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Author: Amika Sood Publisher: ISBN: Category : Languages : en Pages : 236
Book Description
Specific carbohydrate-protein interactions are crucial in numerous physiological processes, disruption of which has been implicated in many different diseases like cancer. This provides researchers an opportunity to utilize carbohydrates as biomarkers and targets for therapeutics for such diseases. There has been a tremendous surge in the research being conducted towards the development of techniques to analyze carbohydrates and their specificity and affinity for different proteins. However, owing to their complex three-dimensional structure, stereochemistry, low binding affinities and broad specificity, carbohydrates have proven to be challenging to study. Therefore, new techniques and improvements in the existing methodologies are required. Here, we show that the incorporation of experimental data into molecular modeling can be used as a powerful combination to gain an understanding of the structural features of proteins and carbohydrates leading to the specificity in their interactions. Firstly, hydroxyl radical protein footprinting (HRPF) was used to establish a relationship between the oxidation of amino acids exposed on the surface of a protein and their solvent accessible surface area (SASA). Oxidation, as well as SASA, are both directly proportional to the exposure of an amino acid to the solvent. This relationship was used to estimate SASA of residues of a protein in solution, which was then successfully utilized as a score to quantify the quality of models generated through a molecular dynamics (MD) simulation and homology modeling. This relationship can also be used to study protein- carbohydrate interactions, which remains to be tested. Secondly, the functional groups of a monosaccharide essential for forming protein-carbohydrate interactions were identified by using co-crystal structures and per-atom binding energy analysis, which shows that not all chemically-equivalent functional groups are equally significant for binding. Lastly, the 3D structure of a group of monosaccharides was analyzed and it was observed that two monosaccharides can possess structural similarities depending on their alignment, which can be used to explain cross-reactivity between a protein and more than one carbohydrate.
Author: Amika Sood Publisher: ISBN: Category : Languages : en Pages : 236
Book Description
Specific carbohydrate-protein interactions are crucial in numerous physiological processes, disruption of which has been implicated in many different diseases like cancer. This provides researchers an opportunity to utilize carbohydrates as biomarkers and targets for therapeutics for such diseases. There has been a tremendous surge in the research being conducted towards the development of techniques to analyze carbohydrates and their specificity and affinity for different proteins. However, owing to their complex three-dimensional structure, stereochemistry, low binding affinities and broad specificity, carbohydrates have proven to be challenging to study. Therefore, new techniques and improvements in the existing methodologies are required. Here, we show that the incorporation of experimental data into molecular modeling can be used as a powerful combination to gain an understanding of the structural features of proteins and carbohydrates leading to the specificity in their interactions. Firstly, hydroxyl radical protein footprinting (HRPF) was used to establish a relationship between the oxidation of amino acids exposed on the surface of a protein and their solvent accessible surface area (SASA). Oxidation, as well as SASA, are both directly proportional to the exposure of an amino acid to the solvent. This relationship was used to estimate SASA of residues of a protein in solution, which was then successfully utilized as a score to quantify the quality of models generated through a molecular dynamics (MD) simulation and homology modeling. This relationship can also be used to study protein- carbohydrate interactions, which remains to be tested. Secondly, the functional groups of a monosaccharide essential for forming protein-carbohydrate interactions were identified by using co-crystal structures and per-atom binding energy analysis, which shows that not all chemically-equivalent functional groups are equally significant for binding. Lastly, the 3D structure of a group of monosaccharides was analyzed and it was observed that two monosaccharides can possess structural similarities depending on their alignment, which can be used to explain cross-reactivity between a protein and more than one carbohydrate.
Author: Anna Panchenko Publisher: Springer Science & Business Media ISBN: 1848001258 Category : Science Languages : en Pages : 198
Book Description
The biological interactions of living organisms, and protein-protein interactions in particular, are astonishingly diverse. This comprehensive book provides a broad, thorough and multidisciplinary coverage of its field. It integrates different approaches from bioinformatics, biochemistry, computational analysis and systems biology to offer the reader a comprehensive global view of the diverse data on protein-protein interactions and protein interaction networks.
Author: M Michael Gromiha Publisher: World Scientific ISBN: 9811211884 Category : Science Languages : en Pages : 424
Book Description
This book is indexed in Chemical Abstracts ServiceThe interactions of proteins with other molecules are important in many cellular activities. Investigations have been carried out to understand the recognition mechanism, identify the binding sites, analyze the the binding affinity of complexes, and study the influence of mutations on diseases. Protein interactions are also crucial in structure-based drug design.This book covers computational analysis of protein-protein, protein-nucleic acid and protein-ligand interactions and their applications. It provides up-to-date information and the latest developments from experts in the field, using illustrations to explain the key concepts and applications. This volume can serve as a single source on comparative studies of proteins interacting with proteins/DNAs/RNAs/carbohydrates and small molecules.
