Characteritzation of protein-protein interfaces and identification of transient cavities for its modulation

Protein-protein interactions (PPIs) play an essential role in many biological processes, including disease conditions. Strategies to modulate PPIs with small molecules have therefore attracted increasing interest over the last few years, where successful PPI inhibitors have been reported into transient cavities from previously flat PPIfs. Recent studies emphasize on hot-spots (those residues contribute for most of the energy of binding) as promising targets for the modulation of PPI. PyDock is the only computational method that uses docking to predict PPIfs and hot-spots (HS) residues. Using Normalized Interface Propensity (NIP) values derived from rigid-body protein docking simulation, we are able to predict the PPIfs and HS residues without any prior structural knowledge of the complex. We benchmarked the protocol in a small set of protein-protein complexes for which both structural data and PPI inhibitors are known. We present an approach aimed at identifying HS and transient pockets from predicted PPIfs in order to find potential small molecules capable of modulating PPIs. The method uses pyDock to identify PPIfs and HS and molecular dynamics (MD) techniques to describe the possible fluctuations of the interacting proteins in order to suggest transient pockets. Afterwards, we evaluated the validity of predicted HS and pockets for in silico drug design by using ligand docking. We present a strategy based on MD and NIP which allows to identify cavities as potentially good targets to bind inhibitors when there is no information at all about the protein-protein complex structure

Synthesis of Y1Ba2Cu3O(sub x) superconducting powders by intermediate phase reaction

One of the more striking problems for the synthesis of the Y1Ba2Cu3Ox compound is the high-temperature decomposition of the BaCO3. This compound is present as raw material or as an intermediate compound in chemical processes such as amorphous citrate, coprecipitation oxalate, sol-gel process, acetate pyrolisis, etc. This fact makes difficult the total formation reaction of the Y1Ba2Cu3Ox phase and leads to the presence of undesirable phases such as the BaCuO2 phase, the 'green phase', Y2BaCuO5 and others. Here, a new procedure to overcome this difficulty is studied. The barium cation is previously combined with yttrium and/or copper to form intermediate compounds which can react between them to give Y1Ba2Cu3Ox. BaY2O4 and BaCu2O3 react according to the equation BaY2O4+3BaCu2O3 yields 2Y1Ba2Cu3Ox. BaY2O4 is a stable compound of the Y2O3-BaO system; BaCu2O3 is an intimate mixture of BaCuO2 and uncombined CuO. The reaction kinetics of these phases have been established between 860 and 920 C. The phase evolution has been determined. The crystal structure of the Y1Ba2Cu3Ox obtained powder was studied. According to the results obtained from the kinetics study the Y1Ba2Cu3Ox the synthesis was performed at temperatures of 910 to 920 C for short treatment times (1 to 2 hours). Pure Y1Ba2Cu3Ox was prepared, which develops orthorombic type I structure despite of the cooling cycle. Superconducting transition took place at 91 K. The sintering behavior and the superconducting properties of sintered samples were studied. Density, microstructure and electrical conductivity were measured. Sintering densities higher than 95 percent D(sub th) were attained at temperatures below 940 C. Relatively fine grained microstructure was observed, and little or no-liquid phase was detected

Synthesis of Y1BaCu3O(x) superconducting powders by intermediate phase reactions

A procedure for synthesizing Y1Ba2Cu3O(x) by solid state reactions was developed. The method is based on the use of barium compounds, previously synthesized, as intermediate phases for the process. The reaction kinetics of this procedure were established between 860 C and 920 C. The crystal structure and the presence of second phases were studied by means of XRD. The sintering behavior and ceramic parameters were also determined. The orthorhombic type-I structure was obtained on the synthesized bodies after a cooling cycle in an air atmosphere. Superconducting transition took place at 91 K. Sintering densities higher than 95 percent D sub th were attained at temperatures below 940 C

Prediction of protein-binding areas by small-world residue networks and application to docking

