A5084011333- Computational Drug Discovery Methods
- Protein Structure and Dynamics
- Receptor Mechanisms and Signaling
- Monoclonal and Polyclonal Antibodies Research
- Chemical Synthesis and Analysis
- Pharmacological Receptor Mechanisms and Effects
- Protein Degradation and Inhibitors
- Chronic Lymphocytic Leukemia Research
- Enzyme Structure and Function
- Ion channel regulation and function
- Genetics, Bioinformatics, and Biomedical Research
- Scientific Computing and Data Management
- Protein Tyrosine Phosphatases
- Melanoma and MAPK Pathways
- Natural Compound Pharmacology Studies
- Cholinesterase and Neurodegenerative Diseases
- Gene Regulatory Network Analysis
- Cancer Mechanisms and Therapy
- Mosquito-borne diseases and control
- Chronic Myeloid Leukemia Treatments
- Protein purification and stability
- Advanced Proteomics Techniques and Applications
- Phytochemistry and biological activities of Ficus species
- Galectins and Cancer Biology
- PI3K/AKT/mTOR signaling in cancer
Memorial Sloan Kettering Cancer Center
2023-2025
Humboldt-Universität zu Berlin
2021-2025
Charité - Universitätsmedizin Berlin
2020-2025
Freie Universität Berlin
2017-2025
Abstract 3D pharmacophore models are three‐dimensional ensembles of chemically defined interactions a ligand in its bioactive conformation. They represent an elegant way to decipher encoded information and have therefore become valuable tool drug design. In this review, we provide overview on the basic concept method summarize key studies for applying virtual screening mechanistic protein functionality. Moreover, discuss recent developments field. The combination with molecular dynamics...
Small molecule kinase inhibitors are critical in the modern treatment of cancers, evidenced by existence over 80 FDA-approved small-molecule inhibitors. Unfortunately, intrinsic or acquired resistance, often causing therapy discontinuation, is frequently caused mutations therapeutic target. The advent clinical tumor sequencing has opened additional opportunities for precision oncology to improve patient outcomes pairing optimal therapies with mutation profiles. However, efforts hindered lack...
Designing inhibitors is a complex task that requires deep understanding of protein–ligand interactions and their dynamics. Ligands often interact with multiple binding subsites, noncovalent affecting affinity. Conformational changes plasticity both, the ligand protein influence energetics. We investigated tankyrase ADP-ribosyltransferase as promising drug target regulating many cellular pathways. Despite existence diverse inhibitors, energetics contributions flexible cryptic subpockets to...
The tyrosine phosphatase SHP2 controls the activity of pivotal signaling pathways, including MAPK, JAK-STAT, and PI3K-Akt. Aberrant leads to uncontrolled cell proliferation, tumorigenesis, metastasis. was recently linked drug resistance against cancer medications such as MEK BRAF inhibitors. In this work, we present development a novel class azaindole We applied scaffold hopping bioisosteric replacement concepts eliminate unwanted structural motifs improve inhibitor characteristics...
Recent advances in machine learning (ML) are reshaping drug discovery. Structure-based ML methods use physically-inspired models to predict binding affinities from protein:ligand complexes. These promise enable the integration of data for many related targets, which addresses issues scarcity single targets and could generalizable predictions a broad range including mutants. In this work, we report our experiences building KinoML, novel framework target-based small molecule discovery with an...
In this study, we report a ligand-guided homology modeling approach allowing the analysis of relevant binding site residue conformations and identification two novel histamine H3 receptor ligands with affinity in nanomolar range. The newly developed method is based on exploiting an essential charge interaction characteristic for aminergic G-protein coupled receptors ranking 3D models appropriate discovery compounds through virtual screening.
Computational pipelines have become a crucial part of modern drug discovery campaigns. Setting up and maintaining such pipelines, however, can be challenging time-consuming-especially for novice scientists in this domain. TeachOpenCADD is platform that aims to teach domain-specific skills provide pipeline templates as starting points research projects. We offer Python-based solutions common tasks cheminformatics structural bioinformatics the form Jupyter notebooks, based on open source...
Ligands entering a protein binding pocket essentially compete with water molecules for to the protein. Hence, location and thermodynamic properties of in structures have gained increased attention drug design community. Including corresponding data into 3D pharmacophore modeling is essential efficient high throughput virtual screening. Here, we present PyRod, free open-source python software that allows visualization pharmacophoric characteristics, identification hot spots ligand subsequent...
