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computer modeling in molecular biology.pdf

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22 Tim .l I! Hubbard and Arthur M. Leskthe core as a function of sequence divergence. In pairs of distantly related prote<strong>in</strong>sthe size of the cores can vary: In some cases the fraction of residues <strong>in</strong> the core rema<strong>in</strong>shigh, <strong>in</strong> others it can drop to below 50% of the structure.2.3.2 TechniquesA general outl<strong>in</strong>e of the steps <strong>in</strong>volved <strong>in</strong> model build<strong>in</strong>g by homology is as follows:1. The sequence of unknown structure is aligned to the sequence(s) of known structureand the sequence of unknown structure is divided <strong>in</strong>to SCR’s and SVR’s:regions where the alignment has sufficient sequence conservation to be conservedstructurally (alignable) are def<strong>in</strong>ed as SCR’s (Structurally Conserved Regions).The rema<strong>in</strong><strong>in</strong>g regions (nonalignable - <strong>in</strong>clud<strong>in</strong>g but not restricted to loopregions) are def<strong>in</strong>ed as SVR’s (Structurally Variable Regions).2. The ma<strong>in</strong> cha<strong>in</strong> conformation and spatial relationship of the SCR’s are takenfrom the coord<strong>in</strong>ates of the known structure to which they were aligned. Conformationsare generated for each SVR <strong>in</strong> the sequence, with correct endpo<strong>in</strong>tgeometry and length, which do not clash sterically with the rest of the structure,either us<strong>in</strong>g a database search method [44] or any alternative approach. Thiscreates a complete cont<strong>in</strong>uous ma<strong>in</strong> cha<strong>in</strong> model.3. Side cha<strong>in</strong>s are built onto the ma<strong>in</strong> cha<strong>in</strong> model and their conformations optimised.2.3.2.1 Alignment and Division <strong>in</strong>to SCR’s and SVR’sDiscover<strong>in</strong>g a relationship between an <strong>in</strong>put sequence and a structure does notnecessarily give a full or accurate alignment. Frequently more sensitive alignmenttechniques not designed for fold recognition can give a more accurate alignmentonce the sequences to align have been identified. It is important to keep the lessonsfrom evolution <strong>in</strong> m<strong>in</strong>d (Section 2.3.1): There will be regions where there are severalpossible alternative alignments and there will be regions that cannot be aligned(nonalignable) because they are structurally different.The first of these problems can be tackled by us<strong>in</strong>g as much <strong>in</strong>formation as possible(multiple sequence alignments for both known and unknown) and by explor<strong>in</strong>gsignificant alternative sub-optimal alignments [45, 461, and if necessary, by build<strong>in</strong>gmultiple structural models us<strong>in</strong>g alternative alignments.The second problem is to dist<strong>in</strong>guish the regions <strong>in</strong> which the <strong>in</strong>put sequence hasthe same fold as the model (SCR’s) and where it is different (SVR’s). Clearly wherethere are <strong>in</strong>sertions and deletions the cha<strong>in</strong> trace of the model must be different;

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