<p>Abstract</p> <p>Background</p> <p>Protein-protein interactions are involved in most cellular processes, and their detailed physico-chemical and structural characterization is needed in order to understand their function at the molecular level. In-silico docking tools can complement experimental techniques, providing three-dimensional structural models of such interactions at atomic resolution. In several recent studies, protein structures have been modeled as networks (or graphs), where the nodes represent residues and the connecting edges their interactions. From such networks, it is possible to calculate different topology-based values for each of the nodes, and to identify protein regions with high centrality scores, which are known to positively correlate with key functional residues, hot spots, and protein-protein interfaces.</p> <p>Results</p> <p>Here we show that this correlation can be efficiently used for the scoring of rigid-body docking poses. When integrated into the pyDock energy-based docking method, the new combined scoring function significantly improved the results of the individual components as shown on a standard docking benchmark. This improvement was particularly remarkable for specific protein complexes, depending on the shape, size, type, or flexibility of the proteins involved.</p> <p>Conclusions</p> <p>The network-based representation of protein structures can be used to identify protein-protein binding regions and to efficiently score docking poses, complementing energy-based approaches.</p

Structural assembly of two-domain proteins by rigid-body docking.

BACKGROUND: Modelling proteins with multiple domains is one of the central challenges in Structural Biology. Although homology modelling has successfully been applied for prediction of protein structures, very often domain-domain interactions cannot be inferred from the structures of homologues and their prediction requires ab initio methods. Here we present a new structural prediction approach for modelling two-domain proteins based on rigid-body domain-domain docking. RESULTS: Here we focus on interacting domain pairs that are part of the same peptide chain and thus have an inter-domain peptide region (so called linker). We have developed a method called pyDockTET (tethered-docking), which uses rigid-body docking to generate domain-domain poses that are further scored by binding energy and a pseudo-energy term based on restraints derived from linker end-to-end distances. The method has been benchmarked on a set of 77 non-redundant pairs of domains with available X-ray structure. We have evaluated the docking method ZDOCK, which is able to generate acceptable domain-domain orientations in 51 out of the 77 cases. Among them, our method pyDockTET finds the correct assembly within the top 10 solutions in over 60% of the cases. As a further test, on a subset of 20 pairs where domains were built by homology modelling, ZDOCK generates acceptable orientations in 13 out of the 20 cases, among which the correct assembly is ranked lower than 10 in around 70% of the cases by our pyDockTET method. CONCLUSION: Our results show that rigid-body docking approach plus energy scoring and linker-based restraints are useful for modelling domain-domain interactions. These positive results will encourage development of new methods for structural prediction of macromolecules with multiple (more than two) domains.RIGHTS : This article is licensed under the BioMed Central licence at http://www.biomedcentral.com/about/license which is similar to the 'Creative Commons Attribution Licence'. In brief you may : copy, distribute, and display the work; make derivative works; or make commercial use of the work - under the following conditions: the original author must be given credit; for any reuse or distribution, it must be made clear to others what the license terms of this work are

pyDock performance in 5th CAPRI edition: from docking and scoring to binding affinity predictions and other challenges

Proteins form the executive machinery underlying all the biological processes that occur within and between cells, from DNA replication to protein degradation. Although genome-scale technologies enable to clarify their large, intricate and highly dynamics networks, they fail to elucidate the detailed molecular mechanism that underlies the protein association process. Therefore, one of the most challenging objectives in biological research is to functionally characterize protein interactions by solving 3D complex structures. This is, however, not a trivial task as confirmed by the large gap that exist between the number of complexes identified by large-scale proteomics efforts and those for which high-resolution 3D experimental structures are available. For these reasons, computational docking methods, aimed to predict the binding mode of two proteins starting from the coordinates of the individual subunits, are bound to become a complementary approach to solve the structural interactome. Given its importance, the field of protein docking has experienced an explosion in recent years partially propelled by CAPRI (http://www.ebi.ac.uk/msd-srv/capri/). CAPRI (Critical Assessment of PRedicted Interaction) is a community-wide blind experiment aimed at objectively assessing the performance of computational methods for modeling protein interactions by inviting developers to test their algorithms on the same target system and quantitatively evaluating the results. In order to test pyDock,1 a docking scoring algorithm developed in our group, the PID (Protein Interaction and Docking) group of the BSC Life Science Department, we have participated in all the 15 targets (T46 to T58) of the 5th CAPRI edition (2010-2012). Our automated protocol confirmed to be highly successful to provide correct models in easy-to-medium difficulty protein-protein docking cases placing among the Top5 ranked groups out of more than 60 participants. Key words: Complex structure, CAPRI, protein-protein docking, pyDock, protein interactions

Exploring the relationship between gene expression and topological properties of Arabidopsis thaliana interactome network.

