背景(考古学)
寡核苷酸
序列(生物学)
计算生物学
化学
毒性
生物化学
生物
基因
古生物学
有机化学
作者
Jaspreet Kaur Bhamra,M. Hari Krishna,George N. Samaan,Sankha Pattanayak,Swagatam Mukhopadhyay
标识
DOI:10.1002/cbic.202500584
摘要
Antisense oligonucleotides (ASOs) offer a promising therapeutic approach for precise RNA-level gene modulation. Despite advancements in chemical modifications to enhance stability and pharmacokinetics, ASOs still face significant challenges, including liver, immunological, renal, and neurological toxicities, potentially leading to high preclinical failure rates. Current oligonucleotide-based drug optimization strategies to overcome such issues often rely on applying a few commonly used chemical architectures (patterns of linker, sugar, or base modifications), which are conventional in the field, or engaging in expensive and time-consuming trial-and-error screening processes involving both sequence changes and positional chemical modifications. These traditional approaches treat nucleotide sequences ("sequence") and sugar/linkage modification chemistries ("chemistry") as independent contributors to toxicity. However, ample evidence in the literature shows that even minor changes in either sequence or chemical modifications can drastically impact toxicity, suggesting an inseparable synergistic relationship between sequence and chemistry. In support of this sequence-chemistry collusion thesis, this manuscript presents a survey of the systemic toxicity potential of several chemically modified gapmer ASOs by investigating the impact of modifying sugar and backbone chemistries on ASO-induced hepatotoxicity, nephrotoxicity, and immune/inflammatory responses. The data unequivocally demonstrate that ASO toxicity is strongly influenced by the interplay between nucleotide sequence, chemical modifications, and the specific position context of those modifications, highlighting the critical need to rationally engineer the optimal sequence and chemical composition to develop safe and active ASO drug candidates instead of discovering suboptimal ASOs through trial-and-error screening campaigns.
科研通智能强力驱动
Strongly Powered by AbleSci AI