Current Opinion in Structural Biology 
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Curr Opin Struct Biol. 2024 Apr 29;86:102823. doi: 10.1016/j.sbi.2024.102823. Online ahead of print.ABSTRACTSpecimen preparation is a critical but challenging step in high-resolution cryogenic electron microscopy (cryo-EM) structural analysis of macromolecules. In the past decade, graphene has gained much recognition as the supporting substrate to optimize cryo-EM specimen preparation. It improves macromolecule embedding in ice, reduces beam-induced motion, while imposing negligible background noise. Various types of graphene-coated cryo-EM grids were implemented to improve the robustness and efficiency of specimen prepara...
Source: Current Opinion in Structural Biology - April 30, 2024 Category: Biology Authors: Nan Liu Hong-Wei Wang Source Type: research
Multiscale biomolecular simulations in the exascale era
Curr Opin Struct Biol. 2024 Apr 29;86:102821. doi: 10.1016/j.sbi.2024.102821. Online ahead of print.ABSTRACTThe complexity of biological systems and processes, spanning molecular to macroscopic scales, necessitates the use of multiscale simulations to get a comprehensive understanding. Quantum mechanics/molecular mechanics (QM/MM) molecular dynamics (MD) simulations are crucial for capturing processes beyond the reach of classical MD simulations. The advent of exascale computing offers unprecedented opportunities for scientific exploration, not least within life sciences, where simulations are essential to unravel intricat...
Source: Current Opinion in Structural Biology - April 30, 2024 Category: Biology Authors: David Carrasco-Busturia Emiliano Ippoliti Simone Meloni Ursula Rothlisberger J ógvan Magnus Haugaard Olsen Source Type: research
Harnessing the 14-3-3 protein-protein interaction network
Curr Opin Struct Biol. 2024 Apr 28;86:102822. doi: 10.1016/j.sbi.2024.102822. Online ahead of print.ABSTRACTProtein-protein interactions (PPIs) play a critical role in cellular signaling and represent interesting targets for therapeutic intervention. 14-3-3 proteins integrate many signaling targets via PPIs and are frequently implicated in disease, making them intriguing drug targets. Here, we review the recent advances in the 14-3-3 field. It will discuss the roles 14-3-3 proteins play within the cell, elucidation of their expansive interactome, and the complex mechanisms that underpin their function. In addition, the rev...
Source: Current Opinion in Structural Biology - April 30, 2024 Category: Biology Authors: Paulo Pitasse-Santos Isaac Hewitt-Richards Malsha D Abeywickrama Wijewardana Sooriyaarachchi Richard G Doveston Source Type: research
Deep learning for low-data drug discovery: Hurdles and opportunities
Curr Opin Struct Biol. 2024 Apr 25;86:102818. doi: 10.1016/j.sbi.2024.102818. Online ahead of print.ABSTRACTDeep learning is becoming increasingly relevant in drug discovery, from de novo design to protein structure prediction and synthesis planning. However, it is often challenged by the small data regimes typical of certain drug discovery tasks. In such scenarios, deep learning approaches-which are notoriously 'data-hungry'-might fail to live up to their promise. Developing novel approaches to leverage the power of deep learning in low-data scenarios is sparking great attention, and future developments are expected to pr...
Source: Current Opinion in Structural Biology - April 26, 2024 Category: Biology Authors: Derek van Tilborg Helena Brinkmann Emanuele Criscuolo Luke Rossen R ıza Özçelik Francesca Grisoni Source Type: research
Deep learning for low-data drug discovery: Hurdles and opportunities
Curr Opin Struct Biol. 2024 Apr 25;86:102818. doi: 10.1016/j.sbi.2024.102818. Online ahead of print.ABSTRACTDeep learning is becoming increasingly relevant in drug discovery, from de novo design to protein structure prediction and synthesis planning. However, it is often challenged by the small data regimes typical of certain drug discovery tasks. In such scenarios, deep learning approaches-which are notoriously 'data-hungry'-might fail to live up to their promise. Developing novel approaches to leverage the power of deep learning in low-data scenarios is sparking great attention, and future developments are expected to pr...
