Cracking the Code: Enhancing Molecular Tools for Progress in Nanobiotechnology

Abstract

Nature continually refines its processes for optimal efficiency, especially within biological systems. This article explores the collaborative efforts of researchers worldwide, aiming to mimic nature's efficiency by developing smarter and more effective nanoscale technologies and biomaterials. Recent advancements highlight progress and prospects in leveraging engineered nucleic acids and proteins for specific tasks, drawing inspiration from natural functions. The focus is developing improved methods for characterizing, understanding, and reprogramming these materials to perform user-defined functions, including personalized therapeutics, targeted drug delivery approaches, engineered scaffolds, and reconfigurable nanodevices. Contributions from academia, government agencies, biotech, and medical settings offer diverse perspectives, promising a comprehensive approach to broad nanobiotechnology objectives. Encompassing topics from mRNA vaccine design to programmable protein-based nanocomputing agents, this work provides insightful perspectives on the trajectory of nanobiotechnology toward a future of enhanced biomimicry and technological innovation.

Keywords: ISRNN; RNA nanotechnology; mRNA vaccines; nanobiotechnology; nanoparticles; nucleic acid therapies.

Figure 1

On the basis of the fundamental principle of the central dogma in molecular biology, we observe the convergence of DNA, RNA, and protein technologies, which collectively drive personalized treatment strategies forward.

Figure 2

Elucidating the coding language of nucleic acids and modifications. (A) Using 3Dpol to read modified RNA nucleotides. 3Dpol is the RNA-dependent RNA polymerase that is processive in reading through the viral genome of 7500 nucleotides in one round of replication. Using a recombinant 3Dpol prepared in the Hou lab, it was shown that the enzyme readily reads through the entire sequence of a native-state E. coli tRNA-Arg (ACG), which contains nine modified nucleotides of diverse chemical structures (shown as blue circles) generating double-stranded (ds) products that migrated in distribution both as a single-stranded ssRNA and dsRNA species on a denaturing gel, where the RNA sample was heated at 85 °C for 1 min and loaded in a 7 M urea loading dye onto a 12% PAGE/7 M urea gel and run in the Tris-borate-EDTA buffer at 60 °C. Analysis of the 3Dpol replication reaction showed that nearly 100% of the tRNA-hairpin substrate was converted to products in 4 mM Mn²⁺, but only 50% of the substrate was converted to products in 4 mM Mg²⁺, indicating that Mn²⁺ facilitated the enzyme to overcome the secondary and tertiary structure of the tRNA. (B) Modular composition of mRNA with marked structural and functional elements, i.e., 5′ cap structure (G), 5′ and 3′ untranslated regions (UTRs), gene of interest (GOI), polyadenylated tail (poly(A) tail), and various protein factors interacting with them and facilitating their functions, i.e., 40S ribosomal subunit, eIF—transcription initiation factors, PABP—poly(A) binding protein. These elements can be tweaked for the optimal design of mRNA-based vaccines. (C) Cryo-EM structure of SARS CoV-2 Nsp15 bound to dsRNA (PDB ID: 7TJ2). Three different Nsp15 protomers from the hexamer engage the dsRNA substrate (magenta). Residues involved in mediating RNA cleavage (H235*, K291, and H250) and uracil specificity are indicated (S294, N278). H235 is denoted with an* as this residue was mutated to alanine to trap the RNA in the active site. W333 π stacks with the base 3′ of the flipped uracil to help stabilize and engage the dsRNA.

Figure 3

Targeted therapies using nucleic acids. Antagonist conjugation improves RNA nanoparticle binding to SCLC neuroendocrine cells. RNA nanoparticle–cell interaction can be measured using live cell confocal microscopy.

Figure 4

RNA–DNA fibers engineered for reversible control of blood clotting. (A) Anticoagulation and kill-switch mechanisms: RNA–DNA fibers bind and inactivate thrombin, halting the blood clotting. Kill-switches interact with anticoagulant fibers, restoring thrombin function and generating small byproducts for rapid renal excretion. (B) Anticoagulant fibers inhibit the blood coagulation cascade triggered by cancer cells.