Author: Brian Gregory Pierce Publisher: ISBN: Category : Languages : en Pages : 326
Book Description
Abstract: Protein-protein interactions play a key role in the functioning of cells and pathways, and understanding these interactions on a physical and structural level can help greatly in developing therapeutics for diseases. The large amount of protein structures available presents an immense opportunity to model and predict protein interactions using computational techniques. Here we describe the development of algorithms to predict protein complex structures (referred to as protein docking) and to design proteins to improve their interaction affinities. We also present experimental results validating our protein design approach. The protein docking work we present includes the symmetric multimer docking program M-ZDOCK as well as ZRANK which rescores docking predictions using a weighted potential. Both programs have been successful when applied to docking benchmarks and in the CAPRI experiment. In addition, we have used the M-ZDOCK program to produce a tetrameric model for a disease-associated protein, the latent nuclear antigen of the Kaposi's sarcoma-associated herpesvirus. We have also developed a protein design algorithm to improve the binding between two proteins, given their complex structure This was applied to a T cell receptor (TCR) to enhance its binding to the Major Histocompatibility Complex and peptide. Several of the point mutations predicted by our algorithm were verified experimentally to bind several times stronger than wild type; we then combined these mutations to produce a TCR with approximately 100-fold affinity improvement. Further testing of combinations of TCR point mutations has led to striking results regarding the kinetics and cooperativity of the mutations. Finally, we have used our protein design algorithm to predict designability of protein complexes from the Protein Data Bank, and identified the complex between CD4 and HIV gp120 as a target for future structure-based design efforts. Preliminary results for this project are given.
Author: Publisher: Academic Press ISBN: 0128008059 Category : Science Languages : en Pages : 505
Book Description
Since its inception in 1945, this serial has provided critical and informative articles written by research specialists that integrate industrial, analytical, and technological aspects of biochemistry, organic chemistry, and instrumentation methodology in the study of carbohydrates. The articles provide a definitive interpretation of the current status and future trends in carbohydrate chemistry and biochemistry. Features contributions from leading authorities and industry experts Informs and updates on all the latest developments in the field
Author: Elizabeth Yuriev Publisher: Frontiers Media SA ISBN: 2889196380 Category : Immunologic diseases. Allergy Languages : en Pages : 104
Book Description
Interest in understanding the biological role of carbohydrates has increased significantly over the last 20 years. The use of structural techniques to understand carbohydrate-protein recognition is still a relatively young area, but one that is of emerging importance. The high flexibility of carbohydrates significantly complicates the determination of high quality structures of their complexes with proteins. Specialized techniques are often required to understand the complexity of carbohydrate recognition by proteins. In this Research Topic, we will focus on structural and computational approaches to understanding carbohydrate recognition by proteins involved in immunity and infection. Particular areas of focus include cancer immunotherapeutics, carbohydrate-lectin interactions, glycosylation and glycosyltransferases.
Author: Erick Francisco Velasquez Publisher: ISBN: Category : Languages : en Pages : 180
Book Description
The elucidation of a protein's interaction/association network is important for defining itsbiological function. Mass spectrometry-based proteomic approaches have emerged as powerful tools for identifying protein-protein interactions (PPIs) and protein-protein associations (PPAs). However, interactome/association experiments are difficult to interpret considering the complexity and abundance of data that is generated. Although tools have been developed to quantitatively identify protein interactions/associations, there is still a pressing need for easy-to-use tools that allow users to contextualize their results. To address this, we developed CANVS, a computational pipeline that cleans, analyzes,and visualizes mass spectrometry-based interactome/association data. CANVS is wrapped as an interactive Shiny dashboard, allowing users to easily interface with the pipeline. With simple requirements, users can analyze complex experimental data and create PPI/A networks. The application integrates systems biology databases like BioGRID and CORUM to contextualize the results. Furthermore, CANVS features a Gene Ontology tool that allows users to identify relevant GO terms in their results and create visual networks with proteins associated with relevant GO terms. As examples, we recently used the analytical framework included in CANVS to study the PPI/A networks of DUSP7, which helped to define its regulation of ERK2 during mitosis and also to analyze the PPA networks of core spindle assembly checkpoint proteins. Overall, CANVS is an easy-to-use application that benefits all researchers, especially those who lack an established bioinformatic pipeline and are interested in studying interactome/association data. Additionally, we describe a supervised machine learning method that incorporatesannotated data from the contaminant repository for affinity purification data (CRAPome) that predicts contaminants in affinity and proximity purification data. The method involves first calculating amino acid content, sequence order, hydrophobicity and hydrophilicity from protein sequence. Then balancing data using data augmentation methods. Finally, measuring precision and accuracy using protein-protein interaction/association data. The results suggest that our supervised method can predict with 90% accuracy contaminants in protein-protein interaction/association data.
Author: Amika Sood
Author: Amika Sood
Author: Anna Panchenko
Author: M Michael Gromiha
Author: Brian Gregory Pierce
Author: 
Author: Robert Abel
Author: Matteo De Chiara
Author: Elizabeth Yuriev
Author: Joan Segura
Author: Erick Francisco Velasquez