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SUMMARY:Low resolution refinement tools in the program REFMAC - Dr Garib N
  Murshudov\, LMB\, MRC\, Cambridge\, U.K
DTSTART:20111123T101500Z
DTEND:20111123T111500Z
UID:TALK34628@talks.cam.ac.uk
CONTACT:23791
DESCRIPTION:Despite rapid advances in Macromolecular X-ray Crystallographi
 c (MX) methods\, derivation of reliable atomic models\nfrom low resolution
  diffraction data still poses many challenges. The reason for this is that
  the number of\nobservations relative to the number of adjustable paramete
 rs is small and signal to noise ratio in the experimental\ndata is very lo
 w. As a consequence derivation of biologically meaningful information from
  such data is challenging.\nMobility of macromolecules means that in many 
 cases growing crystals diffracting to higher resolution is not\npossible a
 nd low resolution data must be used to derive some useful information.\n\n
 To derive some of information from such data two related but distinct prob
 lems should be tackled: i) stabilisation\nof ill-posedness of refinement p
 rocedures  ii) calculation of maximal signal/minimal noise electron den
 sity.\nSolving the first problem is necessary to derive reliable atomic mo
 del and the second problem to calculate\ninterpretable electron density th
 at is used in model (re)building.\n\n1) The first problem is usually tackl
 ed using restraints based on structural information. Available structural\
 ninformation are a) known similar three-dimensional structures b) secondar
 y structures\; c) NCS if present\; d) in\naddition it is also possible to 
 exploit the fact that during refinement inter-atomic distances should not 
 change\ndramatically. It has already been shown that using these restraint
 s improves reliability of the derived models. As\na result of model improv
 ement errors in the derived atomic models are reduced\, and it means that
   calculated phases\nhave less error hence reducing noise in the electr
 on density related to the model errors.\n2) Sharpening of an electron dens
 ity while increasing signal amplifies noise masking out âtrueâ signal. T
 here are\nseveral approaches to such problems including: a) regularisation
  using Tikhonov-Sobolev method\; b) Wiener filters\nand c) Bayesian filter
 s. These techniques attempt to answer to one common question: how to enhan
 ce signal without\nnoise amplification? Another problem in map sharpening 
 is that it assumes that all atoms have the same B values. It\nis in genera
 l not true and there is a distribution of B values â inverse gamma distri
 bution. Moreover individual\natomsâ oscillation depends on its position i
 n the asymmetric unit. These facts need to be accounted for if accurate\nm
 ap sharpening tools to be designed. In this presentation some applications
  of these techniques to map calculations\nwill be discussed.
LOCATION:Perham's seminar room
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