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Protein Docking (protein + docking)
Selected AbstractsProtein,protein docking dealing with the unknownJOURNAL OF COMPUTATIONAL CHEMISTRY, Issue 2 2010Irina S. Moreira Abstract Protein,protein binding is one of the critical events in biology, and knowledge of proteic complexes three-dimensional structures is of fundamental importance for the biochemical study of pharmacologic compounds. In the past two decades there was an emergence of a large variety of algorithms designed to predict the structures of protein,protein complexes,a procedure named docking. Computational methods, if accurate and reliable, could play an important role, both to infer functional properties and to guide new experiments. Despite the outstanding progress of the methodologies developed in this area, a few problems still prevent protein,protein docking to be a widespread practice in the structural study of proteins. In this review we focus our attention on the principles that govern docking, namely the algorithms used for searching and scoring, which are usually referred as the docking problem. We also focus our attention on the use of a flexible description of the proteins under study and the use of biological information as the localization of the hot spots, the important residues for protein,protein binding. The most common docking softwares are described too. © 2009 Wiley Periodicals, Inc. J Comput Chem, 2010 [source] Docking study and free energy simulation of the complex between p53 DNA-binding domain and azurinJOURNAL OF MOLECULAR RECOGNITION, Issue 4 2007Valentina De Grandis Abstract Molecular interaction between p53 tumor suppressor and the copper protein azurin (AZ) has been demonstrated to enhance p53 stability and hence antitumoral function, opening new perspectives in cancer treatment. While some experimental work has provided evidence for AZ binding to p53, no crystal structure for the p53,AZ complex was solved thus far. In this work the association between AZ and the p53 DNA-binding domain (DBD) was investigated by computational methods. Using a combination of rigid-body protein docking, experimental mutagenesis information, and cluster analysis 10 main p53 DBD,AZ binding modes were generated. The resulting structures were further characterized by molecular dynamics (MD) simulations and free energy calculations. We found that the highest scored docking conformation for the p53 DBD,AZ complex also yielded the most favorable free energy value. This best three-dimensional model for the complex was validated by using a computational mutagenesis strategy. In this structure AZ binds to the flexible L1 and s7,s8 loops of the p53 DBD and stabilizes them through protein,protein tight packing interactions, resulting in high degree of both surface matching and electrostatic complementarity. Copyright © 2007 John Wiley & Sons, Ltd. [source] CIRSE: A solvation energy estimator compatible with flexible protein docking and design applicationsPROTEIN SCIENCE, Issue 7 2006David S. Cerutti Abstract We present the Coordinate Internal Representation of Solvation Energy (CIRSE) for computing the solvation energy of protein configurations in terms of pairwise interactions between their atoms with analytic derivatives. Currently, CIRSE is trained to a Poisson/surface-area benchmark, but CIRSE is not meant to fit this benchmark exclusively. CIRSE predicts the overall solvation energy of protein structures from 331 NMR ensembles with 0.951 ± 0.047 correlation and predicts relative solvation energy changes between members of individual ensembles with an accuracy of 15.8 ± 9.6 kcal/mol. The energy of individual atoms in any of CIRSE's 17 types is predicted with at least 0.98 correlation. We apply the model in energy minimization, rotamer optimization, protein design, and protein docking applications. The CIRSE model shows some propensity to accumulate errors in energy minimization as well as rotamer optimization, but these errors are consistent enough that CIRSE correctly identifies the relative solvation energies of designed sequences as well as putative docked complexes. We analyze the errors accumulated by the CIRSE model during each type of simulation and suggest means of improving the model to be generally useful for all-atom simulations. [source] Research Article: pso@autodock: A Fast Flexible Molecular Docking Program Based on Swarm IntelligenceCHEMICAL BIOLOGY & DRUG DESIGN, Issue 6 2007Vigneshwaran Namasivayam On the quest of novel therapeutics, molecular docking methods have proven to be valuable tools for screening large libraries of compounds determining the interactions of potential drugs with the target proteins. A widely used docking approach is the simulation of the docking process guided by a binding energy function. On the basis of the molecular docking program autodock, we present pso@autodock as a tool for fast flexible molecular docking. Our novel Particle Swarm Optimization (PSO) algorithms varCPSO and varCPSO-ls are suited for rapid docking of highly flexible ligands. Thus, a ligand with 23 rotatable bonds was successfully docked within as few as 100 000 computing steps (rmsd = 0.87 Å), which corresponds to only 10% of the computing time demanded by autodock. In comparison to other docking techniques as gold 3.0, dock 6.0, flexx 2.2.0, autodock 3.05, and sodock, pso@autodock provides the smallest rmsd values for 12 in 37 protein,ligand complexes. The average rmsd value of 1.4 Å is significantly lower then those obtained with the other docking programs, which are all above 2.0 Å. Thus, pso@autodock is suggested as a highly efficient docking program in terms of speed and quality for flexible peptide,protein docking and virtual screening studies. [source] | ||||||||||