Protein Tools for Viral Research

Research output: Contribution to conferenceAbstract

Abstract

The most common question asked by viral researchers of the bioinformatics specialist librarian at Northwestern’s Feinberg School of Medicine is “How can I tell what my protein looks like?” This question occasionally is asked by principal investigators, but most often comes from post-doctoral fellows and graduate students. Most bioinformatics specialists know this is a loaded question: there are no perfect predictors of protein structure. The Galter Health Sciences Bioinformatics Librarian, while working in partnership with viral investigators from three labs, has developed a list of recommended protein prediction tools and references. These tools provide a starting point for choosing the best sites for viral linker mutation studies. The investigator is guided to the PHD tool at the PredictProtein site: http://www.predictprotein.org/ which has been cited by researchers in the Journal of Virology for prediction of structural elements in viral entry glycoproteins [1]. The structural features predicted by PHD provide good guidelines for finding loops in proteins suitable for linker mutations without disruption of major structural features. After these steps, if the investigator wishes to create a predicted view of the protein in question, s/he is directed toward Rensselaer Polytechnic Institute’s HMMSTR/Rosetta Server at http://www.bioinfo.rpi.edu/~bystrc/hmmstr/ , which uses Hidden Markov Model (HMMSTR) and a Monte Carlo Fragment Insertion protein folding program (Rosetta) to return a set of coordinates in Protein Data Bank format. These PDB coordinates can then be loaded into the University of Illinois’ Virtual Molecular Dynamics software for a number of lowest energy structure predictions.
Original languageEnglish
StatePublished - 2007
EventSpecial Libraries Association Annual Conference - Denver, CO
Duration: Jun 1 2001 → …

Conference

ConferenceSpecial Libraries Association Annual Conference
Period6/1/01 → …

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Viral Proteins
Research Personnel
Computational Biology
Research
Librarians
Proteins
Mutation
Virology
Protein Folding
Molecular Dynamics Simulation
Glycoproteins
Software
Medicine
Databases
Guidelines
Students
Health

Cite this

Shaw, P. L. (2007). Protein Tools for Viral Research. Abstract from Special Libraries Association Annual Conference, .
Shaw, Pamela L. / Protein Tools for Viral Research. Abstract from Special Libraries Association Annual Conference, .
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title = "Protein Tools for Viral Research",
abstract = "The most common question asked by viral researchers of the bioinformatics specialist librarian at Northwestern’s Feinberg School of Medicine is “How can I tell what my protein looks like?” This question occasionally is asked by principal investigators, but most often comes from post-doctoral fellows and graduate students. Most bioinformatics specialists know this is a loaded question: there are no perfect predictors of protein structure. The Galter Health Sciences Bioinformatics Librarian, while working in partnership with viral investigators from three labs, has developed a list of recommended protein prediction tools and references. These tools provide a starting point for choosing the best sites for viral linker mutation studies. The investigator is guided to the PHD tool at the PredictProtein site: http://www.predictprotein.org/ which has been cited by researchers in the Journal of Virology for prediction of structural elements in viral entry glycoproteins [1]. The structural features predicted by PHD provide good guidelines for finding loops in proteins suitable for linker mutations without disruption of major structural features. After these steps, if the investigator wishes to create a predicted view of the protein in question, s/he is directed toward Rensselaer Polytechnic Institute’s HMMSTR/Rosetta Server at http://www.bioinfo.rpi.edu/~bystrc/hmmstr/ , which uses Hidden Markov Model (HMMSTR) and a Monte Carlo Fragment Insertion protein folding program (Rosetta) to return a set of coordinates in Protein Data Bank format. These PDB coordinates can then be loaded into the University of Illinois’ Virtual Molecular Dynamics software for a number of lowest energy structure predictions.",
author = "Shaw, {Pamela L}",
year = "2007",
language = "English",
note = "null ; Conference date: 01-06-2001",

}

Shaw, PL 2007, 'Protein Tools for Viral Research' Special Libraries Association Annual Conference, 6/1/01, .

Protein Tools for Viral Research. / Shaw, Pamela L.

2007. Abstract from Special Libraries Association Annual Conference, .

Research output: Contribution to conferenceAbstract

TY - CONF

T1 - Protein Tools for Viral Research

AU - Shaw, Pamela L

PY - 2007

Y1 - 2007

N2 - The most common question asked by viral researchers of the bioinformatics specialist librarian at Northwestern’s Feinberg School of Medicine is “How can I tell what my protein looks like?” This question occasionally is asked by principal investigators, but most often comes from post-doctoral fellows and graduate students. Most bioinformatics specialists know this is a loaded question: there are no perfect predictors of protein structure. The Galter Health Sciences Bioinformatics Librarian, while working in partnership with viral investigators from three labs, has developed a list of recommended protein prediction tools and references. These tools provide a starting point for choosing the best sites for viral linker mutation studies. The investigator is guided to the PHD tool at the PredictProtein site: http://www.predictprotein.org/ which has been cited by researchers in the Journal of Virology for prediction of structural elements in viral entry glycoproteins [1]. The structural features predicted by PHD provide good guidelines for finding loops in proteins suitable for linker mutations without disruption of major structural features. After these steps, if the investigator wishes to create a predicted view of the protein in question, s/he is directed toward Rensselaer Polytechnic Institute’s HMMSTR/Rosetta Server at http://www.bioinfo.rpi.edu/~bystrc/hmmstr/ , which uses Hidden Markov Model (HMMSTR) and a Monte Carlo Fragment Insertion protein folding program (Rosetta) to return a set of coordinates in Protein Data Bank format. These PDB coordinates can then be loaded into the University of Illinois’ Virtual Molecular Dynamics software for a number of lowest energy structure predictions.

AB - The most common question asked by viral researchers of the bioinformatics specialist librarian at Northwestern’s Feinberg School of Medicine is “How can I tell what my protein looks like?” This question occasionally is asked by principal investigators, but most often comes from post-doctoral fellows and graduate students. Most bioinformatics specialists know this is a loaded question: there are no perfect predictors of protein structure. The Galter Health Sciences Bioinformatics Librarian, while working in partnership with viral investigators from three labs, has developed a list of recommended protein prediction tools and references. These tools provide a starting point for choosing the best sites for viral linker mutation studies. The investigator is guided to the PHD tool at the PredictProtein site: http://www.predictprotein.org/ which has been cited by researchers in the Journal of Virology for prediction of structural elements in viral entry glycoproteins [1]. The structural features predicted by PHD provide good guidelines for finding loops in proteins suitable for linker mutations without disruption of major structural features. After these steps, if the investigator wishes to create a predicted view of the protein in question, s/he is directed toward Rensselaer Polytechnic Institute’s HMMSTR/Rosetta Server at http://www.bioinfo.rpi.edu/~bystrc/hmmstr/ , which uses Hidden Markov Model (HMMSTR) and a Monte Carlo Fragment Insertion protein folding program (Rosetta) to return a set of coordinates in Protein Data Bank format. These PDB coordinates can then be loaded into the University of Illinois’ Virtual Molecular Dynamics software for a number of lowest energy structure predictions.

M3 - Abstract

ER -

Shaw PL. Protein Tools for Viral Research. 2007. Abstract from Special Libraries Association Annual Conference, .