TY - GEN
T1 - Docking of protein molecules
AU - Fischer, Daniel
AU - Lin, Shuo L.
AU - Nussinov, Ruth
AU - Wolfson, Haim
N1 - Publisher Copyright:
© 1994 Institute of Electrical and Electronics Engineers Inc.. All rights reserved.
PY - 1994
Y1 - 1994
N2 - The problem of receptor-ligand recognition and binding is encountered in a very large number of biological processes. The behavior of the molecules depends both on their geometric shape and on the chemical interactions among their atoms. This work addresses only the geometrical (key-in-lock) aspect of the problem, where acceptable solutions should exhibit shape complementarity. The problem we are faced with here is reminiscent of partial 3-D surface matching problems in computer vision. Here we present a new 3-D molecular surface representation by (hundreds of) sparse interest (critical) points with associated normals and a subsequent matching approach which is based on the Geometric Hashing paradigm originally developed for Computer Vision motivated object recognition applications. Potential solutions resulting in the interpenetration of the molecules are discarded by a subsequent verification procedure. Numerous examples of the successful geometric prediction of our technique are presented. In all cases the performance of our algorithm has been by several orders of magnitude faster than of other state-of-the-art docking algorithms.
AB - The problem of receptor-ligand recognition and binding is encountered in a very large number of biological processes. The behavior of the molecules depends both on their geometric shape and on the chemical interactions among their atoms. This work addresses only the geometrical (key-in-lock) aspect of the problem, where acceptable solutions should exhibit shape complementarity. The problem we are faced with here is reminiscent of partial 3-D surface matching problems in computer vision. Here we present a new 3-D molecular surface representation by (hundreds of) sparse interest (critical) points with associated normals and a subsequent matching approach which is based on the Geometric Hashing paradigm originally developed for Computer Vision motivated object recognition applications. Potential solutions resulting in the interpenetration of the molecules are discarded by a subsequent verification procedure. Numerous examples of the successful geometric prediction of our technique are presented. In all cases the performance of our algorithm has been by several orders of magnitude faster than of other state-of-the-art docking algorithms.
UR - http://www.scopus.com/inward/record.url?scp=85115216633&partnerID=8YFLogxK
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AN - SCOPUS:85115216633
T3 - Proceedings - International Conference on Pattern Recognition
SP - 145
EP - 149
BT - Proceedings of the 12th IAPR International Conference on Pattern Recognition - Conference B
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 12th IAPR International Conference on Pattern Recognition - Conference B: Pattern Recognition and Neural Networks, ICPR 1994
Y2 - 9 October 1994 through 13 October 1994
ER -