Article
Chemistry, Medicinal
Maywan Hariono, Dominikus B. E. Wijaya, Teddy Chandra, Nico Frederick, Agnes B. Putri, Erlia Herawati, Luthfi A. Warastika, Merry Permatasari, Agata D. A. Putri, Satrio Ardyantoro
Summary: The era of drug design aided by computers has been very welcome to Indonesian researchers. The availability of free and user-friendly software, bioinformatics, and cheminformatics data has increased their interest in using computational methods for drug discovery. The use of computer-aided drug design programs has shown an increasing trend in Indonesia over the past decade, with docking and molecular dynamics being the most commonly used methods. The focus has been on studying the human estrogen receptor alpha, flavonoids, and cancer.
JOURNAL OF CHEMICAL INFORMATION AND MODELING
(2022)
Review
Chemistry, Multidisciplinary
Vesna Rastija, Karolina Vrandecic, Jasenka Cosic, Gabriella Kanizai Saric, Ivana Majic, Maja Karnas
Summary: Coumarins are secondary metabolites widely found in plants, bacteria, fungi, and sponges, with diverse structures and pharmacological activities. They have potential applications in various fields such as antioxidant, antibacterial, antifungal, anti-HIV, anti-tuberculosis, and anti-cancer. However, there is limited research on their practical use in agriculture and their effects on beneficial soil organisms.
APPLIED SCIENCES-BASEL
(2023)
Review
Biochemistry & Molecular Biology
Murtala A. Ejalonibu, Segun A. Ogundare, Ahmed A. Elrashedy, Morufat A. Ejalonibu, Monsurat M. Lawal, Ndumiso N. Mhlongo, Hezekiel M. Kumalo
Summary: Developing new antibiotics targeting resistant Mycobacterium tuberculosis is an appealing strategy to combat the global tuberculosis epidemic, with computational techniques playing a key role in drug design and discovery. Recent advancements in technology have enhanced the chances of drug development, offering hope in the fight against tuberculosis resistance.
INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES
(2021)
Review
Biochemistry & Molecular Biology
Davide Bassani, Stefano Moro
Summary: The use of computational approaches in drug discovery, known as computer-aided drug design (CADD), has become a crucial component in pharmaceutical discovery pipelines. CADD techniques have significantly improved the efficiency of early discovery steps, facilitating the selection of appropriate compounds from a vast chemical space. Furthermore, CADD methods rationalize the biochemical and interactive processes at the molecular level, allowing for rational 3D design and optimization of chemical entities. This review provides an overview of CADD methods, highlighting their potential applications, benefits, limitations, and weaknesses in various scenarios of pharmaceutical and biological interest.
Article
Mathematics
Alina Barbulescu, Lucica Barbes, Cristian Stefan Dumitriu
Summary: This study aims to analyze the similarity degree of molecules belonging to two subgroups of Aminoalkylindoles through Cheminformatics methods. The Tanimoto coefficients were computed to reveal the level of similarity, and dendrograms and heatmaps were built. The study also found atom-pair similarities within the same group and validated the clustering using the Kruskal-Wallis test.
Article
Biochemistry & Molecular Biology
Yasunari Matsuzaka, Yoshihiro Uesawa
Summary: Deep learning (DL) can improve the accuracy of quantitative structure-activity relationship (QSAR) in molecular design and chemical safety assessment. We constructed a high-performance prediction model using the DeepSnap-DL method, which extracts feature values from images generated from three-dimensional (3D) chemical structures. In this study, we improved the DeepSnap-DL system by optimizing parameters, resulting in higher prediction performance for the models of agonists or antagonists of molecular initiation events (MIEs). The improved DeepSnap-DL system will serve as a powerful tool for computer-aided molecular design as a novel QSAR system.
INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES
(2022)
Article
Biochemistry & Molecular Biology
Hanine Hadni, Menana Elhallaoui
Summary: In this study, drug design was carried out targeting the mutations in the p53 gene. New anticancer compounds were predicted using computer simulation methods, and the predictive ability and stability of the models were tested using various validation methods. Based on molecular docking and molecular dynamics simulation results, the designed compounds showed crucial interactions with the active sites of the p53 protein. The results suggest the potential of these compounds for the treatment of colon cancer.
