scholarly journals Integrative modeling of membrane-associated protein assemblies

2020 ◽  
Vol 11 (1) ◽  
Author(s):  
Jorge Roel-Touris ◽  
Brian Jiménez-García ◽  
Alexandre M. J. J. Bonvin
Keyword(s):  
Artificial Intelligence ◽  
Membrane Proteins ◽  
Rigid Body ◽  
Structural Biology ◽  
State Of The Art ◽  
Protein Assemblies ◽  
Integrative Modeling ◽  
Rigid Body Docking ◽  
Shed Light ◽  
Computational Protocol

AbstractMembrane proteins are among the most challenging systems to study with experimental structural biology techniques. The increased number of deposited structures of membrane proteins has opened the route to modeling their complexes by methods such as docking. Here, we present an integrative computational protocol for the modeling of membrane-associated protein assemblies. The information encoded by the membrane is represented by artificial beads, which allow targeting of the docking toward the binding-competent regions. It combines efficient, artificial intelligence-based rigid-body docking by LightDock with a flexible final refinement with HADDOCK to remove potential clashes at the interface. We demonstrate the performance of this protocol on eighteen membrane-associated complexes, whose interface lies between the membrane and either the cytosolic or periplasmic regions. In addition, we provide a comparison to another state-of-the-art docking software, ZDOCK. This protocol should shed light on the still dark fraction of the interactome consisting of membrane proteins.

scholarly journals Integrative Modeling of Membrane-associated Protein Assemblies

2020 ◽  
Author(s):  
Jorge Roel-Touris ◽  
Brian Jiménez-García ◽  
Alexandre M.J.J. Bonvin
Keyword(s):  
Membrane Proteins ◽  
Coarse Grained ◽  
Protein Assemblies ◽  
Topological Information ◽  
Modeling Process ◽  
Cryo Electron Microscopy ◽  
Docking Protocol ◽  
Rigid Body Docking ◽  
Shed Light

AbstractHistorically, membrane protein systems have been considered as one of the most challenging systems to study with experimental structural biology techniques. Over the past years, increased number of experimental structures of membrane proteins have become available thanks in particular to advances in solid-state NMR spectroscopy and cryo-electron microscopy. This has opened the route to modeling the complexes that those membrane proteins form by methods such as docking. Most approaches developed to date are, however, not capable of incorporating the topological information provided by the membrane into the modeling process. Here, we present an integrative computational protocol for the modeling of membrane-associated protein assemblies, specifically complexes consisting of a membrane-embedded protein and a soluble partner. It combines efficient, artificial intelligence-based rigid-body docking by LightDock with a flexible final refinement with HADDOCK to remove potential clashes at the interface. We make use of an equilibrated coarse-grained lipid bilayer to represent the information encoded in the membrane in the form of artificial beads, which allows to target the docking towards the binding-competent regions. We demonstrate the performance of this membrane-driven protocol on eighteen membrane-associated complexes, whose interface lies between the membrane and either the cytosolic or periplasmic regions. In addition, we evaluate how different membrane definitions impact the performance of the docking protocol and provide a comparison, in terms of success rate, to another state-of-the-art docking software, ZDOCK. Finally, we discuss the quality of the generated models and propose possible future developments. Our membrane docking protocol should allow to shed light on the still rather dark fraction of the interactome consisting of membrane proteins.

scholarly journals Reactive Balance Control for Legged Robots under Visco-Elastic Contacts

2020 ◽  
Vol 11 (1) ◽  
pp. 353
Author(s):  
Thomas Flayols ◽  
Andrea Del Prete ◽  
Majid Khadiv ◽  
Nicolas Mansard ◽  
Ludovic Righetti
Keyword(s):  
Inverse Dynamics ◽  
State Of The Art ◽  
Balance Control ◽  
Contact Stiffness ◽  
Poor Performance ◽  
Admittance Control ◽  
Inverse Dynamics Control ◽  
Rigid Contact ◽  
Reactive Balance ◽  
Shed Light

Contacts between robots and environment are often assumed to be rigid for control purposes. This assumption can lead to poor performance when contacts are soft and/or underdamped. However, the problem of balancing on soft contacts has not received much attention in the literature. This paper presents two novel approaches to control a legged robot balancing on visco-elastic contacts, and compares them to other two state-of-the-art methods. Our simulation results show that performance heavily depends on the contact stiffness and the noises/uncertainties introduced in the simulation. Briefly, the two novel controllers performed best for soft/medium contacts, whereas “inverse-dynamics control under rigid-contact assumptions” was the best one for stiff contacts. Admittance control was instead the most robust, but suffered in terms of performance. These results shed light on this challenging problem, while pointing out interesting directions for future investigation.

