Literature DB >> 16934837

Travel depth, a new shape descriptor for macromolecules: application to ligand binding.

Ryan G Coleman1, Kim A Sharp.   

Abstract

Depth is a term frequently applied to the shape and surface of macromolecules, describing for example the grooves in DNA, the shape of an enzyme active site, or the binding site for a small molecule in a protein. Yet depth is a difficult property to define rigorously in a macromolecule, and few computational tools exist to quantify this notion, to visualize it, or analyze the results. We present our notion of travel depth, simply put the physical distance a solvent molecule would have to travel from a surface point to a suitably defined reference surface. To define the reference surface, we use the limiting form of the molecular surface with increasing probe size: the convex hull. We then present a fast, robust approximation algorithm to compute travel depth to every surface point. The travel depth is useful because it works for pockets of any size and complexity. It also works for two interesting special cases. First, it works on the grooves in DNA, which are unbounded in one direction. Second, it works on the case of tunnels, that is pockets that have no "bottom", but go through the entire macromolecule. Our algorithm makes it straightforward to quantify discussions of depth when analyzing structures. High-throughput analysis of macromolecule depth is also enabled by our algorithm. This is demonstrated by analyzing a database of protein-small molecule binding pockets, and the distribution of bound magnesium ions in RNA structures. These analyses show significant, but subtle effects of depth on ligand binding localization and strength.

Entities:  

Mesh:

Substances:

Year:  2006        PMID: 16934837     DOI: 10.1016/j.jmb.2006.07.022

Source DB:  PubMed          Journal:  J Mol Biol        ISSN: 0022-2836            Impact factor:   5.469


  26 in total

1.  Finding and characterizing tunnels in macromolecules with application to ion channels and pores.

Authors:  Ryan G Coleman; Kim A Sharp
Journal:  Biophys J       Date:  2009-01       Impact factor: 4.033

2.  Geometric Detection Algorithms for Cavities on Protein Surfaces in Molecular Graphics: A Survey.

Authors:  Tiago Simões; Daniel Lopes; Sérgio Dias; Francisco Fernandes; João Pereira; Joaquim Jorge; Chandrajit Bajaj; Abel Gomes
Journal:  Comput Graph Forum       Date:  2017-06-01       Impact factor: 2.078

3.  Impact of point mutation P29S in RAC1 on tumorigenesis.

Authors:  Vidya Rajendran; Chandrasekhar Gopalakrishnan; Rituraj Purohit
Journal:  Tumour Biol       Date:  2016-10-03

4.  Modest membrane hydrogen bonds deliver rich results.

Authors:  Gevorg Grigoryan; William F Degrado
Journal:  Nat Chem Biol       Date:  2008-07       Impact factor: 15.040

Review 5.  The importance of discerning shape in molecular pharmacology.

Authors:  Sandhya Kortagere; Matthew D Krasowski; Sean Ekins
Journal:  Trends Pharmacol Sci       Date:  2009-01-31       Impact factor: 14.819

6.  Differences between high- and low-affinity complexes of enzymes and nonenzymes.

Authors:  Heather A Carlson; Richard D Smith; Nickolay A Khazanov; Paul D Kirchhoff; James B Dunbar; Mark L Benson
Journal:  J Med Chem       Date:  2008-10-01       Impact factor: 7.446

7.  A multidimensional strategy to detect polypharmacological targets in the absence of structural and sequence homology.

Authors:  Jacob D Durrant; Rommie E Amaro; Lei Xie; Michael D Urbaniak; Michael A J Ferguson; Antti Haapalainen; Zhijun Chen; Anne Marie Di Guilmi; Frank Wunder; Philip E Bourne; J Andrew McCammon
Journal:  PLoS Comput Biol       Date:  2010-01-22       Impact factor: 4.475

8.  Regression applied to protein binding site prediction and comparison with classification.

Authors:  Joachim Giard; Jérôme Ambroise; Jean-Luc Gala; Benoît Macq
Journal:  BMC Bioinformatics       Date:  2009-09-03       Impact factor: 3.169

9.  Prodepth: predict residue depth by support vector regression approach from protein sequences only.

Authors:  Jiangning Song; Hao Tan; Khalid Mahmood; Ruby H P Law; Ashley M Buckle; Geoffrey I Webb; Tatsuya Akutsu; James C Whisstock
Journal:  PLoS One       Date:  2009-09-17       Impact factor: 3.240

10.  Fpocket: an open source platform for ligand pocket detection.

Authors:  Vincent Le Guilloux; Peter Schmidtke; Pierre Tuffery
Journal:  BMC Bioinformatics       Date:  2009-06-02       Impact factor: 3.169

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.