The Maranas group is working on the development of algorithmic and, in particular, optimization techniques to support the analysis and redesign of biological systems at different scales.

At the protein level, we are interested in computationally inferring what amino acid compositions are likely to yield i) proteins or antibodies with targeted binding affinities, ii) enzymes with improved stability, specificity and activity for specific biotransformations, and iii) protein pores that allow for tailored separations. To this end, we rely on biophysics inspired force fields such as CHARMM and Rosetta to quantify molecular interactions.

At the metabolic network level, we are pursuing methods for automating the generation, curation, and correction of genome-scale models of metabolism. We are also interested in generating isotope mapping models to support metabolic flux elucidation using MFA. In addition, we are working towards developing computational tools to help decide how to engineer (i.e., through gene knock-in/out/up/down(s)) biological production systems. A unifying feature of these seemingly disjoint research targets is the need to systematically search through many network configurations, amino acid compositions, protein structures, etc. and identify the "best" one. To this end, the development of efficient theoretical, algorithmic, and computational techniques for arriving at relevant as well as theoretically sound results while maximizing computational efficiency is pursued.

Professor Maranas is also a member of Faculty of the Operations Research Program. Operations Research (OR) is the use of scientific methodology in the formulation, analysis, and solution of problems in decision making. It draws on techniques from many fields, including economics, mathematics, and engineering. Students with a strong interest in operations research techniques can apply for an Operations Research Dual-title degree, such as a Dual Master degree in OR, Dual Ph.D. degree in OR, and Minor Ph.D. degree in OR. Interested students must submit an application for admission to the Chair of the OR Program and meet the necessary course requirements. Relevant information can be found at:

Reconstruction, Analysis & Redesign of Metabolic Pathways

Reconstruction, Analysis & Redesign of Metabolic Pathways

  • Development of kinetic models of metabolism
  • Computational procedures for strain optimization using kinetic models of metabolism
  • Metabolic modeling of photosynthetic cyanobacteria, anaerobic organisms (Clostridia & Archaea), yeasts, and plants(maize)
  • Metabolic modeling of microbial communities
  • Metabolic flux elucidation using MFA at genome-scale
  • Generation of a metabolites and reaction knowledgebase (MetRxn)
  • Genome-scale gene/reaction essentiality and synthetic lethality analysis
  • Computational procedures for strain optimization using stoichiometric models of metabolism
  • Analysis of network properties of metabolic models
  • Novostoic: A pathway design tool accounting for novel biotransformations
  • dGPredictor: Moiety-based tool for thermodynamic analysis of metabolic pathways

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Computational Protein Design

Computational Protein Modeling & Design

  • Biophysical characterization of the ACE2-RBD interactions and assessment of emerging SARS-CoV-2 variants
  • Computational Protein Design Tool Allowing for Insertions and Deletions
  • Design of Membrane proteins: PoreDesigner
  • Structure-Based Computational Enzyme Design
  • De novo computational antibody design
  • Enzyme design with improved catalytic properties
  • Altering enzyme cofactor specificity
  • A computational procedure for transferring a binding site onto an existing protein scaffold
  • An Iterative Computational Protein Library Redesign and Optimization Procedure
  • Protein library design using scoring functions or clash maps
  • Modeling and optimization of directed evolution protocols

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