Article
Biophysics
Chiara Bernard, Angelo Rosario Carotenuto, Nicola Maria Pugno, Massimiliano Fraldi, Luca Deseri
Summary: Cell membranes are dynamic and heterogeneous environments that mediate various biological mechanisms. This study focuses on the theoretical modeling of the spatio-temporal evolution of lipid rafts, ordered lipid microdomains rich in signaling proteins. By coupling diffusive and mechanical phenomena, the researchers aim to explain the co-localization and synergy between protein activation and raft formation. This research provides insights into the remodeling of cell membranes and suggests mechanically based strategies for controlling their selectivity.
BIOMECHANICS AND MODELING IN MECHANOBIOLOGY
(2023)
Article
Biochemistry & Molecular Biology
Sumin Lee, Seeun Kim, Gyu Rie Lee, Sohee Kwon, Hyeonuk Woo, Chaok Seok, Hahnbeom Park
Summary: This study explores the improvement in modeling and docking strategies for GPCR drug discovery through deep learning (DL) based protein structure predictions. It shows that substantial improvements have been achieved by correct functional-state modeling of receptors and receptor-flexible docking. The success rate of docking on DL-based model structures approaches that of cross-docking on experimental structures, showing over 30% improvement from previous pre-DL protocols. Best-practice modeling strategies and model confidence estimation metric proposed in this work can serve as a guideline for future computer-aided GPCR drug discovery scenarios.
COMPUTATIONAL AND STRUCTURAL BIOTECHNOLOGY JOURNAL
(2023)
Article
Biochemistry & Molecular Biology
Preeti Jha, Shubhra Chaturvedi, Ruchika Bhat, Nidhi Jain, Anil K. Mishra
Summary: The 5HT1A receptor is crucial in the treatment of depression and anxiety disorders, and the developed homology model shows promise in designing high-affinity probes for these neurological disorders.
JOURNAL OF BIOMOLECULAR STRUCTURE & DYNAMICS
(2022)
Article
Chemistry, Medicinal
Tasia Amelia, Jacobus P. D. van Veldhoven, Matteo Falsini, Rongfang Liu, Laura H. Heitman, Gerard J. P. van Westen, Elena Segala, Gregory Verdon, Robert K. Y. Cheng, Robert M. Cooke, Daan van der Es, Adriaan P. IJzerman
Summary: In this study, the crystal structure of an engineered human adenosine A(2A) receptor bound to a partial agonist was determined and compared to structures bound to a full agonist or antagonist/inverse agonist. Interaction between the partial agonist and amino acids in the ligand binding pocket led to the development of a library of derivatives with varied activities. Some derivatives showed partial agonist properties while others acted as inverse agonists, with additional computational docking studies providing insights into this behavior.
JOURNAL OF MEDICINAL CHEMISTRY
(2021)
Article
Chemistry, Medicinal
Torben Gutermuth, Jochen Sieg, Tim Stohn, Matthias Rarey
Summary: In many molecular modeling applications, proteins are commonly treated as single, rigid structures despite the importance of conformational flexibility. However, the handling of this flexibility remains challenging. This study analyzes the presence and usage of alternate locations (AltLocs) in protein structure files and proposes an algorithm to automatically handle AltLocs, allowing structure-based methods to consider alternative protein conformations. The software tool AltLocEnumerator can be used as a preprocessor to effectively utilize AltLocs. While the impact of handling AltLocs is difficult to showcase statistically, it has a substantial influence on a case-by-case basis, making it a valuable approach in many modeling scenarios.
JOURNAL OF CHEMICAL INFORMATION AND MODELING
(2023)
Article
Biochemical Research Methods
Mingwei Pang, Wangqiu He, Xufeng Lu, Yuting She, Liangxu Xie, Ren Kong, Shan Chang
Summary: This study proposes a docking method that combines template-based modeling and a scoring function for ligand binding prediction in CASP15. Among the 21 targets, successful predictions were obtained for 14 targets in the top 5 submissions, and partially successful predictions were obtained for 4 targets. Particularly, the method successfully predicted the binding of most ligands for the most complex target, H1114. Analysis of failed systems revealed that conformational changes in the receptor protein may cause large structural deviations in ligand binding prediction. In summary, the hybrid docking scheme efficiently addresses the challenges in ligand binding prediction in CASP15.
