scholarly journals The seesaw between normal function and protein aggregation: How functional interactions may increase protein solubility

BioEssays ◽  
2021 ◽  
pp. 2100031
Author(s):  
Piero Andrea Temussi ◽  
Gian Gaetano Tartaglia ◽  
Annalisa Pastore
Keyword(s):  
Protein Aggregation ◽  
Protein Solubility ◽  
Normal Function ◽  
Functional Interactions

Prions: Protein Aggregation and Infectious Diseases

2009 ◽  
Vol 89 (4) ◽  
pp. 1105-1152 ◽  
Author(s):  
Adriano Aguzzi ◽  
Anna Maria Calella
Keyword(s):  
Protein Aggregation ◽  
Prion Diseases ◽  
Physiological Role ◽  
Infectious Agent ◽  
Normal Function ◽  
Cellular Prion Protein ◽  
Transmissible Spongiform Encephalopathies ◽  
Pathological Features ◽  
Spongiform Encephalopathies

Transmissible spongiform encephalopathies (TSEs) are inevitably lethal neurodegenerative diseases that affect humans and a large variety of animals. The infectious agent responsible for TSEs is the prion, an abnormally folded and aggregated protein that propagates itself by imposing its conformation onto the cellular prion protein (PrPC) of the host. PrPCis necessary for prion replication and for prion-induced neurodegeneration, yet the proximal causes of neuronal injury and death are still poorly understood. Prion toxicity may arise from the interference with the normal function of PrPC, and therefore, understanding the physiological role of PrPCmay help to clarify the mechanism underlying prion diseases. Here we discuss the evolution of the prion concept and how prion-like mechanisms may apply to other protein aggregation diseases. We describe the clinical and the pathological features of the prion diseases in human and animals, the events occurring during neuroinvasion, and the possible scenarios underlying brain damage. Finally, we discuss potential antiprion therapies and current developments in the realm of prion diagnostics.

scholarly journals A3D 2.0 update for the prediction and optimization of protein solubility

2021 ◽  
Author(s):  
Jordi Pujols ◽  
Valentín Iglesias ◽  
Jaime Santos ◽  
Aleksander Kuriata ◽  
Sebastian Kmiecik ◽  
...  
Keyword(s):  
Protein Aggregation ◽  
Protein Solubility ◽  
Protein Sequences ◽  
Cost Effective ◽  
Computational Pipeline ◽  
Protein Surfaces ◽  
Computational Approaches ◽  
Aggregation Propensity ◽  
Restful Service ◽  
Protein Redesign

AbstractProtein aggregation propensity is a property imprinted in protein sequences and structures, being associated with the onset of human diseases and limiting the implementation of protein-based biotherapies. Computational approaches stand as cost-effective alternatives for reducing protein aggregation and increasing protein solubility. AGGRESCAN 3D (A3D) is a structure-based predictor of aggregation that takes into account the conformational context of a protein, aiming to identify aggregation-prone regions exposed in protein surfaces. Here we inspect the updated 2.0 version of the algorithm, which extends the application of A3D to previously inaccessible proteins and incorporates new modules to assist protein redesign. Among these features, the new server includes stability calculations and the possibility to optimize protein solubility using an experimentally validated computational pipeline. Finally, we employ defined examples to navigate the A3D RESTful service, a routine to handle extensive protein collections. Altogether, this work is conceived to train and assist A3D non-experts in the study of aggregation-prone regions and protein solubility redesign.

scholarly journals A3D Database: Structure-based Protein Aggregation Predictions for the Human Proteome

2021 ◽  
Author(s):  
Aleksandra Elzbieta Badaczewska-Dawid ◽  
Javier Garcia-Pardo ◽  
Aleksander Kuriata ◽  
Jordi Pujols ◽  
Salvador Ventura ◽  
...  
Keyword(s):  
Protein Aggregation ◽  
Rational Design ◽  
Structural Information ◽  
Protein Solubility ◽  
Protein Structures ◽  
Human Proteome ◽  
Human Protein ◽  
Database Structure ◽  
Human Disorders ◽  
User Friendly

