Quantitative structure–selectivity relationships in enantioselective catalysis: past, present, and future

AF Zahrt, SV Athavale, SE Denmark - Chemical reviews, 2019 - ACS Publications
The dawn of the 21st century has brought with it a surge of research related to computer-
guided approaches to catalyst design. In the past two decades, chemoinformatics, the …

Chemical predictive modelling to improve compound quality

JG Cumming, AM Davis, S Muresan… - Nature reviews Drug …, 2013 - nature.com
The'quality'of small-molecule drug candidates, encompassing aspects including their
potency, selectivity and ADMET (absorption, distribution, metabolism, excretion and toxicity) …

Neural‐symbolic machine learning for retrosynthesis and reaction prediction

MHS Segler, MP Waller - Chemistry–A European Journal, 2017 - Wiley Online Library
Reaction prediction and retrosynthesis are the cornerstones of organic chemistry. Rule‐
based expert systems have been the most widespread approach to computationally solve …

[HTML][HTML] RetroPath2. 0: a retrosynthesis workflow for metabolic engineers

B Delépine, T Duigou, P Carbonell, JL Faulon - Metabolic engineering, 2018 - Elsevier
Synthetic biology applied to industrial biotechnology is transforming the way we produce
chemicals. However, despite advances in the scale and scope of metabolic engineering, the …

ExCAPE-DB: an integrated large scale dataset facilitating Big Data analysis in chemogenomics

J Sun, N Jeliazkova, V Chupakhin… - Journal of …, 2017 - Springer
Chemogenomics data generally refers to the activity data of chemical compounds on an
array of protein targets and represents an important source of information for building in …

Machine learning property prediction for organic photovoltaic devices

N Meftahi, M Klymenko, AJ Christofferson… - npj computational …, 2020 - nature.com
Organic photovoltaic (OPV) materials are promising candidates for cheap, printable solar
cells. However, there are a very large number of potential donors and acceptors, making …

Immune-instructive polymers control macrophage phenotype and modulate the foreign body response in vivo

HM Rostam, LE Fisher, AL Hook, L Burroughs… - Matter, 2020 - cell.com
Implanted medical devices often elicit adverse foreign body responses whereby
macrophages play a central role. Here, we identify simple polymers that instruct different …

RetroRules: a database of reaction rules for engineering biology

T Duigou, M Du Lac, P Carbonell… - Nucleic acids …, 2019 - academic.oup.com
RetroRules is a database of reaction rules for metabolic engineering (https://retrorules. org).
Reaction rules are generic descriptions of chemical reactions that can be used in …

[HTML][HTML] Open source molecular modeling

S Pirhadi, J Sunseri, DR Koes - Journal of Molecular Graphics and …, 2016 - Elsevier
The success of molecular modeling and computational chemistry efforts are, by definition,
dependent on quality software applications. Open source software development provides …

Direct prediction of bioaccumulation of organic contaminants in plant roots from soils with machine learning models based on molecular structures

F Gao, Y Shen, JB Sallach, H Li, C Liu… - Environmental Science & …, 2021 - ACS Publications
Root concentration factor (RCF) is an important characterization parameter to describe
accumulation of organic contaminants in plants from soils in life cycle impact assessment …