Article
Biology
Yiquan Wang, Ruipeng Lei, Armita Nourmohammad, Nicholas C. Wu
Summary: This study characterized the local fitness landscape of the NA antigenic region in different human H3N2 strains using combinatorial mutagenesis and next-generation sequencing. The analysis revealed that local net charge governs pairwise epistasis in this antigenic region and residue coevolution is correlated with the pairwise epistasis between charge states, highlighting the importance of quantifying epistasis and biophysical constraints in building a model of influenza evolution. The results provide valuable insights into the evolutionary dynamics of influenza viruses.
Article
Chemistry, Medicinal
Merveille Eguida, Christel Schmitt-Valencia, Marcel Hibert, Pascal Villa, Didier Rognan
Summary: In this paper, we propose a computational approach called POEM to generate target-focused libraries using publicly available structural information on protein-ligand complexes. The approach involves aligning a collection of PDB-derived images with key shapes and pharmacophoric properties to the query target cavity using a computer vision method. The fragments from the most similar PDB subpockets are then positioned in the query cavity using corresponding image transformation matrices. Finally, a deep generative model is used to link suitable connectable atoms of oriented fragment pairs, resulting in fully connected molecules. We applied POEM to generate a library of potential cyclin-dependent kinase 8 inhibitors and achieved significant results with limited resources and only two iterative cycles.
JOURNAL OF MEDICINAL CHEMISTRY
(2022)
Article
Biochemistry & Molecular Biology
Bourougaa Lotfi, Ouassaf Mebarka, Bader Y. Alhatlani, Emad M. Abdallah, Sarkar M. A. Kawsar
Summary: In this study, a novel approach was used to discover neuraminidase inhibitors for the treatment of influenza. Molecular docking analysis and pharmacokinetic evaluations showed that the synthesized breed molecules formed more stable complexes with the neuraminidase receptor and had favorable bioavailability. Molecular dynamics simulations and binding energy assessments further confirmed the stability and enduring complexes formed by these breed molecules.
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
Pharmacology & Pharmacy
Yanni Lai, Tiantian Han, Shaofeng Zhan, Yong Jiang, Xiaohong Liu, Geng Li
Summary: Isoimperatorin, a natural compound, exhibits broad-spectrum antiviral activity against various influenza virus strains, especially showing effective inhibition during the later stages of the virus replication cycle. It also exerts inhibitory effects on neuraminidase-mediated virus release, making it a potential agent for influenza A virus prevention and treatment.
FRONTIERS IN PHARMACOLOGY
(2021)
Article
Biochemistry & Molecular Biology
Lotfi Bourougaa, Mebarka Ouassaf, Amneh Shtaiwi
Summary: A fragment linking methodology was used to generate new neuraminidase inhibitors. 28,977 fragments were obtained and screened for their affinity to the neuraminidase receptor. The top ten molecules were selected and evaluated for their molecular interaction modes and binding affinity, and further analyzed through molecular dynamics simulation.
JOURNAL OF BIOMOLECULAR STRUCTURE & DYNAMICS
(2023)
Article
Immunology
Mariia V. Sergeeva, Ekaterina A. Romanovskaya-Romanko, Vera Z. Krivitskaya, Polina A. Kudar, Nadezhda N. Petkova, Kira S. Kudria, Dmitry A. Lioznov, Marina A. Stukova, Yulia A. Desheva
Summary: Neuraminidase-based immunity has the potential to mitigate the impact of novel antigenic variants of influenza viruses. The dynamics of anti-NA antibody response varies depending on the virus subtype, and the persistence of antibodies is different from that of anti-HA antibodies. The level of NA antibodies after vaccination correlates directly with the preexisting titers.
Article
Virology
Thomas Scior, Karina Cuanalo-Contreras, Angel A. Islas, Ygnacio Martinez-Laguna
Summary: This study presents a method for finding antiviral lead compounds through virtual screening. Filters based on the crystal structures of viral neuraminidase were designed and used to model ligand-receptor interactions. The screening was carried out in a large chemical library, and the top-ranked substances were successfully filed for patent.
Article
Agriculture, Multidisciplinary
Guantian Yang, Yutong Wang, Cong Zhou, Yuxin Li, Yucheng Gu, Zhong Li, Zhiping Xu, Jiagao Cheng, Xiaoyong Xu
Summary: The research successfully synthesized 44 compounds containing monofluoroalkene and found that some of them exhibited excellent larvicidal activity against lepidopteran pests. Three-dimensional QSAR analysis and molecular docking were conducted to investigate the bioactivity mechanisms of these compounds. Additionally, typical symptoms caused by the compounds and the potential insecticidal mechanism were observed.
JOURNAL OF AGRICULTURAL AND FOOD CHEMISTRY
(2023)
Article
Agriculture, Multidisciplinary
Luiz R. Capucho, Ingrid V. Pereira, Adriana C. de Faria, Joyce K. Dare, Elaine F. F. da Cunha, Matheus P. Freitas
Summary: In this study, two sets of newly synthesized mesotrione analogs were investigated using multivariate image analysis applied to quantitative structure-activity relationships (MIA-QSAR). The results showed that the MIA-QSAR models based on van der Waals radii, electronegativity, and the r(vdW)/epsilon ratio were able to accurately predict the herbicidal activities of these compounds. Docking studies also revealed promising agrochemical candidates. Overall, the combination of multivariate image analysis and docking studies can reliably predict the herbicidal activities of mesotrione analogs.