Motivation: Protein aggregation is associated with highly debilitating human disorders and constitutes a major bottleneck for producing therapeutic proteins. Our knowledge of the human protein structures repertoire has dramatically increased with the recent development of the AlphaFold (AF) deep-learning method. This structural information can be used to understand better protein aggregation properties and the rational design of protein solubility. This article uses the Aggrescan3D (A3D) tool to compute the structure-based aggregation predictions for the human proteome and make the predictions available in a database form. Results: Here, we present the A3D Database, in which we analyze the AF-predicted human protein structures (for over 17 thousand non-membrane proteins) in terms of their aggregation properties using the A3D tool. Each entry of the A3D Database provides a detailed analysis of the structure-based aggregation propensity computed with A3D. The A3D Database implements simple but useful graphical tools for visualizing and interpreting protein structure datasets. We discuss case studies illustrating how the database could be used to analyze physiologically relevant proteins. Furthermore, the database enables testing the influence of user-selected mutations on protein solubility and stability, all integrated into a user-friendly interface. Availability and implementation: A3D Database is freely available at: http://biocomp.chem.uw.edu.pl/A3D2/hproteome

scholarly journals Advanced glycation end products (AGEs), protein aggregation and their cross talk: new insight in tumorigenesis

Glycobiology ◽  
2019 ◽  
Vol 30 (1) ◽  
pp. 2-18
Author(s):  
Ejazul Haque ◽  
Mohd Kamil ◽  
Adria Hasan ◽  
Safia Irfan ◽  
Saba Sheikh ◽  
...  
Keyword(s):  
Protein Aggregation ◽  
Advanced Glycation End Products ◽  
Cross Talk ◽  
Structural Changes ◽  
Current Knowledge ◽  
Normal Function ◽  
Protein Glycation ◽  
Advanced Glycation ◽  
Glycation End Products ◽  
End Products

Abstract Protein glycation and protein aggregation are two distinct phenomena being observed in cancer cells as factors promoting cancer cell viability. Protein aggregation is an abnormal interaction between proteins caused as a result of structural changes in them after any mutation or environmental assault. Protein aggregation is usually associated with neurodegenerative diseases like Alzheimer’s and Parkinson’s, but of late, research findings have shown its association with the development of different cancers like lung, breast and ovarian cancer. On the contrary, protein glycation is a cascade of irreversible nonenzymatic reaction of reducing sugar with the amino group of the protein resulting in the modification of protein structure and formation of advanced glycation end products (AGEs). These AGEs are reported to obstruct the normal function of proteins. Lately, it has been reported that protein aggregation occurs as a result of AGEs. This aggregation of protein promotes the transformation of healthy cells to neoplasia leading to tumorigenesis. In this review, we underline the current knowledge of protein aggregation and glycation along with the cross talk between the two, which may eventually lead to the development of cancer.

Aggrescan3D standalone package for structure-based prediction of protein aggregation properties

2019 ◽  
Vol 35 (19) ◽  
pp. 3834-3835 ◽  
Author(s):  
Aleksander Kuriata ◽  
Valentin Iglesias ◽  
Mateusz Kurcinski ◽  
Salvador Ventura ◽  
Sebastian Kmiecik
Keyword(s):  
Protein Aggregation ◽  
Rational Design ◽  
Protein Solubility ◽  
Automated Analysis ◽  
Computational Framework ◽  
Computational Tools ◽  
Non Profit ◽  
Recent Experimental Study ◽  
The Impact ◽  
Python Package

Abstract Summary Aggrescan3D (A3D) standalone is a multiplatform Python package for structure-based prediction of protein aggregation properties and rational design of protein solubility. A3D allows the re-design of protein solubility by combining structural aggregation propensity and stability predictions, as demonstrated by a recent experimental study. It also enables predicting the impact of protein conformational fluctuations on the aggregation properties. The standalone A3D version is an upgrade of the original web server implementation—it introduces a number of customizable options, automated analysis of multiple mutations and offers a flexible computational framework for merging it with other computational tools. Availability and implementation A3D standalone is distributed under the MIT license, which is free for academic and non-profit users. It is implemented in Python. The A3D standalone source code, wiki with documentation and examples of use, and installation instructions for Linux, macOS and Windows are available in the A3D standalone repository at https://bitbucket.org/lcbio/aggrescan3d.

