Article
Agronomy
Stephen O. Duke, Franck E. Dayan
Summary: The demand for new herbicide modes of action has surged due to the evolving resistance of weeds to existing commercial herbicides. Natural products possess many potential new modes of action that have not been utilized by current herbicides, but have yet to be developed for various reasons. Efforts are being made to identify new herbicide targets through pharmaceutical target sites, metabolomic and proteomic information, and the use of artificial intelligence and machine learning. It is likely that new herbicides with new modes of action will be introduced within the next decade to address herbicide resistance management.
PEST MANAGEMENT SCIENCE
(2022)
Review
Plant Sciences
Xile Deng
Summary: This paper summarizes the current progress and limitations of natural safeners, offering guidance for the practical application of natural safeners in preventing herbicide injury.
Article
Agriculture, Multidisciplinary
Hengzhi Wang, Lipeng Wang, Xiaolin Zhang, Shuang Bai, Tao Jin, Weitang Liu, Jinxin Wang
Summary: Tripyrasulfone is a new herbicide that acts by blocking the biosynthesis of HGA in plants. It affects pigment composition and photosynthetic activity, leading to leaf necrosis and plant death. Additionally, Tripyrasulfone tend to be hydrolyzed in plants, inhibiting the activity of HPPD enzymes and causing damages to the photosystem II complex.
JOURNAL OF AGRICULTURAL AND FOOD CHEMISTRY
(2021)
Article
Biochemistry & Molecular Biology
Stephen O. Duke, Zhiqiang Pan, Amar G. Chittiboyina, Daniel R. Swale, Thomas C. Sparks
Summary: New insecticide modes of action are needed for resistance management. The number of molecular targets in commercial herbicides and insecticides is limited. Some compounds have shared activities as herbicides and insecticides through the same target site. Other compounds with novel herbicide targets shared by insects are also discussed. Compounds with dual herbicidal and insecticidal effects can be used for non-crop pests or resistant crops.
PESTICIDE BIOCHEMISTRY AND PHYSIOLOGY
(2023)
Review
Agronomy
Bo He, Yanhao Hu, Wen Wang, Wei Yan, Yonghao Ye
Summary: Effectively controlling resistant weeds has been a major challenge in modern agriculture. Developing new modes of action for herbicides can provide an efficient and timely solution. However, the development of novel herbicide modes of action has been slow. This paper analyzes the limiting factors for the slow development and summarizes recent positive herbicide targets.
Review
Agronomy
Xile Deng
Summary: This review provides insights into the mechanisms of herbicide safeners, analyzes existing problems, and anticipates future research directions and potential strategies for the development of new safeners. The aim of this paper is to uncover the mechanisms of safeners and offer guidance for the development of new safeners.
Article
Biochemistry & Molecular Biology
Jun Li, Wenxing Wei, Zongqiang Lai, Keng Po Lai
Summary: Using computational bioinformatics techniques, the study identified the potential targets and mechanisms of resveratrol against osteosarcoma (OS). The crucial targets were validated in vitro and the study found that resveratrol inhibited cell proliferation and regulated protein expression in OS cells. This suggests that resveratrol may have promising pharmacological effects against OS by targeting multiple pathways.
PROCESS BIOCHEMISTRY
(2022)
Article
Agriculture, Multidisciplinary
Candelario Palma-Bautista, Jose G. Vazquez-Garcia, Jose Alfredo Dominguez-Valenzuela, Kassio Ferreira Mendes, Ricardo Alcantara De la Cruz, Joel Torra, Rafael De Prado
Summary: The study found that some populations of Conyza bonariensis in olive groves from southern Spain have developed resistance to multiple herbicides, with absorption and translocation processes, as well as enhanced metabolism mechanisms being potentially involved.
JOURNAL OF AGRICULTURAL AND FOOD CHEMISTRY
(2021)
Article
Chemistry, Multidisciplinary
Hai-yan Wang, Pian Yu, Xi-sha Chen, Hui Wei, Shi-jie Cao, Meng Zhang, Yi Zhang, Yong-guang Tao, Dong-sheng Cao, Feng Qiu, Yan Cheng
Summary: Physapubenolide (PB), a compound extracted from Physalis minima L., has shown cytotoxic effects on cancer cells by targeting HMGCR. This inhibition leads to decreased proliferation and migration in melanoma cells, as well as increased sensitivity to vemurafenib.