BMC BIOINFORMATICS
(2023)
Article
Multidisciplinary Sciences
Ying Chen, Jinyi Zhang, Yuan Weng, Yueming Xu, Weiqiang Lu, Wei Liu, Mingyao Liu, Tian Hua, Gaojie Song
Summary: This study presents the structures of the human adenosine A2B receptor (A2BR) bound to its agonists NECA and BAY60-6583, elucidating the orthosteric binding pockets and their subtle differences. Selectivity is mainly determined by regions extended from the orthosteric pocket, and the key determinants for BAY60-6583's selectivity against A2BR are identified. This study provides a better understanding of ligand selectivity in the adenosine receptor family and offers a structural template for the development of A2BR ligands for related diseases.
Article
Chemistry, Medicinal
Lim Heo, Sangwoo Park, Chaok Seok
Summary: The article presents a novel method, GalaxyWater-wKGB, for predicting water positions on the protein surface, based on a statistical potential incorporating the generalized Born model. This method is accurate and rapid due to the effective statistical treatment, providing a more precise description of specific protein atom-water interactions compared to traditional methods.
JOURNAL OF CHEMICAL INFORMATION AND MODELING
(2021)
Article
Biochemistry & Molecular Biology
Ilona Michalik, Kamil J. Kuder, Katarzyna Kiec-Kononowicz, Jadwiga Handzlik
Summary: The goal of this study was to obtain a homology model of the GPR18 receptor in the inactive state and evaluate its stability and ability to recognize active ligands. The results indicate that meaningful molecular modeling/docking studies can be carried out using freely available software and academic licenses.
INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES
(2022)
Article
Biochemistry & Molecular Biology
Kwabena Owusu Dankwah, Jonathon E. Mohl, Khodeza Begum, Ming-Ying Leung
Summary: This study computationally predicted the binding of a single ligand to GPCRs from different families and uncovered similar binding pockets that contribute to ligand interactions. These findings can be applied to improve protein function inference, drug repurposing, drug toxicity prediction, and the acceleration of new drug development.
Article
Biochemical Research Methods
Brian J. Bender, Stefan Gahbauer, Andreas Luttens, Jiankun Lyu, Chase M. Webb, Reed M. Stein, Elissa A. Fink, Trent E. Balius, Jens Carlsson, John J. Irwin, Brian K. Shoichet
Summary: Structure-based docking screens of compound libraries are common in early drug and probe discovery. Best practices and control calculations are outlined to evaluate docking parameters prior to undertaking a large-scale prospective screen.
Article
Chemistry, Organic
Yohei Saito, Yukiko Kobayashi, Nanami Yoshida, Masuo Goto, Kyoko Nakagawa-Goto
Summary: Thio-salvinal (4) demonstrated significant antiproliferative effects with IC50 values below 0.95 μM against various cancer cell lines, except for HER2 negative breast cancer cell line MCF-7. However, related thio-lignans 5 and 6 showed weaker antiproliferative effects than 4 and were less potent than the parent natural benzofuran lignans 2 and 3. Newly synthesized thio-lignan 33 affected cell cycle progression by stimulating microtubule depolymerization and nuclear fragmentation.
JOURNAL OF ORGANIC CHEMISTRY
(2021)
Article
Biochemical Research Methods
Chenran Wang, Yang Chen, Yuan Zhang, Keqiao Li, Menghan Lin, Feng Pan, Wei Wu, Jinfeng Zhang
Summary: Protein ligand docking is a computational tool for predicting protein functions and screening drug candidates. In this study, a novel reinforcement learning approach called A3C was developed to address the challenging problem of protein ligand docking. The experimental results showed significant improvement in binding site prediction compared to a naive model.
