Few methods use molecular dynamics simulations in concert with atomically detailed force fields to perform protein–ligand docking calculations because they are considered too time demanding, despite their accuracy. In this paper we present a docking algorithm based on molecular dynamics which has a highly flexible computational granularity. We compare the accuracy and the time required with wel...

Different groups in our community hold strong views about tail docking in domestic dogs. These range from veterinary associations and welfare organisations, which typically want the practice banned, to purebred dog associations, which vigorously oppose the introduction of antidocking legislation. An evaluation of the tail docking issue, which is informed and nonemotive, requires the integration...

Evaluation of Surface Complementarity, Hydrogen bonding, and Electrostatic interaction in molecular Recognition (ESCHER) is a new docking procedure consisting of three modules that work in series. The first module evaluates the geometric complementarity and produces a set of rough solutions for the docking problem. The second module identifies molecular collisions within those solutions, and th...

Protein–ligand docking is the major workhorse in computeraided structure-based lead finding and optimization. Predicted protein–ligand complex configurations are used for studying protein–ligand interactions, estimating binding affinities, and as a final filter step in virtual screening. Early methods on protein–ligand docking treated either both proteins and ligands as rigid molecules or allow...

We here approach the problem of designing a controller for automatic rendezvous and docking (AR&D). As a first step towards a fully reactive neurocontroller (based on state feedback), an artificial neural network is trained offline by a fitness based genetic algorithm to fulfill the docking task. Its performance using one specific docking case, with fixed initial and boundary conditions, is com...

Molecular docking is the methodology of choice for studying in silico protein-ligand binding and for prioritizing compounds to discover new lead candidates. Traditional docking simulations suffer from major limitations, mostly related to the static or semi-flexible treatment of ligands and targets. They also neglect solvation and entropic effects, which strongly limits their predictive power. D...

MOTIVATION Computational modeling of protein-DNA complexes remains a challenging problem in structural bioinformatics. One of the key factors for a successful protein-DNA docking is a potential function that can accurately discriminate the near-native structures from decoy complexes and at the same time make conformational sampling more efficient. Here, we developed a novel orientation-dependen...

Protein-ligand docking is an essential step in modern drug discovery process. The challenge here is to accurately predict and efficiently optimize the position and orientation of ligands in the binding pocket of a target protein. In this paper, we present a new method called PSOVina which combined the particle swarm optimization (PSO) algorithm with the efficient Broyden-Fletcher-Goldfarb-Shann...

Ligand-based and structure-based drug screening methods were integrated for in silico drug development by combining the maximum-volume overlap (MVO) method with a protein-compound docking program. The MVO method is used to select reliable docking poses by calculating volume overlaps between the docking pose in question and the known ligand docking pose, if at least a single protein-ligand compl...