Review
Pharmacology & Pharmacy
Anh T. N. Nguyen, Diep T. N. Nguyen, Huan Yee Koh, Jason Toskov, William MacLean, Andrew Xu, Daokun Zhang, Geoffrey I. Webb, Lauren T. May, Michelle L. Halls
Summary: The application of artificial intelligence in drug discovery for G protein-coupled receptors (GPCRs) is expanding rapidly. It can assist in understanding the actions of GPCRs, discovering new ligand-GPCR interactions, and predicting clinical responses. This article provides an overview of artificial intelligence concepts and its applications in different stages of GPCR drug discovery. The benefits and limitations of artificial intelligence are discussed, along with the potential for further development in assisting GPCR drug discovery.
BRITISH JOURNAL OF PHARMACOLOGY
(2023)
Article
Pharmacology & Pharmacy
Dandan Xia, Baoling Liu, Xiaowei Xu, Ya Ding, Qiuling Zheng
Summary: Drug target discovery is essential for drug innovation, as it elucidates the mechanism of drug action. The Fe3O4 nanoparticle-based approach developed in this study shows potential for drug-target screening in biological matrices by reducing endogenous interference and providing active sites for ligand-protein interactions.
JOURNAL OF PHARMACEUTICAL ANALYSIS
(2021)
Article
Biochemical Research Methods
Gangjun Feng, Xinyi Yuan, Ping Li, Rui Tian, Zhaoling Hou, Xiaoying Fu, Zhongman Chang, Jing Wang, Qian Li, Xinfeng Zhao
Summary: High-performance affinity chromatography is limited by its high cost and high pressure. In this study, the immobilization of beta2-adrenoceptor on a paper-based material successfully constructed a G protein-coupled receptor-in-paper chromatographic platform, which showed good retention of specific drugs and accurate drug-receptor binding constants analysis. The platform was proven to be cost-effective, easy to modify, and applicable for receptor-drug interaction analysis, shedding new light on paper chromatography applications.
JOURNAL OF CHROMATOGRAPHY A
(2021)
Article
Chemistry, Medicinal
Jingxing Wu, Yi Xiao, Mujie Lin, Hanxuan Cai, Duancheng Zhao, Yirui Li, Hailin Luo, Chuanqi Tang, Ling Wang
Summary: In this study, a total of 832 classification models were constructed using the FP-GNN deep learning method, based on the collection of 485,900 compounds and their bioactivity records. These models showed considerable predictive performance, with the highest AUC values of 0.91, 0.88, and 0.91 for targets, academia-sourced cell lines, and NCI60 cancer cell lines, respectively. A user-friendly webserver called DeepCancerMap was developed based on these models, providing various functions for anticancer drug discovery.
EUROPEAN JOURNAL OF MEDICINAL CHEMISTRY
(2023)
Article
Multidisciplinary Sciences
Vaithish Velazhahan, Ning Ma, Gaspar Pandy-Szekeres, Albert J. Kooistra, Yang Lee, David E. Gloriam, Nagarajan Vaidehi, Christopher G. Tate
Summary: GPCRs are divided into six classes, with structures of vertebrate GPCRs well understood but not of fungal class D GPCRs. This study reveals the structure of a class D GPCR in yeast and its coupling to G proteins, providing a template for the design of drugs to treat fungal diseases.
Article
Biochemistry & Molecular Biology
Nam Hyuk Kim, Sumin Kang, Ga Hyeon Park, Goeun Shim, Tae Hyun Kang, Yeon Gyu Yu
Summary: G protein-coupled receptors (GPCRs) have become a popular drug target due to their correlation with disease indications. However, preparing functional GPCRs and efficiently screening antibodies targeting GPCRs remain challenging. This study developed a platform to isolate GPCR-specific antibodies by addressing the difficulties in GPCR preparation, and successfully discovered three GPCR-specific antibodies.
Review
Biochemistry & Molecular Biology
Dehua Yang, Qingtong Zhou, Viktorija Labroska, Shanshan Qin, Sanaz Darbalaei, Yiran Wu, Elita Yuliantie, Linshan Xie, Houchao Tao, Jianjun Cheng, Qing Liu, Suwen Zhao, Wenqing Shui, Yi Jiang, Ming-Wei Wang
Summary: Recent progress in understanding the structure-function relationships of G protein-coupled receptors has accelerated drug development significantly. This article aims to provide a comprehensive overview of this important field to a broader readership interested in drug discovery.
