Comparative in Silico Analysis of Fungal and Bacterial Alkaline Serine Proteases: Insights into Structure, Function, and Evolution

Abstract

Serine proteases are an essential and immensely diverse group of enzymes found in many different organisms, from mammals to viruses. Alkaline serine proteases (ASPs) are a type of serine protease that exhibit their highest activity levels in alkaline conditions. These enzymes play a critical role across a wide range of industries, providing immense value and benefits. ASPs are produced mainly by bacteria and fungi on industrial scales. The present study involved an analysis of various sequences of alkaline serine proteases derived from fungi and bacteria. The analytical approach employed encompassed the assessment of the pseudo amino acid composition (PseAAC), the tripeptide composition (TPC), physicochemical properties, secondary structures, and conserved motifs. Motif discovery and analysis showed that a considerable majority of bacterial alkaline serine protease sequences (over 94%) and fungal alkaline serine protease sequences (99%) in the dataset were associated with the subtilisin-like serine protease superfamily. This finding highlights the prevalence of this particular superfamily in alkaline serine protease sequences and provides valuable insight into the evolutionary relationships between different protease families. Based on the results of the study, the utilization of PseAAC and TPC techniques was successful in categorizing fungal and bacterial ASPs into separate groups. This was made possible by precise predictive models generated using machine learning algorithms. Bacterial and fungal ASPs had no significant differences in amino acid composition, ProtParam features, and GORIV secondary structure prediction outcomes. This underscores the importance of TPC and PseAAC concepts in accurately clustering and predicting ASP sequences. © The Author(s), under exclusive licence to Shiraz University 2024.