scholarly journals A mathematical representation of protein binding sites using structural dispersion of atoms from principal axes for classification of binding ligands

PLoS ONE ◽  
2021 ◽  
Vol 16 (4) ◽  
pp. e0244905
Author(s):  
Galkande Iresha Premarathna ◽  
Leif Ellingson
Keyword(s):  
Coordinate System ◽  
Binding Sites ◽  
Three Dimensional ◽  
Structural Features ◽  
Mathematical Representation ◽  
Computationally Efficient ◽  
Probability Models ◽  
Principal Axes ◽  
Structural Dispersion ◽  
Benchmark Datasets

Many researchers have studied the relationship between the biological functions of proteins and the structures of both their overall backbones of amino acids and their binding sites. A large amount of the work has focused on summarizing structural features of binding sites as scalar quantities, which can result in a great deal of information loss since the structures are three-dimensional. Additionally, a common way of comparing binding sites is via aligning their atoms, which is a computationally intensive procedure that substantially limits the types of analysis and modeling that can be done. In this work, we develop a novel encoding of binding sites as covariance matrices of the distances of atoms to the principal axes of the structures. This representation is invariant to the chosen coordinate system for the atoms in the binding sites, which removes the need to align the sites to a common coordinate system, is computationally efficient, and permits the development of probability models. These can then be used to both better understand groups of binding sites that bind to the same ligand and perform classification for these ligand groups. We demonstrate the utility of our method for discrimination of binding ligand through classification studies with two benchmark datasets using nearest mean and polytomous logistic regression classifiers.

scholarly journals Classification of protein binding ligands using structural dispersion of binding site atoms from principal axes

2020 ◽  
Author(s):  
Galkande Iresha Premarathna ◽  
Leif Ellingson
Keyword(s):  
Coordinate System ◽  
Binding Sites ◽  
Three Dimensional ◽  
Structural Features ◽  
Computationally Efficient ◽  
Probability Models ◽  
Principal Axes ◽  
Structural Dispersion ◽  
Benchmark Datasets ◽  
Computationally Intensive

AbstractMany researchers have studied the relationship between the biological functions of proteins and the structures of both their overall backbones of amino acids and their binding sites. A large amount of the work has focused on summarizing structural features of binding sites as scalar quantities, which can result in a great deal of information loss since the structures are three-dimensional. Additionally, a common way of comparing binding sites is via aligning their atoms, which is a computationally intensive procedure that substantially limits the types of analysis and modeling that can be done. In this work, we develop a novel encoding of binding sites as covariance matrices of the distances of atoms to the principal axes of the structures. This representation is invariant to the chosen coordinate system for the atoms in the binding sites, which removes the need to align the sites to a common coordinate system, is computationally efficient, and permits the development of probability models. These can then be used to both better understand groups of binding sites that bind to the same ligand and perform classification for these ligand groups. We demonstrate the effectiveness of our method through classification studies with two benchmark datasets using nearest mean and polytomous logistic regression classifiers.

scholarly journals DeeplyTough: Learning Structural Comparison of Protein Binding Sites

2019 ◽  
Author(s):  
Martin Simonovsky ◽  
Joshua Meyers
Keyword(s):  
Protein Binding ◽  
Binding Sites ◽  
Protein Function ◽  
Large Scale ◽  
Protein Structures ◽  
Three Dimensional ◽  
Protein Binding Sites ◽  
Data Driven Approach ◽  
Benchmark Datasets ◽  
New Perspective

AbstractMotivationProtein binding site comparison (pocket matching) is of importance in drug discovery. Identification of similar binding sites can help guide efforts for hit finding, understanding polypharmacology and characterization of protein function. The design of pocket matching methods has traditionally involved much intuition, and has employed a broad variety of algorithms and representations of the input protein structures. We regard the high heterogeneity of past work and the recent availability of large-scale benchmarks as an indicator that a data-driven approach may provide a new perspective.ResultsWe propose DeeplyTough, a convolutional neural network that encodes a three-dimensional representation of protein binding sites into descriptor vectors that may be compared efficiently in an alignment-free manner by computing pairwise Euclidean distances. The network is trained with supervision: (i) to provide similar pockets with similar descriptors, (ii) to separate the descriptors of dissimilar pockets by a minimum margin, and (iii) to achieve robustness to nuisance variations. We evaluate our method using three large-scale benchmark datasets, on which it demonstrates excellent performance for held-out data coming from the training distribution and competitive performance when the trained network is required to generalize to datasets constructed independently.Availabilityhttps://github.com/BenevolentAI/[email protected],[email protected]