Source: Current Opinion in Structural Biology - April 26, 2024 Category: Biology Authors: Derek van Tilborg Helena Brinkmann Emanuele Criscuolo Luke Rossen R ıza Özçelik Francesca Grisoni Source Type: research
Deep learning for low-data drug discovery: Hurdles and opportunities
Curr Opin Struct Biol. 2024 Apr 25;86:102818. doi: 10.1016/j.sbi.2024.102818. Online ahead of print.ABSTRACTDeep learning is becoming increasingly relevant in drug discovery, from de novo design to protein structure prediction and synthesis planning. However, it is often challenged by the small data regimes typical of certain drug discovery tasks. In such scenarios, deep learning approaches-which are notoriously 'data-hungry'-might fail to live up to their promise. Developing novel approaches to leverage the power of deep learning in low-data scenarios is sparking great attention, and future developments are expected to pr...
Source: Current Opinion in Structural Biology - April 26, 2024 Category: Biology Authors: Derek van Tilborg Helena Brinkmann Emanuele Criscuolo Luke Rossen R ıza Özçelik Francesca Grisoni Source Type: research
Generative artificial intelligence for de novo protein design
Curr Opin Struct Biol. 2024 Apr 24;86:102794. doi: 10.1016/j.sbi.2024.102794. Online ahead of print.ABSTRACTEngineering new molecules with desirable functions and properties has the potential to extend our ability to engineer proteins beyond what nature has so far evolved. Advances in the so-called 'de novo' design problem have recently been brought forward by developments in artificial intelligence. Generative architectures, such as language models and diffusion processes, seem adept at generating novel, yet realistic proteins that display desirable properties and perform specified functions. State-of-the-art design proto...
Source: Current Opinion in Structural Biology - April 25, 2024 Category: Biology Authors: Adam Winnifrith Carlos Outeiral Brian L Hie Source Type: research
Generative artificial intelligence for de novo protein design
Curr Opin Struct Biol. 2024 Apr 24;86:102794. doi: 10.1016/j.sbi.2024.102794. Online ahead of print.ABSTRACTEngineering new molecules with desirable functions and properties has the potential to extend our ability to engineer proteins beyond what nature has so far evolved. Advances in the so-called 'de novo' design problem have recently been brought forward by developments in artificial intelligence. Generative architectures, such as language models and diffusion processes, seem adept at generating novel, yet realistic proteins that display desirable properties and perform specified functions. State-of-the-art design proto...
Source: Current Opinion in Structural Biology - April 25, 2024 Category: Biology Authors: Adam Winnifrith Carlos Outeiral Brian L Hie Source Type: research
Confronting heterogeneity in cryogenic electron microscopy data: Innovative strategies and future perspectives with data-driven methods
Curr Opin Struct Biol. 2024 Apr 23;86:102815. doi: 10.1016/j.sbi.2024.102815. Online ahead of print.ABSTRACTThe surge in the influx of data from cryogenic electron microscopy (cryo-EM) experiments has intensified the demand for robust algorithms capable of autonomously managing structurally heterogeneous datasets. This presents a wealth of exciting opportunities from a data science viewpoint, inspiring the development of numerous innovative, application-specific methods, many of which leverage contemporary data-driven techniques. However, addressing the challenges posed by heterogeneous datasets remains a paramount yet unr...
Source: Current Opinion in Structural Biology - April 24, 2024 Category: Biology Authors: Dari Kimanius Johannes Schwab Source Type: research
Investigations of membrane protein interactions in cells using fluorescence microscopy
Curr Opin Struct Biol. 2024 Apr 21;86:102816. doi: 10.1016/j.sbi.2024.102816. Online ahead of print.ABSTRACTThe interactions between proteins in membranes govern many cellular functions. Our ability to probe for such interactions has greatly evolved in recent years due to the introduction of new fluorescence techniques. As a result, we currently have a choice of methods that can be used to assess the spatial distribution of a membrane protein, its association state, and the thermodynamic stability of the oligomers in the native milieu. These biophysical measurements have revealed new insights into important biological proc...
