Deciphering Protein Complex Structures From Cryo Electron Microscopy Maps Using Deep Learning

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Deciphering Protein Complex Structures from Cryo-electron Microscopy Maps Using Deep Learning

Author : Jonas Pfab
Publisher :
ISBN 13 :
Total Pages : 58 pages
Book Rating : 4.:/5 (123 download)

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Book Synopsis Deciphering Protein Complex Structures from Cryo-electron Microscopy Maps Using Deep Learning by : Jonas Pfab

Download or read book Deciphering Protein Complex Structures from Cryo-electron Microscopy Maps Using Deep Learning written by Jonas Pfab and published by . This book was released on 2020 with total page 58 pages. Available in PDF, EPUB and Kindle. Book excerpt: Information about macromolecular structure of protein complexes such as SARS-CoV-2, and related cellular and molecular mechanisms can assist the search for vaccines and drug development processes. To obtain such structural information, we present DeepTracer, a fully automatic deep learning-based method for fast de novo multi-chain protein complex structure determination from high-resolution cryo-electron microscopy (cryo-EM) density maps. We applied DeepTracer on a previously published set of 476 raw experimental density maps and compared the results with a current state of the art method. The residue coverage increased by over 30% using DeepTracer and the RMSD value improved from 1.29Å to 1.18Å. Additionally, we applied DeepTracer on a set of 62 coronavirus-related density maps, among them 10 with no deposited structure available in EMDataResource. We observed an average residue match of 84% with the deposited structures and an average RMSD of 0.93Å. Additional tests with related methods further exemplify DeepTracer's competitive accuracy and efficiency of structure modeling. DeepTracer allows for exceptionally fast computations, making it possible to trace around 60,000 residues in 350 chains within only two hours. The web service is globally accessible at https://deeptracer.uw.edu.

Protein Complex Structure Determination Guided by Low-resolution Cryo-electron Microscopy Maps

Author : Daniel P. Farrell
Publisher :
ISBN 13 :
Total Pages : 68 pages
Book Rating : 4.:/5 (13 download)

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Book Synopsis Protein Complex Structure Determination Guided by Low-resolution Cryo-electron Microscopy Maps by : Daniel P. Farrell

Download or read book Protein Complex Structure Determination Guided by Low-resolution Cryo-electron Microscopy Maps written by Daniel P. Farrell and published by . This book was released on 2021 with total page 68 pages. Available in PDF, EPUB and Kindle. Book excerpt: Cryo-electron microscopy of protein complexes often leads to moderate resolution maps (4-8 Ã ), with visible secondary structure elements but poorly resolved loops, making model-building challenging. In the absence of high-resolution structures of homologues, only coarse-grained structural features are typically inferred from these maps, and it is often impossible to assign specific regions of density to individual protein subunits. This dissertation describes a new method for overcoming these difficulties that integrates predicted residue distance distributions from a deep-learned convolutional neural network, computational protein folding using Rosetta, and automated EM-map-guided complex assembly. We will show how this method performs on a diverse benchmarking dataset in addition to describing how it was used to build models for three difficult protein complexes that would have been impossible to solve without this software. We anticipate that our approach will be broadly useful for cryoEM structure determination of large complexes containing many subunits for which there are no homologues of known structure.

Deep Learning to Predict Protein Backbone Structure from High-resolution Cryo-EM Density Maps

Author : Spencer Moritz
Publisher :
ISBN 13 :
Total Pages : 42 pages
Book Rating : 4.:/5 (11 download)

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Book Synopsis Deep Learning to Predict Protein Backbone Structure from High-resolution Cryo-EM Density Maps by : Spencer Moritz

Download or read book Deep Learning to Predict Protein Backbone Structure from High-resolution Cryo-EM Density Maps written by Spencer Moritz and published by . This book was released on 2019 with total page 42 pages. Available in PDF, EPUB and Kindle. Book excerpt:

A Geometric Approach for Deciphering Protein Structure from Cryo-EM Volumes

Author : Sasakthi Senanayaka Abeysinghe
Publisher :
ISBN 13 :
Total Pages : 108 pages
Book Rating : 4.:/5 (741 download)

