Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

A protein folding robot driven by a self-taught agent.

ABSTRACT: This paper presents a computer simulation of a virtual robot that behaves as a peptide chain of the Hemagglutinin-Esterase protein (HEs) from human coronavirus. The robot can learn efficient protein folding policies by itself and then use them to solve HEs folding episodes. The proposed robotic unfolded structure inhabits a dynamic environment and is driven by a self-taught neural agent. The neural agent can read sensors and control the angles and interactions between individual amino acids. During the training phase, the agent uses reinforcement learning to explore new folding forms that conduce toward more significant rewards. The memory of the agent is implemented with neural networks. These neural networks are noise-balanced trained to satisfy the look for future conditions required by the Bellman equation. In the operating phase, the components merge into a wise up protein folding robot with look-ahead capacities, which consistently solves a section of the HEs protein.

SUBMITTER: Chang O

PROVIDER: S-EPMC7834057 | biostudies-literature | 2020 Dec

REPOSITORIES: biostudies-literature

ACCESS DATA

Json Xml

Publications

A protein folding robot driven by a self-taught agent.

Chang Oscar O Gonzales-Zubiate Fernando A FA Zhinin-Vera Luis L Valencia-Ramos Rafael R Pineda Israel I Diaz-Barrios Antonio A

Bio Systems 20201229

This paper presents a computer simulation of a virtual robot that behaves as a peptide chain of the Hemagglutinin-Esterase protein (HEs) from human coronavirus. The robot can learn efficient protein folding policies by itself and then use them to solve HEs folding episodes. The proposed robotic unfolded structure inhabits a dynamic environment and is driven by a self-taught neural agent. The neural agent can read sensors and control the angles and interactions between individual amino acids. Dur ...[more]

PMID: 33358827

Similar Datasets

Disulfide driven folding for a conditionally disordered protein.

Project description:Conditionally disordered proteins are either ordered or disordered depending on the environmental context. The substrates of the mitochondrial intermembrane space (IMS) oxidoreductase Mia40 are synthesized on cytosolic ribosomes and diffuse as intrinsically disordered proteins to the IMS, where they fold into their functional conformations; behaving thus as conditionally disordered proteins. It is not clear how the sequences of these polypeptides encode at the same time for their ability to adopt a folded structure and to remain unfolded. Here we characterize the disorder-to-order transition of a Mia40 substrate, the human small copper chaperone Cox17. Using an integrated real-time approach, including chromatography, fluorescence, CD, FTIR, SAXS, NMR, and MS analysis, we demonstrate that in this mitochondrial protein, the conformational switch between disordered and folded states is controlled by the formation of a single disulfide bond, both in the presence and in the absence of Mia40. We provide molecular details on how the folding of a conditionally disordered protein is tightly regulated in time and space, in such a way that the same sequence is competent for protein translocation and activity.

| S-EPMC5717278 | biostudies-literature

Folding driven self-assembly of a stimuli-responsive peptide-hyaluronan hybrid hydrogel.

Project description:Protein-metal ion interactions are ubiquitous in nature and can be utilized for controlling the self-assembly of complex supramolecular architectures and materials. Here, a tunable supramolecular hydrogel is described, obtained by self-assembly of a Zn2+-responsive peptide-hyaluronic acid hybrid synthesized using strain promoted click chemistry. Addition of Zn2+ triggers folding of the peptides into a helix-loop-helix motif and dimerization into four-helix bundles, resulting in hydrogelation. Removal of the Zn2+ by chelators results in rapid hydrogel disassembly. Degradation of the hydrogels can also be time-programed by encapsulation of a hydrolyzing enzyme within the gel, offering multiple possibilities for modulating materials properties and release of encapsulated species. The hydrogel further shows potential antioxidant properties when evaluated using an in vitro model for reactive oxygen species.

| S-EPMC5539109 | biostudies-literature

Soft Self-Healing Robot Driven by New Micro Two-Way Shape Memory Alloy Spring.

