Computer Aided Drug Design Center, Department of Pharmaceutical Sciences, School of Pharmacy, University of Maryland Baltimore, Baltimore, Maryland 21201, United States.
J Chem Theory Comput. 2022 Sep 13;18(9):5672-5691. doi: 10.1021/acs.jctc.2c00381. Epub 2022 Aug 1.
RNA molecules can act as potential drug targets in different diseases, as their dysregulated expression or misfolding can alter various cellular processes. Noncoding RNAs account for ∼70% of the human genome, and these molecules can have complex tertiary structures that present a great opportunity for targeting by small molecules. In the present study, the site identification by ligand competitive saturation (SILCS) computational approach is extended to target RNA, termed SILCS-RNA. Extensions to the method include an enhanced oscillating excess chemical potential protocol for the grand canonical Monte Carlo calculations and individual simulations of the neutral and charged solutes from which the SILCS functional group affinity maps (FragMaps) are calculated for subsequent binding site identification and docking calculations. The method is developed and evaluated against seven RNA targets and their reported small molecule ligands. SILCS-RNA provides a detailed characterization of the functional group affinity pattern in the small molecule binding sites, recapitulating the types of functional groups present in the ligands. The developed method is also shown to be useful for identification of new potential binding sites and identifying ligand moieties that contribute to binding, granular information that can facilitate ligand design. However, limitations in the method are evident including the ability to map the regions of binding sites occupied by ligand phosphate moieties and to fully account for the wide range of conformational heterogeneity in RNA associated with binding of different small molecules, emphasizing inherent challenges associated with applying computer-aided drug design methods to RNA. While limitations are present, the current study indicates how the SILCS-RNA approach may enhance drug discovery efforts targeting RNAs with small molecules.
RNA 分子可以作为不同疾病的潜在药物靶点,因为它们的表达失调或错误折叠会改变各种细胞过程。非编码 RNA 占人类基因组的∼70%,这些分子可以具有复杂的三级结构,为小分子靶向提供了很好的机会。在本研究中,配体竞争饱和(SILCS)计算方法的靶标识别扩展到 RNA,称为 SILCS-RNA。该方法的扩展包括增强的超震荡过剩化学势协议,用于吉布斯蒙特卡罗计算和中性和带电溶质的单独模拟,从中计算 SILCS 功能组亲和力图(FragMaps),用于随后的结合部位识别和对接计算。该方法是针对七个 RNA 靶标及其报道的小分子配体开发和评估的。SILCS-RNA 提供了小分子结合部位功能组亲和力模式的详细特征,再现了配体中存在的功能组类型。所开发的方法还被证明可用于识别新的潜在结合部位和识别与结合相关的配体部分,提供有助于配体设计的粒度信息。然而,该方法存在局限性,包括能够映射配体磷酸酯部分占据的结合部位区域以及充分考虑与不同小分子结合相关的 RNA 中广泛的构象异质性,强调了将计算机辅助药物设计方法应用于 RNA 所固有的挑战。虽然存在局限性,但本研究表明,SILCS-RNA 方法如何增强针对小分子的 RNA 药物发现工作。