Smyd1 (SET And MYND Domain Containing 1) plays a crucial role in cardiomyocyte differentiation and cardiac morphogenesis, offering promising potential for the treatment of cardiovascular disease. However, lack human crystal structures published inhibitors has hindered progress developing effective therapeutics. To address this gap, our study employs computational methods to identify novel inhibitors. We first generated reliable homology model conducted an in-depth analysis compound binding...
Small molecule kinase inhibitors are critical in the modern treatment of cancers, evidenced by existence over 80 FDA-approved small-molecule inhibitors. Unfortunately, intrinsic or acquired resistance, often causing therapy discontinuation, is frequently caused mutations therapeutic target. The advent clinical tumor sequencing has opened additional opportunities for precision oncology to improve patient outcomes pairing optimal therapies with mutation profiles. However, efforts hindered lack...
The pivotal role of viral proteases in virus replication has already been successfully exploited several antiviral drug design campaigns. However, no efficient antivirals are currently available against flaviviral infections. In this study, we present lead-like small molecule inhibitors the Zika Virus (ZIKV) NS2B-NS3 protease. Since only few nonpeptide competitive ligands known, take advantage high structural similarity with West Nile (WNV) A comparative modeling approach involving our...
New 2-(thien-2-yl)-acrylonitriles with putative kinase inhibitory activity were prepared and tested for their antineoplastic efficacy in hepatoma models. Four out of the 14 derivatives shown to inhibit cell proliferation at (sub-)micromolar concentrations IC50 values below that clinically relevant multikinase inhibitor sorafenib, which served as a reference. Colony formation assays well primary vivo examinations tumors grown on chorioallantoic membrane fertilized chicken eggs (CAM assay)...
Abstract In recent years machine learning has transformed many aspects of the drug discovery process including small molecule design for which prediction bioactivity is an integral part. Leveraging structural information about interactions between a and its protein target great potential downstream scoring approaches, but fundamentally limited by accuracy with protein:ligand complex structures can be predicted in reliable automated fashion. With goal finding practical approaches to...
Abstract G protein-coupled receptors transmit signals across membranes via interaction with intracellular binding partners. While there is an imprinted signaling profile for each receptor, biased ligands are able to shift pathways resulting in different recruitment profiles. We present the first comprehensive database of all literature-known as a resource medicinal chemistry and pharmacology. In addition careful manual curation, we provide analysis data. BiasDB available at...
In this study, we report a ligand-centric data mining approach that guided the identification of suitable target profiles for treating obesity. The newly developed method is based on identifying pairs synergistic positive effects and also encompasses exclusion compounds showing detrimental effect obesity treatment (off-targets). Ligands with known activity against obesity-relevant targets were compared using fingerprint representations. Similar activities to different evaluated mechanism...
Abstract The bioactive components of Garcinia indica , garcinol (camboginol), and isogarcinol (cambogin), are suitable drug candidates for the treatment various human diseases. HIV‐1‐RNase H assay was used to study RNase inhibition by isogarcinol. Docking into active site enzyme carried out rationalize difference in activities between two compounds. Garcinol showed higher than known inhibitor RDS1759 retained full potency against a drug‐resistant HIV‐1 reverse transcriptase form. Isogarcinol...
Abstract Several encouraging pre‐clinical results highlight the melanin‐concentrating hormone receptor 1 (MCHR1) as promising target for anti‐obesity drug development. Currently however, experimentally resolved structures of MCHR1 are not available, which complicates rational design campaigns. In this study, we aimed at developing accurate, homologymodel‐based 3D pharmacophores against MCHR1. We show that traditional approaches involving docking known active small molecules hindered by...
In recent years, machine learning has transformed many aspects of the drug discovery process, including small molecule design, for which prediction bioactivity is an integral part. Leveraging structural information about interactions between a and its protein target great potential downstream scoring approaches but fundamentally limited by accuracy with protein–ligand complex structures can be predicted in reliable automated fashion. With goal finding practical to generating useful...
Abstract For drug design projects it is essential to rationally induce and explain selectivity. In this context shape complementarity as well protein ligand flexibility represent important factors. Currently available tools for the analysis of protein‐ligand interactions focus mainly on electrostatic and/or static structures. Here we address shortcomings methods by presenting two new tools: The first one can be used assess steric in flexible complexes order selectivity known ligands. It...