Article
Multidisciplinary Sciences
Alexander Medvedev, Matt Moeser, Liubov Medvedeva, Elena Martsen, Alexander Granick, Lydia Raines, Kristen Gorman, Benjamin Lin, Ming Zeng, Keith A. Houck, Sergei S. Makarov
Summary: Nuclear receptors (NR) are transcription factors that regulate cell functions and are important drug targets. A newly developed multiplex reporter assay allows simultaneous evaluation of ligand activity across all human NRs, providing highly reproducible and quantitative assessment of individual NR responses. This assay has the potential to study polypharmacology of NR ligands.
SCIENTIFIC REPORTS
(2022)
Article
Biochemistry & Molecular Biology
Kiran Bharat Lokhande, Sangeeta Ballav, Rohit Singh Yadav, K. Venkateswara Swamy, Soumya Basu
Summary: Through molecular docking and dynamic simulation, derivatives of Kaempferol, Quercetin, and Resveratrol were found to have high binding affinities with PPAR-gamma, indicating their potential as anti-inflammatory and anti-cancer agents.
JOURNAL OF BIOMOLECULAR STRUCTURE & DYNAMICS
(2022)
Article
Biochemistry & Molecular Biology
Iris A. Leijten-van de Gevel, Kim H. N. van Herk, Rens M. J. M. de Vries, Nicolaas J. Ottenheym, Christian Ottmann, Luc Brunsveld
Summary: The nuclear receptor PPAR gamma plays a central role in metabolism, and its discovery of partial agonists with novel chemotypes is important. The unique binding mode of MRL-871 to PPAR gamma suggests its potential as a starting point for the development of novel PPAR gamma ligands.
BIOORGANIC & MEDICINAL CHEMISTRY
(2022)
Article
Chemistry, Multidisciplinary
Amer H. Tarawneh, Pankaj Pandey, Lo'ay A. Al-Momani, Anastassiya Gadetskaya, Sultan T. Abu-Orabi, Robert J. Doerksen, Stephen J. Cutler
Summary: The CB2 receptor, as a potential target for treating various neuroinflammatory or neurodegenerative diseases, has attracted significant interest, and the search for new compounds as highly selective CB2 modulators is of great importance.
ARABIAN JOURNAL OF CHEMISTRY
(2022)
Article
Chemistry, Analytical
Ines Klingelhoefer, Long Pham Ngoc, Bart van der Burg, Gertrud E. Morlock
Summary: This study demonstrates the novel combination of chromatographic separations with human cancer cells as biological detectors, leading to the discovery of cytotoxic substances in herbal samples and the detection of specific compounds targeting receptor-mediated signaling pathways. High-resolution mass spectrometry and fragmentation were used to further characterize the discovered compounds.
ANALYTICA CHIMICA ACTA
(2021)
Article
Medicine, Research & Experimental
Haizhang Chen, Andrea Maul-Pavicic, Martin Holzer, Magdalena Huber, Ulrich Salzer, Nina Chevalier, Reinhard E. Voll, Hartmut Hengel, Philipp Kolb
Summary: The study developed a test system for detecting and quantifying the bioactivity of sICs, identifying Fc gamma RIIA(H) and Fc gamma RIIIA as the most sensitive Fc gamma Rs. The research has predictive capabilities regarding the severity of SLE disease and provides a sensitive and scalable tool for evaluating the size, amount, and bioactivity of sICs.
EMBO MOLECULAR MEDICINE
(2022)
Article
Chemistry, Medicinal
Zhiqi Feng, Jiehao Xiang, Hui Liu, Jiaxin Li, Xiangrui Xu, Gang Sun, Runan Zheng, Shangran Zhang, Junlong Liu, Shanlin Yang, Qinglong Xu, Xiaoan Wen, Haoliang Yuan, Hongbin Sun, Liang Dai
Summary: This study reports a series of novel triazolone derivatives as PPAR alpha/delta dual agonists, with compound H11 showing potent and well-balanced PPAR alpha/delta agonistic activity. H11 also exhibited strong anti-NASH effects in preclinical models, indicating its potential for treating NASH and other inflammatory and fibrotic diseases.
