Article
Biochemistry & Molecular Biology
Roberto Arrigoni, Luigi Santacroce, Andrea Ballini, Luigi Leonardo Palese
Summary: The availability of drugs capable of blocking microorganism replication is a major accomplishment in medicine, but the increasing number of resistant strains poses a significant challenge for infectious disease treatment. Therefore, the search for new potential ligands for pathogens' life cycle is a crucial research area today.
Article
Biochemistry & Molecular Biology
Francesco Pellicani, Diego Dal Ben, Andrea Perali, Sebastiano Pilati
Summary: Machine learning has shown potential as a strategy for accurate scoring functions in drug discovery through computational docking. However, recent studies suggest over-optimistic results due to correlations in the experimental databases. In this study, an artificial neural network is used to predict binding affinity using both experimental and computer-generated protein-ligand structures. Promising results are obtained, but there is a decrease in performance when testing on target proteins not included in the training data.
Article
Biochemistry & Molecular Biology
Sunday N. Okafor, Pavimol Angsantikul, Hashim Ahmed
Summary: This research utilized computational tools to screen a large compound library and identified potential HIV-1 protease inhibitors. Two optimized molecules showed promising activity and should be further investigated in vitro and in clinical trials.
INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES
(2022)
Article
Biochemistry & Molecular Biology
Bowen Pan, Sumei Li, Junwei Xiao, Xin Yang, Shouxia Xie, Ying Zhou, Jian Yang, Ying Wei
Summary: This study screened potential antiviral compounds from Sarcandra glabra and investigated their inhibitory effects on HIV-1 and Cathepsin L proteases. The results showed that the extracts from Sarcandra glabra inhibited both proteases, with chlorogenic acid identified as the most potent inhibitor. These findings suggest that Sarcandra glabra extracts and its active ingredients may have dual-inhibition functions against viral proteases and could be used for preventing or treating viral infections, including SARS-CoV-2.
Article
Biochemistry & Molecular Biology
Shangjiu Hu, Ling Ma, Biao Dong, Qi Shan, Jinming Zhou, Guoning Zhang, Minghua Wang, Shan Cen, Mei Zhu, Juxian Wang, Yucheng Wang
Summary: A new class of HIV-1 protease inhibitors with phenol derived P2 ligands and nitro or halogens in P2' ligands have been designed and synthesized. Compound 17d displays potent enzyme inhibitory activity and greater antiviral activity against the DRV-resistant variant than the wild type virus.
BIOORGANIC & MEDICINAL CHEMISTRY
(2022)
Article
Biochemistry & Molecular Biology
Kader Sahin
Summary: In this study, novel indole-based hits against HIV-1 PR were identified by screening molecules containing indole keywords, and using a combination of molecular docking and molecular dynamics simulations.
JOURNAL OF BIOMOLECULAR STRUCTURE & DYNAMICS
(2021)
Article
Biochemistry & Molecular Biology
Gabriele La Monica, Antonino Lauria, Alessia Bono, Annamaria Martorana
Summary: The approval of HIV-1 protease inhibitors marked an important step in AIDS treatment, but also led to severe side effects. In-silico techniques can help design new selective inhibitors with well-fitting selectivity and without undesirable interactions. This new method could be a reliable tool in the research of targeted small molecules.
INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES
(2021)
Article
Chemistry, Medicinal
Bo Wen Pan, Jun Wei Xiao, Su Mei Li, Xin Yang, Xia Zhou, Qing Wen Sun, Mei Chen, Shou Xia Xie, Meena Kishore Sakharkar, Jian Yang, Ying Zhou, Ying Wei
Summary: In this study, the antiviral activities of extracts from the insect gall of Hypericum kouytchense were evaluated. The active ingredients were identified and quantified, and their interactions with proteases were analyzed using molecular docking. The results suggest that these extracts and active ingredients have the potential to be developed for preventing and treating HIV or SARS-CoV-2 infections.
Review
Chemistry, Multidisciplinary
Li Hongjian, Kam-Heung Sze, Lu Gang, Pedro J. Ballester
Summary: This review analyzed machine-learning scoring functions for structure-based virtual screening in the period 2015-2019, and compared their performance with classical scoring functions. Subsequent studies observed that machine-learning scoring functions were substantially more accurate and effective, and were also successfully used in prospective studies for discovering new binders with novel chemical structures.
WILEY INTERDISCIPLINARY REVIEWS-COMPUTATIONAL MOLECULAR SCIENCE
(2021)
Article
Biochemistry & Molecular Biology
Venkatramanan Varadharajan, Gokulakrishnan Sivasundari Arumugam, Sethupathi Shanmugam
Summary: This study screened potential SARS-CoV-2 Mpro inhibitors from existing literature on isatin derivatives, ultimately selecting 4 compounds with good ADMET properties and binding energies as lead candidates for further experimental validation and development.
