Advancing Drug Discovery via Artificial Intelligence

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Protein-protein interactions (PPIs) play important roles in many diseases and their modulation is an attractive strategy for developing new therapeutics. However, the relatively large and often flat binding surfaces of PPIs makes the development of inhibit ...

Purpose The aim of this study was to develop a novel approach for predicting the expression status of Epidermal Growth Factor Receptor (EGFR) and its subtypes in patients with Non-Small Cell Lung Cancer (NSCLC) using a Three-Dimensional Convolutional Neura ...

Anti-cancer therapies often exhibit only short-term effects. Tumors typically develop drug resistance causing relapses that might be tackled with drug combinations. Identification of the right combination is challenging and would benefit from high-content, ...

Dexterous in-hand manipulation in robotics, particularly with multi-fingered robotic hands, poses significant challenges due to the intricate avoidance of collisions among fingers and the object being manipulated. Collision-free paths for all fingers must ...

The discovery of a drug requires over a decade of intensive research and financial investments – and still has a high risk of failure. To reduce this burden, we developed the NICEdrug.ch resource, which incorporates 250,000 bioactive molecules, and studied ...

De novo protein design explores uncharted sequence and structure space to generate novel proteins not sampled by evolution. A main challenge in de novo design involves crafting “designable” structural templates to guide the sequence searches toward adoptin ...

Organoids allow the recapitulation of intestinal homeostasis and cancerogenesis in vitro; however, RNA sequencing (RNA-seq)-based methods for drug screens are missing. We develop targeted organoid sequencing (TORNADO-seq), a high-throughput, high-content d ...

We consider on the torus the scaling limit of stochastic 2D (inviscid) fluid dynamics equations with transport noise to deterministic viscous equations. Quantitative estimates on the convergence rates are provided by combining analytic and probabilistic ar ...

Alpha-synuclein oligomerization is one of the early events on the pathway to Lewy body formation. Therefore, interfering with this process holds tremendous potential for developing therapies that block alpha-Syn pathology formation and toxicity. The develo ...

With the emergence of ultra-portable ultrasound systems, the need to reduce cost and complexity of ultrasound systems has intensified. Sparse arrays, employing fewer transducer elements to acquire images, offer a viable solution by effectively minimizing d ...

The therapeutic efficacy and pharmacokinetics of antibody-drug conjugates (ADCs) in general, and antibody-oligonucleotide conjugates (AOCs) in particular, depend on the drug-to-antibody ratio (DAR) distribution and average value. The DAR is considered a cr ...

Deploying compute-intensive deep neural networks (DNNs) on resource-constrained end devices has become a prominent trend, enabling localized intelligence. However, efficiently deploying these DNNs at scale poses challenges. To address this, extensive resea ...

Peptides have a number of attractive properties that make them an interesting modality for drug development, including their ability to bind challenging targets, their high target specificity, and their non-toxic metabolic products. However, a major limita ...

Coronaviruses represent global health threat. In this century, they have already caused two epidemics and one serious pandemic. Although, at present, there are no approved drugs and therapies for the treatment and prevention of human coronaviruses, several ...

Cyclic peptides are fascinating molecules abundantly found in nature and exploited as molecular format for drug development as well as other applications, ranging from research tools to food additives. Advances in peptide technologies made over many years ...

Reinforcement learning (RL) is inherently rife with non-stationarity since the states and rewards the agent observes during training depend on its changing policy. Therefore, networks in deep RL must be capable of adapting to new observations and fitting n ...

Libraries of DNA-Encoded small molecules created using combinatorial chemistry and synthetic oligonucleotides are being applied to drug discovery projects across the pharmaceutical industry. The majority of reported projects describe the discovery of rever ...

Drug discovery is a complex, multistep process, in which many challenges need to be overcome at each stage, from the discovery of a biomolecular target to the ensuring of the efficacy and safety of a compound in humans. Today's analytical methods allow ten ...

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 ...

Schistosomiasis is a disease of poverty affecting millions of people. Praziquantel (PZQ), with its strengths and weaknesses, is the only treatment available. We previously reported findings on three lead compounds derived from oxamniquine (OXA), an old ant ...

Advancing Drug Discovery via Artificial Intelligence

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Generating macrocyclic inhibitors of protein-protein interactions

Advancing EGFR mutation subtypes prediction in NSCLC by combining 3D pretrained ConvNeXt, radiomics, and clinical features

Combi-seq for multiplexed transcriptome-based profiling of drug combinations using deterministic barcoding in single-cell droplets

Enhancing Dexterity in Confined Spaces: Real-Time Motion Planning for Multifingered In-Hand Manipulation

NICEdrug.ch, a workflow for rational drug design and systems-level analysis of drug metabolism

Exploring “dark-matter” protein folds using deep learning

High-content, targeted RNA-seq screening in organoids for drug discovery in colorectal cancer

Quantitative convergence rates for scaling limit of SPDEs with transport noise

Sequential CNN-based Enhancement of Ultrafast Ultrasound Imaging for Sparse Arrays

Drug-to-Antibody Ratio Estimation via Proteoform Peak Integration in the Analysis of Antibody-Oligonucleotide Conjugates with Orbitrap Fourier Transform Mass Spectrometry

RAPNet: Resolution-Adaptive and Predictive Early Exit Network for Efficient Image Recognition

Towards the Development of Orally Available Peptide Therapeutics

Therapeutic approaches against coronaviruses acute respiratory syndrome

Cyclic Peptides for Drug Development

No Representation, No Trust: Connecting Representation, Collapse, and Trust Issues in PPO

Novel irreversible covalent BTK inhibitors discovered using DNA-encoded chemistry

Miniaturized technologies for high-throughput drug screening enzymatic assays and diagnostics - A review

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

Multidisciplinary Preclinical Investigations on Three Oxamniquine Analogues as New Drug Candidates for Schistosomiasis