Emerging Protein Targets for Anticancer Metallodrugs: Inhibition of Thioredoxin Reductase and Cathepsin B by Antitumor Ruthenium(II)-Arene Compounds

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The phenomenon of allostery, a general property in proteins that has been heralded as "the second secret of life" remains elusive to our understanding and even more challenging to incorporate into protein design. One example of allosteric proteins with gre ...

Cysteine cathepsins proteases are enzymes that play essential physiological roles, but their activity is also associated to different aspects of cancer progression and to the development of other diseases. Therefore, cysteine cathepsins are relevant and pr ...

This data set contains the data collected during the FNS project Green Piezo (Grant no. 179064) in association with the recent publication entitled “3D printing of customizable transient bioelectronics and sensors”. This work aims to study and demonstrate ...

This document contains all the data and the details of the analysis used in the manuscript titled " Control of Ge island coalescence for the formation of nanowires on silicon." https://doi.org/10.1039/D3NH00573A ...

This repository contains microphysics routines, scripts, and processed data from the Weather Research and Forecasting (WRF) model simulations presented in the paper "RaFSIP: Parameterizing ice multiplication in models using a machine learning approach", by ...

Machine learning (ML) enables artificial intelligent (AI) agents to learn autonomously from data obtained from their environment to perform tasks. Modern ML systems have proven to be extremely effective, reaching or even exceeding human intelligence. Altho ...

We developed a rational approach to design peptide-based covalent inhibitors and coupled the inhibitors with antibodies for cell-specific delivery. We used this platform to generate antibody-peptide inhibitor conjugates (APICs) that target a family of prot ...

Image information about the state of a building after an earthquake, which can be collected without endangering the post-earthquake reconnaissance activities, can be used to reduce uncertainties in response predictions for future seismic events. This paper ...

In the domain of computational structural biology, predicting protein interactions based on molecular structure remains a pivotal challenge. This thesis delves into this challenge through a series of interconnected studies. The first chapter introduces th ...

Proteins are foundational biomolecules of life playing a crucial role in a myriad of biological processes. Their function often requires interplay with other biomolecules, including proteins themselves. Protein-protein interactions (PPIs) are essential for ...

Modern neuroscience research is generating increasingly large datasets, from recording thousands of neurons over long timescales to behavioral recordings of animals spanning weeks, months, or even years. Despite a great variety in recording setups and expe ...

Human babies have a natural desire to interact with new toys and objects, through which they learn how the world around them works, e.g., that glass shatters when dropped, but a rubber ball does not. When their predictions are proven incorrect, such as whe ...

High-grade gliomas (HGG) are the most common and most aggressive primary tumors of the brain. Despite recent advances in neuro-oncology survival of these tumors remains around 12-15 months. The first-line of treatment is surgical resection. However, due to ...

The application of computational biology in drug development for membrane protein targets has experienced a boost from recent developments in deep learning-driven structure prediction, increased speed and resolution of structure elucidation, machine learni ...

. High-resolution simulations of particle-based kinetic plasma models typically require a high number of particles and thus often become computationally intractable. This is exacerbated in multi-query simulations, where the problem depends on a set of para ...

ABCG2 is an ATP-binding cassette transporter that exports a wide range of xenobiotic compounds and has been recognized as a contributing factor for multidrug resistance in cancer cells. Substrate and inhibitor interactions with ABCG2 have been extensively ...

This dataset contains aerosol optical absorption coefficients at seven different wavelengths (babs(λ)), averaged to 10 min time resolution, measured during the year-long MOSAiC expedition from October 2019 to September 2020. The measurements were performed ...

The expansive production of data in materials science, their widespread sharing and repurposing requires educated support and stewardship. In order to ensure that this need helps rather than hinders scientific work, the implementation of the FAIR-data prin ...

Proteins control nearly every facet of life on a molecular level. Proteins are formed from linear strings of amino acids, which fold into three-dimensional structures that can enact functions. Evolution has created highly efficient proteins in diverse fold ...

This dataset supports the publication 'Elastocapillary menisci mediate interaction of neighboring structures at the surface of a compliant solid' by Lebo Molefe and John M. Kolinski, Physical Review E, (2023). The data are surface profiles of textured surf ...

Emerging Protein Targets for Anticancer Metallodrugs: Inhibition of Thioredoxin Reductase and Cathepsin B by Antitumor Ruthenium(II)-Arene Compounds

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From Sequence to Dynamics to Function: Computational Design of Allostery and Ligand Selectivity in G-Protein Coupled Receptors

Development of cysteine cathepsin inhibitors combined with cell type-specific delivery for the treatment of B-cell lymphoma and solid tumors

Dataset for '3D printing of customizable transient bioelectronics and sensors'

Data set for control of Ge island coalescence for the formation of nanowires on silicon

Data and scripts for the RaFSIP scheme

Few-shot Learning for Efficient and Effective Machine Learning Model Adaptation

Antibody-peptide conjugates for targeted inhibition of cysteine proteases

Reducing uncertainties in response predictions of earthquake-damaged masonry buildings using data from image-based inspection

Predicting protein interactions using geometric deep learning on protein surfaces

Engineering novel protein interactions with therapeutic potential using deep learning-guided surface design

Robust machine learning for neuroscientific inference

Seeking the new, learning from the unexpected: Computational models of surprise and novelty in the brain

A fatty-acid based probe for near-infrared fluorescence guided surgery of glioblastoma

Computational drug development for membrane protein targets

Adaptive Symplectic Model Order Reduction Of Parametric Particle-Based Vlasov-Poisson Equation

Structural Basis of the Allosteric Inhibition of Human ABCG2 by Nanobodies

Aerosol optical absorption coefficients at seven wavelengths in 10 min resolution measured in the Swiss container during MOSAiC 2019/2020

Shared metadata for data-centric materials science

De novo designed proteins: a study in engineering novel folds and functions

Dataset for "Elastocapillary menisci mediate interaction of neighboring structures at the surface of a compliant solid"