Advancing Drug Discovery via Artificial Intelligence

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The rapid progress of industrial development, urbanization, and traffic has caused air quality degradation that negatively affects human health and environmental sustainability, especially in developed countries. However, due to the limited number of senso ...

G protein-coupled receptors play essential roles in cellular processes such as neuronal signaling, vision, olfaction, tasting, and metabolism. As GPCRs are the most important drug targets, understanding their interactions with ligands is of utmost importan ...

We use quantitative phase digital holographic microscopy (QP-DHM) to image and quantify the beating movement of cardiomyocytes, derived from induced pluripotent stem cells (iPSCs), in control and drug-treated conditions. The development of an analysis algo ...

Machine learning has provided a means to accelerate early-stage drug discovery by combining molecule generation and filtering steps in a single architecture that leverages the experience and design preferences of medicinal chemists. However, designing mach ...

Sample efficiency is a fundamental challenge in de novo molecular design. Ideally, molecular generative models should learn to satisfy a desired objective under minimal calls to oracles (computational property predictors). This problem becomes more apparen ...

A series of three formulations were prepared in view of experimental and theoretical investigation of their drug release potential. The morphology of the film formulations, in terms of distribution of drug into the polymeric matrix and the nature of the dr ...

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 ...

Macrocycles provide an attractive modality for drug development, but generating ligands for new targets is hampered by the limited availability of large macrocycle libraries. We have established a solution-phase macrocycle synthesis strategy in which three ...

If small molecules have led to tremendous progress in curing diseases, new therapeutic agents such as peptides or antibody-drugs conjugates have emerged as a highly promising next generation of pharmaceuticals. As for small molecules, their derivatization ...

Advanced data collection technologies, computational tools, and sophisticated algorithms have a revolutionary impact on sports analytics on various aspects of sports, from athletes performance to fan engagement. Computer Vision (CV) and Deep Learning (DL) ...

Cross-coupling of two alkyl fragments is an efficient method to produce organic molecules rich in sp(3)-hybridized carbon centres, which are attractive candidate compounds in drug discovery. Enantioselective C(sp(3))-C(sp(3)) coupling is challenging, espec ...

The stochastic block model (SBM) is widely studied as a benchmark for graph clustering aka community detection. In practice, graph data often come with node attributes that bear additional information about the communities. Previous works modeled such data ...

In article number 2000733 by Juergen Brugger and co‐workers, a novel composite membrane of silk fibroin, microgels and magnetic nanoparticles whose permeability can be adjusted by temperature for controlled drug release is studied. The temperature induced ...

With the prevalence of smartphones, watches, and Internet of Things (IoT) devices, the ability to track their positions is becoming increasingly important. For many indoor positioning systems (IPSs), providing an uninterrupted flow of information in real-t ...

A major step for the validation of medical drugs is the screening on whole organisms, which gives the systemic information that is missing when using cellular models. Caenorhabditis elegans is a soil worm that catches the interest of researchers who study ...

Advancing Drug Discovery via Artificial Intelligence

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Self-supervised air quality estimation with graph neural network assistance and attention enhancement

Enhancing the Signaling of GPCRs via Orthosteric Ions

Marker-Free Automatic Quantification of Drug-Treated Cardiomyocytes with Digital Holographic Imaging

Machine learning-aided generative molecular design

Augmented Memory: Sample-Efficient Generative Molecular Design with Reinforcement Learning

Experimental And Theoretical Insight Into Formulations Based On Poly(Vinyl Alcohol Boric Acid) And Diclofenac Sodium Salt

Computational drug development for membrane protein targets

Macrocycle synthesis strategy based on step-wise “adding and reacting” three components enables screening of large combinatorial libraries

Development of Photocatalysts towards the Visible-Light driven C-Terminal Bioconjugation of Peptides and Proteins

DeepSportradar-v2: a Multi-Sport Computer Vision Dataset for Sport Understandings

Enantioselective C(sp(3))-C(sp(3)) cross-coupling of non-activated alkyl electrophiles via nickel hydride catalysis

Neural-prior stochastic block model

Reversible Drug Delivery: Thermal and pH Sensitive Composite Membrane for On‐Demand Drug Delivery by Applying an Alternating Magnetic Field (Adv. Mater. Interfaces 17/2020)

Indoor Real-time localization system design for Internet of Things applications

Multimodal imaging and high-throughput image-processing for drug screening on living organisms on-chip