Jeffrey Skolnick

From Wikipedia, the free encyclopedia
Jeffrey Skolnick
Born
Brooklyn, New York
Known forcomputational techniques for protein structure analysis
Awards
Scientific career
Fields
Institutions
Thesis Investigations on a Rod Like Polyelectrolyte Model  (1978)
Doctoral advisorProfessor Marshall Fixman; Ph.D.
Websitewww.biology.gatech.edu/people/jeffrey-skolnick

Jeffrey Skolnick is an American computational biologist. He is currently a Georgia Institute of Technology School of Biology Professor, the Director of the Center for the Study of Systems Biology, the Mary and Maisie Gibson Chair, the Georgia Research Alliance Eminent Scholar in Computational Systems Biology, the Director of the Integrative BioSystems Institute, and was previously the Scientific Advisor at Intellimedix.[1]

He has focused on the development of computational algorithms and their application to proteomes for the prediction of protein structure and function, the prediction of small molecule ligand-protein interactions with applications to drug discovery, the prediction of off-target uses of existing drugs, and the exploration of the interplay between protein physics and evolution in determining protein structure and function. He is a pioneer in the field of protein structure prediction, including the development of CABS and CAS methods of lattice based conformation sampling, and the algorithms Touchstone II and TASSER.

Skolnick is most known for demonstrating that the number of ligand binding pockets in proteins is quite small, thereby justifying the likelihood that large scale drug repurposing will work. This combined with the ability to use predicted as well as experimental structures in virtual ligand screening at higher accuracy and precision than existing approaches will enable FDA approved drugs with novel mechanisms of action to be identified computationally with a high likelihood of experimental success.[2][3][4]

He is also known for his unique teaching methodology and interactive pedagogy to simplify the comprehension of complex concepts in computational chemistry.

Major Discoveries[edit]

Completeness of the library of protein structures and interactions[edit]

Skolnick was first to demonstrate that the library of single domain protein structures is likely complete and that the observed folds in nature arise from the confinement of dense polymer chains. He further demonstrated that the confinement of these dense polymer chains plus hydrodynamic interactions were the dominant contributor to diffusive processes in cells. Moreover, that the hydrodynamic interactions introduced large scale temporal and spatial correlations that may have important functional consequences.[2][3][5][6]

Ligand homology modeling[edit]

He also pioneered the field of ligand homology modeling with his threading based, FINDSITE approach for protein function inference, binding site prediction and virtual ligand screening. The research showed that remotely related proteins identified by threading often share a common ligand binding site occupied by chemically similar ligands that contain strongly conserved anchor functional groups as well as a variable region that accounts for their binding specificity. These insights enable low-resolution predicted structures to be used for ligand screening/binding pose prediction, with comparable accuracy as with high-resolution experimental structures. In virtual ligand screening, the latest version, FINDSITEcomb, was shown to work far better than more traditional virtual screening approaches on both predicted and high resolution experimental structures.[7][8]

TASSER protein structure prediction[edit]

He also developed the TASSER protein structure prediction approach, whose variants were among the top performers in CASP in the 2000s and the basis for the I-TASSER service. TASSER was among the first methods whose models were closer to the native structure than the starting template.[9][10]

Odijk-Skolnick-Fixman electrostatic persistence length[edit]

Skolnick's Ph.D. thesis " “Investigations on a Rod Like Polyelectrolyte Model", along with Fixman and Odijk, developed a theory for the electrostatic persistence length in polyelectrolytes now known as the Odijk-Skolnick-Fixman electrostatic persistence length which is still considered the classical benchmark.[11][12]

Education[edit]

Skolnick graduated summa cum laude from Washington University in 1975 with a Bachelor of Arts degree in chemistry. After Washington University, he moved on to Yale, where he graduated with a Master of Philosophy in Chemistry in 1977 and a Ph.D. in Chemistry just one year later in 1978.

