Identification of fragments binding to SARS-CoV-2 nsp10 reveals ligand-binding sites in conserved interfaces between nsp10 and nsp14/nsp16.
Frank KozielskiCéleste SeleVladimir O TalibovJiaqi LouDanni DongQian WangXinyue ShiMaria NyblomAnnika RogstamTobias KrojerSuzanne Zoë FisherWolfgang KnechtPublished in: RSC chemical biology (2021)
Since the emergence of SARS-CoV-2 in 2019, Covid-19 has developed into a serious threat to our health, social and economic systems. Although vaccines have been developed in a tour-de-force and are now increasingly available, repurposing of existing drugs has been less successful. There is a clear need to develop new drugs against SARS-CoV-2 that can also be used against future coronavirus infections. Non-structural protein 10 (nsp10) is a conserved stimulator of two enzymes crucial for viral replication, nsp14 and nsp16, exhibiting exoribonuclease and methyltransferase activities. Interfering with RNA proofreading or RNA cap formation represents intervention strategies to inhibit replication. We applied fragment-based screening using nano differential scanning fluorometry and X-ray crystallography to identify ligands targeting SARS-CoV-2 nsp10. We identified four fragments located in two distinct sites: one can be modelled to where it would be located in the nsp14-nsp10 complex interface and the other in the nsp16-nsp10 complex interface. Microscale thermophoresis (MST) experiments were used to quantify fragment affinities for nsp10. Additionally, we showed by MST that the interaction by nsp14 and 10 is weak and thereby that complex formation could be disrupted by small molecules. The fragments will serve as starting points for the development of more potent analogues using fragment growing techniques and structure-based drug design.
Keyphrases
- sars cov
- respiratory syndrome coronavirus
- healthcare
- coronavirus disease
- mental health
- public health
- high resolution
- magnetic resonance imaging
- transcription factor
- risk assessment
- drug delivery
- magnetic resonance
- mass spectrometry
- amino acid
- drug induced
- molecular dynamics simulations
- human health
- electronic health record