This letter gives results on improving protein–ligand binding affinity predictions based on
molecular dynamics simulations using machine learning potentials with a hybrid neural …

We introduce the self-relative binding free energy (self-RBFE) approach to evaluate the
intrinsic statistical variance of dual-topology alchemical binding free energy estimators. The …

An alchemical enhanced sampling (ACES) method has recently been introduced to facilitate
importance sampling in free energy simulations. The method achieves enhanced sampling …

The majority of drug-like molecules contain at least one ionizable group, and many common
drug scaffolds are subject to tautomeric equilibria. Thus, these compounds are found in a …

Antimicrobial resistance in bacteria often arises from their ability to actively identify and
expel toxic compounds. The bacterium strain Pseudomonas putida DOT-T1E utilizes its …

Free energies play a central role in characterising the behaviour of chemical systems and
are among the most important quantities that can be calculated by molecular dynamics …

Relative binding free-energy (RBFE) calculations have shown high accuracy in predicting
ligand binding affinity and have been used as an important tool in computer-aided drug …

We present receptor-hopping and ligand-swapping free energy estimation protocols based
on the Alchemical Transfer Method (ATM) to model the binding selectivity of a set of ligands …

We present an analytical description of the Alchemical Transfer Method (ATM) for molecular
binding using the Potential Distribution Theory (PDT) formalism. ATM models the binding …

Molecular recognition plays a crucial role in various biological processes, such as enzymatic
reactions, signal transduction, and genetic information processing. Investigating how …