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Theranostics 2021Exosomes are cell-derived nanovesicles that are involved in the intercellular transportation of materials. Therapeutics, such as small molecules or nucleic acid drugs,... (Review)
Review
Exosomes are cell-derived nanovesicles that are involved in the intercellular transportation of materials. Therapeutics, such as small molecules or nucleic acid drugs, can be incorporated into exosomes and then delivered to specific types of cells or tissues to realize targeted drug delivery. Targeted delivery increases the local concentration of therapeutics and minimizes side effects. Here, we present a detailed review of exosomes engineering through genetic and chemical methods for targeted drug delivery. Although still in its infancy, exosome-mediated drug delivery boasts low toxicity, low immunogenicity, and high engineerability, and holds promise for cell-free therapies for a wide range of diseases.
Topics: Animals; Drug Delivery Systems; Exosomes; Humans; Membrane Proteins; Membranes; Protein Engineering
PubMed: 33537081
DOI: 10.7150/thno.52570 -
Cell Jul 2022Antibody therapeutics are a large and rapidly expanding drug class providing major health benefits. We provide a snapshot of current antibody therapeutics including... (Review)
Review
Antibody therapeutics are a large and rapidly expanding drug class providing major health benefits. We provide a snapshot of current antibody therapeutics including their formats, common targets, therapeutic areas, and routes of administration. Our focus is on selected emerging directions in antibody design where progress may provide a broad benefit. These topics include enhancing antibodies for cancer, antibody delivery to organs such as the brain, gastrointestinal tract, and lungs, plus antibody developability challenges including immunogenicity risk assessment and mitigation and subcutaneous delivery. Machine learning has the potential, albeit as yet largely unrealized, for a transformative future impact on antibody discovery and engineering.
Topics: Antibodies; Drug Delivery Systems; Humans; Machine Learning; Neoplasms; Protein Engineering
PubMed: 35868279
DOI: 10.1016/j.cell.2022.05.029 -
Cell Aug 2023Prime editing enables a wide variety of precise genome edits in living cells. Here we use protein evolution and engineering to generate prime editors with reduced size...
Prime editing enables a wide variety of precise genome edits in living cells. Here we use protein evolution and engineering to generate prime editors with reduced size and improved efficiency. Using phage-assisted evolution, we improved editing efficiencies of compact reverse transcriptases by up to 22-fold and generated prime editors that are 516-810 base pairs smaller than the current-generation editor PEmax. We discovered that different reverse transcriptases specialize in different types of edits and used this insight to generate reverse transcriptases that outperform PEmax and PEmaxΔRNaseH, the truncated editor used in dual-AAV delivery systems. Finally, we generated Cas9 domains that improve prime editing. These resulting editors (PE6a-g) enhance therapeutically relevant editing in patient-derived fibroblasts and primary human T-cells. PE6 variants also enable longer insertions to be installed in vivo following dual-AAV delivery, achieving 40% loxP insertion in the cortex of the murine brain, a 24-fold improvement compared to previous state-of-the-art prime editors.
Topics: Humans; Animals; Mice; Protein Engineering; Bacteriophages; Brain; Cerebral Cortex; DNA-Directed RNA Polymerases
PubMed: 37657419
DOI: 10.1016/j.cell.2023.07.039 -
Science (New York, N.Y.) Oct 2022Although deep learning has revolutionized protein structure prediction, almost all experimentally characterized de novo protein designs have been generated using...
Although deep learning has revolutionized protein structure prediction, almost all experimentally characterized de novo protein designs have been generated using physically based approaches such as Rosetta. Here, we describe a deep learning-based protein sequence design method, ProteinMPNN, that has outstanding performance in both in silico and experimental tests. On native protein backbones, ProteinMPNN has a sequence recovery of 52.4% compared with 32.9% for Rosetta. The amino acid sequence at different positions can be coupled between single or multiple chains, enabling application to a wide range of current protein design challenges. We demonstrate the broad utility and high accuracy of ProteinMPNN using x-ray crystallography, cryo-electron microscopy, and functional studies by rescuing previously failed designs, which were made using Rosetta or AlphaFold, of protein monomers, cyclic homo-oligomers, tetrahedral nanoparticles, and target-binding proteins.