JOURNAL OF MEDICINAL CHEMISTRY
(2022)
Review
Biochemistry & Molecular Biology
Andrew E. Libby, Bryce Jones, Isabel Lopez-Santiago, Emma Rowland, Moshe Levi
Summary: Over the past 30 years, nuclear receptors (NRs) have been recognized as key modulators in maintaining systemic homeostasis and contributing to various diseases, particularly in the kidney where they play crucial roles in regulating processes such as circadian responses and lipid metabolism. Recent advances in genetic tools and small molecule modulators have enabled detailed studies on how renal NRs impact kidney homeostasis and progression of diseases. Understanding dysregulation of NRs in renal conditions over the last decade has significantly shaped our knowledge of renal disease etiology, making NRs attractive therapeutic targets.
MOLECULAR ASPECTS OF MEDICINE
(2021)
Article
Chemistry, Medicinal
Harish C. Upadhyay, Akansha Mishra, Jyotsana Pandey, Pooja Sharma, Akhilesh K. Tamrakar, Arvind K. Srivastava, Feroz Khan, Santosh K. Srivastava
Summary: By modifying the structure of phytol, a series of derivatives were synthesized and evaluated for their in vitro and in vivo antihyperglycemic activity. The results showed that some derivatives exhibited potent antidiabetic activity and significantly improved oral glucose tolerance. In silico docking studies demonstrated high binding affinity and non-toxicity for the derivatives.
MEDICINAL CHEMISTRY
(2022)
Article
Biochemistry & Molecular Biology
Manu Kumar, Sang-Min Chung, Ganuskh Enkhtaivan, Rahul V. Patel, Han-Seung Shin, Bhupendra M. Mistry
Summary: Newly synthesized substituted benzothiazole based berberine derivatives demonstrated interesting anti-influenza virus activity, with BBD7 showing potent neuraminidase activity. Molecular docking analysis suggests that the antiviral mechanisms of these compounds may be similar to oseltamivir through interaction with residues of neuraminidase.
INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES
(2021)
Article
Biochemistry & Molecular Biology
Suliman Almahmoud, Catherine C. Elix, Jeremy O. Jones, Corey R. Hopkins, Jonathan L. Vennerstrom, Haizhen A. Zhong
Summary: The PPAR gamma antagonist is crucial for inhibiting prostate cancer cell growth, and residues Arg288, Lys367, and His449 are important for PPAR gamma antagonist binding.
BIOORGANIC & MEDICINAL CHEMISTRY
(2021)
Article
Chemistry, Multidisciplinary
Kajalben Bharatbhai Patel, Premlata Kumari
Summary: Flavones are natural products with significant biological activities, including anti-inflammatory, anticancer, antiviral, and antibacterial effects. This paper focuses on the anticancer activity of various flavone derivatives and their binding interactions with the PPAR gamma protein. The structure-activity relationships of flavone derivatives are also discussed.
STRUCTURAL CHEMISTRY
(2022)
Article
Biochemical Research Methods
Karina de Paula, Jademilson C. Santos, Ana Carolina Mafud, Alessandro S. Nascimento
Summary: Diabetes is a significant global health issue, with type 2 diabetes being the most common form. Pharmacological management often involves drugs like TZDs, although safety concerns have led to the withdrawal of certain medications. Researchers have identified a class of tetrazole compounds that show potential for interacting with PPAR gamma, providing new avenues for investigating diabetes treatment.
JOURNAL OF MOLECULAR GRAPHICS & MODELLING
(2021)
Article
Plant Sciences
Jaekyeong Kim, Hyejin Ko, Jae-Seoun Hur, Seungchan An, Jin Woo Lee, Stephen T. Deyrup, Minsoo Noh, Sang Hee Shim
Summary: Compounds from an extract of an endolichenic fungus have the potential to promote adiponectin synthesis, making them promising candidates for treating metabolic diseases such as obesity and diabetes.
JOURNAL OF NATURAL PRODUCTS
(2022)
Article
Chemistry, Physical
Ashwini Prem Kumar, Subhankar Mandal, P. Prabitha, Syed Faizan, B. R. Prashantha Kumar, S. P. Dhanabal, Antony Justin
Summary: Peroxisome proliferator-activated receptor (PPAR-gamma) has become an important therapeutic target in various metabolic and neurodegenerative disorders. This study focuses on designing novel glitazones and evaluating their pharmacological activities through structural analysis, docking, and in vitro experiments.
