Integer linear programming for unsupervised training set selection in molecular machine learning by Matthieu Haeberle, Puck van Gerwen, Ruben Laplaza, Ksenia R Briling, Jan Weinreich, Friedrich Eisenbrand, Clémence Corminboeuf

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Cell type‐specific nuclear pores: a case in point for context‐dependent stoichiometry of molecular machines by Alessandro Ori, Niccolò Banterle, Murat Iskar, Amparo Andrés‐Pons, Claudia Escher, Huy Khanh Bui, Lenore Sparks, Victor Solis‐Mezarino, Oliver Rinner, Peer Bork, Edward A Lemke, Martin Beck

“…Abstract To understand the structure and function of large molecular machines, accurate knowledge of their stoichiometry is essential. …”
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Life is chemistry plus information by Richard Liangchen Wang

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MolAnchor method for explaining compound predictions based on substructures by Alec Lamens, Jürgen Bajorath

Subjects: “…Molecular machine learning…”
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pH‐Controlled Gliding Motions in Pillar[5]arene‐Containing Molecular Shuttles by Nihed Becharguia, Iwona Nierengarten, Alix Sournia‐Saquet, Emeric Wasielewski, Rym Abidi, Béatrice Delavaux‐Nicot, Jean‐François Nierengarten

Subjects: “…molecular machines…”
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Microbicidal mechanisms for light-activated molecular nanomachines in Mycobacterium smegmatis: A model for pathogenic bacteria by Thushara Galbadage, Dongdong Liu, James M. Tour, Jeffrey D. Cirillo, Richard S. Gunasekera

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The pathways of secretory cargo export at the endoplasmic reticulum by Vivek Malhotra

“…At the heart of this process is TANGO1, a key component of a molecular machine that works in concert with COPII proteins to construct export routes tailored to the size and quantity of secretory cargo.…”
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Sort & Slice: a simple and superior alternative to hash-based folding for extended-connectivity fingerprints by Markus Dablander, Thierry Hanser, Renaud Lambiotte, Garrett M. Morris

“…Abstract Extended-connectivity fingerprints (ECFPs) are a ubiquitous tool in current cheminformatics and molecular machine learning, and one of the most prevalent molecular feature extraction techniques used for chemical prediction. …”
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Chemical reaction engineering of nutritional phenomena in the human body by Xiao Dong Chen

“…This has revealed interesting aspects, highlighting the human body as a “molecular machine.” It is envisaged that the terms outlined here ought to be established in the future to improve human nutrition.…”
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Benchmarking uncertainty quantification for protein engineering. by Kevin P Greenman, Ava P Amini, Kevin K Yang

“…While studies have benchmarked a variety of deep learning uncertainty quantification (UQ) methods on standard and molecular machine-learning datasets, it is not clear if these results extend to protein datasets. …”
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Spatial mechanisms of quality control during chaperone-mediated assembly of the proteasome by Eshita Das, Linh Le, Vladyslava Sokolova, James D. Orth, Soyeon Park

“…Abstract Cellular protein degradation requires a complex molecular machine, the proteasome. To mitigate the fundamental challenge of assembling the 66-subunit proteasome, cells utilize dedicated chaperones to order subunit addition. …”
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Functional mapping of human dynamin-1-like GTPase domain based on x-ray structure analyses. by Julia Wenger, Eva Klinglmayr, Chris Fröhlich, Clarissa Eibl, Ana Gimeno, Manuel Hessenberger, Sandra Puehringer, Oliver Daumke, Peter Goettig

“…Human dynamin-1-like protein (DNM1L) is a GTP-driven molecular machine that segregates mitochondria and peroxisomes. …”
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CellDynaMo-stochastic reaction-diffusion-dynamics model: Application to search-and-capture process of mitotic spindle assembly. by Evgenii Kliuchnikov, Artem Zhmurov, Kenneth A Marx, Alex Mogilner, Valeri Barsegov

“…This computational infrastructure allows the simulation of hours of molecular machine dynamics in reasonable wall-clock time. …”
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Multi-channel learning for integrating structural hierarchies into context-dependent molecular representation by Yue Wan, Jialu Wu, Tingjun Hou, Chang-Yu Hsieh, Xiaowei Jia

“…However, the data scarcity, combined with the highly non-linear causal relationships between physicochemical and biological properties and conventional molecular featurization schemes, complicates the development of robust molecular machine learning models. Self-supervised learning (SSL) has emerged as a popular solution, utilizing large-scale, unannotated molecular data to learn a foundational representation of chemical space that might be advantageous for downstream tasks. …”
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The EMC acts as a chaperone for membrane proteins by Carolin J. Klose, Kevin M. Meighen-Berger, Martin Kulke, Marina Parr, Barbara Steigenberger, Martin Zacharias, Dmitrij Frishman, Matthias J. Feige

“…Taken together, our study provides detailed insights into an EMC chaperone function, further establishing the role of the EMC as a multifunctional molecular machine in membrane protein biogenesis.…”
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Structure of the herpes simplex virus portal-vertex. by Marion McElwee, Swetha Vijayakrishnan, Frazer Rixon, David Bhella

“…Our data provide new insights into the structure of a molecular machine critical to the biology of an important class of human pathogens.…”
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Staphylococcus aureus Survives with a Minimal Peptidoglycan Synthesis Machine but Sacrifices Virulence and Antibiotic Resistance. by Patricia Reed, Magda L Atilano, Renato Alves, Egbert Hoiczyk, Xinwei Sher, Nathalie T Reichmann, Pedro M Pereira, Terry Roemer, Sérgio R Filipe, José B Pereira-Leal, Petros Ligoxygakis, Mariana G Pinho

“…Many important cellular processes are performed by molecular machines, composed of multiple proteins that physically interact to execute biological functions. …”
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Deepmol: an automated machine and deep learning framework for computational chemistry by João Correia, João Capela, Miguel Rocha

“…Benchmarking on diverse datasets demonstrated its ability to deliver optimized pipelines and superior performance across various molecular machine-learning tasks.…”
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Comprehensive analysis of the type VI secretion system in Neisseria: identification, distribution, and evolutionary insights by Tingting Dong, Wenjing Yi, Meng Zhang, Ning Zhu, Jing Jie, Zhihan Peng, Lili Jiang, Chunyan Wang, Lei Song, Shucheng Hua, Qingtian Guan

“…The type VI secretion system (T6SS), a multifunctional molecular machine that facilitates the ability of gram-negative bacteria to deliver effectors for bacterial competition, virulence, and interaction with host cells, has been widely studied across various bacterial taxa. …”
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Mapping Hsp104 interactions using cross‐linking mass spectrometry by Kinga Westphal, Karolina Michalska, Andrzej Joachimiak, Lukasz A. Joachimiak

“…Molecular machines from the AAA+ (ATPases Associated with diverse cellular Activity) superfamily of protein disaggregases play important roles in protein folding, disaggregation and DNA processing. …”
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