Computational Insights into the Selecting Mechanism of α-Amylase Immobilized on Cellulose Nanocrystals: Unveiling the Potential of α-Amylases Immobilized for Efficient Poultry Feed Hydrolysis.

The selection of an appropriate amylase for hydrolysis poultry feed is crucial for achieving improved digestibility and high-quality feed. Cellulose nanocrystals (CNCs), which are known for their high surface area, provide an excellent platform for enzyme immobilization. Immobilization greatly enhances the operational stability of α-amylases and the efficiency of starch bioconversion in poultry feeds. In this study, we immobilized two metagenome-derived α-amylases, PersiAmy2 and PersiAmy3, on CNCs and employed computational methods to characterize and compare the degradation efficiencies of these enzymes for poultry feed hydrolysis. Experimental in vitro bioconversion assessments were performed to validate the computational outcomes. Molecular docking studies revealed the superior hydrolysis performance of PersiAmy3, which displayed stronger electrostatic interactions with CNCs. Experimental characterization demonstrated the improved performance of both α-amylases after immobilization at high temperatures (80 °C). A similar trend was observed under alkaline conditions, with α-amylase activity reaching 88% within a pH range of 8.0 to 9.0. Both immobilized α-amylases exhibited halotolerance at NaCl concentrations up to 3 M and retained over 50% of their initial activity after 13 use cycles. Notably, PersiAmy3 displayed more remarkable improvements than PersiAmy2 following immobilization, including a significant increase in activity from 65 to 80.73% at 80 °C, an increase in activity to 156.48% at a high salinity of 3 M NaCl, and a longer half-life, indicating greater thermal stability within the range of 60 to 80 °C. These findings were substantiated by the in vitro hydrolysis of poultry feed, where PersiAmy3 generated 53.53 g/L reducing sugars. This comprehensive comparison underscores the utility of computational methods as a faster and more efficient approach for selecting optimal enzymes for poultry feed hydrolysis, thereby providing valuable insights into enhancing feed digestibility and quality.

In-silico discovery of bifunctional enzymes with enhanced lignocellulose hydrolysis from microbiota big data.

Due to the importance of using lignocellulosic biomass, it is always important to find an effective novel enzyme or enzyme cocktail or fusion enzymes. Identification of bifunctional enzymes through a metagenomic approach is an efficient method for converting agricultural residues and a beneficial way to reduce the cost of enzyme cocktail and fusion enzyme production. In this study, a novel stable bifunctional cellulase/xylanase, PersiCelXyn1 was identified from the rumen microbiota by the multi-stage in-silico screening pipeline and computationally assisted methodology. The enzyme exhibited the optimal activity at pH 5 and 50°C. Analyzing the enzyme activity at extreme temperature, pH, long-term storage, and presence of inhibitors and metal ions, confirmed the stability of the bifunctional enzyme under harsh conditions. Hydrolysis of the rice straw by PersiCelXyn1 showed its capability to degrade both cellulose and hemicellulose polymers. Also, the enzyme improved the degradation of various biomass substrates after 168 h of hydrolysis. Our results demonstrated the power of the multi-stage in-silico screening to identify bifunctional enzymes from metagenomic big data for effective bioconversion of lignocellulosic biomass.

A novel metagenome-derived thermostable and poultry feed compatible α-amylase with enhanced biodegradation properties.

According to the numerous applications of feed processing by enzymatic conversion can be a fantastic tool to extreme its industrial usages. In this study, a novel acidic-thermostable α-amylase (PersiAmy3) was in-silico screened from the sheep rumen microbiota by computationally guided experiments instead of costly functional screening. At first, an in-silico screening approach was utilized to find primary candidate enzymes with superior properties. Among the selected candidates, PersiAmy3 was cloned, expressed, purified, and characterized. The PersiAmy3 was able to retain 65% of its maximum activity after 14 days of storage and exhibited optimal activity at pH 6-7 and 50 °C. The enzyme had excellent activity in the presence of various chemicals, it showed an excellent ability to hydrolyze different substrates, and was Ca2+ independent. Due to the high stability and activity of the PersiAmy3 on the corn powder as substrate, its ability to degrade the corn-based poultry feed at three high temperatures (50°C, 70°C, and 85°C), followed by the structural analysis was investigated. The result of this study indicated the power of computational selected candidates to discover novel acidic thermostable α-amylases. The selection method was very accurate, effective biodegradation of the poultry feed for industry was achieved using the selected candidate PersiAmy3.