Literature DB >> 12647401

CASP and CAFASP experiments and their findings.

Philip E Bourne1.   

Abstract

This short introductory chapter is intended simply to introduce a sense of the progress, limitations, challenges, and likely future developments in the field of protein structure prediction through what seems to be a unique scientific process. CASP and CAFASP represent a direct challenge and careful assessment of a field of study that has captured the interest of many scientists. Three of the best scientists in the field and their colleagues provide a more detailed description of the field and how it is developing in Chapters 25, 26, and 27. As prediction methods have advanced the distinction between comparative modeling, fold recognition, and novel fold recognition have blurred somewhat. It is a testament to the community that as the knowledge of the algorithms evolved, World Wide Web servers providing access to these algorithms appeared. Thus, making it relatively straightforward for any investigator to apply a melting pot of methods to the prediction process. What all approaches need are more targets and a continued refinement to the evaluation process. The first need is being met in part by the PDB, which is, with depositors' approval, releasing sequences ahead of structure release (see http://www.rcsb.org/pdb/status.html). Further, the structural genomics projects are reporting their progress for all targets on a weekly basis (see http://targetdb.pdb.org/). While there is no indication that the sequences of the latter will lead to a structure, it is a rich source of targets (17,000 in October 2002). Not only do CASP and CAFASP measure progress, they help define where efforts should be directed to move the field forward. It is a testament to how far the field has come that investigators are now turning to the unknown. Although attempting to predict a structure that will appear experimentally helps improve the methods applied to structure prediction, it does not further our understanding of living systems directly. Attempts at defining the "The Most Wanted" (Abbott, 2001)--the structures most in need of prediction to help further our understanding of the biology, and the efforts to make those predictions, speak to a healthy future for the field of protein structure prediction. To the many individuals who help define the CASP and CAFASP processes, serve the community as assesors and compete in the experiments this is a tribute.

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Year:  2003        PMID: 12647401

Source DB:  PubMed          Journal:  Methods Biochem Anal        ISSN: 0076-6941


  9 in total

1.  Scoring profile-to-profile sequence alignments.

Authors:  Guoli Wang; Roland L Dunbrack
Journal:  Protein Sci       Date:  2004-06       Impact factor: 6.725

2.  Systems level insights into the stress response to UV radiation in the halophilic archaeon Halobacterium NRC-1.

Authors:  Nitin S Baliga; Sarah J Bjork; Richard Bonneau; Min Pan; Chika Iloanusi; Molly C H Kottemann; Leroy Hood; Jocelyne DiRuggiero
Journal:  Genome Res       Date:  2004-05-12       Impact factor: 9.043

Review 3.  Membrane protein prediction methods.

Authors:  Marco Punta; Lucy R Forrest; Henry Bigelow; Andrew Kernytsky; Jinfeng Liu; Burkhard Rost
Journal:  Methods       Date:  2007-04       Impact factor: 3.608

4.  WeFold: a coopetition for protein structure prediction.

Authors:  George A Khoury; Adam Liwo; Firas Khatib; Hongyi Zhou; Gaurav Chopra; Jaume Bacardit; Leandro O Bortot; Rodrigo A Faccioli; Xin Deng; Yi He; Pawel Krupa; Jilong Li; Magdalena A Mozolewska; Adam K Sieradzan; James Smadbeck; Tomasz Wirecki; Seth Cooper; Jeff Flatten; Kefan Xu; David Baker; Jianlin Cheng; Alexandre C B Delbem; Christodoulos A Floudas; Chen Keasar; Michael Levitt; Zoran Popović; Harold A Scheraga; Jeffrey Skolnick; Silvia N Crivelli
Journal:  Proteins       Date:  2014-07-08

5.  Solvent accessible surface area approximations for rapid and accurate protein structure prediction.

Authors:  Elizabeth Durham; Brent Dorr; Nils Woetzel; René Staritzbichler; Jens Meiler
Journal:  J Mol Model       Date:  2009-02-21       Impact factor: 1.810

6.  Prediction of multi-type membrane proteins in human by an integrated approach.

Authors:  Guohua Huang; Yuchao Zhang; Lei Chen; Ning Zhang; Tao Huang; Yu-Dong Cai
Journal:  PLoS One       Date:  2014-03-27       Impact factor: 3.240

7.  Achievements and challenges in structural bioinformatics and computational biophysics.

Authors:  Ilan Samish; Philip E Bourne; Rafael J Najmanovich
Journal:  Bioinformatics       Date:  2014-12-08       Impact factor: 6.937

8.  Does Cation Size Affect Occupancy and Electrostatic Screening of the Nucleic Acid Ion Atmosphere?

Authors:  Magdalena Gebala; Steve Bonilla; Namita Bisaria; Daniel Herschlag
Journal:  J Am Chem Soc       Date:  2016-08-22       Impact factor: 15.419

9.  Automated protein subfamily identification and classification.

Authors:  Duncan P Brown; Nandini Krishnamurthy; Kimmen Sjölander
Journal:  PLoS Comput Biol       Date:  2007-08       Impact factor: 4.475

  9 in total

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