A5102932992- Computational Drug Discovery Methods
- Cancer Cells and Metastasis
- Hippo pathway signaling and YAP/TAZ
- Epigenetics and DNA Methylation
- Analytical Chemistry and Chromatography
- Machine Learning in Materials Science
- Cancer, Stress, Anesthesia, and Immune Response
- CRISPR and Genetic Engineering
- Single-cell and spatial transcriptomics
- Chemical Synthesis and Analysis
- Innovative Microfluidic and Catalytic Techniques Innovation
- Advanced biosensing and bioanalysis techniques
- Genetics, Bioinformatics, and Biomedical Research
- Ubiquitin and proteasome pathways
- Cancer therapeutics and mechanisms
- Hedgehog Signaling Pathway Studies
- Axon Guidance and Neuronal Signaling
- RNA and protein synthesis mechanisms
- PARP inhibition in cancer therapy
- Parallel Computing and Optimization Techniques
- Click Chemistry and Applications
- Dendrimers and Hyperbranched Polymers
- Gene Regulatory Network Analysis
- Bioinformatics and Genomic Networks
- Sirtuins and Resveratrol in Medicine
Pfizer (Germany)
2023-2024
Bayer (Germany)
2017-2023
Max Planck Society
2004-2007
Max Planck Institute for Informatics
2006
University of Applied Sciences Rapperswil
2005
One of the main challenges in small molecule drug discovery is finding novel chemical compounds with desirable properties. In this work, we propose a method that combines silico prediction molecular properties such as biological activity or pharmacokinetics an optimization algorithm, namely Particle Swarm Optimization. Our takes starting compound input and proposes new molecules more (predicted) It navigates machine-learned continuous representation drug-like space guided by defined...
Colon cancer is a heterogeneous tumor driven by subpopulation of stem cells (CSCs). To study CSCs in colon cancer, we used limiting dilution spheroid and serial xenotransplantation assays to functionally define the frequency panel patient-derived organoids. These studies demonstrated organoids be enriched for CSCs, which varied between tumors. Whole-transcriptome analysis identified WNT Hedgehog signaling components enhanced CSC-enriched tumors aldehyde dehydrogenase (ALDH)-positive CSCs....
The Structural Genomics Consortium is an international open science research organization with a focus on accelerating early-stage drug discovery, namely hit discovery and optimization. We, as many others, believe that artificial intelligence (AI) poised to be main accelerator in the field. question then how best benefit from recent advances AI generate, format disseminate data enable future breakthroughs AI-guided discovery. We present here recommendations of working group composed experts...
Target residence time is emerging as an important optimization parameter in drug discovery, yet target and off-target engagement dynamics have not been clearly linked to the clinical performance of drugs. Here we developed high-throughput binding kinetics assays characterize interactions 270 protein kinase inhibitors with 40 clinically relevant targets. Analysis results revealed that on-rates are better correlated affinity than off-rates fraction slowly dissociating drug-target complexes...
In this work, we propose a novel method that combines in silico prediction of molecular properties such as biological activity or pharmacokinetics with an optimization algorithm, namely Particle Swarm Optimization. Our takes starting compound input and proposes new molecules more desirable (predicted) properties. It navigates machine-learned continuous representation drug-like chemical space guided by de fined objective function. The function multiple models, desirability ranges substructure...
Abstract We report the computer‐aided optimization of a synthetic receptor for given guest molecule, based on inverse virtual screening libraries. As an example, set β‐cyclodextrin (β‐CD) derivatives was generated as candidates anticancer drug camptothecin. applied two docking tools AutoDock and GlamDock to generate camptothecin complexes every candidate receptor. Scoring functions were used rank all complexes. From 10 % top‐ranking nine selected experimental validation. They synthesized by...
Recent evidence demonstrates that colon cancer stem cells (CSCs) can generate neurons synapse with tumor innervating fibers required for tumorigenesis and disease progression. Greater understanding of the mechanisms regulate CSC driven neurogenesis may therefore lead to more effective treatments. RNA-sequencing analyses ALDHPositive CSCs from patient-derived organoids (PDOs) xenografts (PDXs) showed be enriched neural development genes. Functional genes differentially expressed in PDO PDX...
Recent data suggest that therapy-resistant quiescent cancer stem cells (qCSCs) are the source of relapse in colon cancer. Here, using patient-derived organoids and xenografts, we identify rare long-term label-retaining qCSCs can re-enter cell cycle to generate new tumors. RNA sequencing analyses demonstrated these display molecular hallmarks tissue cells, including expression p53 signaling genes, enriched for transcripts common damage-induced revival regenerating intestine. In addition,...
Abstract Summary We created bigwig-loader, a data-loader for epigenetic profiles from BigWig files that decompresses and processes information multiple intervals in parallel. This is an access pattern needed to create training batches typical machine learning models on epigenetics data. Using new codec, the decompression can be done graphical processing unit (GPU) making it fast enough during training, mitigating need saving preprocessed examples disk. Availability implementation The...