His Ph.D. thesis, “Investigations on a Rod Like Polyelectrolyte Model”, focused on polymer statistical mechanics with Dr. Marshall Fixman. The methods described by Skolnick and Fixman and independently developed by Theo Odijk are still used as the basis for the electrostatic persistence length of polyelectrolytes.[11]

Academic Recognition[edit]

Awards[edit]

Skolnick has been recognized as a Fellow with the American Association for the Advancement of Science, the Biophysical Society, and the St. Louis Academy of Science. He has also been awarded an Alfred P. Sloan Research Fellowship.[13][14][15][16]

Journals and Editorial Boards[edit]

Dates Journal
2012–present Editorial Board, PeerJ[17]
2012–present Structural Biology Section Editor, Biology Direct[18]
2011–present Editorial Board, Current Bioinformatics[19]
2005–present Editorial Board, Biology Direct[18]
2005–present Editorial Board, Protein Science[20]
1998–present Editorial Board, Proteins[21]

He is also a cofounder of an early stage structural proteomics company, GeneFormatics, and his software has been commercialized by Tripos.[22]

Professional career[edit]

Dates Position
2010–present Director, Integrated Biosystems Institute, Georgia Institute of Technology[1]
2008–present Mary and Maisie Gibson Chair in Computational Systems Biology[23]
2008–2010 Associate Director, Integrated Biosystems Institute, Georgia Institute of Technology[1]
2007–2012 Adjunct Professor, School of Chemistry & Biochemistry, Georgia Institute of Technology
2006–present Director, Center for the Study of Systems Biology, Georgia Institute of Technology[1]
2006–present GRA Eminent Scholar, Computational Systems Biology [1]
2006–present Professor, School of Biology, Georgia Institute of Technology[24]
2002–2005 Director, Buffalo Center of Excellence in Bioinformatics[25]
2002–2005 Professor, Structural Biology, University at Buffalo[26]
1999–2002 Director, Computational/Structural Biology, Danforth Plant Science Center[27]

Patents[edit]

  • System and method for determining three-dimensional structures of proteins, (1993).[28]
  • Prediction of relative binding motifs of biologically active peptides and peptide mimetics, (1999).[29]
  • Methods for using functional site descriptors and predicting protein function, (2003).[30]

References[edit]

