Article
Biochemistry & Molecular Biology
Laise P. A. Chiari, Aldineia P. da Silva, Kathia M. Honorio, Alberico B. F. da Silva
Summary: This study used quantum and chemometric methods to investigate the relationship between the structure and psychoactivity of 50 cannabinoid compounds. QSAR models were successfully built to predict the biological activities of these compounds, and compounds Ic14, Ic18, and Ic19 showed higher predicted biological activities than the main cannabinoid compounds Delta 9-THC and Delta 8-THC. Compound Ic21 stood out as having the highest predicted biological activity in interaction with the CB2 receptor.
JOURNAL OF MOLECULAR MODELING
(2023)
Article
Chemistry, Physical
A. Elsamman, K. F. Khaled, Shimaa Abdel Halim, N. S. Abdelshafi
Summary: This study investigated the corrosion inhibition abilities of seven newly synthesized bispyrazole derivatives on 304 stainless steel in hydrochloric acid solutions. A predictive model was developed using quantitative structure-activity relationship (QSAR) to relate molecular descriptors with inhibition efficiencies. The model was validated by predicting the performance of another inhibitor in the same bispyrazole family.
JOURNAL OF MOLECULAR STRUCTURE
(2023)
Review
Pharmacology & Pharmacy
Xuesong Wang, Gerard J. P. van Westen, Laura H. Heitman, Adriaan P. IJzerman
Summary: G protein-coupled receptors (GPCRs) are the largest class of membrane proteins in the human genome, regulating various biological processes and serving as targets for a significant percentage of drugs on the market. Yeast serves as a useful model for studying GPCRs and offers opportunities for novel drug discovery.
BIOCHEMICAL PHARMACOLOGY
(2021)
Article
Pharmacology & Pharmacy
Harmandeep Kaur, Veera Ganesh Yerra, Sri Nagarjun Batchu, Duc Tin Tran, M. D. Golam Kabir, Youan Liu, Suzanne L. Advani, Phelopater Sedrak, Laurette Geldenhuys, Karthik K. Tennankore, Penelope Poyah, Ferhan S. Siddiqi, Andrew Advani
Summary: In this study, a transcriptional profile of activated kidney fibroblasts and the GPCRs they express was established in mouse models of kidney disease. The marker Tcf21 and the GPCRs Adgra2 and S1pr3 were found to be highly expressed in these activated fibroblasts. This research provides new insights into potential therapeutic targets for treating CKD.
BRITISH JOURNAL OF PHARMACOLOGY
(2023)
Review
Chemistry, Medicinal
Hyeonyeong Im, Ji-Hyun Park, Seowoo Im, Juhyeong Han, Kyungmin Kim, Yun-Hee Lee
Summary: The high incidence of obesity has led to an increased need to discover new therapeutic targets. Recent research has shown that G-protein coupled receptors (GPCRs) could be potential therapeutic targets to regulate adipose tissue metabolism.
ARCHIVES OF PHARMACAL RESEARCH
(2021)
Article
Chemistry, Physical
Nilima Rani Das, Sneha Prabha Mishra, P. Ganga Raju Achary
Summary: This study constructed QSAR models for predicting pEC50(M) for the A(2A) adenosine receptor using different descriptors, showing satisfactory performance. The models were evaluated using statistical parameters and validation techniques, demonstrating stable performance.
JOURNAL OF MOLECULAR STRUCTURE
(2021)
Review
Biochemistry & Molecular Biology
Efpraxia Tzortzini, Antonios Kolocouris
Summary: Most membrane lipids interact with GPCRs structures and modulate their function. PIP2 and cholesterol have an impact on the conformational equilibria of the A(2A) adenosine receptor.
Article
Biochemistry & Molecular Biology
Canyong Guo, Lingyun Yang, Zhijun Liu, Dongsheng Liu, Kurt Wuthrich
Summary: Eight hundred and twenty-six human G protein-coupled receptors (GPCRs) play a significant role in mediating the actions of hormones, neurotransmitters, and drugs. Studying the structure and dynamics of GPCRs in lipid bilayer environments is crucial for understanding their functionality and developing new drugs. This study incorporates the A(2A) adenosine receptor into lipid nanodiscs, providing a detergent-free environment for structural studies using NMR. The findings demonstrate the stability and mimicry of the lipid nanodisc and LMNG/CHS micelles in preserving the overall fold and local structure of the receptor.
