Prologue to protein x-beam crystallography
Slide 3Electromagnetic waves E-electromagnetic field quality An abundancy w - rakish speed n - recurrence l - wavelenght E = A cos w t w = 2 pn E = A cos ( a + w t ) a = 2pZ/l a - stage
Slide 4Wave as a vector F=Acos a +iAsin an or F=exp(i a ) Imaginary pivot An A-wave plentifulness a - wave stage a Real hub
Slide 5What happens to electron when it is hit by x-beams? The electron begins vibrating with an indistinguishable recurrence from the x-beam bar subsequently, optional pillars will be scattered every which way Primary shaft Secondary bars
Slide 6Scattering from an atom Molecule is made out of numerous electrons Each electron will disperse auxiliary radiation uppon introduction to x-beams The scattered auxiliary bars will associate and cause impedance The dissipating from a particle is subject to number of and separations between electrons as it were, scrambling from atom is reliant on its structure If we would know the amplitudes and periods of scattered atom, we could compute the structure of atom... Essential bar
Slide 7practically speaking... Dispersing from a solitary particle is unreasonably powerless to be watched If particles are all arranged similarly (like in precious stone), the disseminating from individual particles will be duplicated in specific bearings
Slide 9Braggs law Scattered pillars in stage, they include Scattered bars not in stage, they wipe out each other n l = 2d sin q http://www.eserc.stonybrook.edu/ProjectJava/Bragg/
Slide 10A run of the mill diffraction design from a protein gem
Slide 11Fourier change F(k)= f(x)e - 2 p ikx dx The electron thickness circulation of sub-atomic structure and its created diffraction example are fourier changes particular to each other
Slide 12The electron thickness condition h,k,l – files of reflections xyz – facilitates F – sufficiency of reflections a – period of reflections V-unit cell volume
Slide 13The Phase Problem With finder you can gauge just the force of reflections The data about stages is lost – there is no such thing as "stage meter" This implies, you should get stage data in some other route For little particles (<100 iotas), coordinate techniques exist. This implies, you can ascertain stages from amplitudes with no additional data. Proteins are dreadfully enormous to utilize coordinate strategies, so different devices are produced
Slide 14Isomorphous substitution By presenting overwhelming particles in protein gem (by dousing), the diffraction example can be adjusted It is conceivable to decide places of substantial iotas and from them the stages One must use no less than 2 diverse substantial particle drenches Problems: 1) Unit cell measurements of precious stone may change after splashing 2) Crystal may get demolished after dousing and not diffract at all 3) Heavy particle particles won't not tie in all around characterized places
Slide 15Molecular substitution Currently the most well-known procedure Applicable just if a comparative structure as of now exists (no less than 25% succession personality) The periods of known structure are joined with forces of obscure Before that, the known model must be in silico put in an artifical unit cell in an indistinguishable introduction and interpretation from source from in the structure of enthusiasm For this, turn and interpretation capacities exist Problems: May not work, if obscure structure is under 30 % idendical to the known structure Model predisposition – what's that?
Slide 16Phases obscure! Watched amplitudes Unknown structure FFT Cat Fourier feline Known structure Calculated amplitudes and stages Manx feline FFT Fourier Manx feline
Slide 17Observed amplitudes, ascertained stages FFT The tail gets to be unmistakable!
Slide 18Be mindful – this happens, if structures are not sufficiently comparative!! Duck Fourier Duck amplitudes + feline stages Looks like a feline!!
Slide 19Model building Fitting of protein grouping in the electron thickness Easy in sub-atomic substitution More troublesome if no underlying model is accessible Unambiquous if determination is sufficiently high (superior to 3.0 Å ) Can be computerized, if determination is near 2 Å or better
Slide 21Refinement Automated change of the model, so it clarifies the watched information better The stages get enhanced also, so the electron thickness maps show signs of improvement
Slide 22Validation Assesment of the last(?) display quality How the geometry of amino acids resemble? (Ramachandran plot) Are non-covalently molecules sufficiently far from each other? (no iota knocks) Are deposits "cheerful" in their surroundings? (hydrophobic in center, polar on surface) Are the hydrogen benefactors/acceptors fulfilled?
Slide 23Depositing of structure in PDB is required for the paper to be acknowledged in many diaries It is a smart thought to store the diffraction information also – this will demonstrate that your structure really has something to do with watched electron thickness
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