Gas-phase pyrolysis of 2,3-dihydro-1,4-diazepines: involvement of the saturated portion of the ring in chemical reactions and novel cis–trans isomerisation of a fused ring system

Ellis, Mary; Lloyd, Douglas R.; McNab, Hamish; Walker, Marion J.

doi:10.1039/c39950002337

Cited by 9 publications

(1 citation statement)

References 4 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…MACCSFP 19 represents the existence of seven-membered rings. Common seven-membered rings, including azepines, benzodiazepines and diazepines, demonstrate a broad range of biological activities and have been important structural scaffolds of CNS drugs [ 54 ]. In our study, 23% of CNS drugs had seven-membered ring structures, while that of non-CNS drugs was only 5%.…”

Section: Discussionmentioning

confidence: 99%

Ensemble modeling with machine learning and deep learning to provide interpretable generalized rules for classifying CNS drugs with high prediction power

Battalora

et al. 2021

Briefings in Bioinformatics

View full text Add to dashboard Cite

The trade-off between a machine learning (ML) and deep learning (DL) model’s predictability and its interpretability has been a rising concern in central nervous system-related quantitative structure–activity relationship (CNS-QSAR) analysis. Many state-of-the-art predictive modeling failed to provide structural insights due to their black box-like nature. Lack of interpretability and further to provide easy simple rules would be challenging for CNS-QSAR models. To address these issues, we develop a protocol to combine the power of ML and DL to generate a set of simple rules that are easy to interpret with high prediction power. A data set of 940 market drugs (315 CNS-active, 625 CNS-inactive) with support vector machine and graph convolutional network algorithms were used. Individual ML/DL modeling methods were also constructed for comparison. The performance of these models was evaluated using an additional external dataset of 117 market drugs (42 CNS-active, 75 CNS-inactive). Fingerprint-split validation was adopted to ensure model stringency and generalizability. The resulting novel hybrid ensemble model outperformed other constituent traditional QSAR models with an accuracy of 0.96 and an F1 score of 0.95. With the power of the interpretability provided with this protocol, our model laid down a set of simple physicochemical rules to determine whether a compound can be a CNS drug using six sub-structural features. These rules displayed higher classification ability than classical guidelines, with higher specificity and more mechanistic insights than just for blood–brain barrier permeability. This hybrid protocol can potentially be used for other drug property predictions.

show abstract

Section: Discussionmentioning

confidence: 99%

Ensemble modeling with machine learning and deep learning to provide interpretable generalized rules for classifying CNS drugs with high prediction power

Battalora

et al. 2021

Briefings in Bioinformatics

View full text Add to dashboard Cite

show abstract

Pyrolysis Involving Compounds withCC,CNandCODouble Bonds

Aitken

Thomas

2009

Patai's Chemistry of Functional Groups

View full text Add to dashboard Cite

Introduction Compounds Containing C  C Double Bonds Compounds Containing C  N Double Bonds Compounds Containing C  O Double Bonds

show abstract

ChemInform Abstract: Gas‐Phase Pyrolysis of 2,3‐Dihydro‐1,4‐diazepines: Involvement of the Saturated Portion of the Ring in Chemical Reactions and Novel cis‐ trans Isomerization of a Fused Ring System.

et al. 1996

View full text Add to dashboard Cite

Gas-Phase Pyrolysis of 2,3-Dihydro-1,4-diazepines: Involvement of the Saturated Portion of the Ring in Chemical Reactions and Novel cis-trans Isomerization of a Fused Ring System. -The observed cis-trans isomerization of fused diazepine systems (I), ( III) is explained mechanistically by sequential 1,5-hydrogen shift (no yields given). -(ELLIS, M. J.; LLOYD, D.; MCNAB, H.; WALKER, M. J.; J. Chem. Soc., Chem.

show abstract

Gas-phase pyrolysis of 2,3-dihydro-1,4-diazepines: involvement of the saturated portion of the ring in chemical reactions and novel cis–trans isomerisation of a fused ring system

Cited by 9 publications

References 4 publications

Ensemble modeling with machine learning and deep learning to provide interpretable generalized rules for classifying CNS drugs with high prediction power

Ensemble modeling with machine learning and deep learning to provide interpretable generalized rules for classifying CNS drugs with high prediction power

Pyrolysis Involving Compounds withCC,CNandCODouble Bonds

ChemInform Abstract: Gas‐Phase Pyrolysis of 2,3‐Dihydro‐1,4‐diazepines: Involvement of the Saturated Portion of the Ring in Chemical Reactions and Novel cis‐ trans Isomerization of a Fused Ring System.

Contact Info

Product

Resources

About