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Book Synopsis A Geometric Approach for Deciphering Protein Structure from Cryo-EM Volumes by : Sasakthi Senanayaka Abeysinghe

Download or read book A Geometric Approach for Deciphering Protein Structure from Cryo-EM Volumes written by Sasakthi Senanayaka Abeysinghe and published by . This book was released on 2010 with total page 108 pages. Available in PDF, EPUB and Kindle. Book excerpt: Electron Cryo-Microscopy or cryo-EM is an area that has received much attention in the recent past. Compared to the traditional methods of X-Ray Crystallography and NMR Spectroscopy, cryo-EM can be used to image much larger complexes, in many different conformations, and under a wide range of biochemical conditions. This is because it does not require the complex to be crystallisable. However, cryo-EM reconstructions are limited to intermediate resolutions, with the state-of-the-art being 3.6A, where secondary structure elements can be visually identified but not individual amino acid residues. This lack of atomic level resolution creates new computational challenges for protein structure identification. In this dissertation, we present a suite of geometric algorithms to address several aspects of protein modeling using cryo-EM density maps. Specifically, we develop novel methods to capture the shape of density volumes as geometric skeletons. We then use these skeletons to find secondary structure elements (SSEs) of a given protein, to identify the correspondence between these SSEs and those predicted from the primary sequence, and to register high-resolution protein structures onto the density volume. In addition, we designed and developed Gorgon, an interactive molecular modeling system, that integrates the above methods with other interactive routines to generate reliable and accurate protein backbone models.

Deep Learning for Validating Resolution and Detecting Secondary Structure Elements of Proteins in 3D Cryo-electron Microscopy Images

Download Deep Learning for Validating Resolution and Detecting Secondary Structure Elements of Proteins in 3D Cryo-electron Microscopy Images PDF Online Free

Author : Todor Kirilov Avramov
Publisher :
ISBN 13 :
Total Pages : 130 pages
Book Rating : 4.:/5 (11 download)

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Book Synopsis Deep Learning for Validating Resolution and Detecting Secondary Structure Elements of Proteins in 3D Cryo-electron Microscopy Images by : Todor Kirilov Avramov

Download or read book Deep Learning for Validating Resolution and Detecting Secondary Structure Elements of Proteins in 3D Cryo-electron Microscopy Images written by Todor Kirilov Avramov and published by . This book was released on 2019 with total page 130 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Machine Learning for Understanding Protein Sequence and Structure

Author : Tristan Wendland Bepler
Publisher :
ISBN 13 :
Total Pages : 200 pages
Book Rating : 4.:/5 (123 download)

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Book Synopsis Machine Learning for Understanding Protein Sequence and Structure by : Tristan Wendland Bepler

Download or read book Machine Learning for Understanding Protein Sequence and Structure written by Tristan Wendland Bepler and published by . This book was released on 2020 with total page 200 pages. Available in PDF, EPUB and Kindle. Book excerpt: Proteins are the fundamental building blocks of life, carrying out a vast array of functions at the molecular level. Understanding these molecular machines has been a core problem in biology for decades. Recent advances in cryo-electron microscopy (cryoEM) has enabled high resolution experimental measurement of proteins in their native states. However, this technology remains expensive and low throughput. At the same time, ever growing protein databases offer new opportunities for understanding the diversity of natural proteins and for linking sequence to structure and function. This thesis introduces a variety of machine learning methods for accelerating protein structure determination by cryoEM and for learning from large protein databases. We first consider the problem of protein identification in the large images collected in cryoEM. We propose a positive-unlabeled learning framework that enables high accuracy particle detection with few labeled data points, both improving data quality and analysis speed. Next, we develop a deep denoising model for cryo-electron micrographs. By learning the denoising model from large amounts of real cryoEM data, we are able to capture the noise generation process and accurately denoise micrographs, improving the ability of experamentalists to examine and interpret their data. We then introduce a neural network model for understanding continuous variability in proteins in cryoEM data by explicitly disentangling variation of interest (structure) for nuisance variation due to rotation and translation. Finally, we move beyond cryoEM and propose a method for learning vector embeddings of proteins using information from structure and sequence. Many of the machine learning methods developed here are general purpose and can be applied to other data domains.

