Research – Biomolecular Structure and Function

DCA-coevolution

 

We use computational tools to study and predict biological structures at the molecular level. We use a combination of mathematical modeling, data analysis, molecular dynamics and biophysical concepts to advance our understanding of how atomic structure affects dynamics and ultimately function. Please find below  a list of representative publications for this focus area in our lab:  

Ricardo N. dos Santos, Xianli Jiang, Leandro Martínez, Faruck Morcos Coevolutionary Signals and Structure-Based Models for the Prediction of Protein Native Conformations Computational Methods in Protein Evolution, Methods in Molecular Biology Vol. 1851. Springer Science+Business Media. 2018

 
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Qin Zhou, Nikesh Kunder, José Alberto De la Paz, Alexandra E. Lasley, Vandita D. Bhat, Faruck Morcos* and Zachary T. Campbell* Global pairwise RNA interaction landscapes reveal core features of protein recognition Nature Communications. 9, Article number: 2511. 2018 (* Co-corresponding)

[EurekAlert]

 
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Ricardo N dos Santos, Allan J R Ferrari, Hugo C R de Jesus, Fábio C Gozzo, Faruck Morcos, Leandro Martínez. Enhancing protein fold determination by exploring the complementary information of chemical cross-linking and coevolutionary signals. Bioinformatics. 2018.

 
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Jeffrey K. Noel, Faruck Morcos and Jose N. Onuchic. Sequence co-evolutionary information is a natural partner to minimally-frustrated models of biomolecular dynamics F1000Research 5(F1000 Faculty Rev):106. 5:13652, 2016.

 
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Biman Jana, Faruck Morcos and Jose N. Onuchic. From Structure to Function: the Convergence of Structure Based Models and Co-evolutionary Information. Physical Chemistry Chemical Physics. Vol. 16, No. 14, Pages 6496-507, 2014

 
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Faruck Morcos, Biman Jana, Terence Hwa and Jose N. Onuchic. Coevolutionary signals across protein lineages help capture multiple protein conformations. Proc Natl Acad Sci USA. Vol 110, No. 51, p. 20533-20538. 2013
Press Highlight in ScienceDaily: Proteins' passing phases revealed

 
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Joanna I. Sulkowska*, Faruck Morcos*, Martin Weigt, Terence Hwa and Jose N. Onuchic. Genomics-aided structure prediction. Proc Natl Acad Sci USA. Vol. 109, No. 26, p. 10340-45, 2012. (*equivalent contribution)
Protein residues kiss, don't tell: Genomes reveal contacts, scientists refine methods for protein-folding prediction

 
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Faruck Morcos*, Andrea Pagnani*, Bryan Lunt, Arianna Bertolino, Debora S. Marks, Chris Sander, Riccardo Zecchina,
Jose N. Onuchic, Terence Hwa and Martin Weigt. Direct-coupling analysis of residue coevolution captures native contacts across many protein families. Proc Nat Acad Sci USA. Vol. 108, No. 49, E1293-E1301, 2011. (*equivalent contribution)

 
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Faruck Morcos, R. Lopez, S. Chatterjee, P. Brenner, C. McClendon, J. Zintsmaster, M. Ercsey-Ravasz, C.R. Sweet,
M. Jacobson, J. Peng and J. Izaguirre. Modeling conformational ensembles of slow functional motions in Pin1-WW. PLoS Computational Biology. 6(12): e1001015, 2010.

 
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Zaher Dawy, Faruck Morcos, Johanna Weindl and Jakob C. Mueller. Translation initiation modeling and mutational analysis based on the 3-end of the Escherichia coli 16S rRNA sequence. Elsevier BioSystems. 96 (1), p. 58-64, 2009

 
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S. Flores, K. Keating, J. Painter, F. Morcos, K. Nguyen, E. Merrit, L. Kuhn and M. Gerstein. HingeMaster: normal mode hinge prediction approach and integration of complementary predictors. Proteins: Structure, Function, and Bioinformatics. Vol. 73, Issue 2, Pages 299-319, Nov, 2008

 
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Zaher Dawy, Pavol Hanus, Johanna Weindl, Janis Dingel, Faruck Morcos. On genomic coding theory. European Transactions on Telecommunications , John Wiley & Sons, Ltd. Vol. 18, Issue 8, pp. 873-879, 2007

 
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