Conformation of Ribosomes from Escherichia Coli

1974 ◽  
Vol 32 ◽  
pp. 210-211
Author(s):  
M. Boublik ◽  
W. Hellmann ◽  
F. Jenkins
Keyword(s):  
Binding Sites ◽  
Ribosomal Proteins ◽  
Fluorescent Dyes ◽  
Protein Biosynthesis ◽  
Three Dimensional ◽  
Spatial Arrangement ◽  
Dimensional Structure ◽  
Complete Understanding ◽  
And Function

The present knowledge of the three-dimensional structure of ribosomes is far too limited to enable a complete understanding of the various roles which ribosomes play in protein biosynthesis. The spatial arrangement of proteins and ribonuclec acids in ribosomes can be analysed in many ways. Determination of binding sites for individual proteins on ribonuclec acid and locations of the mutual positions of proteins on the ribosome using labeling with fluorescent dyes, cross-linking reagents, neutron-diffraction or antibodies against ribosomal proteins seem to be most successful approaches. Structure and function of ribosomes can be correlated be depleting the complete ribosomes of some proteins to the functionally inactive core and by subsequent partial reconstitution in order to regain active ribosomal particles.

Methods for making stereoslides and -prints, with freeze-etched olfactory epithelium as example

1984 ◽  
Vol 42 ◽  
pp. 704-705
Author(s):  
Bert Ph. M. Menco ◽  
Ido F. Menco ◽  
Frans L.T. Verdonk
Keyword(s):  
Electron Microscope ◽  
Olfactory Epithelium ◽  
Three Dimensional ◽  
Supporting Cell ◽  
Structural Features ◽  
Extensive Study ◽  
Sprague Dawley ◽  
Freezing Method ◽  
Respiratory Epithelia ◽  
Three Dimensional Presentation

Previously we presented an extensive study of the distributions of intramembranous particles of structures in apical surfaces of nasal olfactory and respiratory epithelia of the Sprague-Dawley rat. For the same structures these distributions were compared in samples which were i) chemically fixed and cryo-protected with glycerol before cryo-fixation, after excision, and ii)ultra-rapidly frozen by means of the slam-freezing method. Since a three-dimensional presentation markedly improves visualization of structural features micrographs were presented as stereopairs. Two exposures were made by tiling the sample stage of the electron microscope 6° in either direction with an eucentric goniometer. The negatives (Agfa Pan 25 Professional) were reversed with Kodak Technical Pan Film 2415 developed in D76 1:1. The prints were made from these reversed negatives. As an example tight-junctional features of an olfactory supporting cell in a region where this cell conjoined with two other cells are presented (Fig. 1).

scholarly journals Agent-Based Modeling Demonstrates How Local Chemotactic Behavior Can Shape Biofilm Architecture

mSphere ◽  
2019 ◽  
Vol 4 (3) ◽  
Author(s):  
Emily G. Sweeney ◽  
Andrew Nishida ◽  
Alexandra Weston ◽  
Maria S. Bañuelos ◽  
Kristin Potter ◽  
...  
Keyword(s):  
Helicobacter Pylori ◽  
Three Dimensional ◽  
Structural Features ◽  
Agent Based Modeling ◽  
Emergent Properties ◽  
Cellular Interactions ◽  
Biofilm Growth ◽  
Content Type ◽  
Agent Based ◽  
H Pylori

