Partial surface matching by using directed footprints

AbstractIn this paper we present a new technique for partial surface and volume matching of images in three dimensions. In this problem, we are given two objects in 3-space, each represented as a set of points, scattered uniformly along its boundary or inside its volume. The goal is to find a rigid motion of one object which makes a sufficiently large portion of its boundary lying sufficiently close to a corresponding portion of the boundary of the second object. This is an important problem in pattern recognition and in computer vision, with many industrial, medical, and chemical applications. Our algorithm is based on assigning a directed footprint to every point of the two sets, and locating all the pairs of points (one of each set) whose undirected components of the footprints are sufficiently similar. The algorithm then computes for each such pair of points all the rigid transformations that map the first point to the second, while making the respective direction components of their footprints coincide. A voting scheme is employed for computing transformations which map significantly large number of points of the first set to points of the second set. Experimental results on various examples are presented and show the accurate and robust performance of our algorithm

Simulating molecular docking with haptics

Intermolecular binding underlies various metabolic and regulatory processes of the cell, and the therapeutic and pharmacological properties of drugs. Molecular docking systems model and simulate these interactions in silico and allow the study of the binding process. In molecular docking, haptics enables the user to sense the interaction forces and intervene cognitively in the docking process. Haptics-assisted docking systems provide an immersive virtual docking environment where the user can interact with the molecules, feel the interaction forces using their sense of touch, identify visually the binding site, and guide the molecules to their binding pose. Despite a forty-year research e�ort however, the docking community has been slow to adopt this technology. Proprietary, unreleased software, expensive haptic hardware and limits on processing power are the main reasons for this. Another signi�cant factor is the size of the molecules simulated, limited to small molecules. The focus of the research described in this thesis is the development of an interactive haptics-assisted docking application that addresses the above issues, and enables the rigid docking of very large biomolecules and the study of the underlying interactions. Novel methods for computing the interaction forces of binding on the CPU and GPU, in real-time, have been developed. The force calculation methods proposed here overcome several computational limitations of previous approaches, such as precomputed force grids, and could potentially be used to model molecular exibility at haptic refresh rates. Methods for force scaling, multipoint collision response, and haptic navigation are also reported that address newfound issues, particular to the interactive docking of large systems, e.g. force stability at molecular collision. The i ii result is a haptics-assisted docking application, Haptimol RD, that runs on relatively inexpensive consumer level hardware, (i.e. there is no need for specialized/proprietary hardware)

Engineering derivatives from biological systems for advanced aerospace applications

The present study consisted of a literature survey, a survey of researchers, and a workshop on bionics. These tasks produced an extensive annotated bibliography of bionics research (282 citations), a directory of bionics researchers, and a workshop report on specific bionics research topics applicable to space technology. These deliverables are included as Appendix A, Appendix B, and Section 5.0, respectively. To provide organization to this highly interdisciplinary field and to serve as a guide for interested researchers, we have also prepared a taxonomy or classification of the various subelements of natural engineering systems. Finally, we have synthesized the results of the various components of this study into a discussion of the most promising opportunities for accelerated research, seeking solutions which apply engineering principles from natural systems to advanced aerospace problems. A discussion of opportunities within the areas of materials, structures, sensors, information processing, robotics, autonomous systems, life support systems, and aeronautics is given. Following the conclusions are six discipline summaries that highlight the potential benefits of research in these areas for NASA's space technology programs

Department of Computer Science Activity 1998-2004

This report summarizes much of the research and teaching activity of the Department of Computer Science at Dartmouth College between late 1998 and late 2004. The material for this report was collected as part of the final report for NSF Institutional Infrastructure award EIA-9802068, which funded equipment and technical staff during that six-year period. This equipment and staff supported essentially all of the department\u27s research activity during that period

QCSPScore: a new scoring function for driving protein-ligand docking with quantitative chemical shifts perturbations

