Literature summary extracted from

de Avila, M.B.; de Azevedo, W.F.
Development of machine learning models to predict inhibition of 3-dehydroquinate dehydratase (2018), Chem. Biol. Drug Des., 92, 1468-1474 .

Crystallization (Commentary)

EC Number	Crystallization (Comment)	Organism
4.2.1.10	study on the crystallographic structures of DHQD in complex with competitive inhibitors, and application of supervised machine learning techniques elaborate a robust DHQD-targeted model to predict binding affinity. The prevalence of intermolecular electrostatic interactions between DHQD and competitive inhibitors is of great importance for the binding affinity against the enzyme	Mycobacterium tuberculosis

Organism

EC Number	Organism	UniProt	Comment	Textmining
4.2.1.10	Mycobacterium tuberculosis	P9WPX7	-	-
4.2.1.10	Mycobacterium tuberculosis H37Rv	P9WPX7	-	-

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Release 2023.1 (January 2023)