PanDDA analysis of DCP2B screened against DSPL/DSi Poised, OxXChem fragment libraries and initial follow up chemistry

SGC Oxford has performed a crystallographic fragment screen, and initial follow up chemistry on the Human m7GpppN-mRNA Hydrolase (DCP2/NUDT20, UniProtKB - QIU60). All structures with clearly identifiable ligands were deposited in the Protein Data Bank under Group Deposition ID G_1002061, the corresponding apo structures are deposited under Group Deposition ID G_1002062. Experiment Crystals were prepared at the XChem facility of the Diamond Light Source (DLS). Briefly, crystals were soaked overnight with two fragment libraries; the Diamond- SGC Poised Library set (Cox et al., 2016) and the OxXChem set with nominal fragment concentrations of 100 mM, with DMSO at 20% v/v. Additionally, a series of follow-up compounds based on an initial fragment hit was synthesized and soaked overnight with nominal compound concentrations of 10-200 mM, with DMSO at 20% v/v. All datasets were collected at MX beamlines at DLS. Autoprocessed datasets were analysed by Pan-Dataset Density Analysis (PanDDA) (Pearce et al., 2017). All ligands that were clearly identifiable in PanDDA event maps were modelled, refined and deposited into the PDB. Content This repository contains: Modelled Data Organised by crystal identifier, each folder contains: Autoprocessing data from Diamond Light Source automated pipelines (including MTZ) PDB, CIF & PNG files of all the soaked compounds PanDDA event maps Final refine.pdb and refine.mtz files of all ligand bound structure Superposed structures (refine.pdb) Separated bound & ground states (refine.split.bound.pdb & refine.split.ground.pdb) PanDDA Analysis Data This is split into two directories. This split is only due to technical limitations at the time of preparation of the data, and the timeliness of the data. All results from the PanDDA analysis, including ground-state-mean maps and PanDDA event & Z-maps for all ligand bound structures.This work was supported by funding from the Engineering and Physical Sciences Research Council (EPSRC) and the Medical Research Council (MRC) [grant number EP/L016044/1]. ERN acknowledges support provided by Novartis & UCB Pharma. The SGC is a registered charity (number 1097737) that receives funds from AbbVie, Bayer Pharma AG, Boehringer Ingelheim, Canada Foundation for Innovation, Eshelman Institute for Innovation, Genome Canada, Innovative Medicines Initiative (EU/EFPIA) [ULTRA-DD grant no. 115766], Janssen, Merck KGaA Darmstadt Germany, MSD, Novartis Pharma AG, Ontario Ministry of Economic Development and Innovation, Pfizer, São Paulo Research Foundation-FAPESP, Takeda, and Wellcome [106169/ZZ14/Z]