Source: Current Opinion in Structural Biology - April 22, 2024 Category: Biology Authors: Mahmoud Abouelkheir Tanaya Roy Mateusz A Krzyscik Ece Özdemir Kalina Hristova Source Type: research
Investigations of membrane protein interactions in cells using fluorescence microscopy
Curr Opin Struct Biol. 2024 Apr 21;86:102816. doi: 10.1016/j.sbi.2024.102816. Online ahead of print.ABSTRACTThe interactions between proteins in membranes govern many cellular functions. Our ability to probe for such interactions has greatly evolved in recent years due to the introduction of new fluorescence techniques. As a result, we currently have a choice of methods that can be used to assess the spatial distribution of a membrane protein, its association state, and the thermodynamic stability of the oligomers in the native milieu. These biophysical measurements have revealed new insights into important biological proc...
Source: Current Opinion in Structural Biology - April 22, 2024 Category: Biology Authors: Mahmoud Abouelkheir Tanaya Roy Mateusz A Krzyscik Ece Özdemir Kalina Hristova Source Type: research
How exascale computing can shape drug design: A perspective from multiscale QM/MM molecular dynamics simulations and machine learning-aided enhanced sampling algorithms
Curr Opin Struct Biol. 2024 Apr 16;86:102814. doi: 10.1016/j.sbi.2024.102814. Online ahead of print.ABSTRACTMolecular simulations are an essential asset in the first steps of drug design campaigns. However, the requirement of high-throughput limits applications mainly to qualitative approaches with low computational cost, but also low accuracy. Unlocking the potential of more rigorous quantum mechanical/molecular mechanics (QM/MM) models combined with molecular dynamics-based free energy techniques could have a tremendous impact. Indeed, these two relatively old techniques are emerging as promising methods in the field. Th...
Source: Current Opinion in Structural Biology - April 17, 2024 Category: Biology Authors: Giulia Rossetti Davide Mandelli Source Type: research
Apprehensions and emerging solutions in ML-based protein structure prediction
Curr Opin Struct Biol. 2024 Apr 16;86:102819. doi: 10.1016/j.sbi.2024.102819. Online ahead of print.ABSTRACTThe three-dimensional structure of proteins determines their function in vital biological processes. Thus, when the structure is known, the molecular mechanism of protein function can be understood in more detail and obtained information utilized in biotechnological, diagnostics, and therapeutic applications. Over the past five years, machine learning (ML)-based modeling has pushed protein structure prediction to the next level with AlphaFold in the front line, predicting the structure for hundreds of millions of pro...
Source: Current Opinion in Structural Biology - April 17, 2024 Category: Biology Authors: K äthe M Dahlström Tiina A Salminen Source Type: research
How exascale computing can shape drug design: A perspective from multiscale QM/MM molecular dynamics simulations and machine learning-aided enhanced sampling algorithms
Curr Opin Struct Biol. 2024 Apr 16;86:102814. doi: 10.1016/j.sbi.2024.102814. Online ahead of print.ABSTRACTMolecular simulations are an essential asset in the first steps of drug design campaigns. However, the requirement of high-throughput limits applications mainly to qualitative approaches with low computational cost, but also low accuracy. Unlocking the potential of more rigorous quantum mechanical/molecular mechanics (QM/MM) models combined with molecular dynamics-based free energy techniques could have a tremendous impact. Indeed, these two relatively old techniques are emerging as promising methods in the field. Th...
Source: Current Opinion in Structural Biology - April 17, 2024 Category: Biology Authors: Giulia Rossetti Davide Mandelli Source Type: research
Apprehensions and emerging solutions in ML-based protein structure prediction
Curr Opin Struct Biol. 2024 Apr 16;86:102819. doi: 10.1016/j.sbi.2024.102819. Online ahead of print.ABSTRACTThe three-dimensional structure of proteins determines their function in vital biological processes. Thus, when the structure is known, the molecular mechanism of protein function can be understood in more detail and obtained information utilized in biotechnological, diagnostics, and therapeutic applications. Over the past five years, machine learning (ML)-based modeling has pushed protein structure prediction to the next level with AlphaFold in the front line, predicting the structure for hundreds of millions of pro...
Source: Current Opinion in Structural Biology - April 17, 2024 Category: Biology Authors: K äthe M Dahlström Tiina A Salminen Source Type: research