The aim of this study is to integrate and link up transcriptomic data with biological networks approaches. The main objective was to determinate the correlation of transcriptomic profiles with PPI topology, seeking to demonstrate relational or structural patterns within the network internal organization

pyDock performance in 5th CAPRI edition: from docking and scoring to binding affinity predictions and other challenges

Proteins form the executive machinery underlying all the biological processes that occur within and between cells, from DNA replication to protein degradation. Although genome-scale technologies enable to clarify their large, intricate and highly dynamics networks, they fail to elucidate the detailed molecular mechanism that underlies the protein association process. Therefore, one of the most challenging objectives in biological research is to functionally characterize protein interactions by solving 3D complex structures. This is, however, not a trivial task as confirmed by the large gap that exist between the number of complexes identified by large-scale proteomics efforts and those for which high-resolution 3D experimental structures are available. For these reasons, computational docking methods, aimed to predict the binding mode of two proteins starting from the coordinates of the individual subunits, are bound to become a complementary approach to solve the structural interactome. Given its importance, the field of protein docking has experienced an explosion in recent years partially propelled by CAPRI (http://www.ebi.ac.uk/msd-srv/capri/). CAPRI (Critical Assessment of PRedicted Interaction) is a community-wide blind experiment aimed at objectively assessing the performance of computational methods for modeling protein interactions by inviting developers to test their algorithms on the same target system and quantitatively evaluating the results. In order to test pyDock,1 a docking scoring algorithm developed in our group, the PID (Protein Interaction and Docking) group of the BSC Life Science Department, we have participated in all the 15 targets (T46 to T58) of the 5th CAPRI edition (2010-2012). Our automated protocol confirmed to be highly successful to provide correct models in easy-to-medium difficulty protein-protein docking cases placing among the Top5 ranked groups out of more than 60 participants. Key words: Complex structure, CAPRI, protein-protein docking, pyDock, protein interactions

Nuevas ecuaciones de cubicación para pino silvestre en "aguas vertientes" (El Espinar, Segovia).

El monte "Aguas Vertientes" (El Espinar) es el nº 138 del C.U.P. de Segovia. Se trata de una masa natural de pino silvestre, con abundante melojo en sus cotas inferiores. Su primer Proyecto de Ordenación fue redactado en 1904, estando actualmente redactada y en fase de aprobación la novena revisión. La madera de pino obtenida es elaborada en un aserradero cercano, perteneciente a la misma entidad propietaria. Durante los últimos años los responsables de dicho aserradero vienen manifestando que la cubicación en pie realizada por la administración forestal presenta errores de magnitud suficiente como para ser necesaria su corrección. Este trabajo fin de carrera ha consistido en comprobar la fiabilidad de los valores modulares empleados hasta ahora, y elaborar nuevas ecuaciones de cubicación. Para ello se ha manejado una muestra de 234 pinos repartidos en malla cuadrada y cubicados en pie mediante el método de Pressler-Bitterlich. Como resultado, se propone una ecuación de doble entrada (función de diámetro normal y altura) para todo el monte; y una ecuación de una entrada (función de diámetro normal) para cotas superiores e inferiores a 1.500 m. Los nuevos modelos son validados mediante una muestra independiente

In silico docking of urokinase plasminogen activator and integrins

Background: Urokinase, its receptor and the integrins are functionally associated and involved in regulation of cell signaling, migration, adhesion and proliferation. No structural information is available on this potential multimolecular complex. However, the tri-dimensional structure of urokinase, urokinase receptor and integrins is known. Results: We have modeled the interaction of urokinase on two integrins, alpha IIb beta 3 in the open configuration and alpha v beta 3 in the closed configuration. We have found that multiple lowest energy solutions point to an interaction of the kringle domain of uPA at the boundary between alpha and beta chains on the surface of the integrins. This region is not far away from peptides that have been previously shown to have a biological role in urokinase receptor/integrins dependent signaling. Conclusions: We demonstrated that in silico docking experiments can be successfully carried out to identify the binding mode of the kringle domain of urokinase on the scaffold of integrins in the open and closed conformation. Importantly we found that the binding mode was the same on different integrins and in both configurations. To get a molecular view of the system is a prerequisite to unravel the complex protein-protein interactions underlying urokinase/urokinase receptor/integrin mediated cell motility, adhesion and proliferation and to design rational in vitro experiments