With the Lasergene 14 release, we introduce NovaDock*, a high-resolution protein-protein docking application that predicts atomic interactions between any two proteins, and works in conjunction with Protean 3D to visualize results. Simply provide your ligand and receptor sequence files, and NovaDock will predict the three-dimensional structure of the macromolecular complex. Utlizing the SwarmDock algorithm, NovaDock explores protein flexibility when docking, resulting in more accurate predictions.



NovaDock can be accessed on the Cloud through NovaCloud Services on our website or within Protean 3D, or as a command-line application run on Linux. For more information, please check out the Nova Applications User Guide, the NovaDock technical requirements, or contact us.


PDF icon Lasergene Structural Biology Suite Overview


*NovaDock is a protein-protein interaction prediction software based on SwarmDock developed in Dr Paul Bates’ laboratory at the Cancer Research UK London Research Institute and ongoing at the Francis Crick Institute, and is provided under license from Cancer Research Technology Limited.

Features & Highlights


Predict Accurate Atomic Interactions

  • Predict accurate 3-dimensional structures for two binding partners utilizing SwarmDock, one of the top three algorithms validated in the CAPRI blind docking experiment
  • Evaluate energy score, cluster size, and number of ligand contacts for each model in a summarized view, and adjust the filtering scheme as desired
  • Rotate, zoom and inspect each individual docking model and examine the residues and atoms of the docking interface for each one


Analyze Structure and Evaluate Secondary Structural Characteristics

  • Spin each model or convert it to a .structure file with a single click
  • Easily identify residues, binding sites, disulfide bonds, helices, and sheets using annotations in the Sequence View
  • Evaluate a broad selection of secondary structural characteristics such as amphiphilicity, charge density, disorder, flexibility, hydropathy, and more, by applying prediction methods