JOURNAL OF BIOMOLECULAR STRUCTURE & DYNAMICS
(2022)
Article
Mathematics
Dessislava Jereva, Petko Alov, Ivanka Tsakovska, Maria Angelova, Vassia Atanassova, Peter Vassilev, Nikolay Ikonomov, Krassimir Atanassov, Ilza Pajeva, Tania Pencheva
Summary: This study evaluates the performance of different types of scoring functions implemented in molecular modeling software packages. The results show that the performance of scoring functions varies depending on the protein target, and none of the studied scoring functions can accurately predict the binding affinities of the compounds.
Article
Chemistry, Multidisciplinary
Zackary Falls, Jonathan Fine, Gaurav Chopra, Ram Samudrala
Summary: The study evaluated a novel molecular docking protocol CANDOCK and demonstrated its superiority in predicting inhibitor potency to the HIV-1 protease. Experimental results showed that CANDOCK performed better than Autodock Vina and Smina in predicting binding scores and discriminating active versus decoy ligands.
FRONTIERS IN CHEMISTRY
(2022)
Article
Chemistry, Multidisciplinary
Kazuhiro J. Fujimoto, Shota Minami, Takeshi Yanai
Summary: We propose a novel machine-learning-based scoring function that incorporates ligand and protein structural information into drug discovery. It accurately predicts binding affinity, surpassing conventional scoring functions. The findings provide chemical insights and are useful for rational drug discovery.
Article
Biochemistry & Molecular Biology
Tsenbeni N. N. Lotha, Kikoleho Richa, Viphrezolie Sorhie, Vevosa Nakro, Vimha Ritse, Lemzila Rudithongru, Nima D. D. Namsa, Latonglila Jamir
Summary: This study reports a cost-effective and environmentally acceptable method for preparing unsymmetrical ureas from thiocarbamate salts using sodium percarbonate as an oxidant. The efficacy of these unsymmetrical ureas as potential HIV-1 protease inhibitors has been evaluated through in silico approach. The results indicate that the urea compounds interact with the active site of the enzyme and have favorable binding affinities, which can potentially hinder the functioning of the enzyme.
MOLECULAR DIVERSITY
(2023)
Article
Multidisciplinary Sciences
Hunday Govindasamy, Sivanandam Magudeeswaran, Saravanan Kandasamy, Kumaradhas Poomani
Summary: The study demonstrates that naringenin acts as a potential inhibitor of MAO-B enzyme, preventing the development of Parkinson's disease. Molecular docking simulations confirm strong binding between naringenin and MAO-B, with the complex remaining stable throughout molecular dynamics simulations. QM/MM analysis reveals the charge density distribution and strength of intermolecular interactions in the naringenin-MAO-B complex.
Article
Chemistry, Medicinal
Mohammad A. Ghattas, Sara Al Rawashdeh, Noor Atatreh, Richard A. Bryce
JOURNAL OF CHEMICAL INFORMATION AND MODELING
(2020)
Article
Chemistry, Multidisciplinary
Ebru Aksanoglu, Yee Hwee Lim, Richard A. Bryce
Summary: The deoxydehydration of carbohydrates can be achieved using a vanadium(V)-based catalyst, with different mechanisms involved for trans-diol and cis-diol substrates. The process involves stepwise cleavage of C-O bonds for cyclic trans-diols, while cyclic cis-diols and linear diols can proceed via a concerted singlet mechanism. This work opens up new possibilities for efficiently converting carbohydrates into alkenes.
Article
Medicine, General & Internal
Guo-Yue Wan, Ka-Man Lam, Ian-Ian Wong, Pedro Fong, Li-Rong Meng
Summary: This study extracted anti-H. pylori peptides from cow milk using in vitro methods and found that casecidin 17 and beta-casein 207-224 showed promising antibacterial effects. The extracts had the lowest minimum inhibitory concentration (MIC90) at low pH values.
ARCHIVES OF MEDICAL SCIENCE
(2022)
Article
Chemistry, Medicinal
Mai A. Elhemely, Asma A. Belgath, Sherihan El-Sayed, Kepa K. Burusco, Manikandan Kadirvel, Annalisa Tirella, Katherine Finegan, Richard A. Bryce, Ian J. Stratford, Sally Freeman
Summary: A set of meta-substituted 3-arylisoquinolinones with substantial cytotoxicity in various cancer cell lines has been discovered. These compounds have the potential to mimic colchicine and interact with microtubules, leading to antiproliferative effects and inhibition of endothelial cell formation.
JOURNAL OF MEDICINAL CHEMISTRY
(2022)
Article
Multidisciplinary Sciences
Lara Alzyoud, Richard A. Bryce, Mohammad Al Sorkhy, Noor Atatreh, Mohammad A. Ghattas
Summary: The druggability of 12 commonly targeted PPIs was assessed using the computational tool SiteMap. The binding sites of PPIs were found to have varying druggability scores due to unique structural and physiochemical features. A classification system based on these features was proposed to assess the druggability of PPI targets. The study also found that protein flexibility and drug-likeness are important factors to consider in the design of PPI inhibitors.
