US 11,538,553 B2Granted

Systems and methods of fragment-centric topographical mapping (FCTM) to target protein-protein interactions

AssigneeNew York University

InventorsYingkai Zhang, David Rooklin

Life of this patent

Estimating the term…

Loading patent…

Abstract

A system for identifying and evaluating a pocket of a protein includes performing a Voronoi tessellation and developing a Voronoi diagram of a surface of the protein. All alpha-spheres on the surface of the protein are identified. The alpha-spheres are filtered based on radius and remaining alpha-spheres are clustered into alpha-clusters. At least one alpha-cluster is selected for quantitative evaluation. Alpha-sphere contact atoms are determined for a plurality of interaction points of the pocket. A Delaunay triangulation of the four contact atoms of each interaction point is performed. A plurality of alpha-spaces for each interaction point are determined. An alpha-atom and an alpha-atom contact surface area (ACSA) of each interaction point is determined. The pocket is ranked, a pocket-fragment complementarity is determined, and the pocket is matched between various conformations of the proteins.

Claims19

Dependent claims

A method for mapping and evaluating protein surfaces;

comprises:
performing, by a processor, a Voronoi tessellation of a protein structure;
developing, by the processor, a Voronoi diagram of the surface of the protein, the Voronoi diagram including a plurality of Voronoi vertices;
identifying, by the processor, all alpha-spheres at the surface of the protein, a center of the alpha-spheres corresponding to the Voronoi vertices;
filtering, by the processor, the alpha-spheres based on radius, the filtering including removing alpha-spheres having a radius below a minimum radius and above a maximum radius;
clustering, by the processor, remaining alpha-spheres into alpha-clusters, the alpha-clusters comprising localized pockets on the protein structure clustered using a linkage algorithm with optimized clustering parameters;
selecting, by the processor, a plurality of alpha-clusters, the plurality of alpha-clusters each comprising an individual pocket of the localized pockets on the protein structure and each of the localized pockets on the protein is proximate to a protein-protein interaction;
and
displaying, on a graphical user interface, at least one of the individual pockets of the localized pockets on the protein structure to a user.

6 more elements

A method for evaluating a pocket of a protein, comprises:

determining sets of alpha-sphere contact atoms in a plurality of localized regions of the pocket, the contact atoms including four atoms of the protein that are equidistant to a corresponding alpha-sphere, the alpha-sphere representing a single interaction point;
performing a Delaunay triangulation of the four contact atoms of each interaction point;
determining a plurality of alpha-spaces of each interaction point, each alpha-space corresponding to a volume of a region defined by the Delaunay triangulation of the contact atoms of each interaction point;
determining an alpha-atom of each interaction point, the alpha-atom comprising a theoretical atom having a radius of 1.8 angstroms in contact with a surface of each of the contact atoms in a localized region of the pocket;
determining an alpha-atom contact surface area (ACSA) of the pocket;
ranking the pocket to determine a pocket score, the pocket score corresponding to a nonpolar-weighted alpha-space volume;
determining a pocket-fragment complementarity by discretely evaluating whether there is overlap for individual alpha-atoms;
matching pockets between various conformations of the protein;
identifying an optimal chemical fragment for binding to the pocket of the protein in a protein-protein interaction;
and
displaying the optimal chemical fragment to a user.

8 more elements

Dependencies are inferred from the claim text.

Facts

Application: 15/559,719Filed 22 Mar 2016 · us provisional application
Priority: 23 Mar 2015
Published: US 2018/0101641 A112 Apr 2018
Granted: 27 Dec 2022
Term ends: Not estimatedThe source records don’t support an estimate.

Classification3 codes

G16B 15/30
ICT specially adapted for analysing two-dimensional [2D] or three-dimensional [3D] molecular structures, e.g. structural or functional relations…:…
G16B 15/00
Ict specially adapted for analysing two-dimensional [2d] or three-dimensional [3d] molecular structures
G16B
Bioinformatics, i.e. information and communication technology [ict] specially adapted for genetic or