SIGNAL TRANSDUCTION AND TARGETED THERAPY
(2021)
Review
Biochemistry & Molecular Biology
Andrew A. Bolinger, Andrew Frazier, Jun-Ho La, John A. Allen, Jia Zhou
Summary: G protein-coupled receptor 37 (GPR37) is an orphan receptor that is highly expressed in the central nervous system and has been implicated in various neurological conditions. Its cellular signaling mechanisms and endogenous receptor ligands are still unknown, but it shows promise as a new therapeutic target.
ACS CHEMICAL NEUROSCIENCE
(2023)
Review
Pharmacology & Pharmacy
Bui San Thai, Ling Yeong Chia, Anh T. N. Nguyen, Chengxue Qin, Rebecca H. Ritchie, Dana S. Hutchinson, Andrew Kompa, Paul J. White, Lauren T. May
Summary: Heart failure remains a significant cause of morbidity and mortality worldwide. Current treatment options have limitations, leading to many patients progressing to advanced stages. Exploration of novel therapeutics targeting G protein-coupled receptors (GPCRs) has shown promise, but efficacy and unwanted effects remain as challenges.
BRITISH JOURNAL OF PHARMACOLOGY
(2023)
Article
Biochemistry & Molecular Biology
Xianlong Gao, Garrett A. Enten, Anthony J. DeSantis, Matthias Majetschak
Summary: This study utilized various biotechniques to confirm that chemokine receptor 4, atypical chemokine receptor 3, alpha(1a)-adrenoceptor, and arginine vasopressin receptor 1A can form hetero-oligomers composed of 2-4 different protomers, with ligand binding and hetero-oligomerization regulating agonist-induced signaling transduction. These findings suggest that receptor hetero-oligomers have unique signaling properties different from individual protomers, providing a mechanism for context-dependent receptor function.
Review
Chemistry, Medicinal
Joshua W. Conner, Daniel P. Poole, Manuela Jorg, Nicholas A. Veldhuis
Summary: This review addresses the key challenges, synthesis approaches, and structure-activity relationships in recent fluorescent small molecule studies for GPCRs, and discusses the advantages of using high-resolution GPCR structures to inform conjugation strategies.
FUTURE MEDICINAL CHEMISTRY
(2021)
Article
Multidisciplinary Sciences
Li-Hua Zhao, Jingyu Lin, Su-Yu Ji, X. Edward Zhou, Chunyou Mao, Dan-Dan Shen, Xinheng He, Peng Xiao, Jinpeng Sun, Karsten Melcher, Yan Zhang, Xiao Yu, H. Eric Xu
Summary: This study presents the structures of CRF2R bound to UCN1 and coupled to G proteins G(11) and G(o), and compares them with the structure of CRF2R bound to G(s), uncovering the structural differences that determine the selective coupling of G protein subtypes by CRF2R.
NATURE COMMUNICATIONS
(2022)
Article
Biochemistry & Molecular Biology
Alessandra de Felice, Simone Aureli, Vittorio Limongelli
Summary: GPCRs, the largest human membrane receptor family, are important drug targets and CPG is a new computational approach that can help analyze cross-activity of drugs towards different GPCR receptors, aiding in the design of more selective compounds.
FRONTIERS IN MOLECULAR BIOSCIENCES
(2021)
Article
Pharmacology & Pharmacy
Tianduanyi Wang, Otto I. Pulkkinen, Tero Aittokallio
Summary: Most drug molecules have the ability to modulate multiple target proteins, which can lead to both therapeutic effects and unwanted side effects. Evaluating the selectivity of a compound is an important factor in drug development and repurposing efforts. Traditional methods for characterizing selectivity fall short in quantifying how selective a compound is against a particular target protein. In this study, we propose an optimization-based selectivity scoring method that allows for the identification of potent and selective compounds against given kinase targets. We demonstrate the effectiveness of this method in finding highly selective compounds in computational experiments using a large-scale kinase inhibitor dataset.
FRONTIERS IN PHARMACOLOGY
(2022)
Article
Chemistry, Medicinal
Yuxin Shi, Yi Chen, Liping Deng, Kui Du, Shaoyong Lu, Ting Chen
Summary: This article summarizes the known structural complexes of G protein-coupled receptors (GPCRs) bound to peptide ligands, with a focus on the interactions between the receptor and its peptide ligand at the orthosteric site. In-depth structural investigations have provided valuable insights into the molecular mechanisms underlying peptide recognition, contributing to the discovery of GPCR peptide drugs with improved therapeutic effects.
