Protein-Protein Docking with F2Dock 2.0 and GB-Rerank

Rezaul Chowdhury is with UT Austin; Muhibur Rasheed is with UT Austin; Maysam Moussalem is with UT Austin; Donald Keidel is with The Scripps Research Institute; Arthur Olson is with The Scripps Research Institute; Michel Sanner is with The Scripps Research Institute; Chandrajit Bajaj is with The Scripps Research Institute.Motivation -- Computational simulation of protein-protein docking can expedite the process of molecular modeling and drug discovery. This paper reports on our new F2 Dock protocol which improves the state of the art in initial stage rigid body exhaustive docking search, scoring and ranking by introducing improvements in the shape-complementarity and electrostatics affinity functions, a new knowledge-based interface propensity term with FFT formulation, a set of novel knowledge-based filters and finally a solvation energy (GBSA) based reranking technique. Our algorithms are based on highly efficient data structures including the dynamic packing grids and octrees which significantly speed up the computations and also provide guaranteed bounds on approximation error. Results -- The improved affinity functions show superior performance compared to their traditional counterparts in finding correct docking poses at higher ranks. We found that the new filters and the GBSA based reranking individually and in combination significantly improve the accuracy of docking predictions with only minor increase in computation time. We compared F2 Dock 2.0 with ZDock 3.0.2 and found improvements over it, specifically among 176 complexes in ZLab Benchmark 4.0, F2 Dock 2.0 finds a near-native solution as the top prediction for 22 complexes; where ZDock 3.0.2 does so for 13 complexes. F2 Dock 2.0 finds a near-native solution within the top 1000 predictions for 106 complexes as opposed to 104 complexes for ZDock 3.0.2. However, there are 17 and 15 complexes where F2 Dock 2.0 finds a solution but ZDock 3.0.2 does not and vice versa; which indicates that the two docking protocols can also complement each other. Availability -- The docking protocol has been implemented as a server with a graphical client (TexMol) which allows the user to manage multiple docking jobs, and visualize the docked poses and interfaces. Both the server and client are available for download. Server: http://www.cs.utexas.edu/~bajaj/cvc/soft​ware/f2dock.shtml. Client: http://www.cs.utexas.edu/~bajaj/cvc/soft​ware/f2dockclient.shtml.The research of C.B., R.C., M.M., and M.R. of University of Texas, was supported in part by National Science Foundation (NSF) grant CNS-0540033, and grants from the National Institutes of Health (NIH) R01-GM074258, R01-GM073087, R01-EB004873. The research of M.M. was additionally supported by an NSF Graduate Research Fellowship. The research of M.S. and A.O. of TSRI was supported in part by a subcontract on NIH grant R01-GM073087. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.Computer Science

TOM: a self-trained Tomography solution for Overlay networks Monitoring

International audienceNetwork tomography is a discipline that aims to infer the internal network characteristics from end-to-end correlated measurements performed at the network edge. This work presents a new tomography approach for link metrics inference in an SDN/NFV environment (even if it can be exported outside this field) that we called TOM (Tomography for Overlay networks Monitoring). In such an environment, we are particularly interested in supervising network slicing, a recent tool enabling to create multiple virtual networks for different applications and QoS constraints on a Telco infrastructure. The goal is to infer the underlay resources states from the measurements performed in the overlay structure. We model the inference task as a regression problem that we solve following a Neural Network approach. Since getting labeled data for the training phase can be costly, our procedure generates artificial data for the training phase. By creating a large set of random training examples, the Neural Network learns the relations between the measures done at path and link levels. This approach takes advantage of efficient Machine Learning solutions to solve a classic inference problem. Simulations with a public dataset show very promising results compared to statistical-based methods. We explored mainly additive metrics such as delays or logs of loss rates, but the approach can also be used for non-additive ones such as bandwidth

Cyclic Peptides as Protein Kinase Inhibitors: Structure–Activity Relationship and Molecular Modeling

