Comparative modelling by restraint-based conformational sampling

A new application of RAPPER for comparative modelling uses positional restraints and knowledge-based sampling to generate models with accuracies comparable to other leading modelling tools. Knowledge-based predictions are based on geometrical features of the homologous templates and rules concerning main-chain and side-chain conformations. By directly changing the restraints derived from available templates we estimate the accuracy limits of the method in comparative modelling.The application of RAPPER to comparative modelling provides an effective means of exploring the conformational space available to a target sequence. Enhanced methods for generating positional restraints can greatly improve structure prediction. Generation of an ensemble of solutions that are consistent with both target sequence and knowledge derived from the template structures provides a more appropriate representation of a structural prediction than a single model. By formulating homologous structural information as sets of restraints we can begin to consider how comparative models might be used to inform conformer generation from sparse experimental data.The three-dimensional (3D) structures of proteins provide valuable insights into their biochemical activities and biological functions. The most widely used experimental methods for determining 3D structures, X-ray crystallography and nuclear magnetic resonance (NMR), have limitations in both time and tractability. For X-ray crystallography sufficient quantities of purified proteins may be difficult to produce and to crystallize when obtained [1]. For NMR, proteins are often too large or insufficiently soluble to be tractable [2]. Nevertheless, genome sequencing projects create a continuing need to translate sequence information into structure [3].Where experimental methods are problematic, theoretical models can often provide valuable information about the structure of interest. Methods that use physical and chemical properties of amino ac