Article
Chemistry, Organic
Sang Xiong, Hao Wu, Zhiyuan Liu, Baosen Zhang
Summary: The GFA algorithm was used to model the QSAR of thiadiazole derivatives, showing that quantum descriptors are a better choice for predicting lubricant performance. Friction coefficient of the lubricants is inversely proportional to their inhibition efficiency and oil film strength for the thiadiazole derivatives.
POLYCYCLIC AROMATIC COMPOUNDS
(2022)
Article
Chemistry, Physical
Laise P. A. Chiari, Aldineia P. da Silva, Aline A. de Oliveira, Celio F. Lipinski, Kathia M. Honorio, Alberico B. F. da Silva
Summary: Neuropathic pain is a difficult-to-treat syndrome that significantly impacts patients' quality of life, with current drugs showing limitations. Research suggests the sigma-1 receptor as a promising target for treatment. Using QSAR techniques, new sigma-1R antagonists with significant biological affinity values were successfully designed and validated.
JOURNAL OF MOLECULAR STRUCTURE
(2021)
Article
Multidisciplinary Sciences
Naveen Thakur, Arka P. P. Ray, Liam Sharp, Beining Jin, Alexander Duong, Niloofar Gopal Pour, Samuel Obeng, Anuradha V. V. Wijesekara, Zhan-Guo Gao, Christopher R. R. McCurdy, Kenneth A. A. Jacobson, Edward Lyman, Matthew T. T. Eddy
Summary: The impact of anionic lipids on the function-related conformational equilibria of A(2A) adenosine receptor was investigated using NMR spectroscopy. Anionic lipids primed the receptor to form complexes with G proteins through a conformational selection process. Computational models showed that anionic lipids mimic the interactions between a G protein and positively charged residues in the receptor, stabilizing a pre-activated receptor conformation.
NATURE COMMUNICATIONS
(2023)
Article
Cell Biology
Guillaume Ferre, Kara Anazia, Larissa O. Silva, Naveen Thakur, Arka P. Ray, Matthew T. Eddy
Summary: G protein-coupled receptor (GPCR) can form ternary signaling complexes with intracellular proteins in response to binding extracellular ligands. By studying the dynamic process of GPCR complex formation with the human A2A adenosine receptor (A2AAR) and an engineered Gs protein, mini-Gs, it was found that the conformation of A2AAR is similar between complexes with an agonist and mini-Gs and with an agonist alone. However, a highly dynamic hot spot of A2AAR was observed in the ternary complex, suggesting an allosteric connection mechanism involving structural plasticity.
Article
Pharmacology & Pharmacy
Alberto Martire, Rita Pepponi, Francesco Liguori, Cinzia Volonte, Patrizia Popoli
Summary: Research has shown that levels and functions of purinergic ionotropic P2X7 receptors are altered in cellular and animal models of Huntington's disease, and in some experimental settings, this abnormal functioning may be attributed to presynaptic activation of A(1) receptors.
FRONTIERS IN PHARMACOLOGY
(2021)
Article
Engineering, Environmental
Giovanna J. Lavado, Diego Baderna, Edoardo Carnesecchi, Alla P. Toropova, Andrey A. Toropov, Jean Lou C. M. Dorne, Emilio Benfenati
Summary: Soil pollution is a critical environmental challenge that can have adverse effects on both humans and the ecosystem. Various bioassays have been developed to investigate the soil ecotoxicity of chemicals, including a 28-day collembolan reproduction test with the springtail Folsomia candida. Despite limited toxicity data for Collembola, QSAR models have been developed for predicting reproductive toxicity induced by organic compounds in Folsomia candida, showing good predictive performance for ecological risk assessment of chemicals.
JOURNAL OF HAZARDOUS MATERIALS
(2022)
Article
Multidisciplinary Sciences
Fatima Ezzahra Bennani, Latifa Doudach, Khalid Karrouchi, Youssef El Rhayam, Christopher E. Rudd, M'hammed Ansar, My El Abbes Faouzi
Summary: Despite decades of scientific studies, cancer remains a leading cause of illness and death globally. This study developed six 2D-QSAR models and used them to predict the anti-cancer activity of pyrazole derivatives.