JOURNAL OF THE SCIENCE OF FOOD AND AGRICULTURE
(2023)
Article
Biochemistry & Molecular Biology
Shenqing Wang, Xiliang Yan, Gaoxing Su, Bing Yan
Summary: The relationship between nanoparticle redox property and toxicity has not been established when all other nanoparticle properties are identical. By synthesizing a diverse gold nanoparticle (GNP) library with different redox properties, it was found that the oxidative reactivity of GNPs directly caused cytotoxicity via induction of cellular oxidative stress. The redox diversity of nanoparticles is regulated by GNPs modified with redox reactive ligands.
Article
Microbiology
Meiling Dai, Wenjuan Du, Carles Martinez-Romero, Tim Leenders, Tom Wennekes, Guus F. Rimmelzwaan, Frank J. M. van Kuppeveld, Ron A. M. Fouchier, Adolfo Garcia-Sastre, Erik de Vries, Cornelis A. M. de Haan
Summary: Research shows that the antigenic and enzymatic properties of the influenza A virus neuraminidase are intertwined, with several residues affecting multiple properties. This entanglement may play a crucial role in the evolution of the neuraminidase.
Article
Pharmacology & Pharmacy
Kamelia M. Amin, Ossama M. El-Badry, Doaa E. Abdel Rahman, Magda H. Abdellattif, Mohammed A. S. Abourehab, Mahmoud H. El-Maghrabey, Fahmy G. Elsaid, Mohamed A. El Hamd, Ahmed Elkamhawy, Usama M. Ammar
Summary: This study utilized a multi-step in silico approach, in vitro biological evaluation, and SAR study to identify novel compounds with anticancer potential and PDE5 inhibitory activity. Compound 11b exhibited the highest potency and molecular dynamic simulation provided insights into its inhibitory mechanism.
Article
Chemistry, Medicinal
Federico Riu, Alessandro Ruda, Olof Engstrom, Claudio Muheim, Hani Mobarak, Jonas Stahle, Paul Kosma, Antonio Carta, Daniel O. Daley, Goran Widmalm
Summary: In this study, docking and molecular dynamics simulations were used to identify potential compounds from libraries A and B that can bind to WaaG. The substructure of the inner core of LPS was also investigated. The findings provide insights into the function and catalytic cycle of the enzyme WaaG.
Article
Biochemistry & Molecular Biology
Mustapha Abdullahi, Adamu Uzairu, Gideon Adamu Shallangwa, Paul Andrew Mamza, Muhammad Tukur Ibrahim, Anshuman Chandra, Vijay Kumar Goel
Summary: Using molecular modelling strategies and quantitative structure-activity relationship studies, substituted indole molecules with anti-IAV activity were identified, and new molecules with enhanced activity were designed. The developed models and contour maps illustrate the relationship between molecular fields and inhibitory effects, and molecular dynamics simulations confirmed the binding stability of the designed molecules with the NA protein.
JOURNAL OF BIOMOLECULAR STRUCTURE & DYNAMICS
(2023)
Article
Multidisciplinary Sciences
Phasit Charoenkwan, Saeed Ahmed, Chanin Nantasenamat, Julian M. W. Quinn, Mohammad Ali Moni, Pietro Lio, Watshara Shoombuatong
Summary: This study presents a novel meta-predictor, AMYPred-FRL, which utilizes a feature representation learning approach to identify amyloid proteins more accurately. By combining multiple machine learning algorithms and sequence-based feature descriptors, AMYPred-FRL generates 60 probabilistic features and forms a hybrid model. Through cross-validation and independent tests, AMYPred-FRL outperforms existing methods in predictive performance.
SCIENTIFIC REPORTS
(2022)
Article
Biology
Phasit Charoenkwan, Nalini Schaduangrat, Mohammad Ali Moni, Pietro Lio, Balachandran Manavalan, Watshara Shoombuatong
Summary: This study presents a novel computational method, SAPPHIRE, for accurately identifying thermophilic proteins (TPPs) using sequence information. The method combines different feature encodings and machine learning algorithms to train baseline models and extract key information of TPPs. SAPPHIRE outperforms existing methods in terms of predictive performance and achieves higher accuracy and correlation coefficient.
COMPUTERS IN BIOLOGY AND MEDICINE
(2022)
Article
Biology
Phasit Charoenkwan, Nalini Schaduangrat, Pietro Lio, Mohammad Ali Moni, Balachandran Manavalan, Watshara Shoombuatong
Summary: This study proposes a novel computational approach, NEPTUNE, for the accurate and large-scale identification of Tumor Homing Peptides (THPs) from sequence information. The results demonstrate that NEPTUNE achieves superior performance in THP prediction and improves interpretability using the SHapley additive explanations method.
COMPUTERS IN BIOLOGY AND MEDICINE
(2022)
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
Chemistry, Analytical
Waralee Ruankham, Tanawut Tantimongcolwat, Kamonrat Phopin, Joan Bausells, Marie Hangouet, Marie Martin, Nadia Zine, Abdelhamid Errachid
Summary: Pesticide contamination in food and its persistence in the environment is a major global issue. A label-free impedimetric aptamer-based biosensor was developed for the determination of chlorpyrifos (CPS) residues. The biosensor showed good selectivity and reproducibility for CPS.
SENSORS AND ACTUATORS B-CHEMICAL
(2022)
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
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.