JOURNAL OF MOLECULAR STRUCTURE
(2022)
Article
Computer Science, Artificial Intelligence
Vignesh Srinivasan, Klaus-Robert Mueller, Wojciech Samek, Shinichi Nakajima
Summary: In this article, the authors propose a strategy called Langevin cooling (L-Cool) to enhance existing methods in image translation and language translation tasks. They suggest using Langevin dynamics to bring fringe samples from low-density areas to high-density areas.
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS
(2023)
Article
Computer Science, Artificial Intelligence
Oliver Eberle, Jochen Buettner, Florian Kraeutli, Klaus-Robert Mueller, Matteo Valleriani, Gregoire Montavon
Summary: This paper proposes a method to make similarities interpretable by decomposing deep similarity models and provides insights into complex similarity models. The method is applied to assess similarity between historical documents in digital humanities.
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
(2022)
Article
Computer Science, Artificial Intelligence
Rick Wilming, Celine Budding, Klaus-Robert Mueller, Stefan Haufe
Summary: Machine learning is increasingly used in high-stakes decision-making, but complex ML models are often considered black boxes. This has led to the field of explainable AI (XAI), which aims to shed light on the inner workings of these models. Saliency methods are commonly used to rank input features, but validating their results is challenging. This study proposes a definition for feature importance and evaluates various explanation methods using a benchmark dataset.
Article
Neurosciences
Mina Jamshidi Idaji, Juanli Zhang, Tilman Stephani, Guido Nolte, Klaus-Robert Mueller, Arno Villringer, Vadim V. Nikulin
Summary: This study introduces a novel method (Harmoni) to remove harmonics from neuronal oscillations, addressing the issue of spurious neuronal interactions in CFS research. Through extensive testing, Harmoni has been shown to significantly suppress false within- and cross-frequency interactions while preserving genuine activities. Furthermore, applying Harmoni to real data reveals intricate remote connectivity patterns.
Article
Biochemistry & Molecular Biology
Philipp Keyl, Philip Bischoff, Gabriel Dernbach, Michael Bockmayr, Rebecca Fritz, David Horst, Nils Bluethgen, Gregoire Montavon, Klaus-Robert Mueller, Frederick Klauschen
Summary: The molecular heterogeneity of cancer cells contributes to the often partial response to targeted therapies and relapse of disease due to the escape of resistant cell populations. Single-cell sequencing has limitations in understanding this heterogeneity, and scGeneRAI is an explainable deep learning approach that can infer gene regulatory networks from single-cell RNA sequencing data to provide functional insights. Our method reveals characteristic network patterns for tumor cells and normal epithelial cells and allows the reconstruction of networks at the level of single cells, which helps characterize the heterogeneity of gene regulation within and across tumors.
NUCLEIC ACIDS RESEARCH
(2023)
Article
Multidisciplinary Sciences
Stefan Chmiela, Valentin Vassilev-Galindo, Oliver T. Unke, Adil Kabylda, Huziel E. Sauceda, Alexandre Tkatchenko, Klaus-Robert Mueller
Summary: We have developed an exact iterative approach to train global symmetric gradient domain machine learning (sGDML) force fields, which can accurately describe complex molecular systems and materials. We evaluated the accuracy and efficiency of sGDML on a newly developed MD22 benchmark dataset containing molecules from 42 to 370 atoms.
Article
Chemistry, Physical
Stefan Bluecher, Klaus-Robert Mueller, Stefan Chmiela
Summary: Kernel machines have achieved continuous progress in the field of quantum chemistry, especially in the low-data regime of force field reconstruction. However, the scalability of kernel machines has been hindered by their quadratic memory and cubical runtime complexity.
JOURNAL OF CHEMICAL THEORY AND COMPUTATION
(2023)
Article
Biochemical Research Methods
Kai J. Miller, Klaus-Robert J. Mueller, Gabriela Ojeda Valencia, Harvey J. Huang, Nicholas M. Gregg, Gregory A. J. Worrell, Dora Hermes
Summary: Single-pulse electrical stimulation, known as cortico-cortical evoked potential measurement, provides a valuable technique for understanding brain region interactions. This study presents a new method, called Canonical Response Parameterization (CRP), to quantify brain stimulation data and compare voltage response traces from different areas. This technique enables the quantification of various parameters, such as cross-projection magnitudes, response duration, canonical shape projection amplitudes, signal-to-noise ratios, explained variance, and statistical significance.
