Article
Chemistry, Medicinal
Zengrui Wu, Qiaohui Wang, Hongbin Yang, Jiye Wang, Weihua Li, Guixia Liu, Yi Yang, Yuzheng Zhao, Yun Tang
Summary: The study discovered new compounds targeting NQO1 through network-based analysis and identification of privileged substructures from a natural product library. Experimental validation revealed potential anticancer activity of the compounds, showing the effectiveness of the workflow and computational methods in drug discovery and development.
JOURNAL OF CHEMICAL INFORMATION AND MODELING
(2021)
Article
Biochemistry & Molecular Biology
Karen Rodriguez-Villar, Lilian Yepez-Mulia, Miguel Cortes-Gines, Jacobo David Aguilera-Perdomo, Edgar A. Quintana-Salazar, Kevin Samael Olascoaga Del Angel, Francisco Cortes-Benitez, Juan Francisco Palacios-Espinosa, Olivia Soria-Arteche, Jaime Perez-Villanueva
Summary: This study synthesized 22 new indazole derivatives and evaluated their antiprotozoal activity, revealing structural features that favor activity against protozoa.
Article
Biochemistry & Molecular Biology
Rodinei Vieira Veloso, Anwar Shamim, Yann Lamarrey, Helio A. Stefani, Juliana Mozer Sciani
Summary: Sickle cell disease is a genetic condition with no effective treatment currently available. Research has identified a new antioxidant molecule that can reduce oxidative stress, showing promise for the treatment of SCD.
BIOORGANIC CHEMISTRY
(2021)
Article
Construction & Building Technology
Bao Meng, Liangde Li, Weihui Zhong, Zheng Tan, Yuhui Zheng
Summary: The study demonstrated that as the span ratio of composite beams increased, the bearing capacities of the structures decreased and displacements increased. The primary failure mode involved tension fractures in the long leg of the top/seat angle. Short composite beams provided greater total resistance compared to long composite beams.
STEEL AND COMPOSITE STRUCTURES
(2021)
Review
Biochemistry & Molecular Biology
Samantha Stone, David J. Newman, Steven L. Colletti, Derek S. Tan
Summary: Natural products have been playing a significant role in drug discovery from 1981 to 2019, with half of new chemical entities being structurally based on natural products. These natural product-based drugs exhibit a wide range of diversity in chemical space, while macrocycles occupy distinctive regions.
NATURAL PRODUCT REPORTS
(2022)
Article
Agriculture, Multidisciplinary
Yisheng Wang, Youjin Xiong, Eduardo Alejandro Lozano Garcia, Yiqing Wang, Christopher J. Butch
Summary: This article examines the chemical diversity of herbicides and finds that the development of new herbicidal mechanisms and scaffolds has been slower compared to pharmaceuticals. By using machine learning and molecular docking, researchers propose a strategy to increase the diversity of herbicide scaffolds and demonstrate its effectiveness.
JOURNAL OF AGRICULTURAL AND FOOD CHEMISTRY
(2022)
Article
Biochemistry & Molecular Biology
Silvia Cesarini, Ilaria Vicenti, Federica Poggialini, Massimiliano Secchi, Federica Giammarino, Ilenia Varasi, Camilla Lodola, Maurizio Zazzi, Elena Dreassi, Giovanni Maga, Lorenzo Botta, Raffaele Saladino
Summary: Current therapy against SARS-CoV-2 relies on Remdesivir, Molnupiravir, and Nirmatrelvir, but they have limitations. By synthesizing and evaluating derivatives, a promising compound with antiviral activity and low cytotoxicity was identified as a candidate for future optimization studies.
Article
Computer Science, Artificial Intelligence
Junjie Chen, Li Niu, Liqing Zhang
Summary: This paper introduces a method that uses RGB input to hallucinate depth attention, and builds the model upon modulated deformable convolutional layer and hallucinate dual attention. Experimental results demonstrate that the method outperforms the state-of-the-art methods in depth privileged scene recognition.
