How to Prepare Proteins and Ligands for AutoDock Vina
Prepare receptor and ligand inputs for AutoDock Vina with a reproducible workflow for structure selection, protonation, PDBQT generation, inspection, and preparation records.
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Evidence-led articles on scientific methods, reproducible workflows, and software decisions.
How to Interpret AutoDock Vina Results: Affinity, RMSD, and Pose Selection
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.
Is an AutoDock Vina GUI Worth Paying For? A Practical Workflow Comparison
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.
Vina vs Vinardo: How to Choose a Scoring Function for Reproducible Molecular Docking
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.
AI-Generated Ligands Need More Than a Score: What to Evaluate in a Molecular Docking Workflow
Molecular docking for AI-generated ligands needs chemical preparation, controlled protocols, pose review, and traceable results. See a documented CDK2 case in MolNexus.
How to Keep Molecular Docking Runs Organized Across Receptors, Ligands, and Poses
Loose files and ambiguous names make docking studies difficult to reconstruct. Learn how to connect receptors, ligands, parameters, poses, exports, and persistent job history.
How to Choose Molecular Docking Software for Reproducible Small-Molecule Screening
A practical buyer guide for researchers evaluating molecular docking software: preparation, search-space control, engine settings, pose review, job history, export, licensing, and fit.
AlphaFold Didn’t Replace Molecular Docking—It Unlocked Its Next Era
AlphaFold has dramatically reduced the structural bottleneck that kept many protein targets outside docking studies. Learn how predicted structures become receptor starting points for protein–small-molecule docking and virtual screening with AutoDock Vina.
How to Predict Protein Antigenicity In Silico: A Reproducible Workflow
Learn what a Kolaskar–Tongaonkar-derived propensity profile measures, how Classic Antigenicity calculates it, and how to prioritize candidate linear regions with reproducible evidence.