AIMC Topic: Kinetics

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Using Machine Learning to Predict First-Order Reaction Rate Constants of PFAS Degradation.

Bulletin of environmental contamination and toxicology
Per- and polyfluoroalkyl substances (PFAS) are environmentally persistent pollutants, posing challenges for effective remediation. This study presented a machine learning (ML) framework to predict the first-order reaction rate constant (k) of PFAS de...

Predicting grain growth kinetic in steels using machine learning and XAI for mechanical properties.

PloS one
Understanding and controlling grain growth kinetics in steels is crucial for optimizing mechanical properties during thermomechanical processing. However, traditional empirical models often fail to account for the complex, nonlinear interactions betw...

Characterizing DPPM inhibition of butyrylcholinesterase: integrated enzymatic kinetics and Raman spectroscopy with chemometric analysis.

The Analyst
Butyrylcholinesterase (BChE) may serve as a scavenger enzyme protecting against various toxic compounds, but we still don't fully understand how it interacts with fentanyl analogues. We investigated how Despropionyl -methyl fentanyl (DPPM) inhibits e...

Assembly of Macromolecular Complexes in the Whole-Cell Model of a Minimal Cell.

The journal of physical chemistry. B
Macromolecular complexes in the genetically minimized bacterium, JCVI-syn3A, support gene expression (RNA polymerase, ribosome, degradosome), metabolism (ABC transporters, ATP synthase), and chromosome dynamics. In this work, we further incorporate t...

Advances in Machine Learning Models for Predicting Enzyme Kinetic Parameters.

Journal of chemical information and modeling
Enzyme kinetic parameters, including , , /, and , are critical for guiding applications in enzyme engineering, metabolic modeling, and synthetic biology by providing quantitative information on enzyme activity under various conditions. Experimental d...

State-space kinetic Ising model reveals task-dependent entropy flow in sparsely active nonequilibrium neuronal dynamics.

Nature communications
Neuronal ensemble activity, including coordinated and oscillatory patterns, exhibits hallmarks of nonequilibrium systems with time-asymmetric trajectories to maintain their organization. However, assessing time asymmetry from neuronal spiking activit...

Characterization of a Novel Mutansucrase (MUT-I) from G29: Enzymatic Properties and Product Analysis.

Journal of agricultural and food chemistry
Glucansucrases are extracellular enzymes capable of synthesizing diverse α-glucan polymers and oligosaccharides, including the industrially relevant mutan. The I-encoded mutansucrase (MUT-I) from G29 was biochemically characterized as a robust bioca...

Talk2Biomodels: AI agent-based open-source LLM initiative for kinetic biological models.

BMC bioinformatics
BACKGROUND: Quantitative kinetic models of biological regulatory processes play an important role in understanding disease mechanisms. However, their simulation and analysis require specialized domain expertise.

Rubisco is slow across the tree of life.

Proceedings of the National Academy of Sciences of the United States of America
Rubisco is the main gateway through which inorganic carbon enters the biosphere, catalyzing the vast majority of carbon fixation on Earth. This pivotal enzyme has long been observed to be kinetically constrained. Yet, this impression is based on kine...

HlightReaxMD: A Machine Learning-Augmented Multiscale Analysis Framework for Radiation Chemistry Dynamics and Damage Prediction.

Journal of chemical information and modeling
Molecular dynamics (MD) simulations are currently widely used to study large-scale displacement cascades based on massive simulation trajectories. However, when the irradiation process involves the complex chemical reactions, effectively analyzing an...