BMC BIOINFORMATICS
(2022)
Article
Chemistry, Medicinal
Timofey V. Losev, Igor S. Gerasimov, Maria V. Panova, Alexey A. Lisov, Yana R. Abdyusheva, Polina V. Rusina, Eugenia Zaletskaya, Oleg V. Stroganov, Michael G. Medvedev, Fedor N. Novikov
Summary: Bioisosteres are molecules with different substituents but similar shapes. They are widely used in drug design to modify metabolism, bioavailability, and activity. However, predicting the affinity of bioisosteres with computational methods has been challenging due to their similarity to standard force fields. In this study, a quantum mechanical (QM)-cluster approach based on the GFN2-xTB method was developed and successfully applied to predict the biological activity change of H -> F bioisosteric replacements. The method showed superior accuracy compared to the ChemPLP scoring function and comparable to in vitro experiments, with a standard deviation of 0.60 kcal/mol.
JOURNAL OF CHEMICAL INFORMATION AND MODELING
(2023)
Article
Chemistry, Medicinal
Florent Barbault, Eric Breemond, Julien Rey, Pierre Tuffery, Francois Maurel
Summary: The elucidation of protein/inorganic surface interfaces is important for the development of bionanotechnology. However, the interfacial structures between proteins and metallic surfaces are not fully understood, hindering the development of devices. To overcome this, a new software called DockSurf is proposed to quickly propose reliable protein/surface structures. The software considers conformational exploration using Euler's angles and interaction energies derived from quantum mechanics computations.
JOURNAL OF CHEMICAL INFORMATION AND MODELING
(2023)
Article
Chemistry, Multidisciplinary
Wenyi Bian, Xueli Shen, Huang Tan, Xing Fan, Yunxia Liu, Haiping Lin, Youyong Li
Summary: The intrinsic coordinating effect of Fe single-atom catalysts in propane dehydrogenation was systematically studied using density functional theory (DFT) calculations. The Fe-N3P-C dual-coordinated site exhibited superior catalytic activity and selectivity at industrial temperatures due to its in-plane configuration that promotes C-H bond scission and offers an appropriate H diffusion rate, ensuring high propylene selectivity and catalyst regeneration.
CHINESE CHEMICAL LETTERS
(2023)
Article
Biochemistry & Molecular Biology
Kinga Ostrowska, Anna Lesniak, Weronika Gryczka, Lukasz Dobrzycki, Magdalena Bujalska-Zadrozny, Bartosz Trzaskowski
Summary: A series of piperazine-containing derivatives of 6-acetyl-7-hydroxy-4-methylcoumarin were designed and synthesized to study their affinity for serotonin receptors. Compounds 4 and 7 exhibited excellent activity for 5-HT1A receptors with Ki values comparable to 8-OH-DPAT. The tested compounds showed differential intrinsic activities in agonist and antagonist modes.
INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES
(2023)
Article
Nanoscience & Nanotechnology
Xiaomin Nie, Yujin Ji, Yi-min Ding, Youyong Li
Summary: Due to limited supply of lithium, the development of non-Li-ion batteries has become a research focus. In this study, the performance of chalcogenide-terminated MXenes as electrodes for Li-ion and non-Li-ion batteries was investigated using first-principles calculations. Different stacking types were observed in O/Te and S/Se terminated Ti2C multilayers. Ti2CO2 was found to be a potential anode material for Na- and K-ion batteries, while Ti2CS2 and Ti2CSe2 showed promise for Na-, K-, and Ca-ion batteries. Among these materials, Ti2CS2 exhibited the highest ion capacity of 616 mAh g(-1). These findings may inspire further experimental and theoretical studies of Ti2C-MXenes as electrodes for metal-ion batteries.
Article
Chemistry, Inorganic & Nuclear
Katarzyna Gajda, Adrian Sytniczuk, Laure Vendier, Bartosz Trzaskowski, Noel Lugan, Anna Kajetanowicz, Stephanie Bastin, Karol Grela, Vincent Cesar
Summary: Three Hoveyda-Grubbs complexes supported by N-(9-alkylfluorenyl)imidazol-2-ylidene ligands were synthesized. The C(sp(3))-H activation of the dangling alkyl group was studied for generating cyclometalated (C,C-NHC) ruthenium complexes for Z-selective olefin metathesis. The methyl derivative led to the expected cyclometalated complex, while no C(sp(2))-H activation of the fluorenyl moiety and no evolution/transformation were observed for the ethyl and benzyl derivatives, respectively. The cyclometalated complex exhibited Z/E stereoselectivity up to 94/6, despite its fragility under catalytic conditions. An unprecedented insertion of the alkylidene moiety into the Ru-C-NHC bond leading to ruthenium N-heterocyclic olefin complexes was also observed and supported by calculations of the corresponding reaction pathway.
