This website uses cookies to improve your experience. More information
Research articles, tutorials, and practical guidance tagged AutoDock Vina.
Find a method, workflow, scientific concept, or software decision.
Screen multiple ligands without losing the scientific record. Preserve stable identities, one frozen Vina protocol, failures, ranked poses, exports, and local job history across the batch.
Read the analysisFilter the publication by research area or keyword.
Evidence-led articles on scientific methods, reproducible workflows, and software decisions.
An SDF file can load and still be unfit for docking. Diagnose valence, aromaticity, fragments, stereochemistry, hydrogens, 3D geometry, minimization, and PDBQT failures before AutoDock Vina.
Validate a molecular docking workflow before committing a ligand library: separate pose recovery from screening discrimination, test early enrichment and robustness, and define a defensible go/no-go decision.
Set an AutoDock Vina search space with defensible center and size coordinates, then pair box volume with exhaustiveness, seeds, visualization, and a reproducible validation record.
Prepare receptor and ligand inputs for AutoDock Vina with a reproducible workflow for structure selection, protonation, PDBQT generation, inspection, and preparation records.
Learn what AutoDock Vina affinity, RMSD lower and upper bounds, and mode ranks actually mean—and use a documented c-Abl case to choose poses without relying on score alone.
AutoDock Vina is open-source, so what makes a paid GUI worth considering? Compare automation, preparation, box control, pose review, history, product fit, and real workflow value.
Compare Vina and Vinardo without mistaking a more negative score for better docking. Use a controlled protocol, target-relevant validation, and a real c-Abl case.
Molecular docking for AI-generated ligands needs chemical preparation, controlled protocols, pose review, and traceable results. See a documented CDK2 case in MolNexus.
Loose files and ambiguous names make docking studies difficult to reconstruct. Learn how to connect receptors, ligands, parameters, poses, exports, and persistent job history.