ABSTRACTBacteria are often found living in aggregated multicellular communities known as biofilms. Biofilms are three-dimensional structures that confer distinct physical and biological properties to the collective of cells living within them. We used agent-based modeling to explore whether local cellular interactions were sufficient to give rise to global structural features of biofilms. Specifically, we asked whether chemorepulsion from a self-produced quorum-sensing molecule, autoinducer-2 (AI-2), was sufficient to recapitulate biofilm growth and cellular organization observed for biofilms ofHelicobacter pylori, a common bacterial resident of human stomachs. To carry out this modeling, we modified an existing platform, Individual-based Dynamics of Microbial Communities Simulator (iDynoMiCS), to incorporate three-dimensional chemotaxis, planktonic cells that could join or leave the biofilm structure, and cellular production of AI-2. We simulated biofilm growth of previously characterizedH. pyloristrains with various AI-2 production and sensing capacities. Using biologically plausible parameters, we were able to recapitulate both the variation in biofilm mass and cellular distributions observed with these strains. Specifically, the strains that were competent to chemotax away from AI-2 produced smaller and more heterogeneously spaced biofilms, whereas the AI-2 chemotaxis-defective strains produced larger and more homogeneously spaced biofilms. The model also provided new insights into the cellular demographics contributing to the biofilm patterning of each strain. Our analysis supports the idea that cellular interactions at small spatial and temporal scales are sufficient to give rise to larger-scale emergent properties of biofilms.IMPORTANCEMost bacteria exist in aggregated, three-dimensional structures called biofilms. Although biofilms play important ecological roles in natural and engineered settings, they can also pose societal problems, for example, when they grow in plumbing systems or on medical implants. Understanding the processes that promote the growth and disassembly of biofilms could lead to better strategies to manage these structures. We had previously shown thatHelicobacter pyloribacteria are repulsed by high concentrations of a self-produced molecule, AI-2, and thatH. pylorimutants deficient in AI-2 sensing form larger and more homogeneously spaced biofilms. Here, we used computer simulations of biofilm formation to show that localH. pyloribehavior of repulsion from high AI-2 could explain the overall architecture ofH. pyloribiofilms. Our findings demonstrate that it is possible to change global biofilm organization by manipulating local cell behaviors, which suggests that simple strategies targeting cells at local scales could be useful for controlling biofilms in industrial and medical settings.

scholarly journals Porous Characteristics of Three-Dimensional Disordered Graphene Networks

Crystals ◽  
2021 ◽  
Vol 11 (2) ◽  
pp. 127
Author(s):  
YongChao Wang ◽  
YinBo Zhu ◽  
HengAn Wu
Keyword(s):  
Pore Size ◽  
Low Temperatures ◽  
Gas Adsorption ◽  
Three Dimensional ◽  
Md Simulations ◽  
Structural Features ◽  
Atomic Scale ◽  
Critical Factors ◽  
Chlorination Process ◽  
Porous Morphology

The porous characteristics of disordered carbons are critical factors to their performance on hydrogen storage and electrochemical capacitors. Even though the porous information can be estimated indirectly by gas adsorption experiments, it is still hard to directly characterize the porous morphology considering the complex 3D connectivity. To this end, we construct full-atom disordered graphene networks (DGNs) by mimicking the chlorination process of carbide-derived carbons using annealing-MD simulations, which could model the structure of disordered carbons at the atomic scale. The porous characteristics, including pore volume, pore size distribution (PSD), and specific surface area (SSA), were then computed from the coordinates of carbon atoms. From the evolution of structural features, pores grow dramatically during the formation of polyaromatic fragments and sequent disordered framework. Then structure is further graphitized while the PSD shows little change. For the obtained DGNs, the porosity, pore size, and SSA increase with decreasing density. Furthermore, SSA tends to saturate in the low-density range. The DGNs annealed at low temperatures exhibit larger SSA than high-temperature DGNs because of the abundant free edges.

scholarly journals Three-Dimensional Structures of Carbohydrates and Where to Find Them

2020 ◽  
Vol 21 (20) ◽  
pp. 7702 ◽  
Author(s):  
Sofya I. Scherbinina ◽  
Philip V. Toukach
Keyword(s):  
Experimental Data ◽  
Molecular Modeling ◽  
Computational Methods ◽  
Three Dimensional ◽  
Structural Diversity ◽  
Structural Data ◽  
Structural Features ◽  
Data Validation ◽  
Data Generation ◽  
Efficient Treatment

Analysis and systematization of accumulated data on carbohydrate structural diversity is a subject of great interest for structural glycobiology. Despite being a challenging task, development of computational methods for efficient treatment and management of spatial (3D) structural features of carbohydrates breaks new ground in modern glycoscience. This review is dedicated to approaches of chemo- and glyco-informatics towards 3D structural data generation, deposition and processing in regard to carbohydrates and their derivatives. Databases, molecular modeling and experimental data validation services, and structure visualization facilities developed for last five years are reviewed.