ACTA PHARMACOLOGICA SINICA
(2022)
Article
Infectious Diseases
Frida Svanberg Frisinger, Bimal Jana, Stefano Donadio, Luca Guardabassi
Summary: A study identified essential proteins in Escherichia coli with low similarity to beneficial gut microbiota, some of which are present in hyper-virulent E. coli ST131 and Klebsiella pneumoniae as potential drug targets. Their findings suggest the possibility of selectively interfering with essential biological processes in Enterobacteriaceae for developing antimicrobial drugs effective against opportunistic pathogens.
Article
Pharmacology & Pharmacy
Youssef Hijazi
Summary: The purpose of this study is to illustrate the use of modeling and compare static and dynamic models in predicting the suppression of target by antibody drugs. The utility of in silico tools in predicting free target suppression was demonstrated, and the assumptions and limitations of key input parameters were clarified. In silico models can guide the discovery and development of antibodies, potentially reducing clinical failure.
EUROPEAN JOURNAL OF CLINICAL PHARMACOLOGY
(2023)
Article
Biochemistry & Molecular Biology
Amit Kumar Halder, M. Natalia D. S. Cordeiro
Summary: This study utilized a multi-target computational modeling approach to analyze the inhibitory potential of MNK-1 and MNK-2, establishing predictive models for mechanistic interpretation and virtual screening of chemical libraries. Through virtual screening and molecular dynamic simulations, promising virtual hits were identified, providing important guidelines for the discovery of potential therapeutic agents.
Article
Pharmacology & Pharmacy
Yingli Zhu, Hongbin Yang, Liwen Han, Lewis H. Mervin, Layla Hosseini-Gerami, Peihai Li, Peter Wright, Maria-Anna Trapotsi, Kechun Liu, Tai-Ping Fan, Andreas Bender
Summary: Uncontrolled angiogenesis is a common problem in many deadly and debilitating diseases, and traditional Chinese medicine offers an alternative source for developing drugs to regulate angiogenesis. In this study, 100 traditional Chinese medicine-derived metabolites were investigated, and 51 metabolites were found to have angiogenic activity. The mechanisms of action of these metabolites were analyzed, and a decision tree was generated to predict their poly-pharmacology. In vitro and in vivo experiments were conducted to validate the predictions and identify specific metabolites with pro-angiogenic or anti-angiogenic effects.
FRONTIERS IN PHARMACOLOGY
(2023)
Article
Agronomy
Shuji Hachisu
Summary: This article discusses the importance of herbicides for farmers to manage weeds in order to grow essential crops for food and energy supply. The agriculture sector is facing a crisis where herbicides are becoming ineffective due to resistant weeds or safety concerns. There is an urgent need for efficacious herbicides with novel modes of action to control resistant weeds and meet public and regulatory requirements for safe and sustainable products.
PEST MANAGEMENT SCIENCE
(2021)
Article
Pharmacology & Pharmacy
Minjee Kim, Hanul Choi, Young Bong Kim
Summary: This study focused on curcumin as a potential therapeutic agent for Zika virus, identifying TNF as the target with the strongest binding. In vitro experiments confirmed the anti-Zika effects of curcumin, indicating its promise for the treatment of ZIKV infections.
EUROPEAN JOURNAL OF PHARMACOLOGY
(2021)
Article
Medicine, Research & Experimental
Olga Obrezanova, Anton Martinsson, Tom Whitehead, Samar Mahmoud, Andreas Bender, Filip Miljkovic, Piotr Grabowski, Ben Irwin, Ioana Oprisiu, Gareth Conduit, Matthew Segall, Graha M. F. Smith, Beth Williamson, Susanne Winiwarter, Nigel Greene
Summary: In this study, machine learning models were developed to predict rat in vivo pharmacokinetic parameters and concentration-time profiles based on molecular structure and in vitro parameters. The models showed better performance compared to traditional machine learning algorithms and deep learning approaches, providing a useful tool for drug design and compound prioritization.
MOLECULAR PHARMACEUTICS
(2022)
Article
Multidisciplinary Sciences
Johanne Brooks-Warburton, Dezso Modos, Padhmanand Sudhakar, Matthew Madgwick, John P. Thomas, Balazs Bohar, David Fazekas, Azedine Zoufir, Orsolya Kapuy, Mate Szalay-Beko, Bram Verstockt, Lindsay J. Hall, Alastair Watson, Mark Tremelling, Miles Parkes, Severine Vermeire, Andreas Bender, Simon R. Carding, Tamas Korcsmaros
Summary: This study introduces a precision medicine workflow called integrated single nucleotide polymorphism network platform (iSNP), aiming to uncover patient-specific pathways affected in complex diseases by combining genomics and network biology approaches.
