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izvor podataka: crosbi

New approach to the evaluation of lignocellulose derived by-products impact on lytic-polysaccharide monooxygenase activity by using molecular descriptor structural causality model (CROSBI ID 310314)

Prilog u časopisu | izvorni znanstveni rad | međunarodna recenzija

Rezić, Tonči ; Vrsalović Presečki, Ana ; Kurtanjek, Želimir New approach to the evaluation of lignocellulose derived by-products impact on lytic-polysaccharide monooxygenase activity by using molecular descriptor structural causality model // Bioresource technology, 342 (2021), 125990, 5. doi: 10.1016/j.biortech.2021.125990

Podaci o odgovornosti

Rezić, Tonči ; Vrsalović Presečki, Ana ; Kurtanjek, Želimir

engleski

New approach to the evaluation of lignocellulose derived by-products impact on lytic-polysaccharide monooxygenase activity by using molecular descriptor structural causality model

Lytic-polysaccharide monooxygenase (LPMO) is one of the most important enzyme involved in biocatalytic lignocellulose degradation, and therefore inhibition of LPMO has significant effects on all related processes. Structural causality model (SCM) were established to evaluate impact of phenolic by- products in lignocellulose hydrolysates on LPMO activity. The molecular descriptors GATS4c, ATS2m, BIC3 and VR2_Dzs were found to be significant in describing inhibition. The causalities of the molecular descriptors and LPMO activity are determined by evaluating the directed acyclic graph (DAG) and the d-separation algorithm. The maximum causality for LPMO activation is β = 0.79 by BIC3 and the maximum causality of inhibition is β = -0.56 for the GATS4c descriptor. The model has the potential to predict the inhibition of LPMO and its application could be useful in selecting an appropriate lignocellulose pretreatment method to minimise the production of a potent inhibitor. This will subsequently lead to more efficient lignocellulose degradation process.

inhibitors ; Lytic-polysaccharide monooxygenase (LPMO) ; molecular descriptor structural causality model (SCM) ; directed acyclic graph (DAG)

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Podaci o izdanju

342

2021.

125990

5

objavljeno

0960-8524

1873-2976

10.1016/j.biortech.2021.125990

Povezanost rada

Biotehnologija, Kemijsko inženjerstvo

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