A Strategy for Combinatorial Cavity Design in De Novo Proteins

Selection of a promiscuous minimalist cAMP phosphodiesterase from a library of de novo designed proteins

The ability of unevolved amino acid sequences to become biological catalysts was key to the emergence of life on Earth. However, billions of years of evolution separate complex modern enzymes from their simpler early ancestors. To probe how unevolved sequences can develop new functions, we use ultrahigh-throughput droplet microfluidics to screen for phosphoesterase activity amidst a library of more than one million sequences based on a de novo designed 4-helix bundle. Characterization of hits revealed that acquisition of function involved a large jump in sequence space enriching for truncations that removed >40% of the protein chain. Biophysical characterization of a catalytically active truncated protein revealed that it dimerizes into an α-helical structure, with the gain of function accompanied by increased structural dynamics. The identified phosphodiesterase is a manganese-dependent metalloenzyme that hydrolyses a range of phosphodiesters. It is most active towards cyclic AMP, with a rate acceleration of ~109 and a catalytic proficiency of >1014 M-1, comparable to larger enzymes shaped by billions of years of evolution.

Improving the enzymatic activity and stability of N-carbamoyl hydrolase using deep learning approach

BACKGROUND

Optically active D-amino acids are widely used as intermediates in the synthesis of antibiotics, insecticides, and peptide hormones. Currently, the two-enzyme cascade reaction is the most efficient way to produce D-amino acids using enzymes DHdt and DCase, but DCase is susceptible to heat inactivation. Here, to enhance the enzymatic activity and thermal stability of DCase, a rational design software "Feitian" was developed based on kcat prediction using the deep learning approach.

RESULTS

According to empirical design and prediction of "Feitian" software, six single-point mutants with high kcat value were selected and successfully constructed by site-directed mutagenesis. Out of six, three mutants (Q4C, T212S, and A302C) showed higher enzymatic activity than the wild-type. Furthermore, the combined triple-point mutant DCase-M3 (Q4C/T212S/A302C) exhibited a 4.25-fold increase in activity (29.77 ± 4.52 U) and a 2.25-fold increase in thermal stability as compared to the wild-type, respectively. Through the whole-cell reaction, the high titer of D-HPG (2.57 ± 0.43 mM) was produced by the mutant Q4C/T212S/A302C, which was about 2.04-fold of the wild-type. Molecular dynamics simulation results showed that DCase-M3 significantly enhances the rigidity of the catalytic site and thus increases the activity of DCase-M3.

CONCLUSIONS

In this study, an efficient rational design software "Feitian" was successfully developed with a prediction accuracy of about 50% in enzymatic activity. A triple-point mutant DCase-M3 (Q4C/T212S/A302C) with enhanced enzymatic activity and thermostability was successfully obtained, which could be applied to the development of a fully enzymatic process for the industrial production of D-HPG.

Ligation of Gold Nanoparticles with Self-Assembling, Coiled-Coil Peptides

The surface of gold nanoparticles (AuNPs) can be conjugated with a wide range of highly functional biomolecules. A common pitfall when utilizing AuNPs is their tendency to aggregate, especially when their surface is functionalized with ligands of low molecular weight (no steric repulsion) or ligands of neutral charge (no electrostatic repulsion). For biomedical applications, AuNPs that are colloidally stable are desirable because they have a high surface area and thus reactivity, resist sedimentation, and exhibit uniform optical properties. Here, we engineer the surface of AuNPs so that they remain stable when decorated with coiled-coil (CC) peptides while preserving the native polypeptide properties. We achieve this by using a neutral, mixed ligand layer composed of lipoic acid poly(ethylene glycol) and lipoic acid poly(ethylene glycol) maleimide to attach the CCs. Tuning the surface fraction of each component within the mixed ligand layer also allowed us to control the degree of AuNP labeling with CCs. We demonstrate the dynamic surface properties of these CC-AuNPs by performing a place-exchange reaction and their utility by designing an energy-transfer-based caspase-3 sensor. Overall, this study optimizes the surface chemistry of AuNPs to quantitatively present functional biomolecules while maintaining colloid stability.