JOURNAL OF BIOMOLECULAR STRUCTURE & DYNAMICS
(2023)
Article
Biochemical Research Methods
Ya Tian, Shuo Shen, Liwei Gu, Jianxin Zhou, Yujie Li, Xiaojun Zheng
Summary: This study used computer-assisted screening technology to design a glucoside targeted molecule with high affinity and stable binding ability, which accelerated the research and development efficiency of new brain-targeted molecules and provided new technical means for the design of new brain-targeted materials.
JOURNAL OF MOLECULAR GRAPHICS & MODELLING
(2021)
Article
Biochemistry & Molecular Biology
Juan Shi, Shuang Gao, Jia-Yu Wang, Tong Ye, Ming-Li Yue, Ying Fu, Fei Ye
Summary: This study established a Topomer comparative molecular field analysis model to screen potential HPPD inhibitors. Molecular docking, ADMET prediction, and drug-like properties evaluation were used to verify the activity of the screened compounds. Molecular dynamics simulation was conducted to validate the stability of the potential inhibitors.
INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES
(2022)
Article
Biochemistry & Molecular Biology
Ossama Daoui, Hassan Nour, Oussama Abchir, Souad Elkhattabi, Mohamed Bakhouch, Samir Chtita
Summary: This study investigated the structure-activity relationship of 4-phenoxypyridine derivatives and designed candidate compounds with high inhibition of c-Met enzymatic activity using computer-aided drug design methods. The structural properties and dynamics of these compounds in an aqueous environment were discussed through molecular dynamics simulations.
JOURNAL OF BIOMOLECULAR STRUCTURE & DYNAMICS
(2023)
Article
Biochemistry & Molecular Biology
Milica Radan, Dusan Ruzic, Mirjana Antonijevic, Teodora Djikic, Katarina Nikolic
Summary: This study combined ligand-based and target-based approaches to design novel potent 5-HT2AR antagonists. By conducting molecular dynamic simulations and molecular docking, bioactive conformations of the ligands and different conformations of the 5-HT2AR were obtained, leading to 3D-QSAR modelling and pharmacophore analysis, demonstrating the reliability and predictive power of the created model.
JOURNAL OF BIOMOLECULAR STRUCTURE & DYNAMICS
(2021)
Article
Chemistry, Multidisciplinary
Liang Li, Chang'en Peng, Yonggang Wang, Chan Xiong, Yefang Liu, Chunjie Wu, Jiaolong Wang
Summary: A 3D-QSAR model was developed using reported IKK-0 inhibitors to identify promising compounds targeting IKK-0. Compound 21MX007 showed potential inhibition based on competitive QSAR prediction and docking scoring.
ARABIAN JOURNAL OF CHEMISTRY
(2022)
Article
Biochemistry & Molecular Biology
Yuan Zhou, Meng Cai, Huan Zhou, Leifeng Hou, Hao Peng, Hongwu He
Summary: Computer aided optimization was utilized to design a series of new agrochemical compounds, which exhibited excellent inhibitory activity against Escherichia coli. Compound 6l showed the best inhibitory activity with an IC50 value of 95 nM. In vitro antibacterial activity tests showed that some compounds exhibited higher inhibition against Ralstonia solanacearum compared to commercial chemical pesticides.
PESTICIDE BIOCHEMISTRY AND PHYSIOLOGY
(2021)
Review
Biochemical Research Methods
Maria Virginia Sabando, Ignacio Ponzoni, Evangelos E. Milios, Axel J. Soto
Summary: With the consolidation of deep learning in drug discovery, several novel algorithms for learning molecular representations have been proposed. However, comparing different molecular embeddings and traditional representations is not straightforward, hindering the process of choosing suitable representations for QSAR modeling. The study conducted experiments comparing different embedding techniques and found that the predictive performance using molecular embeddings did not significantly surpass that of traditional representations.
