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Published byBlaise Jason Gray Modified over 9 years ago
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Direct Use of Phase Information in Refmac Abingdon, 18.3.2008 University of Leiden P. Skubák
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SAD EXPERIMENT PHASING and DENSITY MODIFICATION REFINEMENT and MODEL BUILDING |F||F| |F + |, |F - | |F| = ( |F + | + |F - | ) REFINEMENT WITHOUT PRIOR PHASE INFORMATION
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SAD EXPERIMENT PHASING and DENSITY MODIFICATION REFINEMENT and MODEL BUILDING , P e ( ) |F||F| |F + |, |F - | REFINEMENT WITH INDIRECT PRIOR PHASE INFORMATION P e ( ) = e A cos( ) + B sin( ) + C cos(2. ) + D sin(2. ) |F| = ( |F + | + |F - | )
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SAD EXPERIMENT PHASING and DENSITY MODIFICATION REFINEMENT and MODEL BUILDING , heavy atom model |F + |, |F - | REFINEMENT WITH DIRECT PRIOR PHASE INFORMATION |F + |, |F - | |F| = ( |F + | + |F - | )
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Rice refinement target P( |F o |, o, |F c |, c ) integration over all o P( |F o |, |F c |, c ) P( |F o | ; |F c |, c ) division by P( |F c |, c ) conditional probability distribution P( |F o | ; |F c |, c ) maximum likelihood refinement target with no prior phase information
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MLHL refinement target P( |F o |, o, |F c |, c ) weighted integration over all o P( |F o |, |F c |, c ) P( |F o | ; |F c |, c ) division by P( |F c |, c ) conditional probability distribution P( |F o | ; |F c |, c ) maximum likelihood refinement target indirectly incorporating prior phase information
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P(|F o - |, |F o + | ; |F c - |, c -, |F c + |, c + ) P(|F o - |, |F o + |, |F c - |, c -, |F c + |, c + ) SAD refinement target P(|F o - |, o -, |F o + |, o +, |F c - |, c -, |F c + |, c + ) integration over all o -, o + division by P( |F c - |, c -, |F c + |, c + ) maximum likelihood refinement target directly incorporating prior phase information conditional probability distribution P( |F o - |, |F o + | ; |F c - |, c -, |F c + |, c + )
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SAD distribution P( |F o + |, |F o - | ; A c, B c, A Hc, B Hc ) (strong prior phase information) Rice distribution P( |F o | ; A c, B c ) (no prior phase information)
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SAD distribution (weak prior phase information)
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SAD REFINEMENT TARGET USE IN REFMAC iterated automated model building with SAD function refinement substructure refinement and scaling refinement of models in the final stages
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iterated automated model building with SAD function refinement substructure refinement and scaling refinement of models in the final stages SAD REFINEMENT TARGET USE IN REFMAC
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automated model building programs do not support SAD target (yet), workarounds needed in order to test: the heavy atoms parameters file inputed to model building program separately by a script which also calls Refmac with the extra keywords needed for SAD refinement this workaround used in CRANK for ARP/wARP+Refmac_sad implementation better integration of ARP/wARP with Refmac SAD is on the way MODEL BUILDING WITH SAD REFINEMENT
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Fraction of ARP/wARP built residues to total number of residues resolution lower than 2.4 Åresolution higher than 2.4 Å
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iterated automated model building with SAD function refinement substructure refinement and scaling refinement of models in the final stages SAD REFINEMENT TARGET USE IN REFMAC
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SAD SUBSTRUCTURE REFINEMENT & SCALING IN REFMAC (VERY PRELIMINARY RESULTS) being tested on ~ 200 JSCG datasets using CRANK package with pipeline: Refmac5_sad for scaling, Solomon for DM and Refmac5_sad for model building average phase error after refmac phasing 75.4 deg 70 runs finished, of which 22 with successful model building similar results ( 67 runs finished of which 25 with successful model building ) achieved with the same pipeline using BP3 instead of Refmac5_sad for phasing
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iterated automated model building with SAD function refinement substructure refinement and scaling refinement of models in the final stages SAD REFINEMENT TARGET USE IN REFMAC
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SAD REFINEMENT – CLOSE TO FINAL MODEL
