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Metabolic Engineering
Published in Jean F. Challacombe, Metabolic Pathway Engineering, 2021
The tools of synthetic biology can be used to design custom organisms with desirable traits, and these include DNA synthesis, synthetic protein scaffolds, construction and modulation of synthetic expression components, design, construction, and optimization of novel metabolic pathways and complex cellular networks, and the use of regulatory RNAs to influence gene expression [15, 16, 18, 79–81]. Pathway prediction algorithms that can be used for designing synthetic pathways include Biochemical Network Integrated Computational Explorer (BNICE) [82], RetroPath [83, 84], GEM-Path [85], OptStrain [86], and DESHARKY [87]. The rest of the tools shown in Fig. 5.2 are described in these primary publications [88–112], and a more comprehensive set of tools for pathway design is reviewed here [113]. In addition to pathway prediction, new or improved enzymes can be created with computational protein design tools to identify core parts of protein structure, provide target sites for engineering, and facilitate de novo protein design [114].
Nanoamorphous Drug Delivery Technology and an Exploration of Nanofabrication
Published in Vineet Kumar, Praveen Guleria, Nandita Dasgupta, Shivendu Ranjan, Functionalized Nanomaterials II, 2021
Wen Chin Foo, Keat Theng Chow, Yuet Mei Khong, Rajeev Gokhale
The examples elucidated above illustrate the burgeoning field of protein therapeutics. Nevertheless, it is only in recent years that protein nanotechnology has become an emerging field. Protein nanotechnology refers to the utility of proteins as engineering materials for nanofabrication. This natural development comes as no surprise since proteins possess suitable characteristics making them ideal candidates for nanofabrication: (i) Proteins exist in the nanoscale; (ii) Proteins are the most versatile of biological building blocks with enormous possibilities for chemical functionalization and structural complexity; (iii) Proteins are nanotherapeutics per se, hence can effect therapeutic/synergistic functions; (iv) The incorporation of active proteins as those in molecular machines into nanostructures point to the exciting possibility of engineering nanomotors, although this topic is out of the scope of our discussion. The hierarchical structure of proteins engenders the complex architecture and specificity required for structure-activity relationships, however in silico techniques still fall short of the power needed for de novo protein design, thus current methods manipulate existing protein fragments to create novel structures by engineering specific interactions. Such constructs comprise oligomerizing domains which can be tethered via ligand binding or disulfide bridges, fused by DNA recombination, or designed to interact via novel interaction surfaces (Drobnak et al. 2016). These modular building blocks have been reported to self-assemble into cage-like nanoparticles with potential application for drug delivery (King et al. 2014). Another novel approach is designed protein origami which uses coiled-coil dimers as modular building blocks to form a cage-like polyhedron. The coiled-coil modules are joined by flexible peptide linkers which act as hinges at the vertices of the polyhedron (Ljubetič et al. 2017). Protein-polymer conjugates have also found useful application as bio-hybrid materials for nanofabrication by leveraging on the structural and functional complexity afforded by proteins, and the diversity for chemical functionalization of polymeric materials. Perhaps, the ideal situation is one where the protein is both the nanotherapeutic and the nanostructure. This is exemplified by the fabrication of nanostructures consisting of only immune signals (antigen and adjuvant) without any polymeric carrier, termed immune polyelectrolyte multilayers (‘iPEM’) as they were fabricated using a layer-by-layer electronic process (Chiu et al. 2016).
Cadmium contamination in food crops: Risk assessment and control in smart age
Published in Critical Reviews in Environmental Science and Technology, 2023
Yan Huili, Zhang Hezifan, Hao Shuangnan, Wang Luyao, Xu Wenxiu, Ma Mi, Luo Yongming, He Zhenyan
With the help of emerging technologies such as de novo protein design and homology modeling, artificial design sites can be directionally and universally predicted. With deeper acknowledgement of mechanisms, researchers have designed artificial variations based on several key sites. i.e., Plegaria et al., de novo designed an artificial protein apo α3DIV containing a 3-cysteine heavy-metal binding motif/sites (Cys18-Cys28-Cys68), which showed activity of sequestering Cd, Pb and Hg and proved the feasibility of de novo designing Cd-chelating proteins (Plegaria et al., 2015) Using crystal structures and literature on NRAMP structure-to-function, libraries were semi-rationally built to create variants into native yeast heavy metal transporter SMF1. By introducing artificial sites of S105C, M276C, and S269T, a SMF1 transporter specific to Cd was created (Sun et al., 2019). Based on homology modeling, analysis highlighted amino acids sites forming the metal permeation pathway of HMA4, whose importance was subsequently investigated functionally through mutagenesis and complementation experiments in plants. The results revealed artificial HMA4 mutants exhibited different Cd translocation abilities in Arabidopsis, providing instruments for the future design of low-Cd food crops (Lekeux et al., 2019).
In-silico investigation of the efficiency of microbial dioxygenases in degradation of sulfonylurea group herbicides
Published in Bioremediation Journal, 2022
Sutapa Bauri, Madhab Kumar Sen, Renuka Das, Sunil Kanti Mondal
Among the most dynamically developing scientific fields, protein engineering has changed thrillingly due to developing technologies like high throughput and deep sequencing, directed evolution methods, and fluorescence-based sorting technologies. In silico studies, aiding in protein design and engineering are being developed with new experimental techniques. Results from our molecular docking studies with microbial dioxygenase from three different microorganisms (Pseudomonas putida, Brevibacterium fuscum and Arthrobacter globiformis) with chlorsulfuron and metsulfuron-methyl, showed that homoprotocatechuate 2,3-dioxygenase from B. fuscum and A. globiformis were more effective than catechol 2, 3-dioxygenase from P. putida. So, B. fuscum and A. globiformis have more potential than P. putida to remediate chlorsulfuron and metsulfuron-methyl. Our results will help in the scientific development and usage of herbicides and their microbial degradation mechanisms. The bioinformatics approaches can be most successfully used for engineering protein stability due to their ability to produce good resolution data and identify stabilizing mutations. The results of this study will be socially beneficial in order to maintain the soil health in which appropriate growth of crop plants are dependent. Therefore, microbial biodegradation of herbicides can be considered as a suitable option for future studies. In future, use of bioherbicides is expected to relieve our dependency on chlorsulfuron and metsulfuron-methyl to minimize ever-increasing environmental pollution.
Subsets of adjacent nodes (SOAN): a fast method for computing suboptimal paths in protein dynamic networks
Published in Molecular Physics, 2021
Thomas Dodd, Xin-Qiu Yao, Donald Hamelberg, Ivaylo Ivanov
Allosteric regulation is a key functional feature of many proteins and protein complexes, involving communication between distal protein regions. The process is initiated by ligand binding or some other structural or dynamic perturbation, which occurs at one site and is subsequently propagated through the protein to influence the activities at a distal site. Knowledge of allosteric communication mechanisms has an impact on the fields of rational drug discovery [1] and protein design [2]. While classical models of allosteric regulation have suggested that a binding event induces substantial conformational changes in the distal site [3,4], other studies have observed allostery in the absence of large-scale conformational change [5,6]. This suggests that subtle differences in dynamics can alter the population distribution of the conformational ensemble without drastically altering the average conformation of the biomolecule.