We have used various computational methodologies including molecular dynamics, density functional theory, virtual screening, ADMET predictions and molecular interaction field studies to design and analyze four novel potential inhibitors of farnesyltransferase (FTase). Evaluation of two proposals regarding their drug potential as well as lead compounds have indicated them as novel promising FTase inhibitors, with theoretically interesting pharmacotherapeutic profiles, when Compared to the very active and most cited FTase inhibitors that have activity data reported, which are launched drugs or compounds in clinical tests. One of our two proposals appears to be a more promising drug candidate and FTase inhibitor, but both derivative molecules indicate potentially very good pharmacotherapeutic profiles in comparison with Tipifarnib and Lonafarnib, two reference pharmaceuticals. Two other proposals have been selected with virtual screening approaches and investigated by LIS, which suggest novel and alternatives scaffolds to design future potential FTase inhibitors. Such compounds can be explored as promising molecules to initiate a research protocol in order to discover novel anticancer drug candidates targeting farnesyltransferase, in the fight against cancer. (C) 2009 Elsevier Inc. All rights reserved.; CNPq; CAPES; FAPESP; FAPERJ
The assembly of molecular machines and transient signaling complexes does not typically occur under circumstances in which the appropriate proteins are isolated from all others present in the cell. Rather, assembly must proceed in the context of large-scale protein-protein interaction (PPI) networks that are characterized both by conflict and combinatorial complexity. Conflict refers to the fact that protein interfaces can often bind many different partners in a mutually exclusive way, while combinatorial complexity refers to the explosion in the number of distinct complexes that can be formed by a network of binding possibilities. Using computational models, we explore the consequences of these characteristics for the global dynamics of a PPI network based on highly curated yeast two-hybrid data. The limited molecular context represented in this data-type translates formally into an assumption of independent binding sites for each protein. The challenge of avoiding the explicit enumeration of the astronomically many possibilities for complex formation is met by a rule-based approach to kinetic modeling. Despite imposing global biophysical constraints, we find that initially identical simulations rapidly diverge in the space of molecular possibilities...
The mechanical properties of cartilage tissue depend largely on the macromolecules that make up its extracellular matrix (ECM). Aggrecan is the most abundant proteoglycan in articular cartilage. It is composed of a core protein with highly charged, densely packed glycosaminoglycan (GAG) side chains, which are responsible for [approximately] 50% of the equilibrium compressive stiffness of the tissue. Using atomic force microscopy (AFM) and high resolution force spectroscopy (HRFS), it is now possible to directly measure nanoscale interactions between ECM macromolecules in physiologically relevant aqueous solution conditions. In order to interpret these data and compare them to macroscopic tissue measurements, a combination of experiments and theoretical modeling must be used. In this thesis, a new molecular-scale continuum Poisson-Boltzmann (PB)-based model was developed to predict the intermolecular interactions between GAG macromolecules by taking into account nanoscale space varying electric potential and fields between neighboring GAGs. A rod-like charge density distribution describing the time averaged space occupied by a single GAG chain was formulated. The spacing and size of the rods greatly influenced the calculated force even when the total charge was kept constant. The theoretical simulations described HRFS experimental data of the normal interaction force between two surfaces chemically end-grafted with an array of GAGs ("brushes") more accurately than simpler models which approximate the GAG charge as a homogeneous volume or planar surface charge. Taken together...
There have been a number of recent proposals for link and network-layer protocols in the sensor networking literature, each of which claims to be superior to other approaches. However, a proposal for a networking protocol at a given layer in the stack is typically evaluated in the context of a single set of carefully selected protocols at other layers, as well as a particular network topology and application workload. Because of the limited data available about interactions between different protocols at various layers of the stack, it is difficult for developers of sensor network applications to select from amongst the range of alternative sensor networking protocols. This thesis attempts to remedy this situation by evaluating the interaction between several protocols at the MAC and network layers and measuring their performance in terms of end-to-end throughput and loss on a large, real-world TinyOS and Mica2 mote-based tested. We report on different combinations of protocols using different application workloads and power-management schemes. This thesis analyzes the effects of various services provided by the different protocols, such as link-level retransmission, neighborhood management, and link-quality estimation. Our analysis suggests some common sources of poor performance that developers may experience during real-life deployments; based on this experience...
An important goal in genomic research is the reconstruction of the complete picture of temporal interactions among all genes, but this inference problem is not tractable because of the large number of genes, the small number of experimental observations for each gene, and the complexity of biological networks. We focus instead on the B cell receptor (BCR) signaling pathway, which narrows the inference problem and provides a clinical application, as B cell chronic lymphocytic leukemia (B-CLL) is believed to be related to BCR response. In this work, we infer population-dependent gene networks of temporal interaction within the BCR signaling pathway. We develop simple statistical models that capture the temporal behavior of differentially expressed genes and then estimate the parameters in an Expectation-Maximization framework, resulting in clusters with a biological interpretation for each subject population. Using the cluster labels to define a small number of modes of interaction and imposing sparsity constraints to effectively limit the number of genes influencing each target gene makes the ill-posed problem of network inference tractable.; (cont.) For both the clustering and the inference of the predictive models, we have statistical results that show that we successfully capture the temporal structure of and the interactions between the genes relevant to the BCR. signaling pathway. We have confirmatory results from a biological standpoint...