Protein Structure Determination from Cryo-electron Microscopy Density Maps

Author : Yu-Ruei Wang
Publisher :
ISBN 13 :
Total Pages : 71 pages
Book Rating : 4.:/5 (932 download)

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Book Synopsis Protein Structure Determination from Cryo-electron Microscopy Density Maps by : Yu-Ruei Wang

Download or read book Protein Structure Determination from Cryo-electron Microscopy Density Maps written by Yu-Ruei Wang and published by . This book was released on 2015 with total page 71 pages. Available in PDF, EPUB and Kindle. Book excerpt: Single-particle cryo-electron microscopy (cryo-EM) has emerged as a powerful tool in structure determination of macromolecular complexes that are not suitable for crystallographic studies. Recent advances in direct electron detectors and image-processing techniques have allowed cryo-EM to reach near-atomic resolution (3--5 Å) from small particles with low or even no symmetry. However, tools to determine structures from cryo-EM maps have lagged behind. In this dissertation we describe approaches that apply Rosetta high-resolution structure prediction methods to model-building from cryo-EM maps. Using knowledge-based information gathered from proteins of known atomic structure, we describe the development of novel tools for de novo model-building from near-atomic resolution cryo-EM maps, and for architecture determination of multi-component macromolecular assemblies from medium- to low-resolution (5--15 Å) cryo- EM maps. We demonstrate that these new computational tools have shown usefulness in determining the structures from newly reconstructed cryo-EM maps, which would otherwise be difficult or impossible for human to do. These methods should enable rapid and reliable structure determination from cryo-EM maps.

The Resolution Revolution: Recent Advances In cryoEM

Author :
Publisher : Academic Press
ISBN 13 : 0128054352
Total Pages : 488 pages
Book Rating : 4.1/5 (28 download)

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Book Synopsis The Resolution Revolution: Recent Advances In cryoEM by :

Download or read book The Resolution Revolution: Recent Advances In cryoEM written by and published by Academic Press. This book was released on 2016-08-26 with total page 488 pages. Available in PDF, EPUB and Kindle. Book excerpt: cryoEM, a new volume in the Methods in Enzymology series, continues the legacy of this premier serial with quality chapters authored by leaders in the field. This volume covers research methods and new developments in recording images, the creation, evaluation and validation of 3D maps from the images, model building into maps and refinement of the resulting atomic structures, and applications of essentially single particle methods to helical structures and to sub-tomogram averaging. Continues the legacy of this premier serial with quality chapters authored by leaders in the field Covers research methods that determine the structures of biological molecules, a vital step for understanding their function Contains the technical developments underpinning the advances of cryoEM and captures the exciting insights that have resulted

Cryo-Electron Microscopy in Structural Biology

Author : Krishnarao Appasani
Publisher : CRC Press
ISBN 13 : 1040118844
Total Pages : 488 pages
Book Rating : 4.0/5 (41 download)

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Book Synopsis Cryo-Electron Microscopy in Structural Biology by : Krishnarao Appasani

Download or read book Cryo-Electron Microscopy in Structural Biology written by Krishnarao Appasani and published by CRC Press. This book was released on 2024-10-17 with total page 488 pages. Available in PDF, EPUB and Kindle. Book excerpt: Cryo-electron microscopy, in combination with tomography, has emerged as a new technology for visualizing molecular structures at a resolution beyond even 1 Å. Using this technology has revealed the native molecular details of viruses, membranes, enzymes, ribosomes, and cells. This comprehensive volume brings together authoritative overviews of these methods from structural and biological perspectives. It is a must-have for researchers and graduate students, as well as those working in industry, primarily in the areas of biophysics, structural biology, crystallography, and genomics. Key Features • Focuses on the applications of cryo-EM to structural biology • Documents the importance of cryo-EM/ET approaches in studying the structural determinants of cellular organelle and membrane protein biochemistry • Reviews the applications of high-resolution structures of viruses • Emphasizes structural insights of nuclear and gene machineries • Includes a section focused entirely on the applications of cryo-EM/ET in drug discovery and therapeutic development

