AIMC Topic: Static Electricity

Clear Filters Showing 1 to 10 of 53 articles

Role of electrostatics in cold adaptation: A comparative study of eury- and stenopsychrophilic triose phosphate isomerase.

Biochimica et biophysica acta. Proteins and proteomics Apr 11, 2025
Psychrophilic (cold-active) organisms have developed enzymes that facilitate sufficient metabolic activity at low temperatures to sustain life. This occurs through molecular adaptations that tend to increase protein flexibility at the expense of stab...
Bacterial Proteins Triose-Phosphate Isomerase Kinetics Static Electricity Enzyme Stability Adaptation, Physiological Cold Temperature
View on PubMed DOI

Long-Range Electrostatics in Serine Proteases: Machine Learning-Driven Reaction Sampling Yields Insights for Enzyme Design.

Journal of chemical information and modeling Feb 10, 2025
Computational enzyme design is a promising technique for producing novel enzymes for industrial and clinical needs. A key challenge that this technique faces is to consistently achieve the desired activity. Fundamental studies of natural enzymes reve...
Static Electricity Protein Engineering Models, Molecular Quantum Theory Catalytic Domain Machine Learning Serine Proteases Biocatalysis
View on PubMed DOI

Monolithic electrostatic actuators with independent stiffness modulation.

Nature communications Jan 30, 2025
Robotic artificial muscles, inspired by the adaptability of biological muscles, outperform rigid robots in dynamic environments due to their flexibility. However, the intrinsic compliance of the soft actuators restricts force transmission capacity an...
Humans Biomechanical Phenomena Robotics Equipment Design Elasticity Wearable Electronic Devices Muscle, Skeletal Static Electricity Viscosity Muscle Contraction
View on PubMed DOI

Physics-Based Machine Learning Trains Hamiltonians and Decodes the Sequence-Conformation Relation in the Disordered Proteome.

Journal of chemical theory and computation Nov 6, 2024
Intrinsically disordered proteins and regions (IDPs) are involved in vital biological processes. To understand the IDP function, often controlled by conformation, we need to find the link between sequence and conformation. We decode this link by inte...
Static Electricity Intrinsically Disordered Proteins Protein Conformation Proteome Molecular Dynamics Simulation Machine Learning
View on PubMed DOI

Data and Molecular Fingerprint-Driven Machine Learning Approaches to Halogen Bonding.

Journal of chemical information and modeling Oct 29, 2024
The ability to predict the strength of halogen bonds and properties of halogen bond (XB) donors has significant utility for medicinal chemistry and materials science. XBs are typically calculated through expensive ab initio methods. Thus, the develop...
Thermodynamics Halogens Machine Learning Models, Molecular Static Electricity Density Functional Theory
View on PubMed DOI

Developing a Differentiable Long-Range Force Field for Proteins with E(3) Neural Network-Predicted Asymptotic Parameters.

Journal of chemical theory and computation Jun 18, 2024
Accurately describing long-range interactions is a significant challenge in molecular dynamics (MD) simulations of proteins. High-quality long-range potential is also an important component of the range-separated machine learning force field. This st...
Neural Networks, Computer Proteins Dipeptides Protein Conformation Molecular Dynamics Simulation Static Electricity Thermodynamics
View on PubMed DOI

Cocrystal Prediction of Nifedipine Based on the Graph Neural Network and Molecular Electrostatic Potential Surface.

AAPS PharmSciTech Jun 11, 2024
Nifedipine (NIF) is a dihydropyridine calcium channel blocker primarily used to treat conditions such as hypertension and angina. However, its low solubility and low bioavailability limit its effectiveness in clinical practice. Here, we developed a c...
Calcium Channel Blockers Crystallization Nifedipine Static Electricity Neural Networks, Computer Solubility
View on PubMed DOI

Coordinate-Free and Low-Order Scaling Machine Learning Model for Atomic Partial Charge Prediction for Any Size of Molecules.

Journal of chemical information and modeling May 17, 2024
The atomic partial charge is of great importance in many fields, such as chemistry and drug-target recognition. However, conventional quantum-based computing of atomic charges is relatively slow, limiting further applications of atomic charge analysi...
Models, Molecular Static Electricity Neural Networks, Computer Machine Learning
View on PubMed DOI

Poisson-Boltzmann-based machine learning model for electrostatic analysis.

Biophysical journal Feb 15, 2024
Electrostatics is of paramount importance to chemistry, physics, biology, and medicine. The Poisson-Boltzmann (PB) theory is a primary model for electrostatic analysis. However, it is highly challenging to compute accurate PB electrostatic solvation ...
Molecular Dynamics Simulation Machine Learning Static Electricity Poisson Distribution Thermodynamics
View on PubMed DOI

Bound ion effects: Using machine learning method to study the kinesin Ncd's binding with microtubule.

Biophysical journal Dec 30, 2023
Drosophila Ncd proteins are motor proteins that play important roles in spindle organization. Ncd and the tubulin dimer are highly charged. Thus, it is crucial to investigate Ncd-tubulin dimer interactions in the presence of ions, especially ions tha...
Protein Multimerization Kinesins Static Electricity Tubulin Protein Binding Microtubules Ions Machine Learning Molecular Dynamics Simulation Drosophila Proteins Solvents Animals
View on PubMed DOI
Popular Topics
Recent Journals