This dissertation shows how statistical dependence estimation underlies two key problems in visual surveillance and wide-area tracking. The first problem is to detect and describe interactions between moving objects. The goal is to measure the influence objects exert on one another. The second problem is to match objects between non-overlapping cameras. There, the goal is to pair the departures in one camera with the arrivals in a different camera so that the resulting distribution of relationships best models the data. Both problems have become important for scaling up surveillance systems to larger areas and expanding the monitoring to more interesting behaviors. We show how statistical dependence estimation generalizes previous work and may have applications in other areas. The two problems represent different applications of our thesis that statistical dependence estimation underlies the learning of the structure of probabilistic models. First, we analyze the relationship between Bayesian, information-theoretic, and classical statistical methods for statistical dependence estimation. Then, we apply these ideas to formulate object interaction in terms of dependency structure model selection.; (cont.) We describe experiments on simulated and real interaction data to validate our approach. Second...
This thesis presents IntuiSec, a framework for intuitive user interaction with Smart Home security. The design approach of IntuiSec is to introduce a layer of indirection between user-level intent and the system-level security infrastructure. This layer is implemented by a collection of distributed middleware and user-level tools. It encapsulates system-level security events and exposes only concepts and real-world metaphors that are intuitive to non-expert users. It also translates user intent to the appropriate system-level security actions. The IntuiSec framework presents the user with intuitive steps for setting up a secure home network, establishing trusted relationships between devices, and granting temporal, selective access for both home occupants and visitors to devices within the home. The middleware exposes APIs that allow other applications to present the user with meaningful visualizations of security-related parameters and concepts. I present the IntuiSec system design and an example proof-of-concept implementation, which demonstrates the user experience and provides more insight into the framework.; by Saad Safer Shakhshir.; Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science...
The study of protein interactions from the networks point of view has yielded new insights into systems biology [Bar03, MA03, RSM+02, WS98]. In particular, "network motifs" become apparent as a useful and systematic tool for describing and exploring networks [BP06, MKFV06, MSOI+02, SOMMA02, SV06]. Finding motifs has involved either exact counting (e.g. [MSOI+02]) or subgraph sampling (e.g. [BP06, KIMA04a, MZW05]). In this thesis we develop an algorithm to count all instances of a particular subgraph, which can be used to query whether a given subgraph is a significant motif. This method can be used to perform exact counting of network motifs faster and with less memory than previous methods, and can also be combined with subgraph sampling to find larger motifs than ever before -- we have found motifs with up to 15 nodes and explored subgraphs up to 20 nodes. Unlike previous methods, this method can also be used to explore motif clustering and can be combined with network alignment techniques [FNS+06, KSK+03]. We also present new methods of estimating parameters for models of biological network growth, and present a new model based on these parameters and underlying binding domains. Finally, we propose an experiment to explore the effect of the whole genome duplication [KBL04] on the protein-protein interaction network of S. cerevisiae...
by Kaigham Jacob Gabriel.; Thesis (Sc. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1983.; MICROFICHE COPY AVAILABLE IN ARCHIVES AND ENGINEERING.; Includes 5 leaves of bibliography.
The study of proteins in biological systems requires a comprehensive approach: investigating dynamics, interaction and identification. This thesis will examine several technological approaches we have developed to address these needs. To enable the study of the dynamics of biological systems, we have developed a method for using atomic force microscopy (AFM) to image motion on an angstrom scale with microsecond time resolution. As proteins move, diffuse, or are actively trafficked within the cellular environment, they interact with other biological molecules. Protein microarrays offer a high-throughput method of investigating these protein interactions, but their use has largely been hindered by the need to clone and purify thousands of proteins. We have developed a novel technique to pattern proteome-scale microarrays using a cellular lysate, whereby all relevant proteins are synthesized with the correct post-translational modifications. Additionally, we have integrated the identification of proteins with quantitative mass spectrometry (SILAC). Using these arrays we have probed changes in the phosphorylation state of cells in response to activation of the Erb1 and Erb2 receptors. Using our microarray platform we were able to further probe the phosphoproteome for proteins that have multiple post-translational modifications. The widespread use of protein...
Identification of protein-protein interactions is important for drug design and the treatment of diseases. We propose a novel threading algorithm, LTHREADER, which generates accurate local sequence-structure alignments and integrates various statistical scores and experimental binding data to predict interactions. LTHREADER uses a profile of secondary structure and solvent accessibility predictions with residue contact maps to guide and constrain alignments. Using a decision tree classifier and low-throughput experimental data for training, it combines information inferred from statistical interaction potentials, energy functions, correlated mutations and conserved residue pairs to predict likely interactions. The significance of predicted interactions is evaluated using the scores for randomized binding surfaces within each family. We first apply our method to cytokines, which play a central role in the development of many diseases including cancer and inflammatory and autoimmune disorders. We tested our approach on two representative families from different structural classes (all-alpha and all-beta proteins) of cytokines. In comparison with the state-of-the-art threader RAPTOR, LTHREADER generates on average 20% more accurate alignments of interacting residues and shows dramatic improvement in prediction accuracy over existing methods. To further improve alignment accuracy for all PPI families...
