Measurement of protein surface shape by solid angles
Journal of Molecular Graphics
SIAM Journal on Discrete Mathematics
Recognizing solid objects by alignment with an image
International Journal of Computer Vision
SCG '94 Proceedings of the tenth annual symposium on Computational geometry
Approximate decision algorithms for point set congruence
Computational Geometry: Theory and Applications
On the approximation of largest common subtrees and largest common point sets
Theoretical Computer Science
Model-Based Object Recognition by Geometric Hashing
ECCV '90 Proceedings of the First European Conference on Computer Vision
Approximation Algorithms for 3-D Commom Substructure Identification in Drug and Protein Molecules
WADS '99 Proceedings of the 6th International Workshop on Algorithms and Data Structures
Computing Largest Common Point Sets under Approximate Congruence
ESA '00 Proceedings of the 8th Annual European Symposium on Algorithms
MAPPIS: multiple 3D alignment of protein-protein interfaces
CompLife'05 Proceedings of the First international conference on Computational Life Sciences
Geometric sieving: automated distributed optimization of 3D motifs for protein function prediction
RECOMB'06 Proceedings of the 10th annual international conference on Research in Computational Molecular Biology
Proceedings of the ACM Conference on Bioinformatics, Computational Biology and Biomedicine
Isolating Influential Regions of Electrostatic Focusing in Protein and DNA Structure
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
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We present a novel computational method, MultiBind, for recognition of binding patterns common to a set of protein structures. It is the first method which performs a multiple alignment between protein binding sites in the absence of overall sequence, fold or binding partner similarity. MultiBind recognizes common spatial arrangements of physico-chemical properties in the binding sites. These should be important for recognition of function, prediction of binding and drug design. We discuss the theoretical aspects of the computational problem of multiple structure alignment. This problem involves solving a 3D k-partite matching problem, which we show to be NP-Hard. The MultiBind method, applies an efficient Geometric Hashing technique to detect a potential set of multiple alignments of the given binding sites. To overcome the exponential number of possible multiple combinations it applies a very efficient filtering procedure which is heavily based on the selected scoring function. Our method guarantees detection of an approximate solution in terms of pattern proximity as well as cardinality of multiple alignment. We show applications of MultiBind to several biological targets. The method recognizes patterns which are responsible for binding small molecules such as estradiol, ATP/ANP and transition state analogues. The presented computational results agree with the available biological ones. Availability: http://bioinfo3d.cs.tau.ac.il/MultiBind/.