EUROPEAN JOURNAL OF INORGANIC CHEMISTRY
(2023)
Article
Materials Science, Multidisciplinary
Yuyan Liu, Yujin Ji, Yi-Min Ding, Youyong Li, Shuit-Tong Lee
Summary: In this study, a comprehensive investigation of the MA(2)Z(4) family as anodes for LIBs and SIBs was conducted based on first-principle calculations. It was found that there is a linear relationship between the lowest unoccupied states energy level and ion adsorption energy, where lower energy level leads to stronger adsorption. Among the MA(2)Z(4) materials, NbGe2N4 was predicted as the most promising candidate for LIBs and VSi2P4 was better for SIBs, with high theoretical capacities and low ion diffusion barriers. Additionally, both NbGe2N4 and VSi2P4 demonstrated good phase stabilities. This study explores the application prospects of MA(2)Z(4) materials in LIBs and SIBs and provides insights into their intrinsic electronic mechanisms.
Article
Chemistry, Multidisciplinary
Jie Feng, Zhihao Dong, Yujin Ji, Youyong Li
Summary: By introducing a dynamic embedding layer, we propose a universal graph neural network called CrystalGNN, which can automatically update atomic inputs during the training process. We train a model based on this framework to accurately predict the formation energies of 10,500 IrO2 configurations and discover 8 unreported metastable phases. Among them, C2/m-IrO2 and P62-IrO2 are identified as excellent electrocatalysts that can reach the theoretical OER overpotential limit at their most stable surfaces. Our self-learning-input CrystalGNN framework exhibits reliable accuracy, generalization, and transferring ability and successfully accelerates the bottom-up catalyst design to boost the OER activity.
Article
Biophysics
Adrian Koterwa, Mattia Pierpaoli, Bozena Nejman-Falenczyk, Sylwia Bloch, Artur Zielinski, Wioletta Adamus-Bialek, Zofia Jeleniewska, Bartosz Trzaskowski, Robert Bogdanowicz, Grzegorz Wegrzyn, Pawel Niedzialkowski, Jacek Ryl
Summary: This manuscript presents a novel approach using multiparametric impedance discriminant analysis (MIDA) to address the challenges of electrode fouling and highly complex electrode nanoarchitecture in biosensors operating in real environments. Real-time monitoring combined with singular value decomposition and partial least squares discriminant analysis enables selective identification of the analyte from raw impedance data without the use of electric equivalent circuits. The proposed approach offers a limit of detection of 11.3 CFU/mL for detecting uropathogenic Escherichia coli in real human urine.
BIOSENSORS & BIOELECTRONICS
(2023)
Article
Chemistry, Physical
Zhihao Dong, Jie Feng, Yujin Ji, Youyong Li
Summary: We propose a self-learning-input graph neural network framework, called SLI-GNN, to predict the properties of both crystals and molecules. By using a dynamic embedding layer and the Infomax mechanism, the input features are dynamically updated and the average mutual information between local and global features is maximized. Experimental results show that our SLI-GNN achieves comparable performance to other GNNs in material property prediction, indicating promising potential for accelerating new material discovery.
JOURNAL OF PHYSICAL CHEMISTRY A
(2023)
Article
Chemistry, Physical
Hongshuai Wang, Jie Feng, Zhihao Dong, Lujie Jin, Miaomiao Li, Jianyu Yuan, Youyong Li
Summary: Organic photovoltaics have gained global attention for their unique advantages in developing low-cost, lightweight, and flexible power sources. Researchers have proposed functional molecular design and synthesis to accelerate the discovery of ideal organic semiconductors. However, experimental screening of a wide range of organic compounds is prohibitively expensive. In this study, a framework combining a deep learning model and an ensemble learning model is developed for rapid and accurate screening of organic photovoltaic molecules. This framework establishes the relationship between molecular structure, properties, and device efficiency, providing an efficient method for developing new organic optoelectronic materials.