Article
Chemistry, Medicinal
Arkaprava Banerjee, Agnieszka Gajewicz-Skretna, Kunal Roy
Summary: In this study, a novel quantitative read-across structure-property relationship (q-RASPR) approach was used to model the specific surface area of various perovskites by combining Read-Across (RA) and quantitative structure-property relationship (QSPR). Several machine learning models were developed using different algorithms based on error-based measures and previously selected features. The PLS model was selected as the best predictor for specific surface area, and the new q-RASPR method shows promise for predicting other property endpoints in materials science.
MOLECULAR INFORMATICS
(2023)
Article
Marine & Freshwater Biology
Aniket Nath, Probir Kumar Ojha, Kunal Roy
Summary: In this study, toxicity models for PCNs were developed using 2D descriptors and validated using internal and external validation metrics. The models were interpreted using descriptors and endpoint values for better understanding. The prediction quality was improved using a novel quantitative read-across approach.
AQUATIC TOXICOLOGY
(2023)
Article
Chemistry, Medicinal
Arkaprava Banerjee, Kunal Roy
Summary: The novel q-RASAR approach enhances the external prediction quality of conventional QSAR models by incorporating novel similarity-based functions as additional descriptors. This study compares q-RASAR models developed using different machine learning algorithms, showing improved predictive capabilities compared to previous QSAR models. The incorporation of RASAR descriptors, RA function, gm, and average similarity is crucial in developing accurate q-RASAR models.
CHEMICAL RESEARCH IN TOXICOLOGY
(2023)
Article
Automation & Control Systems
Arkaprava Banerjee, Kunal Roy
Summary: Recently, a new concept called quantitative Read-Across Structure-Activity Relationship (q-RASAR) has been introduced to improve the predictivity of models in quantitative structure-activity relationship (QSAR) modeling by using machine learning similarity functions. In this study, the q-RASAR approach is applied to predict hERG K+ channel inhibition cardiotoxicity using curated data from literature. The resulting models show enhanced predictivity and can be used for quick screening of molecules for cardiotoxic potential in the drug discovery pipeline.
CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS
(2023)
Article
Agriculture, Multidisciplinary
Shilpayan Ghosh, Mainak Chatterjee, Kunal Roy
Summary: A novel quantitative modeling approach, called q-RASPR, was developed to predict the retention time (log t (R)) of pesticidal compounds in reverse-phase high-performance liquid chromatography (HPLC). The model, using similarity-based descriptors, showed good fit, robustness, and external predictivity. The study also revealed that lipophilicity is the most important chemical property that positively correlates with the retention time (log t (R)).
JOURNAL OF AGRICULTURAL AND FOOD CHEMISTRY
(2023)
Article
Chemistry, Multidisciplinary
R. Paul, J. Roy, K. Roy
Summary: Soil invertebrates are important indicators of soil quality, but there are few in silico models available for assessing the soil toxicity of chemicals. In this study, soil ecotoxicity data for Folsomia candida were collected and analyzed using quantitative structure-activity relationship (QSAR) analysis. The developed models showed that factors such as molecular weight, phosphate groups, electron donor groups, and polyhalogen substitution have a significant impact on soil ecotoxicity. These models can be used for prioritizing the ecotoxicological risk assessment of organic chemicals in soil.
SAR AND QSAR IN ENVIRONMENTAL RESEARCH
(2023)
Article
Chemistry, Multidisciplinary
J. Roy, K. Roy
Summary: Metal oxide nanoparticles (MeOxNPs) can be made safer by understanding the interaction between the immune system and nanoparticles. A nano-quantitative structure-activity relationship (nano-QSAR) model can be used to quickly and conveniently evaluate nanoparticle risk. Researchers developed nano-QSAR models to determine the inflammatory potential of MeOxNPs based on the THP-1 cell line. The results showed that periodic table-based descriptors can be reliable for modeling pro-inflammatory potential, which can be used to design metal oxide nanoparticles with lower toxicity.