Figure 5

Single-stranded RNA nanostars (shown in different conformations) that interact via kissing loops to form phase-separated RNA condensates. RNA strands are designed computationally and can be adapted to optimize the biophysical properties of the condensates and their interactions. By including RNA aptamers, condensates can be used to recruit peptides and small molecules with specificity.

Figure 6

(A) Exosomes were modified with RNA nanoparticles to load therapeutic RNA nanoparticles harboring miR122 and paclitaxel with specific delivery to hepatocellular carcinoma through GalNAc displaying RNA nanoparticles. Resulting exosomes were delivered intravenously into mice harboring hepatocellular carcinoma xenografts, were specifically accumulated into tumors and overcome drug efflux mechanisms for effective tumor inhibition. (B) Cell-free protein synthesis uses cellular machinery in solutions to synthesize membrane proteins, which are then inserted into nanovesicle membranes. Panel A reproduced with permission from ref (60). Copyright 2023 Elsevier Inc.

Figure 7

Evaluation of various models for predicting RNA-ligand binding modes and virtual screening against a dynamic ensemble of HIV-1 TAR structures. (A) Top-1 and top-3 success rates were achieved by various docking/scoring models during the redocking of a test set with 38 RNA-ligand complexes. Results for DrugScore RNA, DOCK6, and LigandRNA+DOCK6 are adopted from the literature. (B) The secondary structure of the 29-nt HIV-1 TAR was used in this study. (C) Alignment of the 20 distinct residual dipolar coupling (RDC)-derived HIV-1 TAR conformations.^, (D) Illustration of five representative RDC-derived 3D conformations. (E) Enrichment factors (EFs) are achieved by various scoring functions when considering the top-3%, top-5%, and top-10% ranked compounds during virtual screening against the RDC-derived HIV-1 TAR structural ensemble. The compound library [19] includes 651 compounds, with 14 demonstrating TAR binding capabilities. (F) Illustration of an experimentally verified hit compound [19] along with its top-scored binding mode predicted by RLDOCK. The potential stacking and hydrogen bonding interactions are highlighted with dashed lines in black and cyan, respectively. Only nucleotides engaged in stacking or hydrogen bonding with the ligand are shown in stick representations and labeled with nucleotides, the remaining nucleotides are shown as cartoon ladders.

Figure 8

Design of Aha dTRAP variants and Cryo-EM data analysis. (A) Left: apo dTRAP, middle: holo WT-Mut dTRAP, right: apo dTRAP. (B) Side view of the Cryo-EM maps of dTRAP. Left: apo dTRAP, middle: holo dTRAP WT-Mut, right: holo dTRAP. The boxed region is the ligand binding site between adjacent protomers.

Figure 9

Conceptual organization of NACs and nanozymes. (A) Linear representation of the engineered NAC: RUs are inserted in loop regions of the target proteins and are distal from the active site. The regulation of an active site of a target protein is achieved by inserting small protein domains, regulatory units (RU1, RU2), into the target gene. These regulatory units sense a particular queue, either endogenous or exogenous, and through allosteric coupling to the active site regulate the activity of the target protein. (B) Three-dimensional wiring of NAC. The regulation of RUs’ conformations leads to a change in NAC activity. (B–D) Rational design of nanozymes and their therapeutic applications.

Figure 10

Race toward therapeutic precision begins at the design phase, where the integration of artificial intelligence (AI) and liposomal, protein, and nucleic acid technologies navigates a challenging track, mastering hurdles that represent critical obstacles in therapeutic development: delivery barriers, targeting precision, stability and sustainability, safety, and cost-effectiveness. Overcoming these hurdles will lead us toward a future where tailored therapeutic treatments offer precision and efficacy.