hp-Adaptive simulation and inversion of magnetotelluric measurements

xlix, 121 p.

A Computational Module Assembled from Different Protease Family Motifs Identifies PI PLC from Bacillus cereus as a Putative Prolyl Peptidase with a Serine Protease Scaffold

Proteolytic enzymes have evolved several mechanisms to cleave peptide bonds. These distinct types have been systematically categorized in the MEROPS database. While a BLAST search on these proteases identifies homologous proteins, sequence alignment methods often fail to identify relationships arising from convergent evolution, exon shuffling, and modular reuse of catalytic units. We have previously established a computational method to detect functions in proteins based on the spatial and electrostatic properties of the catalytic residues (CLASP). CLASP identified a promiscuous serine protease scaffold in alkaline phosphatases (AP) and a scaffold recognizing a beta-lactam (imipenem) in a cold-active Vibrio AP. Subsequently, we defined a methodology to quantify promiscuous activities in a wide range of proteins. Here, we assemble a module which encapsulates the multifarious motifs used by protease families listed in the MEROPS database. Since APs and proteases are an integral component of outer membrane vesicles (OMV), we sought to query other OMV proteins, like phospholipase C (PLC), using this search module. Our analysis indicated that phosphoinositide-specific PLC from Bacillus cereus is a serine protease. This was validated by protease assays, mass spectrometry and by inhibition of the native phospholipase activity of PI-PLC by the well-known serine protease inhibitor AEBSF (IC50 = 0.018 mM). Edman degradation analysis linked the specificity of the protease activity to a proline in the amino terminal, suggesting that the PI-PLC is a prolyl peptidase. Thus, we propose a computational method of extending protein families based on the spatial and electrostatic congruence of active site residues.

Atomistic simulation studies of the cement paste components

230 p.

Insights into mechanism kinematics for protein motion simulation

Background: The high demanding computational requirements necessary to carry out protein motion simulations make it difficult to obtain information related to protein motion. On the one hand, molecular dynamics simulation requires huge computational resources to achieve satisfactory motion simulations. On the other hand, less accurate procedures such as interpolation methods, do not generate realistic morphs from the kinematic point of view. Analyzing a protein's movement is very similar to serial robots; thus, it is possible to treat the protein chain as a serial mechanism composed of rotational degrees of freedom. Recently, based on this hypothesis, new methodologies have arisen, based on mechanism and robot kinematics, to simulate protein motion. Probabilistic roadmap method, which discretizes the protein configurational space against a scoring function, or the kinetostatic compliance method that minimizes the torques that appear in bonds, aim to simulate protein motion with a reduced computational cost. Results: In this paper a new viewpoint for protein motion simulation, based on mechanism kinematics is presented. The paper describes a set of methodologies, combining different techniques such as structure normalization normalization processes, simulation algorithms and secondary structure detection procedures. The combination of all these procedures allows to obtain kinematic morphs of proteins achieving a very good computational cost-error rate, while maintaining the biological meaning of the obtained structures and the kinematic viability of the obtained motion. Conclusions: The procedure presented in this paper, implements different modules to perform the simulation of the conformational change suffered by a protein when exerting its function. The combination of a main simulation procedure assisted by a secondary structure process, and a side chain orientation strategy, allows to obtain a fast and reliable simulations of protein motion.