Project description:Soft robotic bodies are susceptible to mechanical fatigue, punctures, electrical breakdown, and aging, which can result in the degradation of performance or unexpected failure. To overcome these challenges, a soft self-healing robot is created using a thermoplastic methyl thioglycolate-modified styrene-butadiene-styrene (MG-SBS) elastomer tube fabricated by melt-extrusion, to allow the robot to self-heal autonomously at room temperature. After repeated damage and being separated into several parts, the robot is able to heal its stiffness and elongation to break to enable almost complete recovery of robot performance after being allowed to heal at room temperature for 24 h. The self-healing capability of the robot is examined across the material scale to robot scale by detailed investigations of the healing process, healing efficiency, mechanical characterization of the robot, and assessment of dynamic performance before and after healing. The self-healing robot is driven by a new micro two-way shape-memory alloy (TWSMA) spring actuator which achieved a crawling speed of 21.6 cm/min, equivalent to 1.57 body length per minute. An analytical model of the robot is created to understand the robot dynamics and to act as an efficient tool for self-healing robot design and optimization. This work therefore provides a new methodology to create efficient, robust, and damage-tolerant soft robots.

| S-EPMC10787064 | biostudies-literature

On the benefits of self-taught learning for brain decoding.

Project description:ContextWe study the benefits of using a large public neuroimaging database composed of functional magnetic resonance imaging (fMRI) statistic maps, in a self-taught learning framework, for improving brain decoding on new tasks. First, we leverage the NeuroVault database to train, on a selection of relevant statistic maps, a convolutional autoencoder to reconstruct these maps. Then, we use this trained encoder to initialize a supervised convolutional neural network to classify tasks or cognitive processes of unseen statistic maps from large collections of the NeuroVault database.ResultsWe show that such a self-taught learning process always improves the performance of the classifiers, but the magnitude of the benefits strongly depends on the number of samples available both for pretraining and fine-tuning the models and on the complexity of the targeted downstream task.ConclusionThe pretrained model improves the classification performance and displays more generalizable features, less sensitive to individual differences.

| S-EPMC10155221 | biostudies-literature

Non-Equilibrium Protein Folding and Activation by ATP-Driven Chaperones.

Project description:Recent experimental studies suggest that ATP-driven molecular chaperones can stabilize protein substrates in their native structures out of thermal equilibrium. The mechanism of such non-equilibrium protein folding is an open question. Based on available structural and biochemical evidence, I propose here a unifying principle that underlies the conversion of chemical energy from ATP hydrolysis to the conformational free energy associated with protein folding and activation. I demonstrate that non-equilibrium folding requires the chaperones to break at least one of four symmetry conditions. The Hsp70 and Hsp90 chaperones each break a different subset of these symmetries and thus they use different mechanisms for non-equilibrium protein folding. I derive an upper bound on the non-equilibrium elevation of the native concentration, which implies that non-equilibrium folding only occurs in slow-folding proteins that adopt an unstable intermediate conformation in binding to ATP-driven chaperones. Contrary to the long-held view of Anfinsen's hypothesis that proteins fold to their conformational free energy minima, my results predict that some proteins may fold into thermodynamically unstable native structures with the assistance of ATP-driven chaperones, and that the native structures of some chaperone-dependent proteins may be shaped by their chaperone-mediated folding pathways.

| S-EPMC9221429 | biostudies-literature

Folding and self-assembly of a small protein complex.

Project description:The synthetic homotetrameric ββα (BBAT1) protein possesses a stable quaternary structure with a ββα fold. Because of its small size (a total of 84 residues), the homotetramer is an excellent model system with which to study the self-assembly and protein-protein interactions. We find from replica exchange molecular dynamics simulations with the coarse-grain UNRES force field that the folding and association pathway consists of three well-separated steps, where that association to a tetramer precedes and facilitates folding of the four chains. At room temperature the tetramer exists in an ensemble of diverse structures. The crystal structure becomes energetically favored only when the molecule is put in a dense and crystal-like environment. The observed picture of folding promoted by association may mirror the mechanism according to which intrinsically unfolded proteins assume their functional structure.

| S-EPMC3771543 | biostudies-literature

Affect-Driven Learning of Robot Behaviour for Collaborative Human-Robot Interactions.

