical evolution of quantitative structure-activity relationship …
CAESAR models for developmental toxicity
Background The new REACH legislation requires assessment of a large number of
chemicals in the European market for several endpoints. Developmental toxicity is one of the …
chemicals in the European market for several endpoints. Developmental toxicity is one of the …
Real external predictivity of QSAR models: how to evaluate it? Comparison of different validation criteria and proposal of using the concordance correlation coefficient
N Chirico, P Gramatica - Journal of chemical information and …, 2011 - ACS Publications
The main utility of QSAR models is their ability to predict activities/properties for new
chemicals, and this external prediction ability is evaluated by means of various validation …
chemicals, and this external prediction ability is evaluated by means of various validation …
[PDF][PDF] Validation of QSAR models-strategies and importance
Quantitative Structure-Activity Relationship (QSAR) is based on the hypothesis that changes
in molecular structure reflect changes in the observed response or biological activity. The …
in molecular structure reflect changes in the observed response or biological activity. The …
Some case studies on application of “rm2” metrics for judging quality of quantitative structure–activity relationship predictions: Emphasis on scaling of response …
Quantitative structure–activity relationship (QSAR) techniques have found wide application
in the fields of drug design, property modeling, and toxicity prediction of untested chemicals …
in the fields of drug design, property modeling, and toxicity prediction of untested chemicals …
Further exploring rm2 metrics for validation of QSPR models
Quantitative structure–property relationship (QSPR) models are widely used for prediction of
properties, activities and/or toxicities of new chemicals. Validation strategies check the …
properties, activities and/or toxicities of new chemicals. Validation strategies check the …
[HTML][HTML] On two novel parameters for validation of predictive QSAR models
P Pratim Roy, S Paul, I Mitra, K Roy - Molecules, 2009 - mdpi.com
Validation is a crucial aspect of quantitative structure–activity relationship (QSAR) modeling.
The present paper shows that traditionally used validation parameters (leave-one-out Q 2 for …
The present paper shows that traditionally used validation parameters (leave-one-out Q 2 for …