Critical Assessment of protein Structure Prediction (CASP) is a community-wide, worldwide experiment for protein structure prediction taking place every two years since 1994. CASP provides research groups with an opportunity to objectively test their structure prediction methods and delivers an independent assessment of the state of the art in protein structure modeling to the research community and software users. Even though the primary goal of CASP is to help advance the methods of identifying protein three-dimensional structure from its amino acid sequence, many view the experiment more as a “world championship” in this field of science. More than 100 research groups from all over the world participate in CASP on a regular basis and it is not uncommon for entire groups to suspend their other research for months while they focus on getting their servers ready for the experiment and on performing the detailed predictions.
Rosetta@home is a distributed computing project for protein structure prediction on the Berkeley Open Infrastructure for Network Computing (BOINC) platform, run by the Baker laboratory at the University of Washington. Rosetta@home aims to predict protein–protein docking and design new proteins with the help of about fifty-five thousand active volunteered computers processing at over 487,946 GigaFLOPS on average as of September 19, 2020. Foldit, a Rosetta@home videogame, aims to reach these goals with a crowdsourcing approach. Though much of the project is oriented toward basic research to improve the accuracy and robustness of proteomics methods, Rosetta@home also does applied research on malaria, Alzheimer's disease, and other pathologies.
The global distance test (GDT), also written as GDT_TS to represent "total score", is a measure of similarity between two protein structures with known amino acid correspondences but different tertiary structures. It is most commonly used to compare the results of protein structure prediction to the experimentally determined structure as measured by X-ray crystallography, protein NMR, or, increasingly, cryoelectron microscopy. The metric was developed by Adam Zemla at Lawrence Livermore National Laboratory and originally implemented in the Local-Global Alignment (LGA) program. It is intended as a more accurate measurement than the common root-mean-square deviation (RMSD) metric - which is sensitive to outlier regions created, for example, by poor modeling of individual loop regions in a structure that is otherwise reasonably accurate. The conventional GDT_TS score is computed over the alpha carbon atoms and is reported as a percentage, ranging from 0 to 100. In general, the higher the GDT_TS score, the more closely a model approximates a given reference structure.
In computational biology, de novo protein structure prediction refers to an algorithmic process by which protein tertiary structure is predicted from its amino acid primary sequence. The problem itself has occupied leading scientists for decades while still remaining unsolved. According to Science, the problem remains one of the top 125 outstanding issues in modern science. At present, some of the most successful methods have a reasonable probability of predicting the folds of small, single-domain proteins within 1.5 angstroms over the entire structure.
Søren Brunak is a Danish biological and physical scientist working in bioinformatics, systems biology and medical informatics. He is professor of Disease Systems Biology at the University of Copenhagen and professor of Bioinformatics at the Technical University of Denmark. As Research Director at the Novo Nordisk Foundation Center for Protein Research at the University of Copenhagen Medical School he leads a research effort where molecular level systems biology data are combined with phenotypic data from the healthcare sector, such as electronic patient records, registry information and biobank questionnaires. A major aim is to understand the network biology basis for time-ordered comorbidities and discriminate between treatment related disease correlations and other comorbidities in disease trajectories. Søren Brunak also holds a position as Medical Informatics Officer at Rigshospitalet, Capital Region of Denmark.
RAPTOR is protein threading software used for protein structure prediction. It has been replaced by RaptorX, which is much more accurate than RAPTOR.
Phyre and Phyre2 are free web-based services for protein structure prediction. Phyre is among the most popular methods for protein structure prediction having been cited over 1500 times. Like other remote homology recognition techniques, it is able to regularly generate reliable protein models when other widely used methods such as PSI-BLAST cannot. Phyre2 has been designed to ensure a user-friendly interface for users inexpert in protein structure prediction methods. Its development is funded by the Biotechnology and Biological Sciences Research Council.
Pavel Arkadevich Pevzner is the Ronald R. Taylor Professor of Computer Science and Director of the NIH Center for Computational Mass Spectrometry at University of California, San Diego. He serves on the Editorial Board of PLoS Computational Biology and he is a member of the Genome Institute of Singapore scientific advisory board.
RaptorX is a software and web server for protein structure and function prediction that is free for non-commercial use. RaptorX is among the most popular methods for protein structure prediction. Like other remote homology recognition/protein threading techniques, RaptorX is able to regularly generate reliable protein models when the widely used PSI-BLAST cannot. However, RaptorX is also significantly different from those profile-based methods in that RaptorX excels at modeling of protein sequences without a large number of sequence homologs by exploiting structure information. RaptorX Server has been designed to ensure a user-friendly interface for users inexpert in protein structure prediction methods.
Burkhard Rost is a scientist leading the Department for Computational Biology & Bioinformatics at the Faculty of Informatics of the Technical University of Munich (TUM). Rost chairs the Study Section Bioinformatics Munich involving the TUM and the Ludwig Maximilian University of Munich (LMU) in Munich. From 2007-2014 Rost was President of the International Society for Computational Biology (ISCB).
Molecular recognition features (MoRFs) are small intrinsically disordered regions in proteins that undergo a disorder-to-order transition upon binding to their partners. MoRFs are implicated in protein-protein interactions, which serve as the initial step in molecular recognition. MoRFs are disordered prior to binding to their partners, whereas they form a common 3D structure after interacting with their partners. As MoRF regions tend to resemble disordered proteins with some characteristics of ordered proteins, they can be classified as existing in an extended semi-disordered state.
Alfonso Valencia is a Spanish biologist, ICREA Professor, current director of the Life Sciences department at Barcelona Supercomputing Center. and of Spanish National Bioinformatics Institute (INB-ISCIII). From 2015-2018, he was President of the International Society for Computational Biology. His research is focused on the study of biomedical systems with computational biology and bioinformatics approaches.
Bonnie Anne Berger is an American mathematician and computer scientist, who works as the Simons professor of mathematics and professor of electrical engineering and computer science at the Massachusetts Institute of Technology. Her research interests are in algorithms, bioinformatics and computational molecular biology.
Christine Anne Orengo is a Professor of Bioinformatics at University College London (UCL) known for her work on protein structure, particularly the CATH database. Orengo serves as president of the International Society for Computational Biology (ISCB), the first woman to do so in the history of the society.
Shoshana Wodak is a computational biologist and an organizational leader in the field of protein-protein docking. Wodak was one of the first people to dock proteins together using a computer program.
AlphaFold is an artificial intelligence (AI) program developed by Alphabets's/Google's DeepMind which performs predictions of protein structure. The program is designed as a deep learning system.
Collin M. Stultz is an American biomolecular engineer, physician-scientist and academic at the Massachusetts Institute of Technology and the Massachusetts General Hospital. He is the Nina T. and Robert H. Rubin Professor in Medical Engineering and Science at MIT, a Professor of Electrical Engineering and Computer Science also at MIT, a faculty member in the Harvard-MIT Division of Health Sciences and Technology, and a cardiologist at the Massachusetts General Hospital.
Rita Casadio is a Professor of Biochemistry at the University of Bologna.
Zhiping Weng is the Li Weibo Professor of biomedical research and chair of the program in integrative biology and bioinformatics at the University of Massachusetts Medical School. She was awarded Fellowship of the International Society for Computational Biology (ISCB) in 2020 for outstanding contributions to computational biology and bioinformatics.