SAR AND QSAR IN ENVIRONMENTAL RESEARCH
(2023)
Article
Toxicology
Ankur Kumar, Probir Kumar Ojha, Kunal Roy
Summary: Chronic toxicity is an important endpoint in toxicology that affects human health. This study aimed to develop a quantitative structure-activity relationship (QSAR) model to predict the chronic toxicity of compounds. Important descriptors were selected using stepwise regression and a genetic algorithm. The statistically validated model demonstrated reliability, robustness, and predictive ability. Additionally, factors such as hydrophobicity, electronegativity, lipophilicity, bulkiness, complex chemical structure, bridgehead atoms, and phosphate group were found to play a crucial role in chronic toxicity.
COMPUTATIONAL TOXICOLOGY
(2023)
Article
Chemistry, Medicinal
Arkaprava Banerjee, Kunal Roy
Summary: The field of cheminformatics has advanced, leading to a decrease in animal testing by using cheminformatics methods to predict the activity, property, and toxicity of chemicals. The emerging concept of read-across structure-activity relationship (RASAR) utilizes similarity functions derived from chemical information to develop highly predictive models. This study aims to demonstrate the improvement in predicting the skin-sensitizing potential of organic compounds by developing classification-based RASAR (c-RASAR) models.
CHEMICAL RESEARCH IN TOXICOLOGY
(2023)
Article
Nanoscience & Nanotechnology
Joyita Roy, Souvik Pore, Kunal Roy
Summary: This study used nano-QSAR models to predict the cytotoxicity of heavy metals adsorbed on nano-TiO2 to cells. The models were developed using an ensemble learning approach and periodic table descriptors, and achieved good predictive performance.
BEILSTEIN JOURNAL OF NANOTECHNOLOGY
(2023)
Article
Nanoscience & Nanotechnology
Arkaprava Banerjee, Supratik Kar, Souvik Pore, Kunal Roy
Summary: The RASAR approach based on read-across structure-activity relationship is able to efficiently predict the cytotoxicity of TiO2-based multi-component nanoparticles and enhance the external prediction quality of QSAR models.
Article
Marine & Freshwater Biology
Shilpayan Ghosh, Mainak Chatterjee, Kunal Roy
Summary: We have developed quantitative toxicity prediction models for organic pesticides of agricultural importance using a novel quantitative Read-across structure-activity relationship approach. The models were validated using experimental data of different fish species and were found to have good fit, robustness, and external predictivity. The qRASAR approach shows potential as an effective alternative method for aquatic toxicity prediction and ecotoxicity potential identification.
AQUATIC TOXICOLOGY
(2023)
Article
Chemistry, Analytical
Mainak Chatterjee, Kunal Roy
Summary: This study developed a predictive model for the toxicity of mixtures of antibiotics and their degradation products using in silico new approach methodologies and machine-learning algorithms. The model showed promising quality and predictability, and could be used for environmental risk assessment and toxicity prediction of antibiotic mixtures. The study highlights the importance of understanding the environmental risks and impacts of antibiotics and their degradation products.
ENVIRONMENTAL SCIENCE-PROCESSES & IMPACTS
(2023)
Article
Materials Science, Multidisciplinary
Shubham Kumar Pandey, Arkaprava Banerjee, Kunal Roy
Summary: The quantitative Read-Across Structure-Property Relationship (q-RASPR) is a novel method that combines similarity-based predictions and statistical modelling-based predictions to predict the detonation heat of nitrogen-containing compounds. The study applied the q-RASPR modeling approach and various ML algorithms, and selected the best model based on external validation metrics. The developed model shows enhanced prediction quality compared to previous models and can be used effectively for the detection of the detonation heat of compounds containing nitrogen.
MATERIALS ADVANCES
(2023)
Review
Chemistry, Multidisciplinary
Joyita Roy, Kunal Roy
Summary: With the rapid growth of nanotechnology, understanding the hazardous effects of metal oxide nanoparticles in the ecosystem is crucial. Quantitative structure-activity relationship (QSAR) models, using molecular descriptors, play a vital role in toxicological research. However, classical QSAR descriptors cannot accurately describe the structural details of metal oxide nanostructures, making modeling complex. This review discusses the use of periodic table-based descriptors in nano-QSAR modeling, their advantages in accurately simulating the toxicity of various nanomaterials, and the potential for developing universal descriptors.
ENVIRONMENTAL SCIENCE-NANO
(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)