Efficient Geometric Approaches for Mining Protein Structure from Cryo-EM Density Maps

Author : Hang Dou
Publisher :
ISBN 13 :
Total Pages : 100 pages
Book Rating : 4.:/5 (13 download)

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Book Synopsis Efficient Geometric Approaches for Mining Protein Structure from Cryo-EM Density Maps by : Hang Dou

Download or read book Efficient Geometric Approaches for Mining Protein Structure from Cryo-EM Density Maps written by Hang Dou and published by . This book was released on 2017 with total page 100 pages. Available in PDF, EPUB and Kindle. Book excerpt: A protein's 3D structure is the key to understanding its biological function. In recent years, cryo-electron microscopy or cryo-EM has established itself as a mainstream technique to capture proteins' structure at near-native conditions. However the vast majority of cryo-EM data are at medium (5-10A) or low (>10A) resolutions, which is insufficient to capture a protein's atomic structure. Fortunately, at such resolutions, some intrinsic structures of a protein, such as secondary structure elements (SSEs) and smooth c-alpha backbone fragments (SCBFs), can be recognized or robustly detected. In this dissertation, we present efficient protein fitting pipelines to recover a protein's atomic structure given the protein's cryo-EM density map by leveraging the intrinsic structure information detected from the density map. Specifically, we first compute the correspondences between the protein features (SSEs or SCBFs) detected from the cryo-EM density map and those extracted from the template model. Then we fit the template model into the cryo-EM density map guided by the obtained correspondences.

The Science Behind AlphaFold

Author : StoryBuddiesPlay
Publisher : StoryBuddiesPlay
ISBN 13 :
Total Pages : 58 pages
Book Rating : 4./5 ( download)

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Book Synopsis The Science Behind AlphaFold by : StoryBuddiesPlay

Download or read book The Science Behind AlphaFold written by StoryBuddiesPlay and published by StoryBuddiesPlay. This book was released on 2024-06-03 with total page 58 pages. Available in PDF, EPUB and Kindle. Book excerpt: AlphaFold, a groundbreaking AI system, has cracked the code on protein structure prediction, a challenge that baffled scientists for decades. This book explores the science behind AlphaFold, delving into deep learning, big data, and the inner workings of this remarkable program. Uncover how AlphaFold is revolutionizing protein science, with the potential to accelerate drug discovery, personalize medicine, and design innovative materials. This comprehensive guide explores: The significance of protein structures and the challenges of prediction How AlphaFold leverages deep learning and vast data resources The process of protein structure prediction with AlphaFold, including its strengths and limitations The ethical considerations surrounding AI in protein science The exciting future applications of AlphaFold in various scientific fields Whether you're a scientist, student, or simply curious about the future of biology, this book provides a clear and engaging exploration of AlphaFold and its transformative impact on protein science.

Enabling Deep Geometric Learning on Cryo-EM Maps Using Neural Representation

Author : Nathan Ranno
Publisher :
ISBN 13 :
Total Pages : 44 pages
Book Rating : 4.:/5 (129 download)

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Book Synopsis Enabling Deep Geometric Learning on Cryo-EM Maps Using Neural Representation by : Nathan Ranno

