BEGIN:VCALENDAR
VERSION:2.0
PRODID:-//CERN//INDICO//EN
BEGIN:VEVENT
SUMMARY:Short Talk 2\, Sergei Grudinin - Novel algorithms for integrative 
 structural biology.
DTSTART;VALUE=DATE-TIME:20191009T121500Z
DTEND;VALUE=DATE-TIME:20191009T123500Z
DTSTAMP;VALUE=DATE-TIME:20260526T101415Z
UID:indico-contribution-754@lindico453.srv.lu.se
DESCRIPTION:Speakers: Sergei Grudinin (Inria / CNRS)\nIn my talk I will pr
 esent our approach for modeling macromolecular\nflexibility of large molec
 ular assemblies and how it can be combined with\nsparse experimental data 
 obtained with small-angle and cross-linking\nexperiments.\nLarge macromole
 cular machines\, such as proteins and their complexes\, are\ntypically ver
 y flexible at physiological conditions\, and this flexibility is\nimportan
 t for their structure and function. Computationally\, it can be often\napp
 roximated with just a few collective coordinates\, which can be computed\n
 e.g. using the Normal Mode Analysis (NMA). NMA determines low-frequency\nm
 otions at a very low computational cost and these are particularly\nintere
 sting to the structural biology community because they are commonly\nassum
 ed to give insight into protein function and dynamics [1].\nOne of the cha
 llenges in the community is the explanation of solution smallangle\nscatte
 ring profiles. Very recently\, we designed a computational scheme\nthat us
 es the nonlinear normal modes [2] as a low-dimensional representation\nof 
 the protein motion subspace and optimizes protein structures guided by the
 \nSAXS and SANS profiles [3\,4]. For example\, in the CASP12 and CASP13\ne
 xercises\, this scheme obtained best models for some (3 out of 9 in CASP12
 )\nSAXS-assisted targets [5\,6]. Overall\, the flexible fitting scheme typ
 ically allows\na significant improvement of the goodness of fit to experim
 ental profiles in a\nvery reasonable computational time. The NMA analysis 
 also allows to\nautomatically split macromolecules into rigid domains\, or
  to be used together\nwith the cross-linking data\, as we demonstrated in 
 the recent CASP13\nchallenge [7].\n\nReferences:\n[1] Grudinin\, S.\, Lain
 e\, E.\, & Hoffmann\, A. (2019). Predicting protein functional\nmotions: a
 n old recipe with a new twist. bioRxiv\, 703652.\n[2] Hoffmann\, A. & Grud
 inin\, S. (2017). J. Chem. Theory Comput. 13\, 2123 –\n2134. For more in
 formation https://team.inria.fr/nano-d/software/nolbnormal-\nmodes/\n[3] G
 rudinin\, S. et al. (2017). Acta Cryst. D\, D73\, 449 – 464. For more\ni
 nformation https://team.inria.fr/nano-d/software/pepsi-saxs/\n[4] https://
 team.inria.fr/nano-d/software/pepsi-sans/\n[5] http://predictioncenter.org
 /casp13/zscores_final_assisted.cgi?target_flag=S\n[6] Tamò\, G. E.\, Abri
 ata\, L. A.\, Fonti\, G.\, & Dal Peraro\, M. (2018). Proteins:\nStructure\
 , Function\, and Bioinformatics\, 86\, 215-227.\n[7] http://predictioncent
 er.org/casp13/zscores_final_assisted.cgi?target_flag=X\n\nhttps://lindico4
 53.srv.lu.se/event/125/contributions/754/
LOCATION:Kulturen Auditorium
URL:https://lindico453.srv.lu.se/event/125/contributions/754/
END:VEVENT
END:VCALENDAR