PLOS COMPUTATIONAL BIOLOGY
(2023)
Article
Mathematics
Alexander Bauer, Shinichi Nakajima, Klaus-Robert Mueller
Summary: The paper introduces an efficient exact inference method for local models, which allows for finer interactions between the energy of the core model and the sufficient statistics of the global terms. This greatly increases the range of admissible applications and improves upon the theoretical guarantees of computational efficiency.
Article
Computer Science, Artificial Intelligence
Lorenz Linhardt, Klaus-Robert Mueller, Gregoire Montavon
Summary: This paper investigates the issue of mismatches between the decision strategy of the explainable model and the user's domain knowledge, and proposes a new method EGEM to mitigate hidden flaws in the model. Experimental results demonstrate that the approach can significantly reduce reliance on Clever Hans strategies and improve the accuracy of the model on new data.
INFORMATION FUSION
(2024)
Article
Chemistry, Physical
Joshua Scheidt, Alexander Diener, Michael Maiworm, Klaus-Robert Mueller, Rolf Findeisen, Kurt Driessens, F. Stefan Tautz, Christian Wagner
Summary: A nanofabrication technique involving the assembly of functional molecular structures using a scanning probe microscope (SPM) has been developed. The key challenge was the lack of simultaneous actuation and imaging capabilities of the SPM tip, which hindered continuous monitoring of molecular configuration during manipulation. However, in this study, configuration monitoring was achieved through modelling the manipulation process as a partially observable Markov decision process (POMDP) and using a particle filter. The proposed methodology is an important step towards the robotic and possibly automated creation of supramolecular structures.
JOURNAL OF PHYSICAL CHEMISTRY C
(2023)
Article
Chemistry, Physical
Bipeng Wang, Ludwig Winkler, Yifan Wu, Klaus-Robert Muller, Huziel E. Sauceda, Oleg V. Prezhdo
Summary: Nonadiabatic molecular dynamics (MD) is crucial for understanding far-from-equilibrium processes, but requires expensive calculations of excitation energies and nonadiabatic couplings. In this study, a bidirectional long short-term memory network (Bi-LSTM) is employed in the time domain to interpolate the Hamiltonian, achieving significant computational savings compared to direct ab initio calculation. The Bi-LSTM-NAMD method outperforms previous models and captures slow and fast time scales, extending MD simulation times from picoseconds to nanoseconds.
JOURNAL OF PHYSICAL CHEMISTRY LETTERS
(2023)
Article
Automation & Control Systems
Armin W. Thomas, Ulman Lindenberger, Wojciech Samek, Klaus-Robert Mueller
Summary: Research has shown that transfer learning improves the performance of deep learning models in datasets with small sample sizes. In this study, the application of transfer learning to cognitive decoding analysis using functional neuroimaging data is systematically evaluated. Pre-trained deep learning models consistently achieve higher decoding accuracies and require less training time and data compared to models trained from scratch. The benefits of pre-training come from the ability to reuse learned features when training with new data. However, challenges arise when interpreting the decoding decisions of pre-trained models, as they may utilize fMRI data in unforeseen and counterintuitive ways.
JOURNAL OF THE FRANKLIN INSTITUTE-ENGINEERING AND APPLIED MATHEMATICS
(2023)
Article
Computer Science, Artificial Intelligence
Leo Andeol, Yusei Kawakami, Yuichiro Wada, Takafumi Kanamori, Klaus-Robert Mueller, Gregoire Montavon
Summary: This paper addresses the domain shift problem in machine learning and proposes a method that can generate more invariant representations and more stable prediction performance across different domains, using mathematical relations with the Wasserstein distance. Empirical results on multiple image datasets show the effectiveness of the proposed approach.
Article
Psychology, Educational
Amna Ghani, Caroline Di Bernardi Luft, Smadar Ovadio-Caro, Klaus-Robert Mueller, Joydeep Bhattacharya
Summary: Chance favors the prepared mind, said Louis Pasteur. In this study, the researchers investigated the brain's receptivity to integrate new information and the experience of creative insights known as Aha! moments. They hypothesized that the transient oscillatory states of the brain would characterize its preparedness for these insights. Through a real-time brain-state-dependent cognitive stimulation experiment, they found that participants were more successful in utilizing clues and experienced more Aha responses when clues were presented at the up-regulated state of right temporal alpha oscillation. Additionally, they observed a negative correlation between the coupling of alpha oscillation phase and gamma oscillation power and the frequency of Aha moments. These findings highlight the role of brain oscillations in the Aha experience and provide insights into the neural mechanism underlying the brain's receptivity to integrate semantic information.
