Silvia N. Crivelli

SEA domain proteolysis determines the functional composition of dystroglycan

Post‐translational modifications of the extracellular matrix receptor dystroglycan (DG) determine its functional state, and defects in these modifications are linked to muscular dystrophies and cancers. A prominent feature of DG biosynthesis is a precursor cleavage that segregates the ligand‐binding and transmembrane domains into the noncovalently attached α‐and β‐subunits. We investigate here the structural determinants and functional significance of this cleavage. We show that cleavage of DG elicits a conspicuous change in its ligand‐binding activity. Mutations that obstruct this cleavage result in increased capacity to bind laminin, in part, due to enhanced glycosylation of α‐DG. Reconstitution of DG cleavage in a cell‐free expression system demonstrates that cleavage takes place in the endoplasmic reticulum, providing a suitable regulatory point for later processing events. Sequence and mutational analyses reveal that the cleavage occurs within a full SEA (sea urchin, enterokinase, agrin) module with traits matching those ascribed to autoproteolysis. Thus, cleavage of DG constitutes a control point for the modulation of its ligand‐binding properties, with therapeutic implications for muscular dystrophies. We provide a structural model for the cleavage domain that is validated by experimental analysis and discuss this cleavage in the context of mucin protein and SEA domain evolution. Akhavan, A., Crivelli, S. N., Singh, M., Lingappa, V. R., Muschler, J. L. SEA domain proteolysis determines the functional composition of dystroglycan. FASEB J. 22, 612–621 (2008)

ProteinShop: A tool for interactive protein manipulation and steering

We describe ProteinShop, a new visualization tool that streamlines and simplifies the process of determining optimal protein folds. ProteinShop may be used at different stages of a protein structure prediction process. First, it can create protein configurations containing secondary structures specified by the user. Second, it can interactively manipulate protein fragments to achieve desired folds by adjusting the dihedral angles of selected coil regions using an Inverse Kinematics method. Last, it serves as a visual framework to monitor and steer a protein structure prediction process that may be running on a remote machine. ProteinShop was used to create initial configurations for a protein structure prediction method developed by a team that competed in CASP5. ProteinShops use accelerated the process of generating initial configurations, reducing the time required from days to hours. This paper describes the structure of ProteinShop and discusses its main features.

BuildBeta—A system for automatically constructing beta sheets

We describe a method that can thoroughly sample a protein conformational space given the protein primary sequence of amino acids and secondary structure predictions. Specifically, we target proteins with β‐sheets because they are particularly challenging for ab initio protein structure prediction because of the complexity of sampling long‐range strand pairings. Using some basic packing principles, inverse kinematics (IK), and β‐pairing scores, this method creates all possible β‐sheet arrangements including those that have the correct packing of β‐strands. It uses the IK algorithms of ProteinShop to move α‐helices and β‐strands as rigid bodies by rotating the dihedral angles in the coil regions. Our results show that our approach produces structures that are within 4–6 Å RMSD of the native one regardless of the protein size and β‐sheet topology although this number may increase if the protein has long loops or complex α‐helical regions. Proteins 2010.

A new load-balancing strategy for the solution of dynamical large-tree-search problems using a hierarchical approach

We describe a new load-balancing strategy, applied here to the protein structure prediction problem, for improving the efficiency of the hierarchical approach when dealing with coarse-grained problems associated with large tree searches. Unlike other load-balancing strategies that reassign load from the heavily loaded processors to the lightly loaded or idle ones, the proposed strategy changes the virtual communication tree among the processors as the computational tree changes. The strategy incurs minimal overhead and is scalable.

A Hierarchical Approach for Parallelization of a Global Optimization Method for Protein Structure Prediction

We discuss the parallelization of our protein structure prediction algorithm on distributed-memory computers. Because the computation can be represented as a search through a vast tree of possible solutions, a hierarchical approach that assigns subtrees to different groups of processors allows us to partition the work efficiently and maintain information updated without incurring significant communication overhead. Our results show that a dynamic strategy for load balancing outperforms the static one.

An optimization approach to the problem of protein structure prediction

Abstract.We describe a large-scale, stochastic-perturbation global optimization algorithm used for determining the structure of proteins. The method incorporates secondary structure predictions (which describe the more basic elements of the protein structure) into the starting structures, and thereafter minimizes using a purely physics-based energy model. Results show this method to be particularly successful on protein targets where structural information from similar proteins is unavailable, i.e., the most difficult targets for most protein structure prediction methods. Our best result to date is on a protein target containing over 4000 atoms and ∼12,000 cartesian coordinates.

Visualization of Force Fields in Protein Structure Prediction

The force fields used in molecular computational biology are not mathematically defined in such a way that their representation would facilitate a straightforward application of volume visualization techniques. To visualize energy, it is necessary to define a spatial mapping for these fields. Equipped with such a mapping, we can generate volume renderings of the internal energy states of a molecule. We describe our force field, the spatial mapping that we use for energy, and the visualizations that we produce from this mapping. We provide images and animations that offer insight into the computational behavior of the energy optimization algorithms that we employ.

ProteinShop and POSE: bringing robotics and intelligent systems into the field of molecular modeling

ProteinShop and POSE are graphical infrastructures for the interactive modeling, manipulation, optimization and analysis of molecules. They were designed to bring interactive computer graphics in the field of molecular modeling to a level not attempted by other visualization programs. To achieve that goal, we adapted inverse kinematics algorithms commonly used in robotics to permit interactive manipulation of protein structures in a natural and intuitive way.