In this thesis, I present a system for reasoning with common sense knowledge in multiple natural languages, as part of the Open Mind Common Sense project. The knowledge that Open Mind collects from volunteer contributors is represented as a semantic network called ConceptNet. Using principal component analysis on the graph structure of ConceptNet yields AnalogySpace, a vector space representation of common sense knowledge. This representation reveals large-scale patterns in the data, while smoothing over noise, and predicts new knowledge that the database should contain. The inferred knowledge, which a user survey shows is often correct, is used as part of a feedback loop that shows contributors what the system is learning and guides them to contribute useful new knowledge.; by Robert Speer.; Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2007.; This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.; Includes bibliographical references (p. 107-110).
This thesis demonstrates that creating a system with a visual representation of the face which mirrors the user's facial gestures appears to solve problems in teaching a user to use the new input affordances of face-based interfaces. From experiences with the Attentive Interaction Design Toolkit, "Attention Meter," a methodology for helping the user design their own interactions with an unfamiliar input modality is created. This methodology is then applied to face-based interfaces, through a program called "Face Interface." The subsequent evaluations of Face Interface through its revisions show that it is ready to successfully apply the methodology through further experimentation.; by Jon William Wetzel.; Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2007.; Includes bibliographical references (p. 61-63).
Our thesis is that a networked public display/kiosk system, that provides information for a local community, functions best when it is decentralized and interactive. We deployed such a system at MIT that has two aspects, DomeView for distributed decentralized display and content distribution, and PhoneView for enhanced user consumption of that content. PhoneView is an implementation that we propose to solve a number of issues with current interactive public kiosk deployments, as well as enables scenarios of enhanced interactions. By using the Hands-Free Bluetooth profile as the basis for the communication between a mobile phone and a kiosk, we provide an enhanced personalized interaction for all passersby with Bluetooth-enabled mobile phones, without requiring the installation of custom software. Some examples include the ability to remotely control a kiosk, exchange calendar and contact data with the kiosk, and play games on a kiosk with other users via one's mobile phone. By removing the software installation barrier and providing new mechanisms of public interaction, this implementation is ripe for wide-spread and immediate adoption across multiple public kiosk platforms.; by Harel M. Williams.; Thesis (M. Eng.)--Massachusetts Institute of Technology...
This thesis presents a sketch-based interaction system that can be used to illustrate the process of reasoning about an electrical circuit in an educational setting. Recognition of hand-drawn shapes is accomplished in a two stage process where strokes are first processed into primitives like lines or ellipses, then combined into the appropriate circuit device symbols using a shape description language called LADDER. The circuit is then solved by a constraint-propagation reasoning component. The solution is shown to the user along with the justifications that support each deduction. The level of detail and the speed of the solution playback can be customized to tailor to a student's particular learning pace. A small user study was conducted to test the performance of the recognition component, which revealed several recognition problems common to almost all of the users' experiences with the system. Suggestions for dealing with these problems are also presented.; by Chang She.; Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2006.; Includes bibliographical references (p. 42).
One approach to monitoring a dynamic system relies on decomposition of the
system into weakly interacting subsystems. An earlier paper introduced a notion
of weak interaction called separability, and showed that it leads to exact
propagation of marginals for prediction. This paper addresses two questions
left open by the earlier paper: can we define a notion of approximate
separability that occurs naturally in practice, and do separability and
approximate separability lead to accurate monitoring? The answer to both
questions is afirmative. The paper also analyzes the structure of approximately
separable decompositions, and provides some explanation as to why these models
perform well.; Comment: Appears in Proceedings of the Twenty-Second Conference on Uncertainty
in Artificial Intelligence (UAI2006)
Many real-world applications are associated with structured data, where not
only input but also output has interplay. However, typical classification and
regression models often lack the ability of simultaneously exploring high-order
interaction within input and that within output. In this paper, we present a
deep learning model aiming to generate a powerful nonlinear functional mapping
from structured input to structured output. More specifically, we propose to
integrate high-order hidden units, guided discriminative pretraining, and
high-order auto-encoders for this purpose. We evaluate the model with three
datasets, and obtain state-of-the-art performances among competitive methods.
Our current work focuses on structured output regression, which is a less
explored area, although the model can be extended to handle structured label
This paper presents an immersive application where users receive sound and
visual feedbacks on their interactions with a virtual environment. In this
application, the users play the part of conductors of an orchestra of factory
machines since each of their actions on interaction devices triggers a pair of
visual and audio responses. Audio stimuli were spatialized around the listener.
The application was exhibited during the 2013 Science and Music day and
designed to be used in a large immersive system with head tracking, shutter
glasses and a 10.2 loudspeaker configuration.; Comment: Sonic Interaction for Virtual Environments, Minneapolis : United