The two faces of Janus: functional interactions and protein aggregation

2012 ◽  
Vol 22 (1) ◽  
pp. 30-37 ◽  
Author(s):  
Annalisa Pastore ◽  
Piero Andrea Temussi
Keyword(s):  
Protein Aggregation ◽  
Functional Interactions

scholarly journals Effect of Protein Oxidation on the Conformational Properties of Peanut Protein Isolate

2013 ◽  
Vol 2013 ◽  
pp. 1-6 ◽  
Author(s):  
Lin Ye ◽  
Yu Liao ◽  
Mouming Zhao ◽  
Weizheng Sun
Keyword(s):  
Protein Aggregation ◽  
Conformational Changes ◽  
Protein Oxidation ◽  
Protein Solubility ◽  
Surface Hydrophobicity ◽  
Protein Isolate ◽  
Peanut Protein ◽  
Peroxyl Radicals ◽  
Peanut Protein Isolate ◽  
Conformational Properties

Peanut protein isolate (PPI) was oxidized by peroxyl radicals derived from 2,2′-azobis (2-amidinopropane) dihydrochloride (AAPH), and the conformational properties of oxidized PPI were investigated. Oxidation of PPI resulted in gradual carbonyl generation and free sulfydryl group degradation. The analysis of the maximum emission wavelength indicated change in the tertiary conformation of PPI after oxidation. Lower level oxidation could generate soluble protein aggregates with more flexible structure, while higher level oxidation would induce the formation of insoluble aggregates. Result from dynamic light scattering (DLS) and protein solubility showed that protein aggregation was correlated with protein surface hydrophobicity, indicating that protein oxidation and heat treatment could induce protein aggregation, leading to PPI conformational changes.

scholarly journals Recurring functional interactions predict network architecture of interictal and ictal states in neocortical epilepsy

2016 ◽  
Author(s):  
Ankit N. Khambhati ◽  
Danielle S. Bassett ◽  
Brian S. Oommen ◽  
Stephanie H. Chen ◽  
Timothy H. Lucas ◽  
...  
Keyword(s):  
Network Architecture ◽  
Brain Regions ◽  
Normal Function ◽  
Machine Learning Technique ◽  
Functional Interactions ◽  
Human Epilepsy ◽  
Spontaneous Seizures ◽  
Learning Technique ◽  
Neocortical Epilepsy ◽  
Intracranial Recordings

AbstractHuman epilepsy patients suffer from spontaneous seizures, which originate in brain regions that also subserve normal function. Prior studies demonstrate focal, neocortical epilepsy is associated with dysfunction, several hours before seizures. How does the epileptic network perpetuate dysfunction during baseline periods? To address this question, we developed an unsupervised machine learning technique to disentangle patterns of functional interactions between brain regions, or subgraphs, from dynamic functional networks constructed from approximately 100 hours of intracranial recordings in each of 22 neocortical epilepsy patients. Using this approach, we found: (i) subgraphs from ictal (seizure) and interictal (baseline) epochs are topologically similar, (ii) interictal subgraph topology and dynamics can predict brain regions that generate seizures, and (iii) subgraphs undergo slower and more coordinated fluctuations during ictal epochs compared to interictal epochs. Our observations suggest that the epileptic network drives dysfunction by controlling dynamics of functional interactions between brain regions that generate seizures and those that underlie normal function.

An Ultra-Structural Study of Human Melanoma in Vivo and Vitro

1976 ◽  
Vol 34 ◽  
pp. 258-259
Author(s):  
James R. Gaylor ◽  
Fredda Schafer ◽  
Robert E. Nordquist
Keyword(s):  
Endoplasmic Reticulum ◽  
Golgi Apparatus ◽  
Protein Aggregation ◽  
Structural Study ◽  
Human Melanoma ◽  
Protein Matrix ◽  
Early Form ◽  
Endoplasmic Reticulum Protein ◽  
Mitochondrial Origin

Several theories on the origin of the melanosome exist. These include the Golgi origin theory, in which a tyrosinase-rich protein is "packaged" by the Golgi apparatus, thus forming the early form of the melanosome. A second theory postulates a mitochondrial origin of melanosomes. Its author contends that the melanosome is a modified mitochondria which acquires melanin during its development. A third theory states that a pre-melanosome is formed in the smooth or rough endoplasmic reticulum. Protein aggregation is suggested by one author as a possible source of the melanosome. This fourth theory postulates that the melanosome originates when the protein products of several genetic loci aggregate in the cytoplasm of the melanocyte. It is this protein matrix on which the melanin is deposited. It was with these theories in mind that this project was undertaken.

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