MRNA‐based therapy has emerged as the most promising nucleic acid therapy in the fight against COVID‐19. However, a safe and efficacious systemic delivery remains a challenge for mRNA therapy. Lipid nanoparticles (LNPs) are currently widely used in mRNA delivery vehicles. Here, a series of ionizable LNPs is rationally designed. YK009‐LNP is an optimal delivery platform to carry mRNA. YK009‐LNP exhibits higher mRNA delivery efficiency, a more favorable biodistribution pattern, and better safety than the approved MC3‐LNP. In addition, mRNA encoding severe acute respiratory syndrome coronavirus 2 Omicron receptor binding domain protein is synthesized and intramuscular administration of mice with YK009‐LNP‐Omicron mRNA induces a robust immune response and immune protective effect. A novel mRNA delivery vehicle with more powerful delivery efficiency and better safety than the approved LNPs is provided here.

Traditional antiviral peptide (AVP) discovery is a time-consuming and expensive process. This study introduces AVP-GPT, a novel deep learning method utilizing transformer-based language models and multimodal architectures specifically designed for AVP design. AVP-GPT demonstrated exceptional efficiency, generating 10,000 unique peptides and identifying potential AVPs within two days on a GPU system. Pre-trained on a respiratory syncytial virus (RSV) dataset, AVP-GPT successfully adapted to influenza A virus (INFVA) and other respiratory viruses. Compared to state-of-the-art models like LSTM and SVM, AVP-GPT achieved significantly lower perplexity (2.09 vs. 16.13) and higher AUC (0.90 vs. 0.82), indicating superior peptide sequence prediction and AVP classification. AVP-GPT generated a diverse set of peptides with excellent novelty and identified candidates with remarkably higher antiviral success rates than conventional design methods. Notably, AVP-GPT generated novel peptides against RSV and INFVA with exceptional potency, including four peptides exhibiting EC50 values around 0.02 uM—the strongest anti-RSV activity reported to date. These findings highlight AVP-GPT’s potential to revolutionize AVP discovery and development, accelerating the creation of novel antiviral drugs. Future studies could explore the application of AVP-GPT to other viral targets and investigate alternative AVP design strategies.

Development of potent and broad‐spectrum drugs against severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) remains one of the top priorities, especially in the cases of the emergence of mutant viruses and inability of current vaccines to prevent viral transmission. In this study, we have generated a novel membrane fusion‐inhibitory lipopeptide IPB29, which is currently under clinical trials; herein, we report its design strategy and preclinical data. First, we surprisingly found that IPB29 with a rigid linker between the peptide sequence and lipid molecule had greatly improved α‐helical structure and antiviral activity. Second, IPB29 potently inhibited a large panel of SARS‐CoV‐2 variants including the previously and currently circulating viruses, such as Omicron XBB.5.1 and EG.5.1. Third, IPB29 could also cross‐neutralize the bat‐ and pangolin‐isolated SARS‐CoV‐2‐related CoVs (RatG13, PCoV‐GD, and PCoV‐GX) and other human CoVs (SARS‐CoV, MERS‐CoV, HCoV‐NL63, and HCoV‐229E). Fourth, IPB29 administrated as an inhalation solution (IPB29‐IS) in Syrian hamsters exhibited high therapeutic and preventive efficacies against SARS‐CoV‐2 Delta or Omicron variant. Fifth, the pharmacokinetic profiles and safety pharmacology of IPB29‐IS were extensively characterized, providing data to support its evaluation in humans. In conclusion, our studies have demonstrated a novel design strategy for viral fusion inhibitors and offered an ideal drug candidate against SARS‐CoV‐2 and other coronaviruses.

Angiotensinogen (AGT) is the precursor of angiotensin II, a potent vasopressor in the renin-angiotensin-aldosterone system. Small interfering RNAs (siRNAs) targeting hepatic AGT can lower blood pressure in hypertension patients by reducing AGT levels, with effects lasting over 6 months. Existing siRNA molecules are effective, but novel ones with better inhibitory activity and longer duration periods may be developed. In this study, we demonstrated an entire development process for a novel siRNA targeting hepatic AGT. Through the proper combination of bioinformatic on-target/off-target screening on sequences, chemical modification patterns optimization, and liver-targeting delivery ligands conjugation, we have successfully developed several promising siRNAs with equivalent or better inhibitory activity, duration of effect, and safety profile compared with previously reported siRNA. Moreover, our comprehensive analysis has elucidated the correlation between the efficacy and free energy of siRNAs. Currently, there exists no reliable model capable of precisely predicting the activity and off-target risk associated with fully modified siRNAs. Therefore, the implementation of efficient screening procedures is of utmost importance during the development of siRNA candidates. This study presents a meticulous and valuable reference for the development of potent and safe siRNAs on other targets.

Current therapeutics for chronic hepatitis B virus (HBV) infection are insufficient due to immune exhaustion caused by high circulating hepatitis B surface antigen (HBsAg) levels. Here, an HBV S region-targeted small interfering RNA (siRNA) is reported, aiming to dramatically suppress HBsAg and provide windows for host immune restoration. This siRNA agent, called KC13-M2G2, exhibits potent antiviral efficacy against all HBV genotypes in vitro. Notably, in multiple mouse models, KC13-M2G2 triggers rapid and sustained loss of HBsAg and HBV DNA accompanied by hepatitis B surface antibody seroconversion, outperforming the clinical drug elebsiran and bepirovirsen. Toxicity studies in Sprague-Dawley rats and cynomolgus monkeys indicate satisfactory biosafety profiles of KC13-M2G2. Given that elebsiran and bepirovirsen have achieved a functional cure rate of no more than 20% in their clinical studies, KC13-M2G2 as a more potent candidate drug is expected to exhibit superior performance in clinical applications.