BRIEFINGS IN BIOINFORMATICS
(2022)
Article
Engineering, Chemical
Yi Peng Heng, Ho Yan Lee, Jia Wen Chong, Raymond R. Tan, Kathleen B. Aviso, Nishanth G. Chemmangattuvalappil
Summary: This study proposes a rough set-based machine learning approach to predict the olfaction properties of fragrance molecules and applies it to a computer-aided molecular design framework. By generating rule-based models, the structure-odour relationship of fragrance molecules is determined, and the combination of multiple rules increases the coverage of different classes of molecules.
Editorial Material
Chemistry, Multidisciplinary
Iseult Lynch, Antreas Afantitis, Dario Greco, Maria Dusinska, Miguel A. Banares, Georgia Melagraki
Review
Biochemistry & Molecular Biology
Varnavas D. Mouchlis, Antreas Afantitis, Angela Serra, Michele Fratello, Anastasios G. Papadiamantis, Vassilis Aidinis, Iseult Lynch, Dario Greco, Georgia Melagraki
Summary: De novo drug design is a process of generating novel molecular structures using computational methods, with traditional approaches including structure-based and ligand-based design. Artificial intelligence and machine learning have a positive impact in this field.
INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES
(2021)
Article
Environmental Sciences
Anastasios G. Papadiamantis, Antreas Afantitis, Andreas Tsoumanis, Eugenia Valsami-Jones, Iseult Lynch, Georgia Melagraki
Summary: The physicochemical characterisation data of 69 engineered nanomaterials has been utilized to develop a nanoinformatics model for predicting the ENM zeta-potential. The model includes five critical parameters, such as ENM size and coating, as well as three molecular descriptors, each of which significantly influences the zeta-potential values. The model is available as a web service for the community through specific Horizon 2020 projects.
Review
Biochemistry & Molecular Biology
Mary Gulumian, Charlene Andraos, Antreas Afantitis, Tomasz Puzyn, Neil J. Coville
Summary: The physicochemical properties of nanomaterials have an impact on their toxicity and pathogenicity, with nanotopography being an important factor. Despite its significance, the role of surface topography in nanotoxicity is often overlooked. By manipulating surface topography and applying principles from catalysis, it is possible to create safer nanomaterials by reducing surface properties contributing to toxicity.
INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES
(2021)
Article
Biochemistry & Molecular Biology
Dimitra Papadopoulou, Antonios Drakopoulos, Panagiotis Lagarias, Georgia Melagraki, George Kollias, Antreas Afantitis
Summary: The study identified potential anti-TNF small molecule inhibitors in vitro, with Nepalensinol B and Miyabenol A showing efficacy in reducing TNF-induced cytotoxicity. Nepalensinol B was also found to abolish TNF-TNFR1 binding at non-toxic concentrations.
INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES
(2021)
Article
Biochemistry & Molecular Biology
Daiki Hayashi, Varnavas D. Mouchlis, Edward A. Dennis
Summary: This study reveals the unique substrate selectivity of human phospholipase A2s (PLA2) for different fatty acids, discussing the substrate preferences and active site properties of cytosolic cPLA2 enzymes, calcium-independent iPLA2 enzymes, and secreted sPLA2 enzymes.
JOURNAL OF LIPID RESEARCH
(2021)
Review
Materials Science, Biomaterials
Zhiling Guo, Swaroop Chakraborty, Fazel Abdolahpur Monikh, Dimitra-Danai Varsou, Andrew J. Chetwynd, Antreas Afantitis, Iseult Lynch, Peng Zhang
Summary: The research reviews the impact of surface functionalization of graphene-based materials on nanotoxicity and safe design, including studies on intentionally designed functions for applications as well as unintentionally acquired effects from the environment and biota.
Article
Multidisciplinary Sciences
Varnavas D. Mouchlis, Daiki Hayashi, Alexis M. Vasquez, Jian Cao, J. Andrew McCammon, Edward A. Dennis
Summary: Lipoprotein-associated phospholipase A(2) (Lp-PLA(2)) associates with lipoproteins in human plasma and hydrolyzes oxidized phospholipids. The mechanism of enzyme-membrane association and substrate specificity were studied using lipidomics and mass spectrometry techniques.
