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Kinetics

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GraphVAMPNet, using graph neural networks and variational approach to Markov processes for dynamical modeling of biomolecules.

The Journal of chemical physics
Finding a low dimensional representation of data from long-timescale trajectories of biomolecular processes, such as protein folding or ligand-receptor binding, is of fundamental importance, and kinetic models, such as Markov modeling, have proven us...

Predicting Residence Time of GPCR Ligands with Machine Learning.

Methods in molecular biology (Clifton, N.J.)
Drug-target residence time, the duration of binding at a given protein target, has been shown in some protein families to be more significant for conferring efficacy than binding affinity. To carry out efficient optimization of residence time in drug...

Application of a deep learning-based image analysis and live-cell imaging system for quantifying adipogenic differentiation kinetics of adipose-derived stem/stromal cells.

Adipocyte
Quantitative methods for assessing differentiative potency of adipose-derived stem/stromal cells may lead to improved clinical application of this multipotent stem cell, by advancing our understanding of specific processes such as adipogenic differen...

Optimization of metronidazole SR buccal tablet for gingivitis using genetic algorithm.

Pakistan journal of pharmaceutical sciences
Gingivitis is a condition that needs sustained concentration of antibiotic locally over extended period of time. The current study aimed to formulate and evaluate the sustained and localized release of metronidazole (MTZ) as mucoadhesive buccal table...

Bound2Learn: a machine learning approach for classification of DNA-bound proteins from single-molecule tracking experiments.

Nucleic acids research
DNA-bound proteins are essential elements for the maintenance, regulation, and use of the genome. The time they spend bound to DNA provides useful information on their stability within protein complexes and insight into the understanding of biologica...

AI-based spectroscopic monitoring of real-time interactions between SARS-CoV-2 and human ACE2.

Proceedings of the National Academy of Sciences of the United States of America
The novel coronavirus, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), invades a human cell via human angiotensin-converting enzyme 2 (hACE2) as the entry, causing the severe coronavirus disease (COVID-19). The interactions between hACE...

A machine learning system with reinforcement capacity for predicting the fate of an ART embryo.

Systems biology in reproductive medicine
The aim of this work was o construct a score issued from a machine learning system with self-improvement capacity able to predict the fate of an ART embryo incubated in a time lapse monitoring (TLM) system. A retrospective study was performed. For th...

In-Cell Single-Molecule Analysis of Molecular State and Reaction Kinetics Coupling.

Advances in experimental medicine and biology
Cellular signaling is regulated by the spatiotemporal dynamics and kinetics of molecular behavior. To investigate the mechanisms at the molecular level, fluorescence single-molecule analysis is an effective method owing to the direct observation of i...

A combination of machine learning and infrequent metadynamics to efficiently predict kinetic rates, transition states, and molecular determinants of drug dissociation from G protein-coupled receptors.

The Journal of chemical physics
Determining the drug-target residence time (RT) is of major interest in drug discovery given that this kinetic parameter often represents a better indicator of in vivo drug efficacy than binding affinity. However, obtaining drug-target unbinding rate...

Flagellar nanorobot with kinetic behavior investigation and 3D motion.

Nanoscale
Wirelessly controlled nanorobots have the potential to perform highly precise maneuvers within complex in vitro and in vivo environments. Flagellar nanorobots will be useful in a variety of biomedical applications, however, to date there has been lit...