scholarly journals Insertion of plastidic β-barrel proteins into the outer envelopes of plastids involves an intermembrane space intermediate formed with Toc75-V/OEP80

2021 ◽  
Author(s):  
Lucia E Gross ◽  
Anna Klinger ◽  
Nicole Spies ◽  
Theresa Ernst ◽  
Nadine Flinner ◽  
...  
Keyword(s):  
Membrane Proteins ◽  
Protein Import ◽  
Membrane Insertion ◽  
Intermembrane Space ◽  
Envelope Membrane ◽  
Outer Envelope ◽  
Pea Proteins ◽  
Outer Envelope Membrane ◽  
Correct Topology ◽  
Shed Light

Abstract The insertion of organellar membrane proteins with the correct topology requires the following: First, the proteins must contain topogenic signals for translocation across and insertion into the membrane. Second, proteinaceous complexes in the cytoplasm, membrane, and lumen of organelles are required to drive this process. Many complexes required for the intracellular distribution of membrane proteins have been described, but the signals and components required for the insertion of plastidic β-barrel-type proteins into the outer membrane are largely unknown. The discovery of common principles is difficult, as only a few plastidic β-barrel proteins exist. Here, we provide evidence that the plastidic outer envelope β-barrel proteins OEP21, OEP24, and OEP37 from pea (Pisum sativum) and Arabidopsis thaliana contain information defining the topology of the protein. The information required for translocation of pea proteins across the outer envelope membrane is present within the six N-terminal β-strands. This process requires the action of TOC (translocon of the outer chloroplast membrane). After translocation into the intermembrane space, β-barrel proteins interact with TOC75-V, as exemplified by OEP37 and P39, and are integrated into the membrane. The membrane insertion of plastidic β-barrel proteins is affected by mutation of the last β-strand, suggesting that this strand contributes to the insertion signal. These findings shed light on the elements and complexes involved in plastidic β-barrel protein import.

scholarly journals A Survey on Bias and Fairness in Machine Learning

2021 ◽  
Vol 54 (6) ◽  
pp. 1-35
Author(s):  
Ninareh Mehrabi ◽  
Fred Morstatter ◽  
Nripsuta Saxena ◽  
Kristina Lerman ◽  
Aram Galstyan
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Deep Learning ◽  
Real World ◽  
State Of The Art ◽  
Future Directions ◽  
Discriminatory Behavior ◽  
Real World Applications ◽  
Near Future ◽  
Different Sources

With the widespread use of artificial intelligence (AI) systems and applications in our everyday lives, accounting for fairness has gained significant importance in designing and engineering of such systems. AI systems can be used in many sensitive environments to make important and life-changing decisions; thus, it is crucial to ensure that these decisions do not reflect discriminatory behavior toward certain groups or populations. More recently some work has been developed in traditional machine learning and deep learning that address such challenges in different subdomains. With the commercialization of these systems, researchers are becoming more aware of the biases that these applications can contain and are attempting to address them. In this survey, we investigated different real-world applications that have shown biases in various ways, and we listed different sources of biases that can affect AI applications. We then created a taxonomy for fairness definitions that machine learning researchers have defined to avoid the existing bias in AI systems. In addition to that, we examined different domains and subdomains in AI showing what researchers have observed with regard to unfair outcomes in the state-of-the-art methods and ways they have tried to address them. There are still many future directions and solutions that can be taken to mitigate the problem of bias in AI systems. We are hoping that this survey will motivate researchers to tackle these issues in the near future by observing existing work in their respective fields.

scholarly journals Artificial intelligence and machine learning in design of mechanical materials

2021 ◽  
Author(s):  
Kai Guo ◽  
Zhenze Yang ◽  
Chi-Hua Yu ◽  
Markus J. Buehler
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
State Of The Art ◽  
The State

This review revisits the state of the art of research efforts on the design of mechanical materials using machine learning.

Automatic Story Generation

2021 ◽  
Vol 54 (5) ◽  
pp. 1-38
Author(s):  
Arwa I. Alhussain ◽  
Aqil M. Azmi
Keyword(s):  
Artificial Intelligence ◽  
Automatic Generation ◽  
Evaluation Methods ◽  
Extensive Study ◽  
Computational Creativity ◽  
Story Generation ◽  
To Receive ◽  
Shed Light

Computational generation of stories is a subfield of computational creativity where artificial intelligence and psychology intersect to teach computers how to mimic humans’ creativity. It helps generate many stories with minimum effort and customize the stories for the users’ education and entertainment needs. Although the automatic generation of stories started to receive attention many decades ago, advances in this field to date are less than expected and suffer from many limitations. This survey presents an extensive study of research in the area of non-interactive textual story generation, as well as covering resources, corpora, and evaluation methods that have been used in those studies. It also shed light on factors of story interestingness.

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