NPJ COMPUTATIONAL MATERIALS
(2023)
Article
Chemistry, Physical
Yanxia Ma, Yuyan Liu, Yujin Ji, Youyong Li
Summary: In this study, the structural stabilities, electronic properties, and hydrogen evolution performances of nine kinds of 2D M4/3B2 materials were investigated using density functional theory calculations. The results showed that most of the materials were stable and promising for hydrogen production, except for Cr4/3B2. Monolayers of metallic Ti4/3B2 and Ta4/3B2 were susceptible to oxidation in aqueous environments, but had optimal hydrogen adsorption free energies and exchange current densities.
MATERIALS TODAY ENERGY
(2023)
Article
Chemistry, Physical
Rongfeng Guan, Pan Wang, Yujin Ji, Youyong Li, Yang Song
Summary: In this work, the pressure-induced phase transitions of N2H4BH3 were studied using vibrational spectroscopy, X-ray diffraction, and density functional theory (DFT). It was found that N2H4BH3 exhibits remarkable structural stability up to 15 GPa, followed by two phase transitions. DFT calculations revealed that the stability of N2H4BH3 and the late phase transformations are related to the pressure-mediated evolutions of dihydrogen bonding frameworks, the compressibility, and the enthalpies of the high-pressure polymorphs. These findings provide important insights into the structures and bonding properties of N2H4BH3 for hydrogen storage applications.
PHYSICAL CHEMISTRY CHEMICAL PHYSICS
(2023)
Article
Chemistry, Physical
Jie Feng, Yujin Ji, Youyong Li
Summary: We investigated the performance of copper alloys in NO electroreduction reaction (NORR) using first-principles calculations and machine learning (ML). We found that the adsorption energy of N atoms is an effective catalytic descriptor for NORR. By screening 140 copper alloys, Cu@Cu3Ni and Cu2Ni2@Cu3Ni were discovered with low limiting potentials and kinetic barriers. We constructed an accurate ML model predicting the adsorption energy and identified Ni as an optimal alloy element to enhance NORR activity. This work opens up new possibilities for efficient alloy catalyst design and ML-accelerated discovery of novel NORR catalysts.
JOURNAL OF MATERIALS CHEMISTRY A
(2023)
Article
Chemistry, Physical
Wenzhen Xu, Yunpeng Shu, Mengmeng Xu, Juan Xie, Youyong Li, Huilong Dong
Summary: In this study, the effect of strain engineering on the electrocatalysis of CO reduction reaction (CORR) by 2D transition metal embedded polyphthalocyanines (MPPcs) was computationally explored. It was found that only CrPPc under biaxial strain had the potential to significantly enhance the catalytic performance. The free energy diagrams showed that the optimal reaction pathway and rate-determining step were changed under specific biaxial strains, and applying 5% compressive strain on CrPPc resulted in unexpected electrocatalytic activity.
PHYSICAL CHEMISTRY CHEMICAL PHYSICS
(2023)
Article
Biochemistry & Molecular Biology
Wentao Qi, Dong Zhai, Danna Song, Chengcheng Liu, Junxia Yang, Lei Sun, Youyong Li, Xingwei Li, Weiqiao Deng
Summary: Considering the global challenge of low-cost and efficient anti-COVID-19 drug production, we developed a low-cost and efficient synthesis route for favipiravir using improved retrosynthesis software. This route involves only 3 steps under safe and near-ambient air conditions, achieving a yield of 32% and cost of $1.54 per g. We also applied the same strategy to optimize the synthesis of sabizabulin. These synthetic routes are expected to contribute to the prevention and treatment of COVID-19.
RSC MEDICINAL CHEMISTRY
(2023)
Article
Chemistry, Multidisciplinary
Piao Wang, Changle Zhang, Jiabao Ding, Yujin Ji, Youyong Li, Weifeng Zhang
Summary: Combining iridium dopants with highly active iridium atoms, Ir-SMO exhibits excellent performance for water oxidation in acidic conditions, making it an efficient and stable electrocatalyst.