Mechanical Strength of 17 134 Model Proteins and Cysteine Slipknots

A new theoretical survey of proteins' resistance to constant speed stretching is performed for a set of 17 134 proteins as described by a structure-based model. The proteins selected have no gaps in their structure determination and consist of no more than 250 amino acids. Our previous studies have dealt with 7510 proteins of no more than 150 amino acids. The proteins are ranked according to the strength of the resistance. Most of the predicted top-strength proteins have not yet been studied experimentally. Architectures and folds which are likely to yield large forces are identified. New types of potent force clamps are discovered. They involve disulphide bridges and, in particular, cysteine slipknots. An effective energy parameter of the model is estimated by comparing the theoretical data on characteristic forces to the corresponding experimental values combined with an extrapolation of the theoretical data to the experimental pulling speeds. These studies provide guidance for future experiments on single molecule manipulation and should lead to selection of proteins for applications. A new class of proteins, involving cystein slipknots, is identified as one that is expected to lead to the strongest force clamps known. This class is characterized through molecular dynamics simulations.Comment: 40 pages, 13 PostScript figure

Implementation and evaluation of new protocol for comparative modeling of protein structures

Template-based modeling (termed also Comparative or Homology Modeling) of a protein structure is one of ubiquitous tasks of structural bioinfor matics. The method can deliver model structures important for testing biological hypotheses, virtual docking and drug design. The performance of these methods is evaluated every two years during a Critical Assessment of Protein Structure Prediction (CASP) experiment. In this contribution we present a new automated protocol for template-base d modeling, which combines computational tools recently developed in our laboratory: the dat abase of protein domain structures (BDDB) with one dimensional and three dimensional thread ing applications. The protocol was tested during a CASP11 experiment

Mechanical unfolding of DDFLN4 studied by coarse-grained knowledge-based CABS model

Mechanical unfolding of the fourth domain of Distyostelium discoideum filamin ( DDFLN 4) was studied using a CABS – coarse-grained knowledge-based protein model. Our study demonstrates that CABS is capable of reproducing the unfolding free energy landscape of protein unfolding and highlights an important role of non-native interactions in the protein unfolding process. The obtained three peaks in the force-extension profile suggest a four-state picture of DDFLN 4 protein unfolding and correspond reasonably to the results of the all-atom simulation in explicit solvent

BioShell 3.0: Library for Processing Structural Biology Data

BioShell is an open-source package for processing biological data, particularly focused on structural applications. The package provides parsers, data structures and algorithms for handling and analyzing macromolecular sequences, structures and sequence profiles. The most frequently used routines are accessible by a set of easy-to-use command line utilities for a Linux environment. The full functionality of the package assumes knowledge of C++ or Python to assemble an application using this software library. Since the last publication that announced the version 2.0, the package has been greatly expanded and rewritten in C++ standard 11 (C++11) to improve its modularity and efficiency. A new testing platform has been implemented to continuously test the correctness and integrity of the package. More than two hundred test programs have been published to provide simple examples that can be used as templates. This makes BioShell an easy to use library that greatly speeds up development of bioinformatics applications and web services without compromising computational efficiency