NDLI: Capturing molecular energy landscapes with probabilistic conformational roadmaps

Content Provider	IEEE Xplore Digital Library
Author	Apaydin, M.S. Singh, A.P. Brutlag, D.L. Latombe, J.-C.
Copyright Year	2001
Description	Author affiliation: Dept. of Comput. Sci., Stanford Univ., CA, USA (Apaydin, M.S.)
Abstract	Probabilistic roadmaps are an effective tool to compute the connectivity of the collision-free subset of high-dimensional robot configuration spaces. This paper extends them to capture the pertinent features of continuous functions over high-dimensional spaces. We focus here on computing energetically favorable motions of bio-molecules. A molecule is modeled as an articulated structure moving in an energy field. The set of all its 3D placements is the molecule's conformational space, over which the energy field is defined. A probabilistic conformational roadmap (PCR) tries to capture the connectivity of the low-energy subset of a conformational space, in the form of a network of weighted local pathways. The weight of a pathway measures the energetic difficulty for the molecule to move along it. The power of a PCR derives from its ability to compactly encode a large number of energetically favorable molecular pathways, each defined as a sequence of contiguous local pathways. This paper describes general techniques to compute and query PCRs, and presents implementations to study ligand-protein binding and protein folding.
Sponsorship	IEEE Robotics & Autom. Soc
Starting Page	932
Ending Page	939
File Size	1255137
Page Count	8
File Format	PDF
ISBN	0780365763
ISSN	10504729
DOI	10.1109/ROBOT.2001.932670
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2001-05-21
Publisher Place	South Korea
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Energy capture Proteins Drugs Computational modeling Orbital robotics Shape Predictive models Computer science Process design Context modeling
Content Type	Text
Resource Type	Article
Subject	Artificial Intelligence Control and Systems Engineering Electrical and Electronic Engineering Software

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

Anytime dynamic path-planning with flexible probabilistic roadmaps

Capturing Molecular Energy Landscapes with Probabilistic Conformational Roadmaps (2001)

Visibility-based pursuit-evasion with probabilistic evader models

Probabilistic roadmaps-putting it all together

Learning Capture Points for Bipedal Push Recovery

Capturing Molecular Energy Landscapes with Probabilistic Conformational Roadmaps

On the use of probabilistic relational affordance models for sequential manipulation tasks in robotics

Manipulation Planning with Probabilistic Roadmaps

Robots that validate learned perceptual models

Capturing molecular energy landscapes with probabilistic conformational roadmaps

Similar Documents

Anytime dynamic path-planning with flexible probabilistic roadmaps

Capturing Molecular Energy Landscapes with Probabilistic Conformational Roadmaps (2001)

Visibility-based pursuit-evasion with probabilistic evader models

Probabilistic roadmaps-putting it all together

Learning Capture Points for Bipedal Push Recovery

Capturing Molecular Energy Landscapes with Probabilistic Conformational Roadmaps

On the use of probabilistic relational affordance models for sequential manipulation tasks in robotics

Manipulation Planning with Probabilistic Roadmaps

Robots that validate learned perceptual models

Capturing molecular energy landscapes with probabilistic conformational roadmaps