Potentials of mean force for protein structure prediction vindicated, formalized and generalized.

Understanding protein structure is of crucial importance in science, medicine and biotechnology. For about two decades, knowledge-based potentials based on pairwise distances--so-called "potentials of mean force" (PMFs)--have been center stage in the prediction and design of protein structure and the simulation of protein folding. However, the validity, scope and limitations of these potentials are still vigorously debated and disputed, and the optimal choice of the reference state--a necessary component of these potentials--is an unsolved problem.

Beyond rotamers: a generative, probabilistic model of side chains in proteins.

Background: Accurately covering the conformational space of amino acid side chains is essential for important applications such as protein design, docking and high resolution structure prediction. Today, the most common way to capture this conformational space is through rotamer libraries - discrete collections of side chain conformations derived from experimentally determined protein structures. The discretization can be exploited to efficiently search the conformational space.

Mocapy++--a toolkit for inference and learning in dynamic Bayesian networks.

Background: Mocapy++ is a toolkit for parameter learning and inference in dynamic Bayesian networks (DBNs). It supports a wide range of DBN architectures and probability distributions, including distributions from directional statistics (the statistics of angles, directions and orientations).

Results: The program package is freely available under the GNU General Public Licence (GPL) from SourceForge http://sourceforge.

Applying Undertaker to quality assessment.

Our group tested three quality assessment functions in CASP8: a function which used only distance constraints derived from alignments (SAM-T08-MQAO), a function which added other single-model terms to the distance constraints (SAM-T08-MQAU), and a function which used both single-model and consensus terms (SAM-T08-MQAC). We analyzed the functions both for ranking models for a single target and for producing an accurate estimate of GDT_TS. Our functions were optimized for the ranking problem, so are perhaps more appropriate for metaserver applications than for providing trustworthiness estimates for single models.

Model quality assessment using distance constraints from alignments.

Given a set of alternative models for a specific protein sequence, the model quality assessment (MQA) problem asks for an assignment of scores to each model in the set. A good MQA program assigns these scores such that they correlate well with real quality of the models, ideally scoring best that model which is closest to the true structure. In this article, we present a new approach for addressing the MQA problem.

Reconstructing protein structure from solvent exposure using tabu search.

Background: A new, promising solvent exposure measure, called half-sphere-exposure (HSE), has recently been proposed. Here, we study the reconstruction of a protein's Calpha trace solely from structure-derived HSE information. This problem is of relevance for de novo structure prediction using predicted HSE measure.