NATURE COMMUNICATIONS
(2022)
Review
Chemistry, Multidisciplinary
Andreas Bender, Nadine Schneider, Marwin Segler, W. Patrick Walters, Ola Engkvist, Tiago Rodrigues
Summary: This article discusses method development and evaluation guidelines for different types of machine learning-based publications in the field of chemistry, focusing on supervised learning. By providing examples from various authors and disciplines in chemistry, emphasizing reporting completeness, standardizing comparisons between tools, and proposing a checklist, it aims to improve transparency and credibility in machine learning.
NATURE REVIEWS CHEMISTRY
(2022)
Article
Biochemistry & Molecular Biology
Maria-Anna Trapotsi, Elizabeth Mouchet, Guy Williams, Tiziana Monteverde, Karolina Juhani, Riku Turkki, Filip Miljkovic, Anton Martinsson, Lewis Mervin, Kenneth R. Pryde, Erik Mullers, Ian Barrett, Ola Engkvist, Andreas Bender, Kevin Moreau
Summary: PROteolysis TArgeting Chimeras (PROTACs) utilize the ubiquitin-proteasome system to degrade specific proteins for therapeutic purposes. Although targeted protein degradation technology has shown significant advancements, there is a need to identify reliable methods to assess the safety risks associated with PROTACs in order to develop effective and safe compounds. This study utilized an unbiased high-content imaging method called Cell Painting to identify phenotypic signatures of PROTACs. By employing chemical clustering and model prediction, a mitotoxicity signature was identified that could not have been predicted by screening individual components of PROTACs. The findings underscore the value of unbiased phenotypic methods in identifying toxic signatures and their potential impact on drug design.
ACS CHEMICAL BIOLOGY
(2022)
Article
Medicine, Legal
Peter S. R. Wright, Graham F. Smith, Katharine A. Briggs, Robert Thomas, Gareth Maglennon, Paulius Mikulskis, Melissa Chapman, Nigel Greene, Benjamin U. Phillips, Andreas Bender
Summary: Virtual Control Groups (VCGs) based on Historical Control Data (HCD) have the potential to reduce animal usage in preclinical toxicity testing. Replacing Concurrent Control Groups (CCGs) with VCGs can improve the consistency of study outcomes. However, some covariates may affect the identification of treatment-relatedness.
REGULATORY TOXICOLOGY AND PHARMACOLOGY
(2023)
Article
Medicine, Legal
Peter S. R. Wright, Katharine A. Briggs, Robert Thomas, Graham F. Smith, Gareth Maglennon, Paulius Mikulskis, Melissa Chapman, Nigel Greene, Benjamin U. Phillips, Andreas Bender
Summary: By comparing histopathological findings and target organ toxicities across different preclinical species, this study found that positive concordance is more common than negative concordance in histopathological results, and there is low concordance in target organ toxicities. It provides new statistically significant associations between preclinical species but finds that concordance is rare.
REGULATORY TOXICOLOGY AND PHARMACOLOGY
(2023)
Article
Pharmacology & Pharmacy
Hongbin Yang, Olga Obrezanova, Amy Pointon, Will Stebbeds, Jo Francis, Kylie A. Beattie, Peter Clements, James S. Harvey, Graham F. Smith, Andreas Bender
Summary: Functional changes to cardiomyocytes during drug discovery pose risks of cardiovascular adverse effects. A new approach using calcium transients in hiPSC-CMs has been developed to detect early contractility changes. By deriving 25 parameters from each calcium transient waveform, a modified Random Forest method was able to predict inotropic effects with improved accuracy compared to traditional methods. This study demonstrates the potential of advanced waveform parameters and machine learning techniques in predicting cardiovascular risks associated with inotropic effects.
TOXICOLOGY AND APPLIED PHARMACOLOGY
(2023)
Article
Pharmacology & Pharmacy
Yingli Zhu, Hongbin Yang, Liwen Han, Lewis H. Mervin, Layla Hosseini-Gerami, Peihai Li, Peter Wright, Maria-Anna Trapotsi, Kechun Liu, Tai-Ping Fan, Andreas Bender
Summary: Uncontrolled angiogenesis is a common problem in many deadly and debilitating diseases, and traditional Chinese medicine offers an alternative source for developing drugs to regulate angiogenesis. In this study, 100 traditional Chinese medicine-derived metabolites were investigated, and 51 metabolites were found to have angiogenic activity. The mechanisms of action of these metabolites were analyzed, and a decision tree was generated to predict their poly-pharmacology. In vitro and in vivo experiments were conducted to validate the predictions and identify specific metabolites with pro-angiogenic or anti-angiogenic effects.