  1. ^ a b c d e "SURA Honors Georgia Tech Biologist as Distinguished Scientist". Proteomics Weekly. NewsRX. March 24, 2014. Archived from the original on March 29, 2015. Retrieved 3 August 2014.
  2. ^ a b Zhang, Y.; Hubner, I. A.; Arakaki, A. K.; Shakhnovich, E.; Skolnick, J. (14 February 2006). "On the origin and highly likely completeness of single-domain protein structures". Proceedings of the National Academy of Sciences. 103 (8): 2605–2610. Bibcode:2006PNAS..103.2605Z. doi:10.1073/pnas.0509379103. PMC 1413790. PMID 16478803.
  3. ^ a b Skolnick, Jeffrey; Zhou, Hongyi; Brylinski, Michal (14 June 2012). "Further Evidence for the Likely Completeness of the Library of Solved Single Domain Protein Structures". The Journal of Physical Chemistry B. 116 (23): 6654–6664. doi:10.1021/jp211052j. PMC 3351587. PMID 22272723.
  4. ^ "Protein study suggests drug side effects are inevitable". Drug Discovery Today. May 23, 2013.
  5. ^ Zhang, Yang (2009). "Protein structure prediction: when is it useful?". Current Opinion in Structural Biology. 19 (2): 145–155. doi:10.1016/j.sbi.2009.02.005. PMC 2673339. PMID 19327982.
  6. ^ Saltsman, Kirstie. "Modeling How Molecules Move Inside Cells". National Institutes of Health.
  7. ^ Brylinski, M.; Skolnick, J. (28 December 2007). "A threading-based method (FINDSITE) for ligand-binding site prediction and functional annotation". Proceedings of the National Academy of Sciences. 105 (1): 129–134. doi:10.1073/pnas.0707684105. PMC 2224172. PMID 18165317.
  8. ^ Karypis, George; Rangwala, Huzefa (March 16, 2011). Introduction to Protein Structure Prediction: Methods and Algorithms. John Wiley & Sons. p. 349. ISBN 978-1-118-09946-9.
  9. ^ Zhang, Yang; Arakaki, Adrian K.; Skolnick, Jeffrey (2005). "TASSER: An automated method for the prediction of protein tertiary structures in CASP6". Proteins: Structure, Function, and Bioinformatics. 61 (S7): 91–98. doi:10.1002/prot.20724. PMID 16187349. S2CID 16802808.
  10. ^ Roy, Ambrish; Kucukural, Alper; Zhang, Yang (25 March 2010). "I-TASSER: a unified platform for automated protein structure and function prediction". Nature Protocols. 5 (4): 725–738. doi:10.1038/nprot.2010.5. PMC 2849174. PMID 20360767.
  11. ^ a b Skolnick, Jeffrey; Fixman, Marshall (1977). "Electrostatic Persistence Length of a Wormlike Polyelectrolyte". Macromolecules. 10 (5): 944–948. Bibcode:1977MaMol..10..944S. doi:10.1021/ma60059a011.
  12. ^ Dias, Rita; Lindman, Bjorn. DNA Interactions with Polymers and Surfactants. John Wiley & Sons. p. 26.
  13. ^ "Past Fellows". Alfred P. Sloan Foundation. Archived from the original on 25 February 2016. Retrieved 3 August 2014.
  14. ^ "AAAS News & Notes". American Association for the Advancement of Science. Archived from the original on 30 July 2012.
  15. ^ "Fellow of the Biophysical Society Award". biophysics.org. Biophysical Society. Retrieved 3 August 2014.
  16. ^ "Academy Fellows". academyofsciencestl.org. St. Louis Academy of Science. Retrieved 3 August 2014.
  17. ^ "Advisory Board and Editors Computational Biology". peerj.com. PeerJ. Retrieved 3 August 2014.
  18. ^ a b "Editorial Board". biologydirect.com. Biology Direct. Retrieved 3 August 2014.
  19. ^ "Editorial Board ::: Current Bioinformatics". Bentham Science. Retrieved 3 August 2014.
  20. ^ "Protein Science - Editorial Board - Wiley Online Library". Protein Science. doi:10.1002/(ISSN)1469-896X.
  21. ^ "Proteins: Structure, Function, and Bioinformatics - Editorial Board - Wiley Online Library". Proteins: Structure, Function, and Bioinformatics. doi:10.1002/(ISSN)1097-0134.
  22. ^ Hoerr, Dorothy. "The Business of Biotech". Albright College. Retrieved 3 August 2014.
  23. ^ "DRUG DISCOVERY & THERAPY WORLD CONGRESS 2015". ddtwc.com/. Archived from the original on 11 August 2014. Retrieved 3 August 2014.
  24. ^ "Georgia Tech Research Suggests Drug Side Effects Are Inevitable". Global Biodefense. Stemar Media Group, LLC. Retrieved 3 August 2014.
  25. ^ Drury, Tracey (1 March 2004). "Bioinformatics scientists stoked by UB's Simpson". Buffalo Business First. The Business Journals. Retrieved 3 August 2014.
  26. ^ "UB Honors Pataki, Welcomes New Bioinformatics Director". WBFO Buffalo's NPR News Station. 10 May 2002. Retrieved 3 August 2014.
  27. ^ Hopkin, Karen (12 June 2002). "Computational Biologists Join the Fold". Bio-ITWorld. Cambridge Healthtech Institute. Retrieved 3 August 2014.
  28. ^ US 5265030, Skolnick, Jeffrey & Kolinski, Andrzej, "System and method for determining three-dimensional structures of proteins", published 1993-11-23, assigned to Scripps Clinic and Research Foundation 
  29. ^ US 5933819, Skolnick, Jeffrey; Milik, Mariusz & Kolinski, Andrezej, "Prediction of relative binding motifs of biologically active peptides and peptide mimetics", published 1999-08-03, assigned to The Scripps Research Institute 
  30. ^ US 6631332, Skolnick, Jeffrey & Fetrow, Jacquelyn S., "Methods for using functional site descriptors and predicting protein function", published 2003-10-07, assigned to The Scripps Research Institute 

External links[edit]

Retrieved from "https://en.wikipedia.org/w/index.php?title=Jeffrey_Skolnick&oldid=1208336277"