Bioethanol industries and bioprocesses have many challenges that constantly impede commercialization of the end product. One of the bottlenecks in the bioethanol industry is the challenge of discovering highly efficient catalysts that can improve biomass conversion. The current promising bioethanol conversion catalysts are microorganism-based cellulolytic enzymes, but lack optimization for high bioethanol conversion, due to biological and other factors. A better understanding of molecular underpinnings of cellulolytic enzyme mechanisms and significant ways to improve them can accelerate the bioethanol commercial production process. In order to do this, experimental methods are the primary choice to evaluate and characterize cellulase’s properties, but they are time-consuming and expensive. A time-saving, complementary approach involves computational methods that evaluate the same properties and improves our atomistic-level understanding of enzymatic mechanism of action. Theoretical methods in many cases have proposed research routes for subsequent experimental testing and validation, reducing the overall research cost. Having a plethora of tools to evaluate cellulases and the yield of the enzymatic process will aid in planning more optimized experimental setups. Thus, there is a need to connect the computational evaluation methods with the experimental methods to overcome the bottlenecks in the bioethanol industry. This review discusses various experimental and computational methods and their use in evaluating the multiple properties of cellulases.

No abstract

No abstract

The members of the Deinococcaceae family have the ability to survive extreme environmental conditions. Deinococcus species have a complex cell envelope composed of L-ornithine containing peptidoglycan. Anabolism of L-ornithine is intrinsically linked to L-lysine and L-arginine biosynthetic pathways. To understand these two pathways, we analyzed the L-lysine and L-arginine pathways using 23 Deinococcus genomes, including D. indicus. We used BLAST-P based ortholog identification using D. radiodurans genes as the query. We identified some BLAST-P hits that shared the same functional annotation. We analyzed three (class I aminotransferase, acetyl-lysine deacetylase, and acetyl glutamate/acetyl aminoadipate kinase) from L-lysine biosynthesis pathway and three (bifunctional ornithine acetyltransferase or N-acetyl glutamate synthase protein, nitric oxide synthase-like protein, and Acetyl-lysine deacetylase) from L-arginine biosynthesis pathway. Two proteins showed certain structural variations. Specifically, [LysW]-lysine hydrolase protein sequence and structure level changes indicated changes in oligomeric conformation, which could likely be a result of divergent evolution. And, bifunctional ornithine acetyltransferase or N-acetyl glutamate synthase had its active site pocket positions shifted at the structural level and we hypothesize that it may not perform at the optimal level. Thus, we were able to compare and contrast different Deinococcus species indicating some genes occurring because of divergent evolution.