FRONTIERS IN PHARMACOLOGY
(2023)
Review
Biochemical Research Methods
Anika Liu, Srijit Seal, Hongbin Yang, Andreas Bender
Summary: This review discusses various sources of information, including biological data such as gene expression and cell morphology, for better understanding and predicting compound activity and safety-related endpoints. It introduces different types of chemical, in vitro, and in vivo information that can describe compounds and adverse effects. The review explores how compound descriptors based on chemical structure or biological perturbation response can predict safety-related endpoints, and how biological data can enhance understanding of adverse effects mechanistically. These applications highlight the potential of large-scale biological information in predictive toxicology and drug discovery projects.
Article
Biochemical Research Methods
Layla Hosseini-Gerami, Ixavier Alonzo Higgins, David A. Collier, Emma Laing, David Evans, Howard Broughton, Andreas Bender
Summary: This study performed a comprehensive evaluation of four causal reasoning algorithms in different networks, and found that the choice of algorithm and network greatly influenced the performance of causal reasoning algorithms. SigNet performed best in recovering direct targets, while CARNIVAL with Omnipath network excelled in recovering informative signaling pathways. The performance of causal reasoning methods was somewhat correlated with the connectivity and biological role of the targets.
BMC BIOINFORMATICS
(2023)
Article
Biochemistry & Molecular Biology
Benoit Baillif, Jason Cole, Patrick McCabe, Andreas Bender
Summary: Deep generative models have become popular in chemical design. This article focuses on explicit 3D molecular generative models, which have gained interest recently. Multiple models have been developed to generate molecules in 3D, providing atom types and coordinates. These models can be guided by structural information and produce molecules with similar docking scores to known actives, but they are less efficient and sometimes generate unrealistic conformations. The article advocates for a unified benchmark of metrics and proposes future perspectives to be addressed.
CURRENT OPINION IN STRUCTURAL BIOLOGY
(2023)
Article
Medicine, Research & Experimental
Koichi Handa, Peter Wright, Saki Yoshimura, Michiharu Kageyama, Takeshi Iijima, Andreas Bender
Summary: This study developed machine learning models to predict plasma concentration-time profiles of drugs after intravenous and oral administration. The predictive accuracy of different models was investigated, and random forest showed the best performance. The importance of in vitro pharmacokinetic parameters was also explored and found to be well-reflected in the model.
MOLECULAR PHARMACEUTICS
(2023)
Article
Chemistry, Medicinal
Lavinia-Lorena Pruteanu, Andreas Bender
Summary: Gene expression and cell morphology data are important for drug discovery. They can describe different biological states and the effects of compound treatment, and are useful for drug repurposing and compound characterization. This paper discusses recent advances in this area, and emphasizes the need for better understanding the applicability domain of readouts and their relevance for decision-making.
ACS MEDICINAL CHEMISTRY LETTERS
(2023)
Article
Chemistry, Multidisciplinary
Srijit Seal, Hongbin Yang, Maria-Anna Trapotsi, Satvik Singh, Jordi Carreras-Puigvert, Ola Spjuth, Andreas Bender
Summary: In this study, similarity-based merger models were developed to combine outputs of individual models trained on cell morphology and chemical structure, as well as the structural and morphological similarities of compounds in the test dataset. Logistic regression models were used to apply these similarity-based merger models on predictions and similarities from 177 assays, achieving better performance compared to using structural or cell painting models alone. These results demonstrate that similarity-based merger models combining structure and cell morphology can accurately predict a wide range of biological assay outcomes and expand the applicability domain.
JOURNAL OF CHEMINFORMATICS
(2023)
Article
Chemistry, Medicinal
Lavinia-Lorena Pruteanu, Andreas Bender
Summary: Gene expression and cell morphology data are valuable in drug discovery, providing insight into biological systems in different states and after compound treatment. This article discusses recent advances in using these data for drug repurposing and highlights the need for further understanding of the applicability domain and relevance of the readouts for decision making.
ACS MEDICINAL CHEMISTRY LETTERS
(2023)
Article
Biochemical Research Methods
Nousheen Parvaiz, Asma Abro, Syed Sikander Azam
Summary: Protein Tyrosine Phosphatase 1B (PTP1B) is a negative regulator of insulin signaling pathways and has potential as a medicinal target. This study explores the binding and conformational orientation of zinc(II) complexes in PTP1B using advanced computational methods. The findings suggest that zinc(II) complexes can bind to important residues in the enzyme and inhibit its activity.
