Abstract

An understanding of the activities of enzymes could help to elucidate the metabolic pathways of thousands of chemical reactions that are catalyzed by enzymes in living systems. Sophisticated applications such as drug design and metabolic reconstruction could be developed using accurate enzyme reaction annotation. Because accurate enzyme reaction annotation methods create potential for enhanced production capacity in these applications, they have received greater attention in the global market. We propose the enzyme reaction prediction (ERP) method as a novel tool to deduce enzyme reactions from domain architecture. We used several frequency relationships between architectures and reactions to enhance the annotation rates for single and multiple catalyzed reactions. The deluge of information which arose from high-throughput techniques in the postgenomic era has improved our understanding of biological data, although it presents obstacles in the data-processing stage. The high computational capacity provided by cloud computing has resulted in an exponential growth in the volume of incoming data. Cloud services also relieve the requirement for large-scale memory space required by this approach to analyze enzyme kinetic data. Our tool is designed as a single execution file; thus, it could be applied to any cloud platform in which multiple queries are supported.

Highlights

  • Enzymes are biochemical agents that efficiently catalyze the conversion of substrates into products in organisms

  • Enzymes are essential to the metabolic activity of living systems, and they share 3 features: catalytic power, specificity, and regulation [1]

  • Because domains are fundamental structural units that can fold into a compact block, we considered the appearance of a domain in an enzyme and omitted the repetition of domains

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Summary

Introduction

Enzymes are biochemical agents that efficiently catalyze the conversion of substrates into products in organisms. Enzymes are essential to the metabolic activity of living systems, and they share 3 features: catalytic power, specificity, and regulation [1]. Catalytic power is the ratio of the rate of an enzyme-catalyzed reaction to the rate of the uncatalyzed reaction. Enzyme-catalyzed reactions provide faster rates than traditional biochemical processes because enzymes reduce the energy required for biochemical reactions. Their selection should be specific to the desired reaction; the use of enzymes can avoid competing reactions from producing side products. Enzyme applications are increasingly being employed in industrial applications. Enzyme activities can be optimized to provide metabolic reaction rates that are appropriate to cellular requirements

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