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SIRAS EXPERIMENT DIRECT USE OF PRIOR PHASES SIRAS X-RAY EXPERIMENT PHASING and DENSITY MODIFICATION REFINEMENT and MODEL BUILDING substructure model |F N |, |F D + |,|F D - | P( |F oN |,|F oD - |, |F oD + | ; |F cN |, cN,|F cD - |, cD -, |F cD + |, cD + )
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SIRAS IMPLEMENTATION REQUIREMENTS AND TODO numerical approximations to the 3-dimensional SIRAS integral – done for the function and first derivatives evaluation second derivatives of SIRAS function should be calculated and used in minimisation too modelling of non-isomorphism: more models in Refmac with restraints between them and their parts
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SIRAS VERY PRELIMINARY RESULTS –number of protein residues correctly built : –results from Refmac5D - not modeling non-isomorphism (sharing protein part for native and derivative model), heavy atom refinement outside of Refmac, only first derivatives etc
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Plans for the coming months run and analyze massive JCSG tests on both Refmac SAD substructure refinement and scaling and protein model building with iterative Refmac SAD refinement analyze the SAD target improvements for close to final models better integration of SAD with model building programs anisotropic ATP's refinement for SAD target simultaneous refinement of occupancies and ATP's for all targets more models in Refmac (input, output, refinement etc) geometry restraints between more models SIRAS target implementation and testing for substructure refinement and scaling and protein model building target for joint refinement of protein and ligand P( |F oP |,|F oPL |; |F cP |, cP,|F cPL |, cPL )
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I. Original Refmac5 code files II. Modified Refmac5 code files III. Bridge code files – layer between Refmac5 and SAD function itself IV. SAD function code files Refmac5 code organisation fortran C/C++
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SAD/SIRAS function implementation standalone C++ template class with double or single precision general likelihood function for 1 or 2 observed structure factors and N model structure factors (includes a.o. SAD, SIR or Rice functions for both centric and acentric cases) possibility to define arbitrary covariance matrices for different experiments/situations, with real or complex terms calculation of functional value, 1. and 2. derivatives with regards to calculated structure factors and Luzzati D parameters Gaussian integration over unknown observed phases use of tabulated Sin, Cos, Exp and modified Bessel I 0, I 1 functions to increase the evaluation speed use of LAPACK package for calculation of eigenvalues of covariance matrices
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I. Original Refmac5 code files II. Modified Refmac5 code files III. Bridge code files – layer between Refmac5 and SAD function itself IV. SAD function code files Refmac5 code organisation fortran C/C++
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Tasks performed by bridge layer passing the calls and parameters between Refmac5 part and likelihood function part in both directions place of instantiation and “life” of likelihood class transformation of derivatives with regards to structure factors amplitudes and phases (polar coordinates) to derivates with regards to real and imaginary structure factore part (as used by Refmac5) role in read/write of substructure files checks of reasonability and/or correctness of some input and output likelihood function parameters
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I. Original Refmac5 code files II. Modified Refmac5 code files III. Bridge code files – layer between Refmac5 and SAD function itself IV. SAD function code files Refmac5 code organisation fortran C/C++
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Tasks performed by modified Refmac5 files input, output and availability in code of observed |F + |, |F - | columns (via standard CCP4 libraries to read and write mtz files) input, output and availability in code of substructure parameters (standard pdb file format and new internally used refmac5 format for both input and output) gathering and precomputation of all information required as input by SAD function calling of SAD function passing all required input information(via bridge functions) replacement and/or modification of all original Refmac5 subroutines requiring different treatment with SAD function harvesting of input keywords specific for SAD refinement all original tasks performed by these files
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