Topics: Amino Acid Sequence; Cryoelectron Microscopy; Crystallography, X-Ray; Deep Learning; Protein Conformation; Protein Engineering; Proteins
PubMed: 36108050
DOI: 10.1126/science.add2187 -
Protein Science : a Publication of the... Aug 2020New enzyme functions often evolve through the recruitment and optimization of latent promiscuous activities. How do mutations alter the molecular architecture of enzymes... (Review)
Review
New enzyme functions often evolve through the recruitment and optimization of latent promiscuous activities. How do mutations alter the molecular architecture of enzymes to enhance their activities? Can we infer general mechanisms that are common to most enzymes, or does each enzyme require a unique optimization process? The ability to predict the location and type of mutations necessary to enhance an enzyme's activity is critical to protein engineering and rational design. In this review, via the detailed examination of recent studies that have shed new light on the molecular changes underlying the optimization of enzyme function, we provide a mechanistic perspective of enzyme evolution. We first present a global survey of the prevalence of activity-enhancing mutations and their distribution within protein structures. We then delve into the molecular solutions that mediate functional optimization, specifically highlighting several common mechanisms that have been observed across multiple examples. As distinct protein sequences encounter different evolutionary bottlenecks, different mechanisms are likely to emerge along evolutionary trajectories toward improved function. Identifying the specific mechanism(s) that need to be improved upon, and tailoring our engineering efforts to each sequence, may considerably improve our chances to succeed in generating highly efficient catalysts in the future.
Topics: Directed Molecular Evolution; Enzymes; Evolution, Molecular; Protein Domains; Protein Engineering; Substrate Specificity
PubMed: 32557882
DOI: 10.1002/pro.3901 -
Nature Chemical Biology Aug 2020G-protein-coupled receptors (GPCRs) remain major drug targets, despite our incomplete understanding of how they signal through 16 non-visual G-protein signal transducers...
G-protein-coupled receptors (GPCRs) remain major drug targets, despite our incomplete understanding of how they signal through 16 non-visual G-protein signal transducers (collectively named the transducerome) to exert their actions. To address this gap, we have developed an open-source suite of 14 optimized bioluminescence resonance energy transfer (BRET) Gαβγ biosensors (named TRUPATH) to interrogate the transducerome with single pathway resolution in cells. Generated through exhaustive protein engineering and empirical testing, the TRUPATH suite of Gαβγ biosensors includes the first Gα15 and GαGustducin probes. In head-to-head studies, TRUPATH biosensors outperformed first-generation sensors at multiple GPCRs and in different cell lines. Benchmarking studies with TRUPATH biosensors recapitulated previously documented signaling bias and revealed new coupling preferences for prototypic and understudied GPCRs with potential in vivo relevance. To enable a greater understanding of GPCR molecular pharmacology by the scientific community, we have made TRUPATH biosensors easily accessible as a kit through Addgene.
Topics: Biosensing Techniques; GTP-Binding Proteins; HEK293 Cells; Humans; Protein Engineering; Receptors, G-Protein-Coupled; Signal Transduction
PubMed: 32367019
DOI: 10.1038/s41589-020-0535-8 -
Natural Product Reports Jan 2021Covering: up to June 2020Ribosomally-synthesized and post-translationally modified peptides (RiPPs) are a large group of natural products. A community-driven review in... (Review)
Review
Covering: up to June 2020Ribosomally-synthesized and post-translationally modified peptides (RiPPs) are a large group of natural products. A community-driven review in 2013 described the emerging commonalities in the biosynthesis of RiPPs and the opportunities they offered for bioengineering and genome mining. Since then, the field has seen tremendous advances in understanding of the mechanisms by which nature assembles these compounds, in engineering their biosynthetic machinery for a wide range of applications, and in the discovery of entirely new RiPP families using bioinformatic tools developed specifically for this compound class. The First International Conference on RiPPs was held in 2019, and the meeting participants assembled the current review describing new developments since 2013. The review discusses the new classes of RiPPs that have been discovered, the advances in our understanding of the installation of both primary and secondary post-translational modifications, and the mechanisms by which the enzymes recognize the leader peptides in their substrates. In addition, genome mining tools used for RiPP discovery are discussed as well as various strategies for RiPP engineering. An outlook section presents directions for future research.
