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Detecting conformational heterogeneity in biological macromolecules is a key for the understanding of their biological function. We here provide a comparison between two independent approaches to assess conformational heterogeneity: molecular dynamics simulations, performed without inclusion of any experimental data, and maximum occurrence (MaxOcc) distribution over the topologically available conformational space. The latter only reflects the extent of the averaging and identifies regions which are most compliant with the experimentally measured NMR Residual Dipolar Couplings (RDCs). The analysis was performed for the HIV-1 TAR RNA, consisting of two helical domains connected by a flexible bulge junction, for which four sets of RDCs were available as well as an 8.2 μs all-atom molecular dynamics simulation. A sample and select approach was previously applied to extract from the molecular dynamics trajectory conformational ensembles in agreement with the four sets of RDCs. The MaxOcc analysis performed here identifies the most likely sampled region in the conformational space of the system which, strikingly, overlaps well with the structures independently sampled in the molecular dynamics calculations and even better with the RDC selected ensemble.
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http://dx.doi.org/10.1039/c5cp03993b | DOI Listing |
Biochem Biophys Rep
December 2025
Henan University of Chinese Medicine, Zhengzhou, 450046, China.
Introduction: 5-Hydroxymethyl furfural (5-HMF) is a furan compound with a molecular formula of CHO. Studies have found that 5-HMF has many pharmacological effects, such as improving hemorheology, anti-inflammatory, antioxidant activity and anti-myocardial ischemia. Identifying the preventive effect of 5-HMF against ischemic stroke and its possible mechanism was the aim of this investigation.
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August 2025
School of Cellular and Molecular Medicine, University of Bristol Bristol BS8 1TD UK
Carbapenemases, β-lactamases hydrolysing carbapenem antibiotics, challenge the treatment of multi-drug resistant bacteria. The OXA-48 carbapenemase is widely disseminated in , necessitating new treatments for producer strains. Diazabicyclooctane (DBO) inhibitors, including avibactam and nacubactam, act on a wide range of enzymes to overcome β-lactamase-mediated resistance.
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August 2025
College of Light Industry and Food Engineering, Guangxi University, Nanning, 530004, China.
This study utilized integrated sensory-guided, machine learning, and bioinformatics strategies identify umami-enhancing peptides from , investigated their mechanism of umami enhancement, and confirmed their umami-enhancing properties through sensory evaluations and electronic tongue. Three umami-enhancing peptides (APDGLPTGQ, SDDGFQ, and GLGDDL) demonstrated synergistic/additive effects by significantly enhancing umami intensity and duration in monosodium glutamate (MSG). Furthermore, molecular docking showed that these umami-enhancing peptides enhanced both the binding affinity and interaction forces between MSG and the T1R1/T1R3 receptor system, thereby enhancing umami perception.
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September 2025
Departament de Química, Universitat Autònoma de Barcelona Bellaterra 08193 Barcelona Spain
Mammalian ALOX15 are allosteric enzymes but the mechanism of allosteric regulation remains a matter of discussion. Octyl (-(5-(1-indol-2-yl)-2-methoxyphenyl)sulfamoyl)carbamate inhibits the linoleate oxygenase activity of ALOX15 at nanomolar concentrations, but oxygenation of arachidonic acid is hardly affected. The mechanism of substrate selective inhibition suggests inter-monomer communication within the allosteric ALOX15 dimer complex, in which the inhibitor binding to monomer A induces conformational alterations in the structure of the active site of monomer B.
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August 2025
Engineering Research Center of Cell & Therapeutic Antibody (MOE), School of Pharmacy, Shanghai Jiao Tong University Shanghai 200240 China
Predicting Antibody-Antigen (Ab-Ag) docking and structure-based design represent significant long-term and therapeutically important challenges in computational biology. We present SAGERank, a general, configurable deep learning framework for antibody design using Graph Sample and Aggregate Networks. SAGERank successfully predicted the majority of epitopes in a cancer target dataset.
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