Loop modeling: Difference between revisions

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'''Loop modeling''' is a problem in [[protein structure prediction]] requiring the prediction of the [[chemical conformation|conformations]] of [[loop (biochemistry)|loop]] regions in [[protein]]s with or without the use of a structural template. Computer programs that solve these problems have been used to research a broad range of scientific topics from [[Adenosine diphosphate|ADP]] to [[breast cancer]].<ref>{{cite (journal|last=Perraud|first=AL|coauthors=Takanishi, 2004CL; Shen, B; Kang, S; Smith, MK; Schmitz, C; Knowles, HM; Ferraris, D; Li, W; Zhang, J; Stoddard, BL; Scharenberg, AM|title=Accumulation of free ADP-ribose from mitochondria mediates oxidative stress-induced gating of TRPM2 cation channels.|journal=The Journal of biological chemistry|date=2005 Feb 18|volume=280|issue=7|pages=6138-48|pmid=15561722}}</ref> <ref>{{cite journal|last=Baloria|first=U|coauthors=Akhoon, 2012BA; Gupta, SK; Sharma, S; Verma, V|title=In silico proteomic characterization of human epidermal growth factor receptor 2 (HER-2) for the mapping of high affinity antigenic determinants against breast cancer.|journal=Amino acids|date=2012 Apr|volume=42|issue=4|pages=1349-60|pmid=21229277}}</ref> Because protein function is determined by its shape and the physiochemical properties of its exposed surface, it is important to create an accurate model for protein/ligand interaction studies.<ref>{{cite (journal|last=Fiser|first=A|coauthors=Sali, 2003)A|title=ModLoop: automated modeling of loops in protein structures.|journal=Bioinformatics (Oxford, England)|date=2003 Dec 12|volume=19|issue=18|pages=2500-1|pmid=14668246}}</ref> The problem arises often in [[homology modeling]], where the [[tertiary structure]] of an [[amino acid sequence]] is predicted based on a [[sequence alignment]] to a ''template'', or a second sequence whose structure is known. Because loops have highly variable sequences even within a given [[structural motif]] or [[protein folding|protein fold]], they often correspond to unaligned regions in sequence alignments; they also tend to be located at the [[solvent]]-exposed surface of [[globular protein]]s and thus are more conformationally flexible. Consequently, they often cannot be modeled using standard homology modeling techniques. More constrained versions of loop modeling are also used in the data fitting stages of solving a protein structure by [[X-ray crystallography]], because loops can correspond to regions of low [[electron density]] and are therefore difficult to resolve.

Regions of a structural model that are predicted by non-template-based loop modeling tend to be much less accurate than regions that are predicted using template-based techniques. The extent of the inaccuracy increases with the number of [[amino acid]]s in the loop. The loop amino acids' [[side chain]]s [[dihedral angle]]s are often approximated from a [[rotamer]] library, but can worsen the inaccuracy of side chain packing in the overall model. [[Andrej Sali]]'s homology modeling suite [[MODELLER]] includes a facility explicitly designed for loop modeling by a satisfaction of spatial restraints method.

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==Non-Template Based Techniques==

Otherwise known as an ''ab initio'' method, non-template based approaches use a statistical model to fill in the gaps created by the unknown loop structure. Some of these programs include MODELLER, Loopy, and RAPPER; but each of these programs approaches the problem in a different manner. For example, Loopy uses samples of torsion angle pairs to generate the initial loop structure then it revises this structure to maintain a realistic shape and closure, while RAPPER builds from one end of the gap to the other by extending the stem with different sampled angles until the gap is closed.<ref>{{cite (journal|last=Holtby|first=Daniel|coauthors=Shuai Cheng Li, Ming Li|title=LoopWeaver – Loop Modeling by the Weighted Scaling of Verified Proteins|journal=Lecture Notes in Computer Science|year=2012).|volume=7262|pages=113-126}}</ref> Yet another method is the “divide and conquer” approach. This involves subdividing the loop into 2 segments and then repeatedly dividing and transforming each segment until the loop is small enough to be solved.<ref>{{cite (journal|last=Tosatto|first=SC|coauthors=Bindewald, 2002)E; Hesser, J; Männer, R|title=A divide and conquer approach to fast loop modeling.|journal=Protein engineering|date=2002 Apr|volume=15|issue=4|pages=279-86|pmid=11983928}}</ref> Even with all these methods non-template based approaches are most accurate up to 12 residues (an amino acid within the loop).

There are three problems that arise when using a non-template based technique. First, there are constraints that limit the possibilities for local region modeling. One such constraint is that loop termini are required to end at the correct anchor position. Also, the [[Ramachandran plot| Ramachandran]] space cannot contain a backbone of [[dihedral angle]]s. Second, a modeling program has to use a set procedure. Some programs use the “spare parts” approach as mentioned above. Other programs use a ‘’[[wikt:Special:Search/de novo|de novo]]’’ approach that samples sterically feasible loop conformations and selects the best one. Third, determining the best model means that a scoring method must be created to compare the various conformations.<ref>{{cite (journal|last=Adhikari|first=AN|coauthors=Peng, 2012)J; Wilde, M; Xu, J; Freed, KF; Sosnick, TR|title=Modeling large regions in proteins: applications to loops, termini, and folding.|journal=Protein science : a publication of the Protein Society|date=2012 Jan|volume=21|issue=1|pages=107-21|pmid=22095743}}</ref>

==ReferencesNotes==

* Adhikari A, et al. (2012). Modeling large regions in proteins: Applications to loops, termini, and folding. Protein Science 21: 107-121

* Baloria U, Akhoon B A, Gupta S K, Sharma S, Verma V. In silico proteomic characterization of human epidermal growth factor receptor 2 (HER-2) for the mapping of high affinity antigenic determinants against breast cancer. Amino Acids 42, 1349-1360 (2012).

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* [http://bioinf-applied.charite.de/superlooper SuperLooper], SuperLooper homepage

* [http://falc-loop.seoklab.org FALC-Loop], FALC-Loop homepage

==References==

{{Reflist}}

[[Category:Bioinformatics]]