IEEE TRANSACTIONS ON IMAGE PROCESSING
(2021)
Article
Chemistry, Medicinal
Mabilly Cox Holanda de Barros Dias, Mayara Souza Barbalho, Gevanio Bezerra de Oliveira Filho, Marcos Verissimo de Oliveira Cardoso, Ana Cristina Lima Leite, Aline Caroline da Silva Santos, Ana Catarina Cristovao Silva, Maria Carolina Accioly Brelaz de Castro, Danielle Maria Nascimento Moura, Luiz Felipe Gomes Rebello Ferreira, Marcelo Zaldini Hernandes, Rafael de Freitas e Silva, Valeria Rego Alves Pereira
Summary: Chagas disease is a deadly neglected disease that is becoming a global threat. This study presents a series of novel 1,3-thiazole compounds that show potent activity against Trypanosoma cruzi, the parasite causing Chagas disease. These compounds have potential as drug candidates for the treatment of Chagas disease.
EUROPEAN JOURNAL OF MEDICINAL CHEMISTRY
(2023)
Review
Chemistry, Medicinal
Yichao Wan, Jiabing Long, Han Gao, Zilong Tang
Summary: Cancer is the second leading health killer in human society, and there is an urgent need to develop new anticancer agents with high activity and low toxicity due to multi-drug resistance and side effects. 2-Aminothiazole, as an important scaffold with potential anti-cancer activity, plays a crucial role in the discovery of anti-cancer agents.
EUROPEAN JOURNAL OF MEDICINAL CHEMISTRY
(2021)
Article
Chemistry, Multidisciplinary
D. Sai Reddy, Ivan M. Novitskiy, Andrei G. Kutateladze
Summary: A novel photoinduced cascade reaction has been developed to access complex nitrogen polyheterocycles. This reaction involves excited state intramolecular proton transfer in aromatic amino ketones with tethered dual unsaturated pendants, leading to the formation of four sigma bonds and setting six new stereogenic centers in a single photochemical step with significant complexity increases of up to 220 mcbit.
ANGEWANDTE CHEMIE-INTERNATIONAL EDITION
(2022)
Article
Energy & Fuels
Yi Gao, Yang Zhao, Chengcheng Liu, Bin Yang
Summary: This study integrated the structure and density data of C2-C30 oxygen-containing compounds and established a comprehensive database. The results showed that ring structures had a greater contribution to density, while side chains and single alkane ring frameworks had similar density contribution distributions. The contribution of multi-ring alkane substructures to density first increased and then decreased with the increase of the average number of atoms in the ring and the variance of the number of atoms.
Article
Pharmacology & Pharmacy
Ayushi Sharma, Anjana Goel, Zhijian Lin
Summary: This study aimed to evaluate the effects of Nyctanthes arbor-tristis (NAT) extract on sub-acute toxicity, pharmacovigilance, and anti-rheumatic biomarkers. The results suggest that NAT leaf extract at a dose of 500 mg/kg could be a promising therapeutic option for the treatment of inflammatory arthritis.
FRONTIERS IN PHARMACOLOGY
(2023)
Review
Chemistry, Multidisciplinary
M. Sc. Shivani Chauhan, Tarana Umar, Manpreet K. K. Aulakh
Summary: The burden of neurodegenerative diseases is increasing along with longer life expectancy. Developing effective methods to prevent and treat these diseases is a major challenge. Quinoline and its derivatives have shown significant anti-neurodegenerative activity and have been studied extensively for their potential in developing novel medications. Various heterocyclic substituent quinoline derivatives with good anti-neurodegenerative activity have been discussed in this review.
Article
Biochemistry & Molecular Biology
Tsun-Thai Chai, Clara Chia-Ci Wong, Mohamad Zulkeflee Sabri, Fai-Chu Wong
Summary: In this study, the potential of seafood paramyosins (SP) as sources of anti-angiotensin-converting-enzyme (ACE) and anti-dipeptidyl-peptidase (DPP-IV) peptides was investigated. Through in silico digestion and analysis, several known and novel anti-ACE and anti-DPP-IV peptides were identified in SP. Molecular docking and dynamics simulations revealed the mechanisms of interaction between these peptides and ACE/DPP-IV. The study suggests that SP could be a promising source of bioavailable and safe anti-ACE and anti-DPP-IV peptides. Overall, the study provides valuable insights into the potential therapeutic applications of SP-derived peptides.