Download or read book Enabling Deep Geometric Learning on Cryo-EM Maps Using Neural Representation written by Nathan Ranno and published by . This book was released on 2021 with total page 44 pages. Available in PDF, EPUB and Kindle. Book excerpt: Advances in imagery at atomic and near-atomic resolution, such as cryogenic electron microscopy (cryo-EM), have led to an influx of high resolution images of proteins and other macromolecular structures to data banks worldwide. Deep geometric learning is intriguing for use in structure segmentation, but the native voxel format of cryo-EM maps is unsuitable as input to such methods. We present a novel data format called the neural cryo-EM map that accurately parameterizes cryo-EM maps and provides native, spatially continuous density and gradient data to serve as the basis for a graph-based interpretation of cryo-EM maps. Density values interpolated using the non-linear neural cryo-EM format are more accurate than conventional tri-linear interpolation. Our graph-based interpretations of 115 experimental cryo-EM maps from 1.15 to 4.0 Angstrom resolution provide high coverage of the underlying amino acid residue locations, while accuracy of nodes is correlated with resolution. The nodes of graphs created from atomic resolution maps (higher than 1.6 Angstrom) provide greater than 99% residue coverage as well as 85% full atomic coverage with a mean of 0.19 Angstrom root mean squared deviation (RMSD). Other graphs have a mean 84% residue coverage with less specificity of the nodes due to experimental noise and differences of density context at lower resolutions. Graphs created from atomic resolution maps may serve as input to downstream deep geometric learning applications and may be generalized to transform any 3D grid-based data format into non-linear, continuous, and differentiable format.

Structural Proteomics Towards Studying Protein Complexes in Cellular Context

Author : Caitlyn L. McCafferty
Publisher :
ISBN 13 :
Total Pages : 0 pages
Book Rating : 4.:/5 (135 download)

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Book Synopsis Structural Proteomics Towards Studying Protein Complexes in Cellular Context by : Caitlyn L. McCafferty

Download or read book Structural Proteomics Towards Studying Protein Complexes in Cellular Context written by Caitlyn L. McCafferty and published by . This book was released on 2022 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Recent advances in cryo-electron microscopy (cryo-EM) allow for rapid and direct visualization of high-resolution three-dimensional (3D) structures. Unfortunately, current methods are often limited to identification of and structure determination for highly purified protein samples, preventing characterization of protein complex structures in their native form. Being able to determine a protein structure in the native biological “habitat” by imaging, for example, an unpurified cell lysate, is essential to understanding its role in the mechanisms that drive biological processes. Methods such as shotgun-electron microscopy (shotgun-EM) and cryo-electron tomography (cryo-ET) aim to study structural biology in the biological context of the cell, which allows for the definition of native interaction partners and identification of spatial information. However, a major and frequent tradeoff of imaging biological assemblies in a near-native context is a decrease in structure resolution. Integrating cryo-EM with complementary techniques such as mass spectrometry can allow for characterization of protein architectures without purifying for a specific target. Furthermore, protein-protein interactions identified by mass spectrometry or other computational methods, in conjunction with cutting-edge methods for 3D structure determination and prediction, can actually be used to investigate the architecture of multiple distinct protein complexes from a single mixture. Here, I detail computational methods that I have developed for determining protein interaction interfaces based on surface complementarity. This serves as a useful tool for determining how protein subunits may fit together within an EM map. I then describe an approach for using intermolecular evolutionary couplings between amino acids interfaces to assemble proteins into intermediate- to low-resolution EM maps. Because both of these methods are dependent on reliable protein structure, I then used in situ cross-linking mass spectrometry (XL/MS) to evaluate and improve the quality of AlphaFold predicted protein structures. Finally, I present the use of these methods to study native ciliary protein architectures, such as the intraflagellar transport A (IFT-A) complex. Ciliopathies are a class of diseases that arise from dysfunction in cilia. I show that using integrative methods to study the IFT-A architecture allows for the molecular interpretation of disease-associated alleles. The development and integration of these methods provides a toolbox for studying ciliary assemblies in their native environment and interpreting these lower resolution assemblies with the goal of providing a blueprint for the molecular basis of disease

Textbook of Ion Channels Volume I

Author : Jie Zheng
Publisher : CRC Press
ISBN 13 : 1000857751
Total Pages : 331 pages
Book Rating : 4.0/5 (8 download)

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Book Synopsis Textbook of Ion Channels Volume I by : Jie Zheng

