An in-silico Approach for Enhancing the Lipid Productivity in Microalgae by Manipulating the Fatty Acid Biosynthesis

  • Bunushree Behera
  • S. Selvanayaki
  • R. Jayabalan
  • P. BalasubramanianEmail author
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 816)


To fulfill the impetus of demands on alternative energy, microalgal biofuels have attracted significant attention due to the ease of cultivation, higher photosynthetic rate, as well as, the presence of significant quantity of lipids. However, from an energy perspective, the polyunsaturated fatty acids (PUFA) (substrate for transesterification to biodiesel) constitute only 10–20% of the total lipids. Approaches for increasing lipids include coercing the algal cells under nutrient depletion which also declines their growth rate. Improving the lipid accumulation without compromising growth requires strain modification via genomic or metabolic engineering which necessitates the core understanding of the critical regulators of denovo lipid biogenesis. Increase in activity of the enzyme acetyl-CoA carboxylase (ACCase) has been postulated to improve the lipid synthesis. Thus, the current study utilized the Chlamydomonas reinhardtii as the model organism for understanding the lipid metabolism. In-silico computational approach was used to design the 3D structure of ACCase, the key enzyme that catalyzes the rate-limiting step of lipid synthesis. The accuracy of the predicted structure was validated by the presence of 94% of amino acid residues in the favorable region of Ramachandran plot. The docking studies with four selected ligands (ACP, AMP, Biotin, and Glycine) showed biotin as the suitable ligand with a lowest binding affinity (−5.5 kcal/mol). The ligand–protein complex is expected to increase the enzyme activity driving lipid accumulation in vivo. Such in-silico studies are essential to design and decipher the role of different regulatory enzymes in improving the quantity and quality of microalgal biodiesel.


Microalgae ACCase Lipid production Homology modeling In-silico Docking 



The authors are thankful to the DBT sponsored Bioinformatics Infrastructure Facility (BIF) at Department of Biotechnology and Medical Engineering of NIT Rourkela for their support during the research work. The authors are grateful to Ministry of Human Resources and Development of Government of India (MHRD, GoI) for sponsoring the first author’s Ph.D. program.


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Copyright information

© Springer Nature Singapore Pte Ltd. 2019

Authors and Affiliations

  • Bunushree Behera
    • 1
  • S. Selvanayaki
    • 1
    • 2
  • R. Jayabalan
    • 3
  • P. Balasubramanian
    • 1
    Email author
  1. 1.Department of Biotechnology and Medical EngineeringNational Institute of Technology RourkelaRourkelaIndia
  2. 2.Department of BioinformaticsKarunya UniversityCoimbatoreIndia
  3. 3.Department of Life ScienceNational Institute of Technology RourkelaRourkelaIndia

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