JOURNAL OF MEDICINAL CHEMISTRY
(2023)
Article
Chemistry, Multidisciplinary
Noureldin Saleh, Oliver Hucke, Gert Kramer, Esther Schmidt, Florian Montel, Radoslaw Lipinski, Boris Ferger, Timothy Clark, Peter W. Hildebrand, Christofer S. Tautermann
ANGEWANDTE CHEMIE-INTERNATIONAL EDITION
(2018)
Article
Chemistry, Medicinal
Christian A. Kuttruff, Margit Haile, Johannes Kraml, Christofer S. Tautermann
Article
Pharmacology & Pharmacy
Anita K. Nivedha, Christofer S. Tautermann, Supriyo Bhattacharya, Sangbae Lee, Paola Casarosa, Ines Kollak, Tobias Kiechle, Nagarajan Vaidehi
MOLECULAR PHARMACOLOGY
(2018)
Article
Chemistry, Medicinal
Christofer S. Tautermann, Florian Binder, Frank H. Buettner, Christian Eickmeier, Dennis Fiegen, Ulrike Gross, Marc A. Grundl, Ralf Heilker, Scott Hobson, Stefan Hoerer, Andreas Luippold, Volker Mack, Florian Montel, Stefan Peters, Supriyo Bhattacharya, Nagarajan Vaidehi, Gisela Schnapp, Sven Thamm, Markus Zeeb
JOURNAL OF MEDICINAL CHEMISTRY
(2019)
Article
Biochemistry & Molecular Biology
Anna-Katharina Apel, Robert K. Y. Cheng, Christofer S. Tautermann, Michael Brauchle, Chia-Ying Huang, Alexander Pautsch, Michael Hennig, Herbert Nar, Gisela Schnapp
Article
Chemistry, Medicinal
Aniket Magarkar, Gisela Schnapp, Anna-Katharina Apel, Daniel Seeliger, Christofer S. Tautermann
ACS MEDICINAL CHEMISTRY LETTERS
(2019)
Article
Pharmacology & Pharmacy
Loes E. M. Kistemaker, Carolina R. S. Elzinga, Christofer S. Tautermann, Michael P. Pieper, Daniel Seeliger, Suraya Alikhil, Martina Schmidt, Herman Meurs, Reinoud Gosens
BRITISH JOURNAL OF PHARMACOLOGY
(2019)
Article
Chemistry, Medicinal
Ferruccio Palazzesi, Marc A. Grundl, Alexander Pautsch, Alexander Weber, Christofer S. Tautermann
JOURNAL OF CHEMICAL INFORMATION AND MODELING
(2019)
Article
Biochemistry & Molecular Biology
Markus R. Hermann, Alexander Pautsch, Marc A. Grundl, Alexander Weber, Christofer S. Tautermann
Summary: Drug discovery is a costly and time-consuming process, but quantum chemistry methods can make it more efficient. Calculating the electrophilicity index can provide insights into the reactivity of covalent inhibitors, helping in drug design and development.
JOURNAL OF COMPUTER-AIDED MOLECULAR DESIGN
(2021)
Article
Multidisciplinary Sciences
Joshua J. Goings, Alec White, Joonho Lee, Christofer S. Tautermann, Matthias Degroote, Craig Gidney, Toru Shiozaki, Ryan Babbush, Nicholas C. Rubin
Summary: An accurate assessment of the potential computational advantages of quantum computers in chemical simulation is crucial for their deployment. This study explores the resources required for assessing the electronic structure of cytochrome P450 enzymes using quantum and classical computations, defining a boundary for classical-quantum advantage. The results show that simulation of large-scale CYP models has the potential to be a quantum advantage problem, emphasizing the interplay between classical computations and quantum algorithms in chemical simulation.
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
(2022)
Article
Chemistry, Medicinal
Sven Thamm, Marina K. Willwacher, Gary E. Aspnes, Tom Bretschneider, Nicholas F. Brown, Silke Buschbom-Helmke, Thomas Veser, Emanuele M. Gargano, Daniel Grabowski, Christoph Hoenke, Damian Matera, Katja Mueck, Stefan Peters, Sophia Reindl, Doris Riether, Matthias Schmid, Christofer S. Tautermann, Aaron M. Teitelbaum, Cornelius Truenkle, Martin Winter, Thomas Fox, Lars Wortmann
Summary: Genome-wide association studies have identified HSD17B13 as a potential target for the treatment of liver diseases, but its physiological function and disease-relevant substrate are unknown. In this study, a novel potent and selective HSD17B13 inhibitor (BI-3231) was identified through high-throughput screening using estradiol as a substrate. The compound was characterized for its functional, physicochemical, and DMPK properties, and its NAD+ dependency was investigated. To promote Open Science, the chemical probe BI-3231 will be made available to the scientific community for free.