Download or read book Textbook of Ion Channels Volume I written by Jie Zheng and published by CRC Press. This book was released on 2023-06-09 with total page 331 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Textbook of Ion Channels is a set of three volumes providing a wide-ranging reference source on ion channels for students, instructors and researchers. Ion channels are membrane proteins that control the electrical properties of neurons and cardiac cells; mediate the detection and response to sensory stimuli like light, sound, odor, and taste; and regulate the response to physical stimuli like temperature and pressure. In non-excitable tissues, ion channels are instrumental for the regulation of basic salt balance that is critical for homeostasis. Ion channels are located at the surface membrane of cells, giving them the unique ability to communicate with the environment, as well as the membrane of intracellular organelles, allowing them to regulate internal homeostasis. Ion channels are fundamentally important for human health and diseases, and are important targets for pharmaceuticals in mental illness, heart disease, anesthesia, pain and other clinical applications. The modern methods used in their study are powerful and diverse, ranging from single ion-channel measurement techniques to models of ion channel diseases in animals, and human clinical trials for ion channel drugs. Volume I, Part 1 covers fundamental topics such as the basic principles of ion permeation and selectivity, voltage-dependent, ligand-dependent, and mechano-dependent ion channel activation mechanisms, the mechanisms for ion channel desensitization and inactivation, and basic ion channel pharmacology and inhibition. Volume I, Part 2 offers a practical guide of cardinal methods for researching ion channels, including heterologous expression and voltage-clamp and patch-clamp electrophysiology; isolation of native currents using patch clamping; modeling ion channel gating, structures, and its dynamics; crystallography and cryo-electron microscopy; fluorescence and paramagnetic resonance spectroscopy methods; and genetics approaches in model organisms. All three volumes give the reader an introduction to fundamental concepts needed to understand the mechanism of ion channels; a guide to the technical aspects of ion channel research; a modern guide to the properties of major ion channel families; and includes coverage of key examples of regulatory, physiological and disease roles for ion channels.

Machine Learning Meets Quantum Physics

Author : Kristof T. Schütt
Publisher : Springer Nature
ISBN 13 : 3030402452
Total Pages : 473 pages
Book Rating : 4.0/5 (34 download)

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Book Synopsis Machine Learning Meets Quantum Physics by : Kristof T. Schütt

Download or read book Machine Learning Meets Quantum Physics written by Kristof T. Schütt and published by Springer Nature. This book was released on 2020-06-03 with total page 473 pages. Available in PDF, EPUB and Kindle. Book excerpt: Designing molecules and materials with desired properties is an important prerequisite for advancing technology in our modern societies. This requires both the ability to calculate accurate microscopic properties, such as energies, forces and electrostatic multipoles of specific configurations, as well as efficient sampling of potential energy surfaces to obtain corresponding macroscopic properties. Tools that can provide this are accurate first-principles calculations rooted in quantum mechanics, and statistical mechanics, respectively. Unfortunately, they come at a high computational cost that prohibits calculations for large systems and long time-scales, thus presenting a severe bottleneck both for searching the vast chemical compound space and the stupendously many dynamical configurations that a molecule can assume. To overcome this challenge, recently there have been increased efforts to accelerate quantum simulations with machine learning (ML). This emerging interdisciplinary community encompasses chemists, material scientists, physicists, mathematicians and computer scientists, joining forces to contribute to the exciting hot topic of progressing machine learning and AI for molecules and materials. The book that has emerged from a series of workshops provides a snapshot of this rapidly developing field. It contains tutorial material explaining the relevant foundations needed in chemistry, physics as well as machine learning to give an easy starting point for interested readers. In addition, a number of research papers defining the current state-of-the-art are included. The book has five parts (Fundamentals, Incorporating Prior Knowledge, Deep Learning of Atomistic Representations, Atomistic Simulations and Discovery and Design), each prefaced by editorial commentary that puts the respective parts into a broader scientific context.

