Tohoku University · Biochemistry, Genetics and Molecular Biology
Professor Mitsuo Umetsu's research lab specializes in protein engineering and biomineralization, focusing on the design and functional optimization of proteins for advanced materials and biocatalysis. The lab employs innovative approaches combining molecular evolution, machine learning, and structural analysis to engineer proteins with tailored functions, such as selective binding to inorganic materials like ZnO or enhanced stability and activity in enzyme systems. A key research direction involves the development of artificial cellulosomes and protein-based nanostructures through rational design and hetero-clustering strategies, aiming to improve the efficiency of biomass degradation and materials assembly. The lab also investigates protein folding mechanisms and structural characteristics in inclusion bodies, particularly for hyperthermophilic proteins, to understand and control structural stability during recombinant protein production.
Figures are computed from collected data and may differ slightly.
A peptide with an affinity for ZnO, selected by a phage-display system, preferentially immobilizes ZnO particles on a gold-coated polypropylene plate and assists in the homogeneous assembly of 10 nm diameter ZnO nanoparticles into unique flower-like morphologies (see Figure). The peptide is selective in binding ZnO, but not ZnS or Eu2O3. This combinatorial library approach may yield new peptides used to create new structures via biomineralization.
Molecular evolution based on mutagenesis is widely used in protein engineering. However, optimal proteins are often difficult to obtain due to a large sequence space. Here, we propose a novel approach that combines molecular evolution with machine learning. In this approach, we conduct two rounds of mutagenesis where an initial library of protein variants is used to train a machine-learning model to guide mutagenesis for the second-round library. This enables us to prepare a small library suited
The gradual removal of the denaturing reagent guanidine HCl (GdnHCl) using stepwise dialysis with the introduction of an oxidizing reagent and l-arginine resulted in the highly efficient refolding of various denatured single-chain Fv fragments (scFvs) from inclusion bodies expressed in Escherichia coli. In this study, the influence of the additives on the intermediates in scFv refolding was carefully analyzed on the basis of the stepwise dialysis, and it was revealed that the additive effect cri
Machine learning (ML) is becoming an attractive tool in mutagenesis-based protein engineering because of its ability to design a variant library containing proteins with a desired function. However, it remains unclear how ML guides directed evolution in sequence space depending on the composition of training data. Here, we present a ML-guided directed evolution study of an enzyme to investigate the effects of a known "highly positive" variant (i.e., variant known to have high enzyme activity) in
Cellulose, one of the most abundant carbon resources, is degraded by cellulolytic enzymes called cellulases. Cellulases are generally modular proteins with independent catalytic and cellulose-binding domain (CBD) modules and, in some bacteria, catalytic modules are noncovalently assembled on a scaffold protein with CBD to form a giant protein complex called a cellulosome, which efficiently degrades water-insoluble hard materials. In this study, a catalytic module and CBD are independently prepar
Several recombinant proteins in inclusion bodies expressed in Escherichia coli have been measured by Fourier transform infrared and solid-state nuclear magnetic resonance spectra to provide the secondary structural characteristics of the proteins from hyperthermophilic archaeon Pyrococcus horikoshii OT3 (hyperthermophilic proteins) in inclusion bodies. The beta-strand-rich single chain Fv fragment (scFv) and alpha-helix-rich interleukin (IL)-4 lost part of the native-like secondary structure in
Recent advances in molecular evolution technology enabled us to identify peptides and antibodies with affinity for inorganic materials. In the field of nanotechnology, the use of the functional peptides and antibodies should aid the construction of interface molecules designed to spontaneously link different nanomaterials; however, few material-binding antibodies, which have much higher affinity than short peptides, have been identified. Here, we generated high affinity antibodies from material-
Recently, recombinant antibodies have been dissected into antigen-binding regions and rebuilt into multivalent high-avidity formats. These new structural designs are expected to improve in vivo pharmacokinetics and efficacy in clinical use. Here, we designed effective recombinant bispecific antibody (BsAb) formats based on hEx3, a humanized bispecific diabody with epidermal growth factor receptor and CD3 retargeting. The bispecific and bivalent IgG-like antibodies engineered from hEx3 (or its si
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