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Thermodynamics

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Learning transition path and membrane topological signatures in the folding pathway of bacteriorhodopsin (BR) fragment with artificial intelligence.

The Journal of chemical physics
Membrane protein folding in the viscous microenvironment of a lipid bilayer is an inherently slow process that challenges experiments and computational efforts alike. The folding kinetics is moreover associated with topological modulations of the bio...

GR-pKa: a message-passing neural network with retention mechanism for pKa prediction.

Briefings in bioinformatics
During the drug discovery and design process, the acid-base dissociation constant (pKa) of a molecule is critically emphasized due to its crucial role in influencing the ADMET (absorption, distribution, metabolism, excretion, and toxicity) properties...

AIUPred: combining energy estimation with deep learning for the enhanced prediction of protein disorder.

Nucleic acids research
Intrinsically disordered proteins and protein regions (IDPs/IDRs) carry out important biological functions without relying on a single well-defined conformation. As these proteins are a challenge to study experimentally, computational methods play im...

sincFold: end-to-end learning of short- and long-range interactions in RNA secondary structure.

Briefings in bioinformatics
MOTIVATION: Coding and noncoding RNA molecules participate in many important biological processes. Noncoding RNAs fold into well-defined secondary structures to exert their functions. However, the computational prediction of the secondary structure f...

Deep learning path-like collective variable for enhanced sampling molecular dynamics.

The Journal of chemical physics
Several enhanced sampling techniques rely on the definition of collective variables to effectively explore free energy landscapes. The existing variables that describe the progression along a reactive pathway offer an elegant solution but face a numb...

Solubility of dapsone in deep eutectic solvents: Experimental analysis, molecular insights and machine learning predictions.

Polimery w medycynie
BACKGROUND: Dapsone (DAP) is an anti-inflammatory and antimicrobial active pharmaceutical ingredient used to treat, e.g., AIDS-related diseases. However, low solubility is a feature hampering its efficient use.

Perspective on optimal strategies of building cluster expansion models for configurationally disordered materials.

The Journal of chemical physics
Cluster expansion (CE) provides a general framework for first-principles-based theoretical modeling of multicomponent materials with configurational disorder, which has achieved remarkable success in the theoretical study of a variety of material pro...

Facilitating ab initio configurational sampling of multicomponent solids using an on-lattice neural network model and active learning.

The Journal of chemical physics
We propose a scheme for ab initio configurational sampling in multicomponent crystalline solids using Behler-Parinello type neural network potentials (NNPs) in an unconventional way: the NNPs are trained to predict the energies of relaxed structures ...

Deep learning-based quasi-continuum theory for structure of confined fluids.

The Journal of chemical physics
Predicting the structural properties of water and simple fluids confined in nanometer scale pores and channels is essential in, for example, energy storage and biomolecular systems. Classical continuum theories fail to accurately capture the interfac...

Automated workflow for computation of redox potentials, acidity constants, and solvation free energies accelerated by machine learning.

The Journal of chemical physics
Fast evolution of modern society stimulates intense development of new materials with novel functionalities in energy and environmental applications. Due to rapid progress of computer science, computational design of materials with target properties ...