Article
Chemistry, Multidisciplinary
Phasit Charoenkwan, Nalini Schaduangrat, Pietro Lio, Mohammad Ali Moni, Pramote Chumnanpuen, Watshara Shoombuatong
Summary: This study presents a machine learning-based method for rapid identification of peptides with antimalarial activity using only sequence information. The proposed method achieves high accuracy and correlation in predicting the antimalarial ability of peptides, and provides insights into the functional mechanisms of antimalarial peptides. Additionally, a user-friendly online computational platform is made available for high-throughput identification of potential antimalarial peptide candidates.
Article
Biology
Phasit Charoenkwan, Chonlatip Pipattanaboon, Chanin Nantasenamat, Md Mehedi Hasan, Mohammad Ali Moni, Pietro Lio, Watshara Shoombuatong
Summary: Despite existing cancer therapies, the development of new and effective treatments is necessary to address the ongoing cancer recurrence and new cases. This study proposes a new machine learning-based approach, PSRTTCA, for improving the identification and characterization of tumor T cell antigens (TTCAs) based on their primary sequences.
COMPUTERS IN BIOLOGY AND MEDICINE
(2023)
Article
Biochemistry & Molecular Biology
Adeel Malik, Watshara Shoombuatong, Chang-Bae Kim, Balachandran Manavalan
Summary: A machine learning-based predictor called GPApred was developed to identify LPXTG-like proteins from their primary sequences. This predictor can be utilized for functional characterization and drug targeting in further research.
INTERNATIONAL JOURNAL OF BIOLOGICAL MACROMOLECULES
(2023)
Article
Anatomy & Morphology
Chanasorn Poodendan, Athikhun Suwannakhan, Tidarat Chawalchitiporn, Yuichi Kasai, Chanin Nantasenamat, Laphatrada Yurasakpong, Sitthichai Iamsaard, Arada Chaiyamoon
Summary: This study investigated the morphometric parameters of the C1 vertebra and evaluated its potential for sex prediction. The results showed that the C1 vertebra was longer in males compared to females. Evaluation of these parameters is important for preoperative assessment and treatment of atlas dislocation, and they can also be used for sex prediction.
SURGICAL AND RADIOLOGIC ANATOMY
(2023)
Article
Biology
Phasit Charoenkwan, Pramote Chumnanpuen, Nalini Schaduangrat, Changmin Oh, Balachandran Manavalan, Watshara Shoombuatong
Summary: In this study, a novel computational approach called PSRQSP was developed to improve the prediction and analysis of QSPs. Experimental results showed that PSRQSP outperformed conventional methods in identifying QSPs and demonstrated its predictive capability and effectiveness. PSRQSP also constructed an easy-to-use web server for accelerating the discovery of potential QSPs for drug development.
COMPUTERS IN BIOLOGY AND MEDICINE
(2023)
Article
Biochemistry & Molecular Biology
Phasit Charoenkwan, Nalini Schaduangrat, Nhat Truong Pham, Balachandran Manavalan, Watshara Shoombuatong
Summary: Proposed the first stack-based approach, Pretoria, for accurate and large-scale identification of CD8+ T-cell epitopes (TCEs) of eukaryotic pathogens. Constructed a pool of 144 different machine learning (ML)-based classifiers based on 12 popular ML algorithms and used feature selection method to determine important ML classifiers for building the stacked model. Experimental results demonstrated that Pretoria outperformed several conventional ML classifiers and the existing method, with an accuracy of 0.866, MCC of 0.732, and AUC of 0.921 in the independent test.
