From Protein Structure to Function with Bioinformatics.pdf

3 Comparative Protein Structure Modelling 73regularly updates the fragment library and performs predictions. Predicted segmentsare returned or, optionally, these can be completed with side chain reconstructionand subsequently annealed in the environment of the query protein byconjugate gradient minimization.In summary, the recent reports about the more favourable coverage of loop conformationsin the PDB suggest that database approaches are now limited by theirability to recognize suitable fragments, and not by the lack of these segments(i.e. sampling), as earlier thought.Ab Initio Modelling of LoopsTo overcome the limitations of the database search methods, conformationalsearch methods were developed. There are many such methods, exploiting differentprotein representations, objective function terms, and optimization or enumerationalgorithms. The search strategies include the minimum perturbationmethod (Fine et al. 1986), molecular dynamics simulations (Bruccoleri andKarplus 1987), genetic algorithms (Ring and Cohen 1993), Monte Carlo andsimulated annealing (Abagyan and Totrov 1994; Collura et al. 1993), multiplecopysimultaneous search (Zheng et al. 1993), self-consistent field optimization(Koehl and Delarue 1995), and an enumeration based on the graph theory(Samudrala and Moult 1998). Loop prediction by optimization is applicable toboth simultaneous modelling of several loops and to those loops interacting withligands, neither of which is straightforward for the database search approaches,where fragments are collected from unrelated structures with differentenvironments.The MODLOOP module in MODELLER implements the optimization-basedapproach (Fiser et al. 2000; Fiser and Sali 2003b). Loop optimization inMODLOOP relies on conjugate gradients and molecular dynamics with simulatedannealing. The pseudo energy function is a sum of many terms, includingsome terms from the CHARMM-22 molecular mechanics force field (Brookset al. 1983) and spatial restraints based on distributions of distances (Melo andFeytmans 1997; Sippl 1990) and dihedral angles in known protein structures. Tosimulate comparative modelling problems, the loop modelling procedure wasoptimized and evaluated on a large number of loops of known structure both innative and in only approximately correct environments. The performance of theapproach later was further improved by using CHARMM molecular mechanicforcefield with Generalized Born (GB) solvation potential to rank final conformations(Fiser et al. 2002). Incorporation of solvation terms in the scoring functionwas a central theme in several other subsequent studies (Das and Meirovitch2003; de Bakker et al. 2003; DePristo et al. 2003; Forrest and Woolf 2003).Improved loop prediction accuracy resulted from the incorporation of an entropylike term to the scoring function, the “colony energy”, derived from geometricalcomparisons and clustering of sampled loop conformations (Fogolari andTosatto 2005; Xiang et al. 2002). The continuous improvement of scoring