Location: Crop Improvement and Genetics ResearchTitle: Experimental and computational studies of cellulases as bioethanol enzymes
|RANGANATHAN, SHRIVAISHNAVI - Sastra Deemed To Be University
|MAHESH, SANKAR - Sastra Deemed To Be University
|SURESH, SRUTHI - Sastra Deemed To Be University
|NAGARAJAN, ASHWARYA - Sastra Deemed To Be University
|YENNAMALLI, RAGOTHAMAN - Sastra Deemed To Be University
Submitted to: Bioengineered
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 5/31/2022
Publication Date: 6/22/2022
Citation: Ranganathan, S., Mahesh, S., Suresh, S., Nagarajan, A., Sen, T.Z., Yennamalli, R.M. 2022. Experimental and computational studies of cellulases as bioethanol enzymes. Bioengineered. 13(5):14028-14046. https://doi.org/10.1080/21655979.2022.2085541.
Interpretive Summary: One of the bottlenecks in bioethanol industry is the challenge of discovering efficient catalysts that can increase biofuel conversion. Most current catalysts used in bioethanol conversion are microorganism-based cellulolytic enzymes, which are not optimized for high conversion rate. To increase bioethanol production, it is therefore crucial to study cellulolytic enzymes, understand molecular underpinnings of their enzymatic mechanisms, and suggest routes to increase their efficiency. Experimental methods are the primary choice to evaluate and characterize cellulase properties, but they are slow and costly. A time-saving, complementary approach is to use computational methods to improve our atomistic-level understanding for enzymatic actions of mechanism and propose research routes for subsequent experimental testing and validation, and therefore reduce overall research cost. In this review, we first describe bioethanol production processes using cellulases, then survey experimental evaluation of cellulases, and finally present a range of computational methods and their applications that can be used to evaluate cellulases to increase their efficiency in converting biomass into bioethanol.
Technical Abstract: 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 atomisticlevel 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.