CREATIVITY RESEARCH JOURNAL
(2023)
Article
Chemistry, Medicinal
Shibin Zhao, Julian Maceren, Mia Chung, Samantha Stone, Raphael Geiben, Melissa L. Boby, Bradley S. Sherborne, Derek S. Tan
Summary: Antibiotic resistance is a major threat to public health, with Gram-negative bacteria presenting unique challenges due to their low permeability and efflux pumps. Limited understanding of the chemical rules for overcoming these barriers hinders antibacterial drug discovery. Efforts to address this issue, such as screening compound libraries and using cheminformatic analysis, have led to the design of sulfamidoadenosines with diverse substituents, showing potential utility in accumulation in Escherichia coli.
BIOORGANIC & MEDICINAL CHEMISTRY LETTERS
(2024)
Article
Chemistry, Medicinal
Jichun Li, Qing Li, Shuai Xia, Jiahuang Tu, Longbo Zheng, Qian Wang, Shibo Jiang, Chao Wang
Summary: This study successfully developed a short peptide mimetic as a MERS-CoV fusion inhibitor by reproducing the key recognition features of the HR2 helix. The resulting 23-mer lipopeptide showed comparable inhibitory effect to the 36-mer HR2 peptide HR2P-M2. This has important implications for developing short peptide-based antiviral agents to treat MERS-CoV infection.
BIOORGANIC & MEDICINAL CHEMISTRY LETTERS
(2024)
Article
Chemistry, Medicinal
Krista Jaunsleine, Linda Supe, Jana Spura, Sten van Beek, Anna Sandstrom, Jessica Olsen, Carina Halleskog, Tore Bengtsson, Ilga Mutule, Benjamin Pelcman
Summary: Beta(2)-adrenergic receptor agonists can stimulate glucose uptake by skeletal muscle cells and are therefore potential treatments for type 2 diabetes. The chirality of compounds has a significant impact on the activity of these agonists. This study found that certain synthesized compounds showed higher glucose uptake activity. These findings provide important information for the design of novel beta(2)AR agonists for T2D treatment.
BIOORGANIC & MEDICINAL CHEMISTRY LETTERS
(2024)
Article
Chemistry, Medicinal
Xin Xu, Jia Chen, Guan Wang, Xiaojuan Zhang, Qiang Li, Xiaobo Zhou, Fengying Guo, Min Li
Summary: The study focuses on EZH2, a promising therapeutic target for various types of cancers. Researchers designed and synthesized a series of novel derivatives aiming to enhance the EZH2 inhibition activity. Among them, compound 28 displayed potent EZH2 inhibition activity and showed high anti-proliferative effects in lymphoma cell lines and xenograft mouse models. The study suggests that compound 28 has potential as a therapeutic candidate for EZH2-associated cancers.
BIOORGANIC & MEDICINAL CHEMISTRY LETTERS
(2024)
Article
Chemistry, Medicinal
Wei Zhang, Wei Liu, Ya-Dong Zhao, Li-Zi Xing, Ji Xu, Rui-Jun Li, Yun-Xiao Zhang
Summary: This study developed a series of aromatic amide derivatives based on Rhein and investigated their inhibitory activity against alpha-Syn aggregation. Two of these compounds showed promising potential in treating Parkinson's disease by stabilizing alpha-Syn's conformation and disassembling alpha-Syn oligomers and fibrils.
BIOORGANIC & MEDICINAL CHEMISTRY LETTERS
(2024)
Article
Chemistry, Medicinal
Mani Sharma, S. S. S. S. Sudha Ambadipudi, Neeraj Kumar Chouhan, V. Lakshma Nayak, Srihari Pabbaraja, Sai Balaji Andugulapati, Ramakrishna Sistla
Summary: Therapeutically active lipids in drug delivery systems can enhance the safety and efficacy of treatment. The liposome formulation created using synthesized biologically active lipids showed additive anti-cancer effects and reduced tumorigenic potential.
BIOORGANIC & MEDICINAL CHEMISTRY LETTERS
(2024)
