Machine learning interatomic potentials for heterogeneous catalysis
Atomistic modeling can provide valuable insights into the design of novel heterogeneous
catalysts as needed nowadays in the areas of, eg, chemistry, materials science, and biology …
catalysts as needed nowadays in the areas of, eg, chemistry, materials science, and biology …
Functional dynamics of G protein-coupled receptors reveal new routes for drug discovery
G protein-coupled receptors (GPCRs) are the largest human membrane protein family that
transduce extracellular signals into cellular responses. They are major pharmacological …
transduce extracellular signals into cellular responses. They are major pharmacological …
The open force field initiative: Open software and open science for molecular modeling
Force fields are a key component of physics-based molecular modeling, describing the
energies and forces in a molecular system as a function of the positions of the atoms and …
energies and forces in a molecular system as a function of the positions of the atoms and …
Host–Guest Binding Free Energies à la Carte: An Automated OneOPES Protocol
Estimating absolute binding free energies from molecular simulations is a key step in
computer-aided drug design pipelines, but the agreement between computational results …
computer-aided drug design pipelines, but the agreement between computational results …
Computational screening of the effects of mutations on protein-protein off-rates and dissociation mechanisms by τRAMD
The dissociation rate, or its reciprocal, the residence time (τ), is a crucial parameter for
understanding the duration and biological impact of biomolecular interactions. Accurate …
understanding the duration and biological impact of biomolecular interactions. Accurate …
Current status of computational approaches for small Molecule Drug Discovery
W Xu - Journal of Medicinal Chemistry, 2024 - ACS Publications
2024 has been an exciting year for computational sciences, with the Nobel Prize in Physics
awarded for “artificial neural network” and the Nobel Prize in Chemistry presented for …
awarded for “artificial neural network” and the Nobel Prize in Chemistry presented for …
Detection of putative ligand dissociation pathways in proteins using site-identification by ligand competitive saturation
Drug efficacy often correlates better with dissociation kinetics than binding affinity alone. To
study binding kinetics computationally, it is necessary to identify all of the possible ligand …
study binding kinetics computationally, it is necessary to identify all of the possible ligand …
Mechanism of Ligand Binding to Theophylline RNA Aptamer
Studying RNA-ligand interactions and quantifying their binding thermodynamics and kinetics
are of particular relevance in the field of drug discovery. Here, we combined biochemical …
are of particular relevance in the field of drug discovery. Here, we combined biochemical …
[HTML][HTML] Increased throughput in methods for simulating protein ligand binding and unbinding
SR Zia, A Coricello, G Bottegoni - Current Opinion in Structural Biology, 2024 - Elsevier
By incorporating full flexibility and enabling the quantification of crucial parameters such as
binding free energies and residence times, methods for investigating protein-ligand binding …
binding free energies and residence times, methods for investigating protein-ligand binding …
Investigating the effects of chitosan atomic ratio and drug type on mechanical properties of silica aerogel/chitosan nanocomposites using molecular dynamics …
Understanding the mechanical behavior of the nanocomposites (NCs) can lead to the
development of drug delivery systems with improved stability, durability, and performance …
development of drug delivery systems with improved stability, durability, and performance …