INTERNATIONAL JOURNAL OF BIOLOGICAL MACROMOLECULES
(2023)
Article
Biochemistry & Molecular Biology
Tianshi Yu, Tianyang Huang, Leiye Yu, Chanin Nantasenamat, Nuttapat Anuwongcharoen, Theeraphon Piacham, Ruobing Ren, Ying-Chih Chiang
Summary: Researchers studied Cytochrome P450 17A1 (CYP17A1), a key enzyme in steroidogenesis, and its potential as a druggable target for anti-cancer molecule development. They used cheminformatic analyses and quantitative structure-activity relationship (QSAR) modeling on a dataset of CYP17A1 inhibitors. Different models were built for steroidal and nonsteroidal inhibitors, achieving good accuracy. The findings provide valuable insights for further drug discovery efforts targeting CYP17A1 inhibitors.
Article
Chemistry, Multidisciplinary
Nalini Schaduangrat, Nuttapat Anuwongcharoen, Phasit Charoenkwan, Watshara Shoombuatong
Summary: This study proposes a novel deep learning (DL)-based hybrid framework, named DeepAR, to accurately and rapidly identify AR antagonists by using only the SMILES notation. Experimental results indicate that DeepAR is a more accurate and stable approach for identifying AR antagonists, achieving an accuracy of 0.911 and MCC of 0.823 on an independent test dataset. In addition, the framework provides feature importance information and allows for characterization and analysis of potential AR antagonist candidates.
JOURNAL OF CHEMINFORMATICS
(2023)
Article
Chemistry, Multidisciplinary
Tianshi Yu, Chanin Nantasenamat, Supicha Kachenton, Nuttapat Anuwongcharoen, Theeraphon Piacham
Summary: This study used cheminformatic analysis and machine learning modeling to investigate the chemical space, scaffolds, structure-activity relationship, and landscape of human androgen receptor antagonists. The findings revealed differences in physicochemical properties between potent/active class molecules and intermediate/inactive class molecules. Low scaffold diversity was observed, especially in the potent/active class molecules, indicating the need for developing molecules with novel scaffolds. The study also identified significant activity cliff generators and provided insights and guidelines for the development of novel androgen receptor antagonists.
Article
Chemistry, Multidisciplinary
Ronnakorn Leechaisit, Panupong Mahalapbutr, Pornthip Boonsri, Kun Karnchanapandh, Thanyada Rungrotmongkol, Veda Prachayasittikul, Supaluk Prachayasittikul, Somsak Ruchirawat, Virapong Prachayasittikul, Ratchanok Pingaew
Summary: This study presents a flexible synthesis of novel naphthoquinone-chalcone derivatives and demonstrates their broad-spectrum cytotoxic activities and inhibitory effects on FGFR1.
Article
Chemistry, Multidisciplinary
Waralee Ruankham, Napat Songtawee, Veda Prachayasittikul, Apilak Worachartcheewan, Wilasinee Suwanjang, Ratchanok Pingaew, Virapong Prachayasittikul, Supaluk Prachayasittikul, Kamonrat Phopin
Summary: This study investigated the neuroprotective effects of two synthetic 8-aminoquinoline-uracil copper complexes on human neuroblastoma cells. The complexes restored cell survival, alleviated apoptotic cascades, maintained antioxidant defense, and prevented mitochondrial function. In silico molecular docking and pharmacokinetic prediction suggested that these compounds acted as SIRT1 activators with potential drug-like properties. These findings suggest that the synthetic 8-aminoquinoline-based metal complexes are promising brain-targeting drugs for attenuating neurodegenerative diseases.
Article
Multidisciplinary Sciences
Phasit Charoenkwan, Sajee Waramit, Pramote Chumnanpuen, Nalini Schaduangrat, Watshara Shoombuatong
Summary: HCV infection causes chronic liver diseases, and there is no effective vaccine available. This study proposes a novel approach called TROLLOPE to accurately identify TCE-HCVs from sequence information, with superior predictive performance.
Review
Biology
Muhammad Kabir, Chanin Nantasenamat, Sakawrat Kanthawong, Phasit Charoenkwan, Watshara Shoombuatong
Summary: Phage virion proteins (PVPs) effectively recognize and bind to host cell receptors without harming human or animal cells. Understanding their functional mechanisms is crucial for antibacterial drug discovery and development. This study thoroughly evaluates 13 state-of-the-art PVP predictors, exploring key factors for building accurate and stable predictors.