Through the use of information about the biological target structure, the optimization of potential drugs can be improved. In this work I have developed a procedure that uses the quantitative change in the chemical perturbations (CSP) in the protein from NMR experiments for driving protein-ligand docking. The approach is based on a hybrid scoring function (QCSPScore) which combines traditional DrugScore potentials, which describe the interaction between protein and ligand, with Kendall’s rank correlation coefficient, which evaluates docking poses in terms of their agreement with experimental CSP. Prediction of the CSP for a specific ligand pose is done efficiently with an empirical model, taking into account only ring current effects. QCSPScore has been implemented in the AutoDock software package. Compared to previous methods, this approach shows that the use of rank correlation coefficient is robust to outliers. In addition, the prediction of native-like complex geometries improved because the CSP are already being used during the docking process, and not only in a post-filtering setting for generated docking poses. Since the experimental information is guaranteed to be quantitatively used, CSP effectively contribute to align the ligand in the binding pocket. The first step in the development of QCSPScore was the analysis of 70 protein-ligand complexes for which reference CSP were computed. The success rate in the docking increased from 71% without involvement of CSP to 100% if CSP were considered at the highest weighting scheme. In a second step QCSPScore was used in re-docking three test cases, for which reference experimental CSP data was available. Without CSP, i.e. in the use of conventional DrugScore potentials, none of the three test cases could be successfully re-docked. The integration of CSP with the same weighting factor as described above resulted in all three cases successfully re-docked. For two of the three complexes, native-like solutions were only produced if CSP were considered.Conformational changes in the binding pockets of up to 2 Å RMSD did not affect the success of the docking. QCSPScore will be particularly interesting in difficult protein-ligand complexes. They are in particular those cases in which the shape of the binding pocket does not provide sufficient steric restraints such as in flat protein-protein interfaces and in the virtual screening of small chemical fragments.Durch die Verwendung von Information über die biologische Zielstruktur kann die Optimierung potentieller Wirkstoffe verbessert werden. Im Rahmen dieser Arbeit habe ich ein Verfahren entwickelt, das quantitativ die Veränderung der Chemischen Verschieben (CSP) im Protein aus NMR-Experimenten für das Protein-Ligand-Docking verwendet. Der Ansatz basiert auf einer Hybridbewertungsfunktion (QCSPScore) und kombiniert herkömmliche DrugScore-Potentiale, welche die Wechselwirkung zwischen Protein und Ligand beschreiben, mit dem Rangkorrelationskoeffizienten nach Kendall, der die Dockingposen hinsichtlich ihrer Übereinstimmung mit experimentellen CSP. Die Vorhersage der CSP für einen bestimmten Liganden geschieht effizient mit einem empirischen Modell, wobei nur Ringstromeffekte berücksichtigt werden. QCSPScore wurde in das AutoDock Softwarepaket implementiert. Im Vergleich zu früheren Verfahren zeigt dieser Ansatz, dass die Verwendung des Rangkorrelationskoeffizienten robuster ist gegenüber Ausreißern in den vorhergesagten CSP. Außerdem ist die Vorhersage nativ-ähnlicher Komplexgeometrien verbessert, da die CSP bereits während des Docking-Prozesses eingesetzt werden, und nicht erst in einem nachträglichen Filter für generierte Dockingposen. Da die experimentelle Informationen quantitativ benutzt werden wird sichergestellt, dass die CSP effektiv dazu beitragen, den Liganden in der Bindetasche auszurichten. Der erste Schritt bei der Entwicklung des QCSPScore war die Analyse von 70 Protein-Ligand-Komplexen, für die als Referenz CSP vorhergesagt wurden. Die Erfolgsrate im Docking erhöhte sich von 71 %, ohne Einbeziehung von CSP, auf 100 %, wenn CSP mit höchster Gewichtung mit einbezogen wurden. Die globale Optimierung auf der kombinierten Docking-Energiehyperfläche ist also erfolgreich. In einem zweiten Schritt wurde QCSPScore zum Docking dreier Testfälle verwendet, für die als Referenz experimentelle CSP zur Verfügung standen. Ohne CSP, d.h. bei der Verwendung von herkömmlichen DrugScore-Potentialen, konnte keiner der drei Testfälle erfolgreich gedockt werden. Die Einbeziehung von CSP mit dem selben hohen Gewichtungsfaktor wie oben führte in allen drei Fällen zu erfolgreichen Docking-Ergebnissen. Für zwei der drei Komplexe wurden zudem nur bei Einbeziehung der experimentellen Information nativ-ähnliche Geometrien vorhergesagt. Konformationelle Änderungen der Bindetasche bis zu 2 Å RMSD beeinträchtigen den Erfolg des Dockings nicht. Ich bin davon überzeugt, dass mein Verfahren besonders für Protein-Ligand-Komplexe interessant sein wird, für die die Vorhersage nativ-ähnlicher Komplexe bislang schwierig war. Das sind insbesondere solche Fälle, in denen die Form der Bindetasche zur Vorhersage des Komplexes nicht ausreichend, wie das bei flachen Protein-Protein-Wechselwirkungsregionen oder beim virtuellen Screening kleiner Fragmente der Fall ist

Mobile robot transportation in laboratory automation

In this dissertation a new mobile robot transportation system is developed for the modern laboratory automation to connect the distributed automated systems and workbenches. In the system, a series of scientific and technical robot indoor issues are presented and solved, including the multiple robot control strategy, the indoor transportation path planning, the hybrid robot indoor localization, the recharging optimization, the robot-automated door interface, the robot blind arm grasping & placing, etc. The experiments show the proposed system and methods are effective and efficient

Mass & secondary structure propensity of amino acids explain their mutability and evolutionary replacements

Why is an amino acid replacement in a protein accepted during evolution? The answer given by bioinformatics relies on the frequency of change of each amino acid by another one and the propensity of each to remain unchanged. We propose that these replacement rules are recoverable from the secondary structural trends of amino acids. A distance measure between high-resolution Ramachandran distributions reveals that structurally similar residues coincide with those found in substitution matrices such as BLOSUM: Asn Asp, Phe Tyr, Lys Arg, Gln Glu, Ile Val, Met → Leu; with Ala, Cys, His, Gly, Ser, Pro, and Thr, as structurally idiosyncratic residues. We also found a high average correlation (\overline{R} R = 0.85) between thirty amino acid mutability scales and the mutational inertia (I X ), which measures the energetic cost weighted by the number of observations at the most probable amino acid conformation. These results indicate that amino acid substitutions follow two optimally-efficient principles: (a) amino acids interchangeability privileges their secondary structural similarity, and (b) the amino acid mutability depends directly on its biosynthetic energy cost, and inversely with its frequency. These two principles are the underlying rules governing the observed amino acid substitutions. © 2017 The Author(s)