A de novo protein catalyzes the synthesis of semiconductor quantum dots

De novo proteins constructed from novel amino acid sequences are distinct from proteins that evolved in nature. Construct K (ConK) is a binary-patterned de novo designed protein that rescues Escherichia coli from otherwise toxic concentrations of copper. ConK was recently found to bind the cofactor PLP (pyridoxal phosphate, the active form of vitamin B₆). Here, we show that ConK catalyzes the desulfurization of cysteine to H₂S, which can be used to synthesize CdS nanocrystals in solution. The CdS nanocrystals are approximately 3 nm, as measured by transmission electron microscope, with optical properties similar to those seen in chemically synthesized quantum dots. The CdS nanocrystals synthesized using ConK have slower growth rates and a different growth mechanism than those synthesized using natural biomineralization pathways. The slower growth rate yields CdS nanocrystals with two desirable properties not observed during biomineralization using natural proteins. First, CdS nanocrystals are predominantly of the zinc blende crystal phase; this is in stark contrast to natural biomineralization routes that produce a mixture of zinc blende and wurtzite phase CdS. Second, in contrast to the growth and eventual precipitation observed in natural biomineralization systems, the CdS nanocrystals produced by ConK stabilize at a final size. Future optimization of CdS nanocrystal growth using ConK-or other de novo proteins-may help to overcome the limits on nanocrystal quality typically observed from natural biomineralization by enabling the synthesis of more stable, high-quality quantum dots at room temperature.

From peptides to proteins: coiled-coil tetramers to single-chain 4-helix bundles

The design of completely synthetic proteins from first principles-de novo protein design-is challenging. This is because, despite recent advances in computational protein-structure prediction and design, we do not understand fully the sequence-to-structure relationships for protein folding, assembly, and stabilization. Antiparallel 4-helix bundles are amongst the most studied scaffolds for de novo protein design. We set out to re-examine this target, and to determine clear sequence-to-structure relationships, or design rules, for the structure. Our aim was to determine a common and robust sequence background for designing multiple de novo 4-helix bundles. In turn, this could be used in chemical and synthetic biology to direct protein-protein interactions and as scaffolds for functional protein design. Our approach starts by analyzing known antiparallel 4-helix coiled-coil structures to deduce design rules. In terms of the heptad repeat, abcdefg -i.e., the sequence signature of many helical bundles-the key features that we identify are: a = Leu, d = Ile, e = Ala, g = Gln, and the use of complementary charged residues at b and c. Next, we implement these rules in the rational design of synthetic peptides to form antiparallel homo- and heterotetramers. Finally, we use the sequence of the homotetramer to derive in one step a single-chain 4-helix-bundle protein for recombinant production in E. coli. All of the assembled designs are confirmed in aqueous solution using biophysical methods, and ultimately by determining high-resolution X-ray crystal structures. Our route from peptides to proteins provides an understanding of the role of each residue in each design.

Recent Progress Using De Novo Design to Study Protein Structure, Design and Binding Interactions

De novo protein design is a powerful methodology used to study natural functions in an artificial-protein context. Since its inception, it has been used to reproduce a plethora of reactions and uncover biophysical principles that are often difficult to extract from direct studies of natural proteins. Natural proteins are capable of assuming a variety of different structures and subsequently binding ligands at impressively high levels of both specificity and affinity. Here, we will review recent examples of de novo design studies on binding reactions for small molecules, nucleic acids, and the formation of protein-protein interactions. We will then discuss some new structural advances in the field. Finally, we will discuss some advancements in computational modeling and design approaches and provide an overview of some modern algorithmic tools being used to design these proteins.

Root of the Tree: The Significance, Evolution, and Origins of the Ribosome

The ribosome is an ancient molecular fossil that provides a telescope to the origins of life. Made from RNA and protein, the ribosome translates mRNA to coded protein in all living systems. Universality, economy, centrality and antiquity are ingrained in translation. The translation machinery dominates the set of genes that are shared as orthologues across the tree of life. The lineage of the translation system defines the universal tree of life. The function of a ribosome is to build ribosomes; to accomplish this task, ribosomes make ribosomal proteins, polymerases, enzymes, and signaling proteins. Every coded protein ever produced by life on Earth has passed through the exit tunnel, which is the birth canal of biology. During the root phase of the tree of life, before the last common ancestor of life (LUCA), exit tunnel evolution is dominant and unremitting. Protein folding coevolved with evolution of the exit tunnel. The ribosome shows that protein folding initiated with intrinsic disorder, supported through a short, primitive exit tunnel. Folding progressed to thermodynamically stable β-structures and then to kinetically trapped α-structures. The latter were enabled by a long, mature exit tunnel that partially offset the general thermodynamic tendency of all polypeptides to form β-sheets. RNA chaperoned the evolution of protein folding from the very beginning. The universal common core of the ribosome, with a mass of nearly 2 million Daltons, was finalized by LUCA. The ribosome entered stasis after LUCA and remained in that state for billions of years. Bacterial ribosomes never left stasis. Archaeal ribosomes have remained near stasis, except for the superphylum Asgard, which has accreted rRNA post LUCA. Eukaryotic ribosomes in some lineages appear to be logarithmically accreting rRNA over the last billion years. Ribosomal expansion in Asgard and Eukarya has been incremental and iterative, without substantial remodeling of pre-existing basal structures. The ribosome preserves information on its history.