Outcomes of the EMDataResource cryo-EM Ligand Modeling Challenge
Catherine L. Lawson, Andriy Kryshtafovych, Grigore Pintilie, S.K. Burley, Jiří Černý, Vincent B. Chen, Paul Emsley, Alberto Gobbi, A. Joachimiak, Sigrid Noreng, Michael G. Prisant, Randy J. Read, Jane S. Richardson, Alexis Rohou, Bohdan Schneider, Benjamin D. Sellers, Chenghua Shao, Elizabeth Sourial, Chris Williams, Christopher J. Williams, Ying Yang, Venkat Abbaraju, Pavel V. Afonine, Matthew L. Baker, Paul S. Bond, Tom L. Blundell, Tom Burnley, Arthur J. Campbell, Renzhi Cao, Jianlin Cheng, Grzegorz Chojnowski, Kevin Cowtan, Frank DiMaio, Reza Esmaeeli, Nabin Giri, Helmut Grubmüller, Soon Wen Hoh, Jie Hou, Corey F. Hryc, Carola Hunte, Maxim Igaev, Agnel Praveen Joseph, Wei‐Chun Kao, Daisuke Kihara, Dilip Kumar, Lijun Lang, Sean Lin, Sai Raghavendra Maddhuri Venkata Subramaniya, Sumit Mittal, Arup Mondal, Nigel W. Moriarty, Andrew Muenks, Garib N. Murshudov, Robert A. Nicholls, Mateusz Olek, Colin M. Palmer, Alberto Pérez, Emmi Pohjolainen, Karunakar R. Pothula, Christopher N. Rowley, Daipayan Sarkar, Luisa U. Schäfer, Christopher J. Schlicksup, Gunnar F. Schröder, Mrinal Shekhar, Dong Si, Abhishek Singharoy, Oleg V. Sobolev, Genki Terashi, Andrea C. Vaiana, Sundeep Chaitanya Vedithi, Jacob Verburgt, Xiao Wang, Rangana Warshamanage, Martyn Winn, Simone Weyand, Keitaro Yamashita, Minglei Zhao, Michael F. Schmid, Helen M. Berman, Wah Chiu
Abstract
The EMDataResource Ligand Model Challenge aimed to assess the reliability and reproducibility of modeling ligands bound to protein and protein–nucleic acid complexes in cryogenic electron microscopy (cryo-EM) maps determined at near-atomic (1.9–2.5 Å) resolution. Three published maps were selected as targets: Escherichia coli beta-galactosidase with inhibitor, SARS-CoV-2 virus RNA-dependent RNA polymerase with covalently bound nucleotide analog and SARS-CoV-2 virus ion channel ORF3a with bound lipid. Sixty-one models were submitted from 17 independent research groups, each with supporting workflow details. The quality of submitted ligand models and surrounding atoms were analyzed by visual inspection and quantification of local map quality, model-to-map fit, geometry, energetics and contact scores. A composite rather than a single score was needed to assess macromolecule+ligand model quality. These observations lead us to recommend best practices for assessing cryo-EM structures of liganded macromolecules reported at near-atomic resolution. The EMDataResource Ligand Model Challenge aimed at assessing the reliability and reproducibility of modeling ligands bound to protein and protein–nucleic acid complexes in cryo-EM maps determined at near-atomic resolution. This analysis presents the results and recommends best practices for assessing cryo-EM structures of liganded macromolecules.