Sidharthan Vaishnavi, Sibley Christopher D, Dunne-Dombrink Kara, Yang Mo, Zahurancik Walter J, Balaratnam Sumirtha, Wilburn Damien B, Schneekloth John S, Gopalan Venkat
Department of Chemistry and Biochemistry, The Ohio State University, Columbus, OH 43210, USA.
Center for RNA Biology, The Ohio State University, Columbus, OH 43210, USA.
Nucleic Acids Res. 2025 Jan 7;53(1). doi: 10.1093/nar/gkae1190.
Despite interest in developing therapeutics that leverage binding pockets in structured RNAs-whose dysregulation leads to diseases-such drug discovery efforts are limited. Here, we have used a small molecule microarray (SMM) screen to find inhibitors of a large ribozyme: the Methanobrevibacter smithii RNase P RNA (Msm RPR, ∼300 nt). The ribonucleoprotein form of RNase P, which catalyzes the 5'-maturation of precursor tRNAs, is a suitable drug target as it is essential, structurally diverse across life domains, and present in low copy. From an SMM screen of 7,300 compounds followed by selectivity profiling, we identified 48 hits that bound specifically to the Msm RPR-the catalytic subunit in Msm (archaeal) RNase P. When we tested these hits in precursor-tRNA cleavage assays, we discovered that the drug-like M1, a diaryl-piperidine, inhibits Msm RPR (KI, 17 ± 1 μM) but not a structurally related archaeal RPR, and binds to Msm RPR with a KD(app) of 8 ± 3 μM. Structure-activity relationship analyses performed with synthesized analogs pinpointed groups in M1 that are important for its ability to inhibit Msm RPR. Overall, the SMM method offers prospects for advancing RNA druggability by identifying new privileged scaffolds/chemotypes that bind large, structured RNAs.
尽管人们对开发利用结构化RNA中结合口袋的疗法很感兴趣(其失调会导致疾病),但此类药物发现工作仍很有限。在此,我们使用小分子微阵列(SMM)筛选来寻找一种大型核酶的抑制剂:史密斯甲烷短杆菌核糖核酸酶P RNA(Msm RPR,约300个核苷酸)。核糖核酸酶P的核糖核蛋白形式催化前体tRNA的5'成熟,它是一个合适的药物靶点,因为它至关重要,在生命域中结构多样,且拷贝数低。通过对7300种化合物进行SMM筛选并随后进行选择性分析,我们鉴定出48种与Msm RPR特异性结合的命中物——Msm(古细菌)核糖核酸酶P中的催化亚基。当我们在前体tRNA切割试验中测试这些命中物时,我们发现类药物M1(一种二芳基哌啶)抑制Msm RPR(抑制常数KI,17±1 μM),但不抑制结构相关的古细菌RPR,并且以8±3 μM的表观解离常数KD(app)与Msm RPR结合。用合成类似物进行的构效关系分析确定了M1中对其抑制Msm RPR能力很重要的基团。总体而言,SMM方法通过识别与大型结构化RNA结合的新的优势支架/化学型,为推进RNA可药用性提供了前景。