Textbook of Ion Channels

Author : Jie Zheng
Publisher : CRC Press
ISBN 13 : 1003820239
Total Pages : 1067 pages
Book Rating : 4.0/5 (38 download)

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Book Synopsis Textbook of Ion Channels by : Jie Zheng

Download or read book Textbook of Ion Channels written by Jie Zheng and published by CRC Press. This book was released on 2023-07-06 with total page 1067 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Textbook of Ion Channels is a set of three volumes providing a wide-ranging reference source on ion channels for students, instructors, and researchers. Ion channels are membrane proteins that control the electrical properties of neurons and cardiac cells, mediate the detection and response to sensory stimuli like light, sound, odor, and taste, and regulate the response to physical stimuli like temperature and pressure. In non-excitable tissues, ion channels are instrumental for the regulation of basic salt balance that is critical for homeostasis. Ion channels are located at the surface membrane of cells, giving them the unique ability to communicate with the environment, as well as the membrane of intracellular organelles, allowing them to regulate internal homeostasis. Ion channels are fundamentally important for human health and diseases, and are important targets for pharmaceuticals in mental illness, heart disease, anesthesia, pain and other clinical applications. The modern methods used in their study are powerful and diverse, ranging from single ion-channel measurement techniques to models of ion channel diseases in animals, and human clinical trials for ion channel drugs. All three volumes give the reader an introduction to fundamental concepts needed to understand the mechanism of ion channels, a guide to the technical aspects of ion channel research, offer a modern guide to the properties of major ion channel families, and include coverage of key examples of regulatory, physiological, and disease roles for ion channels.

EMNets

Author : Jingjing Yang
Publisher :
ISBN 13 :
Total Pages : 42 pages
Book Rating : 4.:/5 (11 download)

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Book Synopsis EMNets by : Jingjing Yang

Download or read book EMNets written by Jingjing Yang and published by . This book was released on 2018 with total page 42 pages. Available in PDF, EPUB and Kindle. Book excerpt: The function of a protein is mainly dependent on its exposed surfaces. The protein surface can provide rich information about a protein's function and evolution. Also, identifying protein surface structure is an essential step in the preliminary stages of drug design. There are two worldwide databases for the three-dimensional (3D) structural data of biological molecules: Protein Data Bank (PDB) and Electron Microscopy Data Bank (EMDataBank). The 3D structures in PDB are determined by structural biologists using methods such as X-ray crystallography, nuclear magnetic resonance (NMR) spectroscopy, and cryo-electron microscopy (cryo-EM), which shows the location of each atom relative to each other in the molecule. Unlike the atomic model in PDB, the 3D electron density maps in EMDataBank are determined by cryo-electron microscopy, which provides a general description of the protein surface structure and placement of the helices. Because the 3D structures in PDB are solved atom by atom, PDB equips with real-time searches based on sequence, structure, and function. Comparing with PDB, searches based on structure similarity in the EMDataBank are far behind. High computational cost and rotation invariance are two main challenges for 3D protein surface similarity retrieval. Usually, a global descriptor is used to represent a 3D object in low dimensionality. However, traditional 3D object descriptors don't completely utilize the spatial information in 3D space. In order to efficiently investigate protein function and evolutionary history, we introduce a global protein surface shape representation called EMNets descriptors. EMNets provides an effective and accurate way for protein surface representation and similarity search, and thus contributes to biomedical research. The method uses a Convolutional Autoencoder (CAE) neural network to learn the geometric information of 3D density maps in a data-driven manner. Our approach is the first research that applies neural networks to represent and compare global protein surfaces. Our method effectively represents a 3D cryo-electron microscopy density map by using a descriptor, which consists of only 256 numeric variables, called the EMNets descriptor. Based on the EMNets descriptor, we are able to retrieve similar protein surfaces using the K-nearest-neighbor (KNN) strategy in real-time. The search results of protein surface represented with the EMNets descriptor has shown high agreement with the existing Combinatorial Extension (CE) algorithm of sequence and structure similarity search. Overall, EMNets is a powerful tool for comparing 3D protein structures obtained by cryo-electron microscopy. In the future, we can build a real-time retrieval system based on the EMNets descriptors.