scholarly journals Generic Computing-Assisted Geometric Search for Human Design and Origins

2020 ◽  
Author(s):  
Ayodele Abiola Periola
Keyword(s):  
Geometric Search

scholarly journals An Adaptive Geometric Search Algorithm for Macromolecular Scaffold Selection

2017 ◽  
Author(s):  
Tian Jiang ◽  
P. Douglas Renfrew ◽  
Kevin Drew ◽  
Noah Youngs ◽  
Glenn Butterfoss ◽  
...  
Keyword(s):  
Protein Design ◽  
Active Site ◽  
Metal Binding ◽  
Search Algorithm ◽  
Three Dimensional ◽  
Side Chain ◽  
Enzyme Design ◽  
Hydrogen Binding ◽  
Performance Improvements ◽  
Geometric Search

AbstractA wide variety of protein and peptidomimetic design tasks require matching functional three-dimensional motifs to potential oligomeric scaffolds. Enzyme design, for example, aims to graft active-site patterns typically consisting of 3 to 15 residues onto new protein surfaces. Identifying suitable proteins capable of scaffolding such active-site engraftment requires costly searches to identify protein folds that can provide the correct positioning of side chains to host the desired active site. Other examples of biodesign tasks that require simpler fast exact geometric searches of potential side chain positioning include mimicking binding hotspots, design of metal binding clusters and the design of modular hydrogen binding networks for specificity. In these applications the speed and scaling of geometric search limits downstream design to small patterns. Here we present an adaptive algorithm to searching for side chain take-off angles compatible with an arbitrarily specified functional pattern that enjoys substantive performance improvements over previous methods. We demonstrate this method in both genetically encoded (protein) and synthetic (peptidomimetic) design scenarios. Examples of using this method with the Rosetta framework for protein design are provided but our implementation is compatible with multiple protein design frameworks and is freely available as a set of python scripts (https://github.com/JiangTian/adaptive-geometric-search-for-protein-design).

scholarly journals An adaptive geometric search algorithm for macromolecular scaffold selection

2018 ◽  
Vol 31 (9) ◽  
pp. 345-354
Author(s):  
Tian Jiang ◽  
P Douglas Renfrew ◽  
Kevin Drew ◽  
Noah Youngs ◽  
Glenn L Butterfoss ◽  
...  
Keyword(s):  
Search Algorithm ◽  
Geometric Search

Simulated and Experimental Verification of CMM Feature Fitting Algorithms

2015 ◽  
Author(s):  
Prashant Mohan ◽  
Jami Shah ◽  
Joseph Davidson
Keyword(s):  
Point Cloud ◽  
International Standards ◽  
Least Square ◽  
Shop Floor ◽  
Dimensional Metrology ◽  
Cloud Data ◽  
Verification Methods ◽  
Different Types ◽  
Geometric Search ◽  
Feature Fitting

Coordinate Measuring Machines (CMMs) collect a sampling of points on measured features for use in dimensional metrology. Conformance to specified geometric tolerances is done by analyzing the point cloud to fit the corresponding feature to the point cloud to determine if the simulated feature lies within the specified tolerance limits. Different types of feature fitting algorithms are needed: nominal, minimal/maximal, circumscribing/inscribing, and zone. Studies have shown that the same point cloud data sent to different vendors CMM software, produces different results. It is suspected that some of these algorithms may be inconsistent with the tolerance class definitions in tolerance standards and, in some cases, with shop floor conventional practices. We have previously reported on the development of normative algorithms and a feature fitting library that could be used by all CMMs. This paper gives a summary of those algorithms and then reports on methods used for verification. Three different types of verification methods were used to validate the algorithms developed. The scope of the current work is limited to linear, planar, circular, and cylindrical features. This set of algorithms described conforms to the international Standards for GD&T. In order to reduce the number of points to be analyzed, and to identify the possible candidate points for linear, circular and planar features, 2D and 3D convex hulls are used. For minimum, maximum, and Chebyshev cylinders, geometric search algorithms are used. Algorithms are divided into three major categories: least square, unconstrained, and constrained fits. Primary datums require one sided unconstrained fits for their verification. Secondary datums require one sided constrained fits for their verification. For size and other tolerance verifications, we require both unconstrained and constrained fits. Use of three different methods has validated the robustness, efficiency and accuracy of the algorithms.

Coarse-Grained Parallel Geometric Search

1999 ◽  
Vol 57 (2) ◽  
pp. 224-235 ◽  
Author(s):  
Albert Chan ◽  
Frank Dehne ◽  
Andrew Rau-Chaplin
Keyword(s):  
Coarse Grained ◽  
Geometric Search
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