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
(2022)
Article
Chemistry, Multidisciplinary
P. Tsiros, N. Cheimarios, A. Tsoumanis, A. C. O. Jensen, G. Melagraki, I Lynch, H. Sarimveis, A. Afantitis
Summary: Integrated approaches to testing and assessment (IATA) combine different sources of information to characterize the hazards of chemicals, including nanomaterials. This study presents three computational approaches that can generate data relevant to human health risk assessment. By comparing the performance of these models under different conditions, their capabilities and potential contribution to a nanomaterial-specific IATA for occupational exposure can be evaluated.
ENVIRONMENTAL SCIENCE-NANO
(2022)
Article
Biochemistry & Molecular Biology
Daiki Hayashi, Varnavas D. Mouchlis, Seika Okamoto, Tomoka Namba, Liuqing Wang, Sheng Li, Shuji Ueda, Minoru Yamanoue, Hirofumi Tachibana, Hiroyuki Arai, Hitoshi Ashida, Edward A. Dennis, Yasuhito Shirai
Summary: Alpha-tocopherol (alpha Toc), the active form of vitamin E, has both antioxidant and non-antioxidant effects. It has been discovered that the membrane-bound 67 kDa laminin receptor (67LR) serves as a receptor for alpha Toc, mediating the non-antioxidant effects such as DGK alpha activation. This study provides the first evidence of a membrane receptor for alpha Toc and one of the underlying mechanisms of its non-antioxidant function.
JOURNAL OF NUTRITIONAL BIOCHEMISTRY
(2022)
Review
Chemistry, Multidisciplinary
Varnavas D. Mouchlis, Edward A. Dennis
Summary: Water-soluble proteins and membrane-bound proteins interact with membrane surfaces and bind specific lipid molecules. Phospholipases are important enzymes in biological membranes that catalyze hydrolysis reactions by interacting with membranes and extracting phospholipid substrates. The association of phospholipases with membranes induces conformational changes and stabilizes the enzymes in an active state.
ACCOUNTS OF CHEMICAL RESEARCH
(2022)
Article
Chemistry, Multidisciplinary
Jeaphianne van Rijn, Antreas Afantitis, Mustafa Culha, Maria Dusinska, Thomas E. Exner, Nina Jeliazkova, Eleonora Marta Longhin, Iseult Lynch, Georgia Melagraki, Penny Nymark, Anastasios G. Papadiamantis, David A. Winkler, Hulya Yilmaz, Egon Willighagen
Summary: Management of nanomaterials and nanosafety data requires a unique identifier for each nanomaterial, which is provided by the European Registry of Materials Identifier. This identifier ensures the linking of internal project documentation with publicly released data and knowledge for specific nanomaterials, and has been applied in H2020-funded nanosafety projects.
JOURNAL OF CHEMINFORMATICS
(2022)
Review
Chemistry, Medicinal
Scott Hollingsworth, Scott Johnson, Pouyan Khakbaz, Yilin Meng, Varnavas Mouchlis, Olivia Pierce, Vera Prytkova, Erik Vik, Dahlia Weiss, Veerabahu Shanmugasundaram
Summary: Traditional targets and modalities are no longer the main focus of future drug discovery. There is a shift towards novel modalities such as protein degradation. The review article highlights the emerging targeting chimeras (TACs) and their potential for medicine design and scientific research.
MEDICINAL CHEMISTRY RESEARCH
(2023)
Review
Chemistry, Multidisciplinary
Varnavas D. Mouchlis, Edward A. Dennis
Summary: Water-soluble proteins and membrane-bound proteins bind specific lipid molecules on membrane surfaces. Phospholipases, especially PLA2, play an important role in hydrolyzing phospholipids. The interaction between PLA2 and membranes can induce conformational changes in PLA2 and activate it for catalysis. These studies provide insights into membrane-protein interactions and related biological functions.
ACCOUNTS OF CHEMICAL RESEARCH
(2022)
Article
Plant Sciences
Peng Zhang, Zhiling Guo, Sami Ullah, Georgia Melagraki, Antreas Afantitis, Iseult Lynch
Summary: This Perspective discusses the applications of nanotechnology and artificial intelligence in agriculture, highlighting the opportunities and challenges of using these technologies to achieve sustainable and precision agriculture. By integrating knowledge and adopting new approaches, exciting opportunities can be created for sustainable food production.