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Maximum likelihood density modification by pattern recognition of structural motifs
Maximum likelihood density modification by pattern recognition of structural motifs
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机译:通过结构图案的模式识别最大似然密度修改
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摘要
An electron density for a crystallographic structure having protein regions and solvent regions is improved by maximizing the log likelihood of a set of structures factors {Fh} using a local log-likelihood function:; ;where pPROT(x) is the probability that x is in the protein region, p(&rgr;(x)|PROT) is the conditional probability for &rgr;(x) given that x is in the protein region, and pSOLV(x) and p(&rgr;(x)|SOLV) are the corresponding quantities for the solvent region, pH(x) refers to the probability that there is a structural motif at a known location, with a known orientation, in the vicinity of the point x; and p(&rgr;(x)|H) is the probability distribution for electron density at this point given that the structural motif actually is present. One appropriate structural motif is a helical structure within the crystallographic structure.
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机译:通过最大化一组结构因子& F h Sub>&rcub;的对数似然性,可以提高具有蛋白质区域和溶剂区域的晶体结构的电子密度。使用本地对数似然函数: <数学> <![CDATA [ LL PDAT> ITALIC> HIL> (&rgr;(( PDAT> x,&lcub; F PDAT> ITALIC> HIL> h PDAT> SB> HIL> &rcub;))&equals ; ln&lsqb; PDAT> p PDAT> ITALIC> HIL> (&rgr;( PDAT> x PDAT> ITALIC> HIL> )&verbar; PROT) PDAT> p PDAT> ITALIC> HIL> < SB> PROT PDAT> SB> HIL> ( PDAT> x PDAT> ITALIC> HIL> )&plus; PDAT> p PDAT> ITALIC> HIL> (&rgr;( PDAT> x PDAT> ITALIC> HIL> )&verbar; SOLV) PDAT> p PDAT> ITALIC> HIL> SOLV PDAT> SB> HIL> ( PDAT> x PDAT> ITALIC> HIL> < PDAT>)&plus; PDAT> p PDAT> ITALIC> HIL> (&rgr;( PDAT> x PDAT> ITALIC> HIL> )&verbar; PDAT> H PDAT> ITALIC> HIL> ) PDAT> p PDAT> ITALIC > HIL> H PDAT> SB> HIL> ( PDAT> x PDAT> < / ITALIC> HIL> )&rsqb;, PDAT> PTEXT>]]> MathText> Math> ;其中p PROT Sub>(x)是x在蛋白质区域的概率,p(&rgr;(x)&verbar; PROT)是&rgr;(x)的条件概率(假设x是蛋白质区域中的p SOLV Sub>(x)和p(&rgr;(x)&verbar; SOLV)是溶剂区域的相应量p H Sub>(x )是指在点x附近在已知位置具有已知方向的结构基序的可能性; p(r(x)&verbar; H)是在假定实际存在结构基序的情况下此时电子密度的概率分布。一种合适的结构基序是晶体结构内的螺旋结构。
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