Under-expression or overexpression of protein kinases has been shown to be associated with unregulated cell signal transduction in cancer cells. Therefore, there is major interest in designing protein kinase inhibitors as anticancer agents. We have previously reported [WR]5, a peptide containing alternative arginine (R) and tryptophan (W) residues as a non-competitive c-Src tyrosine kinase inhibitor. A number of larger cyclic peptides containing alternative hydrophobic and positively charged residues [WR]x (x = 6–9) and hybrid cyclic-linear peptides, [R6K]W6 and [R5K]W7, containing R and W residues were evaluated for their protein kinase inhibitory potency. Among all the peptides, cyclic peptide [WR]9 was found to be the most potent tyrosine kinase inhibitor. [WR]9 showed higher inhibitory activity (IC50 = 0.21 μM) than [WR]5, [WR]6, [WR]7, and [WR]8 with IC50 values of 0.81, 0.57, 0.35, and 0.33 μM, respectively, against c-Src kinase as determined by a radioactive assay using [γ-33P]ATP. Consistent with the result above, [WR]9 inhibited other protein kinases such as Abl kinase activity with an IC50 value of 0.35 μM, showing 2.2-fold higher inhibition than [WR]5 (IC50 = 0.79 μM). [WR]9 also inhibited PKCa kinase activity with an IC50 value of 2.86 μM, approximately threefold higher inhibition than [WR]5 (IC50 = 8.52 μM). A similar pattern was observed against Braf, c-Src, Cdk2/cyclin A1, and Lck. [WR]9 exhibited IC50 values of 9 is consistently more potent than other cyclic peptides with a smaller ring size and hybrid cyclic-linear peptides [R6K]W6 and [R5K]W7 against selected protein kinases. Thus, the presence of R and W residues in the ring, ring size, and the number of amino acids in the structure of the cyclic peptide were found to be critical in protein kinase inhibitory potency. We identified three putative binding pockets through automated blind docking of cyclic peptides [WR](5–9). The most populated pocket is located between the SH2, SH3, and N-lobe domains on the opposite side of the ATP binding site. The second putative pocket is formed by the same domains and located on the ATP binding site side of the protein. Finally, a third pocket was identified between the SH2 and SH3 domains. These results are consistent with the non-competitive nature of the inhibition displayed by these molecules. Molecular dynamics simulations of the protein–peptide complexes indicate that the presence of either [WR]5 or [WR]9 affects the plasticity of the protein and in particular the volume of the ATP binding site pocket in different ways. These results suggest that the second pocket is most likely the site where these peptides bind and offer a plausible rationale for the increased affinity of [WR]9

Augmented reality with tangible Auto-Fabricated models for molecular biology applications

Abstract: The evolving technology of computer auto-fabrication ("3-D printing") now makes it possible to produce physical models for complex biological molecules and assemblies. We report on an application that demonstrates the use of auto-fabricated tangible models and augmented reality for research and education in molecular biology, and for enhancing the scientific environment for collaboration and exploration. We have adapted an augmented reality system to allows virtual 3-D representations (generated by the Python Molecular Viewer) to be overlaid onto a tangible molecular model. Users can easily change the overlaid information, switching between different representations of the molecule, displays of molecular properties such as electrostatics, or dynamic information. The physical model provides a powerful, intuitive interface for manipulating the computer models, streamlining the interface between human intent, the physical model, and the computational activity. INTRODUCTION With the prevalence of structural and genomic data, molecular biology has become a human-guided, computer-assisted endeavor. The computer assists the essential human function in two ways: in exploration of scientific data, searching for and testing scientific hypotheses; and in collaboration between two or more scientists, to share knowledge and expertise. As databases grow, as our structure and process models become more complex, and as software methods become more diverse, access and manipulation of digital information is increasingly a critical issue for research in molecular biology. Currently, exploratory research in structural molecular biology is dominated by 3-D representations via computer graphics. Collaboration, both remote and local, is aided by shared viewing of these interactive visual representations of molecular data. Yet, recent advances in the field of human-computer interfaces have not been applied to the technology used by molecular biologists --most work in biomolecular structure and genomics is performed in front of a workstation using a mouse and keyboard as input devices. The tactile and kinesthetic senses provide key perceptual cues to our ability to understand 3-D form and to perform physical manipulations, but are currently under-utilized in molecular biology. Early structure research relied heavily on physical models: Pauling used his newly-invented spacefilling models to predict the basic folding units of protein structures [1] and Watson and Crick used brass-wire molecular models to help them determine the structure of DNA [2], which reconciled decades of genetic data. These researchers "thought with their hands" to produce important scientific results. Current research in molecular biology now focuses on larger assemblies and more complex interactions, for which traditional atomic models are inadequate. Merging physical and virtual objects into an "augmented reality" (AR) environment The evolving technology of computer auto-fabrication ("3D printing") now makes it possible to produce physical models for complex molecular assemblies. In this paper we report on an application that demonstrates the use of auto-fabricated tangible models and AR for research in molecular biology to enhance the scientific environment for collaboration and exploration. The physical models are integrated into an augmented reality environment to streamline the interface between human intent, the physical model, and the computational activity. We have developed an AR system that allows virtual 3-D representations generated by our Python Molecular Viewer (PMV) [5] to be overlaid on an auto-fabricated model of the molecule. The precise registration of the virtual objects with the real world is done using the ARToolKit library developed at the University of Washington We will first describe how we create 3D tangible models of a molecular structure from a known atomic structure, then explain the integration of ARToolKit in our Python framework, and finally present some examples. DESIGN OF PHYSICAL MODELS We use PMV October 10-15

