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UNIX
        SGI IRIX

HOMOLOGY MODELING
        USES & BACKGROUND
        BASIC GUIDE
        FOLD ASSIGNMENT
        TEMPLATE & ALIGNMENT
        BUILDING THE MODEL
        REFINEMENT & EVALUATION

DOCKING
        USES
        BACKGROUND
        SETTING UP THE SYSTEM
        ACCESSING THE RESULTS

RATIONAL DRUG DESIGN
        USES
        BACKGROUND

MOLECULAR DYNAMICS
        USES
        BACKGROUND
        SETTING UP THE SYSTEM
        ACCESSING THE RESULTS

 

 

  

Homology Modeling

The following document gives some indepth information about homology modeling. A modeling tutorial using DS Modeling (Accelrys) can be found here.

STEP 4: Model evaluation

The source of errors in comparative modelling is mainly due to the lack of templates and the decrease in sequence identity between the target and the templates. These errors are split in five categories:

  • Errors in side-chain packing . They are mainly due to the divergence of sequences and critical when occurring in regions involved in the protein function.
  • Shifts of correctly aligned residues . Also they are produced by the divergence of the templates, where the overall fold remains but the scaffold has been locally displaced.
  • Regions without template .This is produced in local regions where the target sequence can not be aligned to any of the parents with known structure. These regions belong to the SVRs, and the structure is derived from general databases, hence increasing the conformational diversity that implies the largest errors on the model.
  • Errors due to misalignments . This is produced by a shift on the alignment between the target sequence and the templates an are the worst source of errors, because up to date they are difficult to be detected. One way of detection is by using multiple alignments including sequences without known structure. However, if the misalignment is produced only in the target sequence the multiple alignment is useless. The best way to detect these errors is by check of the final model and further refinement.
  • Errors produced by incorrect templates . This problem appears when using distantly related sequences (templates with less than 25% identity) and it is also a difficult problem although it is clearly detected. This represents a difficult problem only for models for which no other homolog templates can be used. Unfortunately, distinguishing between errors produced for a model based on an incorrect alignment with the correct template (previous error 4) and errors produced for a model based on an incorrect template is difficult..
The evaluation of a model is critical for testing and suggesting the best and most accurate model or models. Additionally, the environment can have an important influence on the accuracy of the model, particularly if the protein structure is coordinated to metals or the template used is involved in a complex with other molecular compounds . Two criteria are used to filter the models : 1) based on energetic approaches; and 2) based on experimental data. On the first step, the model is checked to preserve the correct stereochemistry of a protein polymer. This is done with programs like PROCHECK , AQUA , SQUID or WHATCHECK and it can be fixed by using optimization programs based on molecular mechanics like CHARMM , GROMOS , AMBER , X-PLOR or WHAT IF. This implies a final refinement step on the modelling that has to be taken cautiously, mainly because the optimization is done in the wrong environment (i.e. with no solvation, no ions and not necessarily meaningful conformation for side-chains). This refinement is meant to simply remove drastic and local clashes and is done by a few cycles (100-1000) of steepest descent or conjugate gradient minimization runs until achieving convergence . The next step on the evaluation is the assessment of the fold which includes the order and length of the secondary structure elements and the use of energetic profiles introduced by statistical criteria extracted from the structure domain classifications. This implies that the structure will have a particular Z-score calculated by means of fold prediction methodologies indicating those regions wrongly modelled (according to statistical means). The programs VERIFY3D , PROSAII , HARMONY or ANOLEA are among those implementing this approach. In summary, these methods compare the modelled conformation with respect to the expected or standard structure on the X-ray solved protein structures. Although some criticism is introduced at this point, it is reasonably that individual contributions of each residue to the overall energy vary widely. Therefore it seems that there should not be a correlation between wrongly modelled regions and the amount of mean force potential on the region. Still, some applications have proved the use of this method by combination with additional information (secondary structure) to refine the models. The work of Aloy et al. is a clear example where mean force potentials detect wrongly modelled regions and suggest a method to improve the model building by: 1) distinguishing the wrongly modelled regions; 2) selecting the best model between several candidates; and 3) selecting a candidate refined structure after inclusion of additional information (i.e. secondary structure).

Finally, the recent work of Lazaridis and Karplus , shows the improvement on the classical molecular mechanics calculation of the energy by including solvation (environmental) terms to detect wrongly modelled regions. Consequently, the criticism on the potential of mean force can not be applied to this approach that did perform as well as statistical functions in discriminating correct and misfolded models .

The experimental evaluation of the model can only be done by site directed mutagenesis or additional information which is not commonly obtained. One way to escape the experiment is by using the knowledge obtained from a highly spread multiple alignments of related sequences introducing the following conditions:

  • From such a multiple alignment there are observed conserved regions shared on all sequences, hence reducing the length of SCRs. The surviving common structural regions produced from an extensive refinement of the structural alignment often include the active sites plus additional core secondary structure elements that appear to lend structural support to the binding site. These regions conserve the stereo-specific interactions involved in ligand binding and catalysis. The structural knowledge of these regions, as well as the support for their presence, grow in importance with the development of structural genomics and introduces a mechanism to evaluate the modelled structure that has to agree with these findings.
  • Those residues with no conservation and mutually involved by a 3D interaction or functionality will present clear correlation in its mutation. Cases of correlated mutations have been deeply studied because of its use on ab initio folding and fold prediction, and in cases where sequences have diverged enough it is possible to use the correlation to evaluate the correct modeling of the target conformation.
 

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