CPSP-web-tools: a server for 3D lattice protein studies

Mann, Martin; Smith, Cameron; Rabbath, Mohamad; Edwards, Marlien; Will, Sebastian; Backofen, Rolf

doi:10.1093/bioinformatics/btp034

Cited by 25 publications

(32 citation statements)

References 12 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Its basic version is tailored for 3D backbone-only HP models [43,45,73,74] but was extended to other models. Among them are the extension to the HPNX model [46,75] or to side-chain structure models [44], both later discussed in detail. In contrast to most tools and approaches in the field, a CPSP implementation is available for local installation [45,76] and ad hoc web usage [44,77].…”

Section: Constraint-based Protein Structure Predictionmentioning

confidence: 99%

“…Among them are the extension to the HPNX model [46,75] or to side-chain structure models [44], both later discussed in detail. In contrast to most tools and approaches in the field, a CPSP implementation is available for local installation [45,76] and ad hoc web usage [44,77]. Thus, it has spawned the compilation of extensive benchmark data sets of protein-like sequences with various folding features [78].…”

Section: Constraint-based Protein Structure Predictionmentioning

confidence: 99%

“…When extending the approach to side-chain lattice protein models [44,50], only an adoption of the CSP is needed while the overall workflow is kept. The contact-based energy computation in side-chain models is restricted to side-chain monomers only [50].…”

Section: Optimal Structure Identificationmentioning

confidence: 99%

“…Self-avoidance is enforced for all variables, i.e., all monomer positions. This CPSP modeling extension enables, for the first time, the exact identification of optimal structures in the side-chain HP model in threedimensional lattices [44,50]. The complete enumeration of optimal side-chain structures is also enabled; however, the enormous structure space growth (see Figure 1) and the high degeneracy of the HP model yield often hundreds to millions optimal structures.…”

Section: Optimal Structure Identificationmentioning

confidence: 99%

“…While the CHCC approach was the first exact PSP method, it was proven to be incomplete when enumerating all optimal structures [43]. In contrast, the constraint-based protein structure prediction (CPSP) approach [43][44][45] was shown to be exact and complete when calculating optimal structures. CPSP uses a similar strategy as CHCC and is thus far the only exact and complete method for protein structure prediction in lattice protein models.…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

Exact methods for lattice protein models

Mann

Backofen²

2014

Bio-Algorithms and Med-Systems

View full text Add to dashboard Cite

Lattice protein models are well-studied abstractions of globular proteins. By discretizing the structure space and simplifying the energy model over regular proteins, they enable detailed studies of protein structure formation and evolution. However, even in the simplest lattice protein models, the prediction of optimal structures is computationally difficult. Therefore, often, heuristic approaches are applied to find such conformations.Commonly, heuristic methods find only locally optimal solutions. Nevertheless, there exist methods that guarantee to predict globally optimal structures. Currently, only one such exact approach is publicly available, namely the constraint-based protein structure prediction method and variants. Here, we review exact approaches and derived methods. We discuss fundamental concepts like hydrophobic core construction and their use in optimal structure prediction, as well as possible applications like combinations of different energy models.

show abstract

Section: Constraint-based Protein Structure Predictionmentioning

confidence: 99%

Section: Constraint-based Protein Structure Predictionmentioning

confidence: 99%

Section: Optimal Structure Identificationmentioning

confidence: 99%

Section: Optimal Structure Identificationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Exact methods for lattice protein models

Mann

Backofen²

2014

Bio-Algorithms and Med-Systems

View full text Add to dashboard Cite

show abstract

A versatile method for systematic conformational searches: Application to CheY

Petrella¹

2011

J Comput Chem

View full text Add to dashboard Cite

A novel molecular structure prediction method, the Z Method, is described. It provides a versatile platform for the development and use of systematic, grid-based conformational search protocols, in which statistical information (i.e., rotamers) can also be included. The Z Method generates trial structures by applying many changes of the same type to a single starting structure, thereby sampling the conformation space in an unbiased way. The method, implemented in the CHARMM program as the Z Module, is applied here to an illustrative model problem in which rigid, systematic searches are performed in a 36-dimensional conformational space that describes the relative positions of the ten secondary structural elements of the protein CheY. A polar hydrogen representation with an implicit solvation term (EEF1) is used to evaluate successively larger fragments of the protein generated in a hierarchical build-up procedure. After a final refinement stage, and a total computational time of about two-and-a-half days on AMD Opteron processors, the prediction is within 1.56 Å of the native structure. The errors in the predicted backbone dihedral angles are found to approximately cancel. Monte Carlo and simulated annealing trials on the same or smaller versions of the problem, using the same atomic model and energy terms, are shown to result in less accurate predictions. Although the problem solved here is a limited one, the findings illustrate the utility of systematic searches with atom-based models for macromolecular structure prediction and the importance of unbiased sampling in structure prediction methods.

show abstract