An evolutionary controllers' placement algorithm for reliable SDN networks

International audienceSDN controllers placement in TelCo networks are generally multi-objective and multi-constrained problems. The solutions proposed in the literature usually model the placement problem by providing a mixed integer linear program (MILP). Their performances are, however, quickly limited for large sized networks, due to the significant increase in the computational delays. In order to avoid the inherent complexity of optimal approaches and the lack of flexibility of heuristics, we propose in this paper a genetic algorithm designed from the NSGA II framework that aims to deal with the controller placement problem. Genetic algorithms can, indeed, be both multi-objective, multi-constraints and can be designed to be computed in parallel. They constitute a real opportunity to find good solutions to this category of problems. Furthermore, the proposed algorithm can be easily adapted to manage dynamic placements scenarios. The goal chosen, in this work, is to maximize the clusters average connectivity and to balance the control's load between clusters, in a way to improve the networks' reliability. The evaluation results on a set of network topologies demonstrated very good performances, which achieve optimal results for small networks

Conditions de l'émergence des représentations d'un point de vue didactique

There is an irreductible polysemia of the term of representation. Indeed, this one is product and process at the same time. The demarcation of the concept of representation sets a problem. In return, we want to show that the conditions of their emergence in the class are now clear, at least from the didactic point of view in which we are interested here. Howewer, it must be recognised that we hold only traces and the underlying structure must be infered. It is no doubt possible to make the representations emerge during a diagnostic evaluation ! But it is advised to help oneself with a problematical field, before any pedagogical project and to submit to a genuine attitude of reception.Il y a une polysémie irréductible du terme de représentation. En effet ; celle-ci est à la fois processus et produit. Le bornage du concept de représentation pose problème. En revanche nous voulons montrer que les conditions de leur émergence dans la classe sont maintenant claires, au moins du point de vue didactique qui nous intéresse ici. Il faut reconnaître pourtant qu’on ne saisit que des traces et qu’il faut inférer la structure sous-jacente. Faire émerger les représentations au cours d’une évaluation diagnostique sans doute ! Mais il est conseillé de s’aider d’une problématique pour s’y reconnaître, au préalable de tout projet pédagogique et de se former à une authentique attitude d’écoute.Sanner Michel. Conditions de l'émergence des représentations d'un point de vue didactique. In: Spirale. Revue de recherches en éducation, hors-série n°2, 1997. Représentations en formation. pp. 37-62

Le point de vue pédagogique chez Gaston Bachelard

Sanner Michel. Le point de vue pédagogique chez Gaston Bachelard. In: Raison présente, n°38, Avril – Mai – Juin 1976. Mythologies et politique. pp. 89-98

SDN control plane architecture and placement of network services in TelCo infrastructures

Le contexte de l'évolution des infrastructures des opérateurs de télécommunications vers les paradigmes SDN et NFV nécessite de lever différents verrous techniques, liés d'une part à la centralisation des fonctions de contrôle, d'autre part aux contraintes d'approches qui s'inspirent directement du Cloud Computing. Dans cette thèse, nous avons abordés deux problématiques. Dans la première nous cherchons à définir une architecture SDN plus adaptée et performante par rapport aux besoins des opérateurs. Pour cela, nous avons proposé un plan de contrôle SDN distribué et flexible visant à dépasser les limites du protocole OpenFlow centralisé ainsi que les contraintes de la virtualisation des fonctions réseaux. L'architecture proposée permet la composition, puis la validation et le déploiement différenciés de services réseaux composables et reconfigurables dynamiquement en prenant en compte les SLA associés aux services. Nous avons illustré certaines propriétés de cette architecture, distribution, composition, dynamicité dans une preuve de concepts. Dans la deuxième, pour réaliser les SLA attendus, nous cherchons à optimiser le placement des services réseaux dans cette infrastructure. Nous avons d'abord traité la problématique du placement de contrôleurs SDN en optimisant des métriques de latence, de charge et de fiabilité, puis de manière plus générale le placement de chaînes de fonctions réseaux virtualisées. Nous avons démontré pour cela les potentialités et les performances des algorithmes évolutionnaires pour tenter de proposer un outil de résolution générique de placement de fonctions réseaux.The evolution of telecommunications operators’ infrastructures towards the SDN and NFV paradigms requires to surmount various technical barriers. On one hand, it is necessary to deal with the centralization of control functions, and on the other hand with the constraints of approaches coming directly from Cloud Computing. In this thesis, we addressed two issues. Firstly, we tried to define a SDN architecture more suited to the requirement of operators. For this purpose, we proposed a distributed and flexible SDN control plane to overcome the limitations of the centralized OpenFlow protocol, as well as the constraints of network function virtualization. The proposed architecture allows for the differentiated composition, validation and deployment of dynamically reconfigurable network services, taking into account the SLAs associated with the services. We have illustrated some of its characteristics, namely, distribution, composition, dynamicity in a proof of concept. Secondly, to achieve the expected SLAs, we try to optimize the placement of network services in this infrastructure. We first dealt with the issue of SDN controllers placement seeking for the optimization of latency, load and reliability metrics. Then, we considered the placement of virtualized network functions chains. We have therefore demonstrated the potentialities and performances of evolutionary algorithms with the perspective to propose a generic resolution tool for placement of network functions