SCIENTIFIC REPORTS
(2022)
Article
Chemistry, Physical
Ismaeel Ramzan, Jas Kalayan, Linghan Kong, Richard A. Bryce, Neil A. Burton
Summary: This work presents a machine learning approach based on pairwise interatomic forces to predict atomic forces in a molecule with quantum chemical accuracy. The method uses a neural network to predict Cartesian forces as a linear combination of force components, which exhibit chemically intuitive profiles and reduce computational costs for molecular dynamics simulations.
INTERNATIONAL JOURNAL OF QUANTUM CHEMISTRY
(2022)
Article
Chemistry, Multidisciplinary
Linghan Kong, Richard A. Bryce
Summary: This research evaluates the ability of machine learning potentials and semiempirical quantum chemical methods to model ring pucker conformers of carbohydrates. The results show that the machine learning method ANI-1ccx accurately reproduces the ring pucker energy landscape and provides the most accurate estimate of the energetics. The study also finds that all three models reproduce chair more accurately than non-chair geometries.
JOURNAL OF COMPUTATIONAL CHEMISTRY
(2022)
Review
Biochemistry & Molecular Biology
Sherihan El-Sayed, Sally Freeman, Richard A. Bryce
Summary: The NLRP3 inflammasome is an important target in drug discovery, and natural products have been explored as potential inhibitors for the design of novel selective NLRP3 inhibitors.
Article
Biochemistry & Molecular Biology
Sherihan El-Sayed, Sally Freeman, Richard A. Bryce
Summary: This study investigates the impact of NEK7 and cofactor interactions on the conformation and dynamics of NLRP3 in aqueous solution through the construction and simulation of computational models. The results demonstrate that molecular dynamics simulation accurately reproduces the characteristics of the ADP-bound NLRP3-NEK7 complex and reveals a more compact closed form of NLRP3 upon the removal of NEK7 during simulations.
Article
Biochemical Research Methods
Richard A. Bryce, James A. Platts
JOURNAL OF MOLECULAR GRAPHICS & MODELLING
(2022)
Article
Biochemical Research Methods
Linghan Kong, Rasha Alqus, Chin W. Yong, Ilian Todorov, Stephen J. Eichhorn, Richard A. Bryce
Summary: The interaction between graphene and cellulose has potential in designing new graphene-carbohydrate biopolymer materials. The hydrophilicity of cellulose and the interactions between cellulose chains and graphene play important roles in the adsorption and structural accommodation process.
JOURNAL OF MOLECULAR GRAPHICS & MODELLING
(2023)
Article
Multidisciplinary Sciences
Pedro Fong, Sut Tong Chan, Pui Nap Lei, Hao Ian Cheong, I. Man Cheong, Weng Lam Hoe
Summary: This study found that Proton pump inhibitors (PPIs) are associated with depression and suicidal ideation. PPI users have a significantly increased risk of suicidal ideation, and middle-aged participants show the greatest difference in suicidal ideation between PPI and non-PPI users.
SCIENTIFIC REPORTS
(2022)
Article
Pharmacology & Pharmacy
Chiufai Kuok, Qi Wang, Pedro Fong, Yong Qin, Lirong Meng
Summary: Hepatocellular carcinoma (HCC) is the third most malignant tumor worldwide, causing 830,000 deaths annually, largely due to the lack of effective drugs. Hernandezine (HER), a compound found in Thalictrum simplex, has been shown to have anti-tumor activity. However, its effects on HCC and the underlying mechanisms are still unclear. This study evaluated the antitumor effects of HER on HCC cell lines and demonstrated that HER induced cell cycle arrest, inhibited proliferation, and promoted apoptosis. These effects were mediated by the PI3K-AKT pathway and reactive oxygen species (ROS). More specifically, HER disrupted the CDK4-CCND1 dimer formation and caused G0/G1 phase arrest, and also induced ROS accumulation and mitochondrial injury, leading to cell apoptosis. Additionally, HER showed tumor suppressive effects in a mouse model. Overall, these findings suggest that HER is a promising anti-tumor drug for the treatment of HCC.
BIOLOGICAL & PHARMACEUTICAL BULLETIN
(2023)
Article
Social Sciences, Interdisciplinary
Kinfong Leong, Pedro Fong, Chiufai Kuok, Lirong Meng
Summary: The factors influencing job satisfaction and burnout among nurses in Macao were studied, along with their associations with demographic characteristics. Age, highest education level, monthly income, type of working organization, and role were found to be associated with job satisfaction, while marital status was associated with burnout. Professional development opportunities and childcare support were identified as main reasons for job dissatisfaction, while coping strategies were the major issue for burnout. No significant correlation was found between job satisfaction and burnout.
Article
Public, Environmental & Occupational Health
P. Fong, Q. T. Wang
Summary: The study found a significant association between oral contraceptive use and Helicobacter pylori seroprevalence, suggesting a potential protective effect of oral contraceptives against H. pylori infection. Other factors such as race, education, poverty income ratio, smoking, and blood lead and cadmium levels were also significantly associated with H. pylori seroprevalence.
EPIDEMIOLOGY AND INFECTION
(2021)