JOURNAL OF MOLECULAR GRAPHICS & MODELLING
(2024)
Article
Biochemical Research Methods
Hira Zubair, Muhamed Salim Akhter, Muhammad Waqas, Mariam Ishtiaq, Ijaz Ahmed Bhatti, Javed Iqbal, Ahmed M. Skawky, Rasheed Ahmad Khera
Summary: Improving open-circuit voltage is crucial for enhancing the overall efficiency of organic solar cells. This study successfully improved the open-circuit voltage by modulating the molecular structure and proposed a promising design concept for acceptor molecules that may contribute to the development of advanced organic solar cells.
JOURNAL OF MOLECULAR GRAPHICS & MODELLING
(2024)
Article
Biochemical Research Methods
Jerica Wilson, Bahrad A. Sokhansanj, Wei Chuen Chong, Rohan Chandraghatgi, Gail L. Rosen, Hai-Feng Ji
Summary: Fragment-based drug design is a computer-aided drug discovery method, however, it has limitations in processing time and success rate. In this study, a new method called Fragment Databases from Screened Ligands Drug Design (FDSL-DD) was proposed, which intelligently incorporates fragment characteristics into the drug design process to improve the binding affinity between drugs and protein targets.
JOURNAL OF MOLECULAR GRAPHICS & MODELLING
(2024)
Article
Biochemical Research Methods
M. Chamani, G. H. Farrahi
Summary: This paper employs the Generalized Particle (GP) method to simulate nanoindentation and nanoscratching, showing that this method maintains consistent atomic properties across different scales and achieves results consistent with full atomic simulations.
JOURNAL OF MOLECULAR GRAPHICS & MODELLING
(2024)
Article
Biochemical Research Methods
Paola Vottero, Elena Carlotta Olivetti, Lucia Chiara D'Agostino, Luca Di Grazia, Enrico Vezzetti, Maral Aminpour, Jacek Adam Tuszynski, Federica Marcolin
Summary: This study aims to characterize the spike protein of the SARS-CoV-2 virus and investigate its interaction with the ACE2 receptor using a geometric analysis. The 3D depth maps of the proteins are filtered using a specific convolutional filter to obtain geometric features. Geometric descriptors and a Support Vector Machine classifier are used for feature extraction and classification, revealing the geometrical reasons for the higher contagiousness of the Omicron variant compared to other variants.
JOURNAL OF MOLECULAR GRAPHICS & MODELLING
(2024)
Article
Biochemical Research Methods
Diana Margarita Mojica-Munoz, Karla Lizbeth Macias-Sanchez, Estefania Odemaris Juarez-Hernandez, Aurora Rodriguez-Alvarez, Jean-Michel Grevy, Armando Diaz-Valle, Mauricio Carrillo-Tripp, Jose Marcos Falcon-Gonzalez
Summary: By employing molecular dynamics simulations, we investigated the molecular mechanisms underlying the plasticization of starch. Our study revealed that chain size affects the solubility of starch, temperature influences its diffusivity and elastic properties, and oleic acid shows potential as an alternative plasticizer. Blending glycerol or oleic acid with water enhances the elasticity of starch.
JOURNAL OF MOLECULAR GRAPHICS & MODELLING
(2024)
Article
Biochemical Research Methods
Sandip Kumar Baidya, Suvankar Banerjee, Balaram Ghosh, Tarun Jha, Nilanjan Adhikari
Summary: This study utilized classification-based QSAR techniques and fragment-based data mining to analyze different MMP-9 inhibitors, revealing the importance of certain molecular fragments in MMP-9 inhibition. These findings have implications for the development of effective MMP-9 inhibitors in the future.
JOURNAL OF MOLECULAR GRAPHICS & MODELLING
(2024)
Article
Biochemical Research Methods
Farid Faraji Chanzab, Saber Mohammadi, Fatemeh Alemi Mahmoudi
Summary: A comprehensive study using molecular dynamics technique was conducted to investigate the behavior of PAP molecules in a n-heptane/toluene solution and the role of SWCNTs, both bare and functionalized with carboxyl groups, in the aggregation of PAP molecules. The study found that the CNTs hindered the association of PAP molecules through steric hindrance and adsorption mechanisms. The presence of carboxyl groups on the CNTs improved the stability and adsorption of PAP molecules. The results have implications for future research on controlling asphaltene precipitation in the oil industry.