Project description:Collaborative interactions require social robots to share the users' perspective on the interactions and adapt to the dynamics of their affective behaviour. Yet, current approaches for affective behaviour generation in robots focus on instantaneous perception to generate a one-to-one mapping between observed human expressions and static robot actions. In this paper, we propose a novel framework for affect-driven behaviour generation in social robots. The framework consists of (i) a hybrid neural model for evaluating facial expressions and speech of the users, forming intrinsic affective representations in the robot, (ii) an Affective Core, that employs self-organising neural models to embed behavioural traits like patience and emotional actuation that modulate the robot's affective appraisal, and (iii) a Reinforcement Learning model that uses the robot's appraisal to learn interaction behaviour. We investigate the effect of modelling different affective core dispositions on the affective appraisal and use this affective appraisal as the motivation to generate robot behaviours. For evaluation, we conduct a user study (n = 31) where the NICO robot acts as a proposer in the Ultimatum Game. The effect of the robot's affective core on its negotiation strategy is witnessed by participants, who rank a patient robot with high emotional actuation higher on persistence, while an impatient robot with low emotional actuation is rated higher on its generosity and altruistic behaviour.

| S-EPMC8898942 | biostudies-literature

Secretion of the Intimin Passenger Domain Is Driven by Protein Folding.

Project description:Intimin is an essential adhesin of attaching and effacing organisms such as entropathogenic Escherichia coli It is also the prototype of type Ve secretion or inverse autotransport, where the extracellular C-terminal region or passenger is exported with the help of an N-terminal transmembrane ?-barrel domain. We recently reported a stalled secretion intermediate of intimin, where the passenger is located in the periplasm but the ?-barrel is already inserted into the membrane. Stalling of this mutant is due to the insertion of an epitope tag at the very N terminus of the passenger. Here, we examined how this insertion disrupts autotransport and found that it causes misfolding of the N-terminal immunoglobulin (Ig)-like domain D00. We could also stall the secretion by making an internal deletion in D00, and introducing the epitope tag into the second Ig-like domain, D0, also resulted in reduced passenger secretion. In contrast to many classical autotransporters, where a proximal folding core in the passenger is required for secretion, the D00 domain is dispensable, as the passenger of an intimin mutant lacking D00 entirely is efficiently exported. Furthermore, the D00 domain is slightly less stable than the D0 and D1 domains, unfolding at ?200 piconewtons (pN) compared with ?250 pN for D0 and D1 domains as measured by atomic force microscopy. Our results support a model where the secretion of the passenger is driven by sequential folding of the extracellular Ig-like domains, leading to vectorial transport of the passenger domain across the outer membrane in an N to C direction.

| S-EPMC5025694 | biostudies-literature

Cell origami: self-folding of three-dimensional cell-laden microstructures driven by cell traction force.

Project description:This paper describes a method of generating three-dimensional (3D) cell-laden microstructures by applying the principle of origami folding technique and cell traction force (CTF). We harness the CTF as a biological driving force to fold the microstructures. Cells stretch and adhere across multiple microplates. Upon detaching the microplates from a substrate, CTF causes the plates to lift and fold according to a prescribed pattern. This self-folding technique using cells is highly biocompatible and does not involve special material requirements for the microplates and hinges to induce folding. We successfully produced various 3D cell-laden microstructures by just changing the geometry of the patterned 2D plates. We also achieved mass-production of the 3D cell-laden microstructures without causing damage to the cells. We believe that our methods will be useful for biotechnology applications that require analysis of cells in 3D configurations and for self-assembly of cell-based micro-medical devices.

| S-EPMC3521028 | biostudies-literature

Pulse-driven robot: Motion via solitary waves.

Project description:The unique properties of nonlinear waves have been recently exploited to enable a wide range of applications, including impact mitigation, asymmetric transmission, switching, and focusing. Here, we demonstrate that the propagation of nonlinear waves can be as well harnessed to make flexible structures crawl. By combining experimental and theoretical methods, we show that such pulse-driven locomotion reaches a maximum efficiency when the initiated pulses are solitons and that our simple machine can move on a wide range of surfaces and even steer. Our study expands the range of possible applications of nonlinear waves and demonstrates that they offer a new platform to make flexible machines to move.

| S-EPMC7195187 | biostudies-literature

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data