Topics: Biological Products; Computational Biology; Enzymes; Hydroxylation; Methylation; Peptides; Phosphorylation; Protein Engineering; Protein Processing, Post-Translational; Protein Sorting Signals; Ribosomes
PubMed: 32935693
DOI: 10.1039/d0np00027b -
International Journal of Molecular... Jul 2019Molecular engineering of the green fluorescent protein (GFP) into a robust and stable variant named Superfolder GFP (sfGFP) has revolutionized the field of biosensor... (Review)
Review
Molecular engineering of the green fluorescent protein (GFP) into a robust and stable variant named Superfolder GFP (sfGFP) has revolutionized the field of biosensor development and the use of fluorescent markers in diverse area of biology. sfGFP-based self-associating bipartite split-FP systems have been widely exploited to monitor soluble expression in vitro, localization, and trafficking of proteins in cellulo. A more recent class of split-FP variants, named « tripartite » split-FP, that rely on the self-assembly of three GFP fragments, is particularly well suited for the detection of protein-protein interactions. In this review, we describe the different steps and evolutions that have led to the diversification of superfolder and split-FP reporter systems, and we report an update of their applications in various areas of biology, from structural biology to cell biology.
Topics: Animals; Green Fluorescent Proteins; Humans; Microscopy, Fluorescence; Protein Engineering; Protein Folding
PubMed: 31311175
DOI: 10.3390/ijms20143479 -
Molecular Cell Dec 2019Protein silencing represents an essential tool in biomedical research. Targeted protein degradation (TPD) strategies exemplified by PROTACs are rapidly emerging as...
Protein silencing represents an essential tool in biomedical research. Targeted protein degradation (TPD) strategies exemplified by PROTACs are rapidly emerging as modalities in drug discovery. However, the scope of current TPD techniques is limited because many intracellular materials are not substrates of proteasomal clearance. Here, we described a novel targeted-clearance strategy (autophagy-targeting chimera [AUTAC]) that contains a degradation tag (guanine derivatives) and a warhead to provide target specificity. As expected from the substrate scope of autophagy, AUTAC degraded fragmented mitochondria as well as proteins. Mitochondria-targeted AUTAC accelerated both the removal of dysfunctional fragmented mitochondria and the biogenesis of functionally normal mitochondria in patient-derived fibroblast cells. Cytoprotective effects against acute mitochondrial injuries were also seen. Canonical autophagy is viewed as a nonselective bulk decomposition system, and none of the available autophagy-inducing agents exhibit useful cargo selectivity. With its target specificity, AUTAC provides a new modality for research on autophagy-based drugs.
Topics: Autophagy; Autophagy-Related Proteins; Cell Line; Guanine; Humans; Mitochondria; Mitophagy; Protein Engineering; Protein Kinases; Protein Stability; Proteolysis
PubMed: 31606272
DOI: 10.1016/j.molcel.2019.09.009 -
Science (New York, N.Y.) Jul 2022The binding and catalytic functions of proteins are generally mediated by a small number of functional residues held in place by the overall protein structure. Here, we...
The binding and catalytic functions of proteins are generally mediated by a small number of functional residues held in place by the overall protein structure. Here, we describe deep learning approaches for scaffolding such functional sites without needing to prespecify the fold or secondary structure of the scaffold. The first approach, "constrained hallucination," optimizes sequences such that their predicted structures contain the desired functional site. The second approach, "inpainting," starts from the functional site and fills in additional sequence and structure to create a viable protein scaffold in a single forward pass through a specifically trained RoseTTAFold network. We use these two methods to design candidate immunogens, receptor traps, metalloproteins, enzymes, and protein-binding proteins and validate the designs using a combination of in silico and experimental tests.
Topics: Binding Sites; Catalysis; Deep Learning; Protein Binding; Protein Engineering; Protein Folding; Protein Structure, Secondary; Proteins
PubMed: 35862514
DOI: 10.1126/science.abn2100