JOURNAL OF MOLECULAR GRAPHICS & MODELLING
(2024)
Article
Biochemical Research Methods
Ramin Bairami Habashi, Mohammad Najafi, Reza Zarghami
Summary: A vigorous Monte Carlo strategy was developed to simulate the copolymerization of ethylene and 1-butene using a dual-site metallocene catalyst. The results showed that the second catalyst site had higher activity than the first site, with ethylene and 1-butene consumption rates five times higher and hydrogen transfer rates three times faster. The molar percentage of 1-butene in the copolymers synthesized from the second site was around 12%, while in the copolymers from the first site it was around 2%. Increasing the 1-butene concentration led to an increase in overall molecular weight, while increasing the hydrogen concentration resulted in a decrease in molecular weight. The ratio of ethylene to 1-butene affected the melt index and the weight fraction of crystals, with higher ratios leading to smaller melt indexes and higher weight fractions of crystals. Increasing the temperature caused changes in molecular weight, bimodal molecular weight distribution, crystal thickness and weight fraction, and density of HDPE.
JOURNAL OF MOLECULAR GRAPHICS & MODELLING
(2024)
Article
Biochemical Research Methods
Yufan Lu, Xingmin Guo, Shuya Liu
Summary: This paper investigates how to control the nontrivial topological structures of DNA nanocages by adjusting the number of ssDNA strands. A new algorithm and program are developed to calculate the component number of polyhedral links, filling the gap in computer programs on this aspect. The study provides a complete list of topological structures with different component numbers for DNA octahedrons assembled from one or more ssDNA strands.
JOURNAL OF MOLECULAR GRAPHICS & MODELLING
(2024)
Article
Biochemical Research Methods
Peng Cui, Shideng Yuan, Heng Zhang, Shiling Yuan
Summary: Understanding the mechanisms of viscosity enhancement in crude oil phases is crucial for optimizing extraction and transportation processes. This study employed molecular dynamics simulations to investigate the behavior and viscosification mechanism of asphaltene molecules in complex oil phases. The research suggests that electrostatic interactions and interactions between asphaltene and crude oil molecules contribute to the enhanced viscosity. The findings provide insight into the viscosity enhancement mechanisms in crude oil phases.
JOURNAL OF MOLECULAR GRAPHICS & MODELLING
(2024)
Article
Biochemical Research Methods
Kun Lv, Jin Zhang, Xiaohua Liu, Yuqiao Zhou, Kai Liu
Summary: In this paper, the authors propose a robust method for evaluating the interactions between chiral catalysts and substrates using computer simulations. The method involves constructing 3D models from point cloud data, filtering out non-interacting points, determining interacting points, and accurately calculating interacted volumes. Experimental results demonstrate the effectiveness of the method in removing non-interacting points and calculating interacted volumes with low errors.
JOURNAL OF MOLECULAR GRAPHICS & MODELLING
(2024)
Article
Biochemical Research Methods
Crisciele Fontana, Joao Luiz de Meirelles, Hugo Verli
Summary: By using the GROMOS force field and molecular simulations, this study assessed the dynamics of STA-analogs in aqueous solution and their interaction with water, expanding the knowledge of the conformational space of these ligands and providing potential implications for understanding conformational selection during complexation.
JOURNAL OF MOLECULAR GRAPHICS & MODELLING
(2024)
Article
Biochemical Research Methods
Wei Zhao, Wenjie Zou, Fengyang Liu, Fang Zhou, N. Emre Altun
Summary: The effect of grafting rate on the water solubility of chitosan-grafted polyacrylamide (Chi-gPAM) was investigated using molecular dynamics simulations. The results showed that the intramolecular hydrogen bonding of Chi-gPAM played a dominant role in its water solubility. Additionally, the interaction between Chi-gPAM and water increased with grafting rate.
JOURNAL OF MOLECULAR GRAPHICS & MODELLING
(2024)
Article
Biochemical Research Methods
Nassima Bachir, Samir Kenouche, Jorge I. Martinez-Araya
Summary: This study investigates the local chemical reactivity of FOX-7 and explores the interaction between the compound and different metals. The findings suggest that the stability and charge transfers of the compound are influenced by the metal involved, and the interaction between Metallocene Methyl Cations and the compound shows potential for neutralization.
JOURNAL OF MOLECULAR GRAPHICS & MODELLING
(2024)