Single-guide RNAs (sgRNAs) targeting the same gene can significantly vary in terms of efficacy and specificity. PAVOOC (Prediction And Visualization On- Off-targets for CRISPR) is a web-based CRISPR sgRNA design tool that employs state art machine learning models to prioritize most effective candidate sgRNAs. In contrast other tools, it maps sgRNAs functional domains protein structures visualizes cut sites on corresponding crystal structures. Furthermore, supports homology-directed repair...
Abstract Summary Optimizing small molecules in a drug discovery project is notoriously difficult task as multiple molecular properties have to be considered and balanced at the same time. In this work, we present our novel interactive silico compound optimization platform termed grünifai support ideation of next generation compounds under constraints multiparameter objective. integrates adjustable models, continuous representation chemical space, scalable particle swarm algorithm possibility...
We present a new algorithm for the fast and reliable structure prediction of synthetic receptor−ligand complexes. Our method is based on protein−ligand docking program FlexX extends our recently introduced technique receptors, which has been implemented in FlexR. To handle flexibility relevant molecules, we apply novel strategy that uses an adaptive two-sided incremental construction incorporates structural both ligand receptor. follow strategy, one molecule expanded by attaching its next...
In this work, we propose a novel method that combines in silico prediction of molecular properties such as biological activity or pharmacokinetics with an optimization algorithm, namely Particle Swarm Optimization. Our takes starting compound input and proposes new molecules more desirable (predicted) properties. It navigates machine-learned continuous representation drug-like chemical space guided by de�fined objective function. The function multiple models, desirability ranges substructure...
Abstract Recent data support a hierarchical model of colon cancer in which tumor growth is driven by subpopulation stem cells (CSCs) that may also be the source relapse following treatment. Elucidation cellular heterogeneity within would therefore facilitate better characterization patient subtypes and lead to more personalized effective treatments. Here, as part OncoTrack* consortium, we report use Matrigel-based 3D vitro models patient-derived for molecular pathways important regulation...
Multimodal single-cell sequencing data provide detailed views into the molecular biology of cells. To allow for interactive analyses such rich and to readily derive insights from it, new analysis solutions are required. In this work, we present Cellenium, our scalable visual analytics web application that enables users semantically integrate organize all their RNA-, ATAC-, CITE-sequencing studies. Users can then find relevant studies analyze within across An cell annotation feature allows...
SUMMARY This study describes the identification and target deconvolution of novel small molecule inhibitors oncogenic YAP1/TAZ activity with potent anti-tumor in vivo. A high-throughput screen (HTS) 3.8 million compounds was conducted using a cellular reporter assay. Target studies identified geranylgeranyltransferase-I (GGTase-I) complex, as direct pathway inhibitors. The block activation Rho-GTPases, leading to subsequent inactivation inhibition cancer cell proliferation vitro....
This study describes the identification and target deconvolution of novel small molecule inhibitors oncogenic YAP1/TAZ activity with potent anti-tumor in vivo. A high-throughput screen (HTS) 3.8 million compounds was conducted using a cellular reporter assay. Target studies identified geranylgeranyltransferase‑I (GGTase‑I) complex, as direct pathway inhibitors. The block activation Rho-GTPases, leading to subsequent inactivation inhibition cancer cell proliferation vitro. Multi-parameter...
Abstract Summary: sgRNAs targeting the same gene can significantly vary in terms of efficacy and specificity. PAVOOC (Prediction And Visualization On- Off-targets for CRISPR) is a web-based CRISPR sgRNA design tool that employs state-of-the art machine learning models to prioritize most effective candidate sgRNAs. In contrast other tools, it maps functional domains protein structures visualizes cut sites on corresponding crystal structures. Furthermore, supports HDR template generation...
Abstract Aberrant activation of the Hippo pathway effectors YAP1/TAZ promotes cell proliferation and tumorigenesis. To identify novel regulators as a possible means to treat cancer, we established novel, FACS-based screening system monitoring activity in MDA-MB-231 breast cancer cells. Using these cells, performed pooled genome-wide CRISPR/Cas9 knockout screen. We identified approximately 50 genes potentially activating with functions Actin Cytoskeleton signaling, p53 polarity or ER stress,...
Abstract Aberrant activation of the Hippo pathway effectors YAP1/TAZ promotes cell proliferation and tumorigenesis. To identify novel regulators in cancer, we established a FACS-based screening system monitoring activity MDA-MB-231 breast cancer cells. Using these cells, performed pooled genome-wide CRISPR/Cas9 knockout CRISPR activation/interference (a/i) screens. The list hits included previously known modulators such as LATS2, AJUBA, TAZ itself, demonstrating robustness screen. Moreover,...