WGS-based screening of the co-chaperone protein DjlA-induced curved DNA binding protein A (CbpA) from a new multidrug-resistant zoonotic mastitis-causing Klebsiella pneumoniae strain: a novel molecular target of selective flavonoids

Through virtual saturation mutagenesis and rational design for superior substrate conversion in engineered d‐amino acid oxidase

“…The newly formed hydrogen bond network is essential for stabilizing the binding interaction between Re DAAO and the substrate d ‐PPT, consequently improving the catalytic efficiency toward d ‐PPT. [ 32–35 ]…”

“…Consequently, MD results from 20 to 50 ns were extracted to generate characteristic structures. [ 32 ] On the other hand, MT‐ Re DAAO exhibited overall greater stability, and MD results from 10 to 50 ns were chosen to generate characteristic structures. Additional investigation of the root mean square value fluctuation (RMSF) data unveiled the most notable alterations in the Loop 101–118, corresponding to the structure in Figure 5A.…”

“…The newly formed hydrogen bond network is essential for stabilizing the binding interaction between ReDAAO and the substrate D-PPT, consequently improving the catalytic efficiency toward D-PPT. [32][33][34][35] Substrate-protein complexes, projected through molecular docking, underwent MD simulations (Figure 5B). Examination of the root mean square deviation (RMSD) plot reveals notable fluctuations in WT-ReDAAO compare to MT-ReDAAO prior to 20 ns.…”

“…Consequently, MD results from 20 to 50 ns were extracted to generate characteristic structures. [32] On the other hand, MT-ReDAAO exhibited overall greater stability, and TA B L E 2 The binding free energy (kcal mol −1 ) with D-PPT of DAAO WT-ReDAAO and MT-ReDAAO (N53V/F57Q/V94R/V242R). flexible.…”

New trends in microbial lipid-based biorefinery for fermentative bioenergy production from lignocellulosic biomass

“…The systematic integration of machine learning algorithms in maintaining an alert and optimized working environment, regulating parameters such as temperature, pH conditions, presence of unwanted compounds in the hydrolysate, and toxicity indexing of the reaction chamber represents a promising avenue for high-throughput LCB fractionation in biofuel industries (Phromphithak et al, 2021). Besides, the optimization of molecular dynamic simulation (Rahman et al, 2023) and quantum mechanics behind the DFT profiles of different pretreatment-solvent systems (Xie et al, 2024) have been emphasized in recent times in predicting the quality and types of fermentative products expected to recover from consecutive biochemical reactions.…”