Celebratio Mathematica

P. Francis-Lyon, S. Gu, J. Hass, N. Amenta, and P. Koehl: “Sampling the conformation of protein surface residues for flexible protein docking,” BMC Bioinform. 11 (2010), pp. 575–588. article

Nina Amenta	Related
Patricia Francis-Lyon	Related
Shengyin Gu	Related
Patrice Koehl	Related

S. Gu, P. Koehl, J. Hass, and N. Amenta: “Surface-histogram: A new shape descriptor for protein-protein docking,” Proteins Struct. Funct. Bioinf. 80 : 1 (January 2012), pp. 221–238. article

Determining the structure of protein-protein complexes remains a difficult and lengthy process, either by NMR or by X-ray crystallography. Several computational methods based on docking have been developed to support and even serve as possible alternatives to these experimental methods. In this article, we introduce a new protein-protein docking algorithm, shDock, based on shape complementarity. We characterize the local geometry on each protein surface with a new shape descriptor, the surface-histogram. We measure the complementarity between two surface-histograms, one on each protein, using a modified Manhattan distance. When a match is found between two local protein surfaces, a model is generated for the protein complex, which is then scored by checking for collision between the two proteins. We have tested our algorithm on Version 3 of the ZDOCK protein-protein docking benchmark. We found that for 110 out of the 124 test cases of bound docking in the benchmark, our algorithm was able to generate a model in the top 3600 candidates for the protein complex within an root-mean-square deviation of \( 2.5\,Å \) from its native structure. For unbound docking predictions, we found a model within \( 2.5\,Å \) in the top 3600 models in 54 out of 124 test cases. A comparison with other shape-based docking algorithms demonstrates that our approach gives significantly improved performance for both bound and unbound docking test cases.

Nina Amenta	Related
Shengyin Gu	Related
Patrice Koehl	Related

A. Tsui, D. Fenton, P. Vuong, J. Hass, P. Koehl, N. Amenta, D. Coeurjolly, C. DeCarli, and O. Carmichael: “Globally optimal cortical surface matching with exact landmark correspondence,” pp. 487–498 in Information processing in medical imaging: 23rd international conference, IPMI 2013 (Asilomar, CA, 28 June–3 July 2013). Edited by J. C. Gee, S. Joshi, K. M. Pohl, W. M. Wells, and L. Zöllei. Lecture Notes in Computer Science 7917. Springer (Berlin), 2013. incollection

We present a method for establishing correspondences between human cortical surfaces that exactly matches the positions of given point landmarks, while attaining the global minimum of an objective function that quantifies how far the mapping deviates from conformality. On each surface, a conformal transformation is applied to the Euclidean distance metric, resulting in a hyperbolic metric with isolated cone point singularities at the landmarks. Equivalently, each surface is mapped to a hyperbolic orbifold: a pillow-like surface with each point landmark corresponding to a pillow corner. An initial surface-to-surface mapping exactly aligns the landmarks, and gradient descent is used to find the single, global minimum of the Dirichlet energy of the remainder of the mapping. Using a population of real MRI-based cortical surfaces with manually labeled sulcus endpoints as landmarks, we evaluate the approach by how much it distorts surfaces and by its biological plausibility: how well it aligns previously-unseen anatomical landmarks and by how well it promotes expected associations between cortical thickness and age. We show that, compared to a painstakingly-tuned approach that balances a tradeoff between minimizing landmark mismatch and Dirichlet energy, our method has similar biological plausibility, superior surface distortion, a better theoretical foundation, and fewer arbitrary parameters to tune. We also compare to conformal mapper in the spherical domain to show that sacrificing exact conformality of the mapping does not cause noticeable reductions in biological plausibility.

Padmini Joshi	Related
Alex Tsui	Related
Phong Vuong	Related
Nina Amenta	Related
Owen Carmichael	Related
David Coeurjolly	Related
Charles DeCarli	Related
David Fenton	Related
Patrice Koehl	Related

@incollection {key76348359,
	AUTHOR = {Tsui, Alex and Fenton, Devin and Vuong,
		 Phong and Hass, Joel and Koehl, Patrice
		 and Amenta, Nina and Coeurjolly, David
		 and DeCarli, Charles and Carmichael,
		 Owen},
	TITLE = {Globally optimal cortical surface matching
		 with exact landmark correspondence},
	BOOKTITLE = {Information processing in medical imaging:
		 23rd international conference, {IPMI}
		 2013},
	EDITOR = {Gee, James C. and Joshi, Sarang and
		 Pohl, Kilian M. and Wells, William M.
		 and Z\"ollei, Lilla},
	SERIES = {Lecture Notes in Computer Science},
	NUMBER = {7917},
	PUBLISHER = {Springer},
	ADDRESS = {Berlin},
	YEAR = {2013},
	PAGES = {487--498},
	DOI = {10.1007/978-3-642-38868-2_41},
	NOTE = {(Asilomar, CA, 28 June--3 July 2013).},
	ISSN = {0302-9743},
	ISBN = {9783642388675},
}

year	title	people

			clear

Joel Hass

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