JOURNAL OF MEDICINAL CHEMISTRY
(2023)
Article
Chemistry, Medicinal
Markus R. Hermann, Christofer S. Tautermann, Peter Sieger, Marc A. Grundl, Alexander Weber
Summary: We conducted a comprehensive study on predicting the reactivity of propynamides. Covalent inhibitors like propynamides have improved potency, selectivity, and unique pharmacologic properties compared to non-covalent counterparts. By using three different in silico methods, we were able to predict the in vitro properties of propynamides, a covalent warhead class found in approved drugs. While the electrophilicity index only applies to specific subclasses, adduct formation and transition state energies are good predictors of in vitro reactivity with glutathione (GSH). Overall, these methods are suitable for estimating the reactivity of propynamides, allowing for the fine tuning of reactivity and speeding up the design process of covalent drugs.
Article
Physics, Multidisciplinary
Thomas E. O'Brien, Michael Streif, Nicholas C. Rubin, Raffaele Santagati, Yuan Su, William J. Huggins, Joshua J. Goings, Nikolaj Moll, Elica Kyoseva, Matthias Degroote, Christofer S. Tautermann, Joonho Lee, Dominic W. Berry, Nathan Wiebe, Ryan Babbush
Summary: This study introduces a new quantum algorithm for computing molecular energy derivatives with significantly lower complexity. Numerical demonstrations show that this algorithm can greatly reduce the computation time for moderate-sized systems, and in fault-tolerant algorithms, the cost of estimating forces is bounded by the cost of estimating energies.
PHYSICAL REVIEW RESEARCH
(2022)
Article
Chemistry, Physical
Lennart Gundelach, Thomas Fox, Christofer S. Tautermann, Chris-Kriton Skylaris
Summary: This study demonstrates a realistic test of the linear-scaling DFT-QM-PBSA method for accurately calculating protein-ligand binding free energies, and compares the differences between quantum mechanical and classical approaches.
PHYSICAL CHEMISTRY CHEMICAL PHYSICS
(2022)
Article
Chemistry, Physical
Lennart Gundelach, Thomas Fox, Christofer S. Tautermann, Chris-Kriton Skylaris
Summary: The study explores the QM-PBSA method for calculating binding free energies of seven ligands to the T4-lysozyme L99A/M102Q mutant, finding that the convergence of QM-PBSA is similar to traditional MM-PBSA even with moderate sampling. The physically-motivated PBE exchange-correlation functional outperforms other modern functionals in the QM-PBSA framework.
PHYSICAL CHEMISTRY CHEMICAL PHYSICS
(2021)
Review
Pharmacology & Pharmacy
Karlie R. Sharma, Christine M. Colvis, Griffih P. Rodgers, Douglas M. Sheeley
Summary: There are many genes within the druggable genome that have not been studied, and the US National Institutes of Health's program provides resources to explore these genes, with the potential for rapid impact on human health.
DRUG DISCOVERY TODAY
(2024)
Review
Pharmacology & Pharmacy
Mohammad Sameer Khan, B. H. Jaswanth Gowda, Waleed H. Almalki, Tanuja Singh, Amirhossein Sahebkar, Prashant Kesharwani
Summary: Mitochondria-specific functional liposomes hold great potential for cancer therapy. This review discusses the association between mitochondria and tumor formation, as well as the advantages of liposomes in delivering drugs to mitochondria.
DRUG DISCOVERY TODAY
(2024)
Review
Pharmacology & Pharmacy
Choong Yong Ung, Cristina Correia, Hu Li, Christopher M. Adams, Jennifer J. Westendorf, Shizhen Zhu
Summary: With increasing human life expectancy, the global medical burden of chronic diseases is growing. Chronic diseases often involve malfunctioning of multiple organs, and understanding the interorgan crosstalk is crucial to understanding the etiology of chronic diseases. Researchers have proposed the locked-state model (LoSM) and cutting-edge systems biology and artificial intelligence strategies to decipher chronic multiorgan locked states. The findings have important clinical implications for improving treatments for chronic diseases.
DRUG DISCOVERY TODAY
(2024)