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The α-helix is pre-eminent in structural biology1 and widely exploited in protein folding2, design3 and engineering4. Although other helical peptide conformations do exist near to the α-helical region of conformational space—namely, 310-helices and π-helices5—these occur much less frequently in protein structures. Less favourable internal energies and reduced tendencies to pack into higher-order structures mean that 310-helices rarely exceed six residues in length in natural proteins, and that they tend not to form normal supersecondary, tertiary or quaternary interactions. Here we show that despite their absence in nature, synthetic peptide assemblies can be built from 310-helices. We report the rational design, solution-phase characterization and an X-ray crystal structure for water-soluble bundles of 310-helices with consolidated hydrophobic cores. The design uses six-residue repeats informed by analysing 310-helical conformations in known protein structures, and incorporates α-aminoisobutyric acid residues. Design iterations reveal a tipping point between α-helical and 310-helical folding, and identify features required for stabilizing assemblies of 310-helices. This work provides principles and rules to open opportunities for designing into this hitherto unexplored region of protein-structure space. A study demonstrates the rational de novo design of water-soluble assemblies constructed from long 310-helical peptides, and details their characterization by circular dichroism spectroscopy, analytical ultracentrifugation and X-ray crystallography.
Computational Protein Design has the potential to contribute to major advances in enzyme technology, vaccine design, receptor-ligand engineering, biomaterials, nanosensors, and synthetic biology. Although Protein Design is a challenging problem, proteins can be designed by experts in Protein Design, …
A protein roadblock forms when a protein binds DNA and hinders translocation of other DNA binding proteins. These roadblocks can have significant effects on gene expression and regulation as well as DNA binding. Experimental methods for studying the effects of such roadblocks often target endogenous sites or introduce non-variable specific sites into DNAs to create binding sites for artificially introduced protein roadblocks. In this work, we describe a method to create programmable roadblocks using dCas9, a cleavage deficient mutant of the CRISPR effector nuclease Cas9. The programmability allows us to custom design target sites in a synthetic gene intended for in vitro studies. These target sites can be coded with multivalency—in our case, internal restriction sites which can be used in validation studies to verify complete binding of the roadblock. We provide full protocols and sequences and demonstrate how to use the internal restriction sites to verify complete binding of the roadblock. We also provide example results of the effect of DNA roadblocks on the translocation of the restriction endonuclease NdeI, which searches for its cognate site using one dimensional diffusion along DNA.
A prototypical biocomposite block comprising a blend of bacteria, fungi and feedstock can be assembled into human-sized, living structures with self-healing and environmental sensing capabilities.
Genetic networks mimic electronic circuits to perform a range of logic functions. Equipped with a series of eight small test tubes, the device glows green when it detects a contaminant. The number of tubes that glow depend upon how much contamination is present. If only one tube glows, then the w
Through synthetic biology, scientists can add novel functions to cells, such as the ability to produce new materials or detect and respond in specific ways to diseases. Though the applications are exciting, the process suffers from some inefficiencies—one of which Stanford University chemical engineer Xiaojing Gao is working to avoid.
Reconfigurable organisms and dissociated stem cells were simulated as elastic voxels using a version of a voxel-based soft-body simulator (40) modified to run on highly parallelized (GPU-based) computing platforms (SI Appendix, Fig. S5).
Synthetic biology has the potential to transform cell- and gene-based therapies for a variety of diseases. Sophisticated tools are now available for both eukaryotic and prokaryotic cells to engineer cells to selectively achieve therapeutic effects in response to one or more disease-related signals, …
The emerging community of cell-free synthetic biology aspires to build complex biochemical and genetic systems with functions that mimic or even exceed those in living cells. To achieve such functions, cell-free systems must be able to sense and respond to the complex chemical signals within and out …
One of the most remarkable features of biological systems is their ability to adapt to the constantly changing environment. By harnessing principles o…
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Cell biology; Stem cells research; Bioinformatics.
Synthetic biology research and its industrial applications rely on deterministic spatiotemporal control of gene expression. Recently, electrochemical control of gene expression has been demonstrated in electrogenetic sys- tems (redox-responsive promoters used alongside redox inducers and electrodes), allowing for the direct inte- gration of electronics with biological processes. However, the use of electrogenetic systems is limited by poor activity, tunability, and standardization. In this work, we developed a strong, unidirectional, redox-responsive promoter before deriving a mutant promoter library with a spectrum of strengths. We constructed genetic circuits with these parts and demonstrated their activation by multiple classes of redox molecules. Last, we demonstrated electrochemical activation of gene expression under aerobic conditions using a novel, modular bioelectro- chemical device. These genetic and electrochemical tools facilitate the design and improve the performance of electrogenetic systems. Furthermore, the genetic design strategies used can be applied to other redox-responsive promoters to further expand the available tools for electrogenetics. https://www.science.org/doi/pdf/10.1126/sciadv.abm5091
Self-organized collective cell behaviors as design principles for synthetic developmental biology
Over the past two decades, molecular cell biology has graduated from a mostly analytic science to one with substantial synthetic capability. This success is built on a deep understanding of the structure and function of biomolecules and molecular mechanisms. For synthetic biology to achieve similar success at the scale of tissues and organs, an equally deep understanding of the principles of development is required. Here, we review some of the central concepts and recent progress in tissue patterning, morphogenesis and collective cell migration and discuss their value for synthetic developmental biology, emphasizing in particular the power of (guided) self-organization and the role of theoretical advances in making developmental insights applicable in synthesis.
Protein-protein interactions (PPIs) govern numerous cellular functions in terms of signaling, transport, defense and many others. Designing novel PPIs poses a fundamental challenge to our understanding of molecular interactions. The capability to robustly engineer PPIs has immense potential for the …
A computational and experimental strategy was developed to redesign biosynthetic gene
clusters into synthetic genetic elements that can be expressed across a wide range
of prokaryote and eukaryote hosts, expanding our ability to discover and characterize
a variety of natural products and biosynthetic pathways.
Mammalian cells were engineered with both a plant hormone system, which provides a
diffusive communication channel, and robust synthetic signaling pathways that allow
for population sensing and control through auxin.
The systematic design of functional peptides has technological and therapeutic applications. However, there is a need for pattern-based search engines that help locate desired functional motifs in primary sequences regardless of their evolutionary conservation
Deep-learning algorithms such as AlphaFold2 and RoseTTAFold can now predict a protein’s 3D shape from its linear sequence — a huge boon to structural biologists.
Protein-protein interactions play critical roles in biology, but the structures of many eukaryotic protein complexes are unknown, and there are likely many interactions not yet identified. We tak
13C metabolic flux analysis (MFA) has emerged as a powerful tool for synthetic biology. This optimization-based approach suffers long computation time and unstable solutions depending on the initial guess. Here, we develop a machine-learning-based framework for 13C fluxomics. S …
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