Comparison Considerations Toward Investigating the Factors of Load and Age Group on the Maximum Reach Envelope

2020 ◽  
pp. 001872082096501
Author(s):  
Heather Johnston ◽  
Colleen Dewis ◽  
John Kozey
Keyword(s):  
Coordinate System ◽  
Three Dimensional ◽  
Spherical Coordinate System ◽  
Upper Body ◽  
Group Differences ◽  
Anthropometric Measures ◽  
Younger Adults ◽  
Present Measurement ◽  
Spherical Coordinate ◽  
Cylindrical Coordinate

Objective The objectives were to compare cylindrical and spherical coordinate representations of the maximum reach envelope (MRE) and apply these to a comparison of age and load on the MRE. Background The MRE is a useful measurement in the design of workstations and quantifying functional capability of the upper body. As a dynamic measure, there are human factors that impact the size, shape, and boundaries of the MRE. Method Three-dimensional reach measures were recorded using a computerized potentiometric system for anthropometric measures (CPSAM) on two adult groups (aged 18–25 years and 35–70 years). Reach trials were performed holding .0, .5, and 1 kg. Results Three-dimensional Cartesian coordinates were transformed into cylindrical ( r, θ , Z) and spherical ( r, θ, ϕ) coordinates. Median reach distance vectors were calculated for 54 panels within the MRE as created by incremented banding of the respective coordinate systems. Reach distance and reach area were compared between the two groups and the loaded conditions using a spherical coordinate system. Both younger adults and unloaded condition produced greater reach distances and reach areas. Conclusions Where a cylindrical coordinate system may reflect absolute reference for design, a normalized spherical coordinate system may better reflect functional range of motion and better compare individual and group differences. Age and load are both factors that impact the MRE. Application These findings present measurement considerations for use in human reach investigation and design.

Androgen receptor: acting in the three-dimensional chromatin landscape of prostate cancer cells

2011 ◽  
Vol 5 (1) ◽  
Author(s):  
Harri Makkonen ◽  
Jorma J. Palvimo
Keyword(s):  
Prostate Cancer ◽  
Androgen Receptor ◽  
Cancer Cells ◽  
Binding Sites ◽  
Target Genes ◽  
Three Dimensional ◽  
Regulatory Elements ◽  
Gene Promoters ◽  
Loop Formation ◽  
Prostate Cancer Cells

AbstractAndrogen receptor (AR) acts as a hormone-controlled transcription factor that conveys the messages of both natural and synthetic androgens to the level of genes and gene programs. Defective AR signaling leads to a wide array of androgen insensitivity disorders, and deregulated AR function, in particular overexpression of AR, is involved in the growth and progression of prostate cancer. Classic models of AR action view AR-binding sites as upstream regulatory elements in gene promoters or their proximity. However, recent wider genomic screens indicate that AR target genes are commonly activated through very distal chromatin-binding sites. This highlights the importance of long-range chromatin regulation of transcription by the AR, shifting the focus from the linear gene models to three-dimensional models of AR target genes and gene programs. The capability of AR to regulate promoters from long distances in the chromatin is particularly important when evaluating the role of AR in the regulation of genes in malignant prostate cells that frequently show striking genomic aberrations, especially gene fusions. Therefore, in addition to the mechanisms of DNA loop formation between the enhancer bound ARs and the transcription apparatus at the target core promoter, the mechanisms insulating distally bound ARs from promiscuously making contacts and activating other than their normal target gene promoters are critical for proper physiological regulation and thus currently under intense investigation. This review discusses the current knowledge about the AR action in the context of gene aberrations and the three-dimensional chromatin landscape of prostate cancer cells.

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