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Conformational Ensembles from Experimental Data
and Computer Simulations
Tuesday Speaker Abstracts
29
Inferring Protein Structure from Sparse and Unreliable Experimental Data
Justin MacCallum
University of Calgary, Calgary, AB, Canada
No Abstract
Averaged Experimental Data: From Algebra to Biology
Enrico Ravera
1
, Luca Sgheri
2
, Giacomo Parigi
1
, Claudio Luchinat
1
.
1
University of Florence, Sesto Fiorentino, Italy,
2
National Research Council (CNR), Sesto
Fiorentino, Italy.
Calculating the expected experimental observables (e.g.: NMR, EPR, SAXS,…) from a given
conformation, or ensemble thereof, is a trivial task. On the contrary finding the relative
population of different conformers that compose the natural ensemble from the averaged
experimental observables is an ill-posed inverse problem that admits an infinite number of
solutions. Several approaches have been provided over the years to address this problem: here
we will examine the relations among different approaches[1] and we will present results on some
biological entities as obtained by a largest-weight approach.[2]
[1] Ravera, Sgheri, Parigi, Luchinat, Phys. Chem. Chem. Phys., 2016, 18(8), 5686-5701;
Bonomi, Heller, Camilloni, Venduscolo, Curr. Opin. Struct. Biol., 2017, 42, 106-116.
[2] Cerofolini, Fields, Fragai, Geraldes, Luchinat, Parigi, Ravera, Svergun, Teixeira, J. Biol.
Chem., 288, 30659-30671; Andralojc, Ravera, Salmon, Parigi, Al-Hashimi, Luchinat, Phys.
Chem. Chem. Phys., 2016, 18(8), 5743-5752; Andralojc, Hiruma, Liu, Ravera, Nojiri, Parigi,
Luchinat, Ubbink, Proc. Natl. Acad. Sci. USA, 2017, 114(10), E1840-E1847.