Landscape Navigator
Energy landscapes describe molecular systems in terms of stable points, transition states, pathways, and the energetic and dynamic relationships between them. This methodology is the foundation of Landscape Navigator.
The product is a computational discovery environment for exploring molecular energy landscapes and chemical spaces in the same workspace. It primarily reasons over ensembles of stable points on an energy landscape, allowing researchers to compare states, follow transition routes, and weigh energetic and dynamic considerations when deciding which conformations, cavities, or mechanisms to drug.
For large target molecules, it helps researchers inspect high-dimensional property datasets, compare minima and transition states, follow pathways through a landscape, and visualise cavities or surface regions on selected structures. By reasoning in ensembles rather than around a single structure, it can reveal binding opportunities that static models can miss.
Chemical spaces can be explored through ligands and conformers, allowing candidate small molecules to be compared and docked against chosen cavities, surface regions, or target states. Once target and chemical spaces are identified, Landscape Navigator can produce high-quality harbour datasets: ranked docking-output databases that connect compounds, target states, poses, and scoring information. These harbour datasets support prioritisation, pose analysis, affinity-oriented interpretation, and follow-on experimental planning.
The environment connects visual exploration with computational work. Many operations can run locally or at the edge as smoke tests, while high-throughput calculations can be submitted to the DOHD ROTU compute supercluster and reviewed in the same workspace.
Landscape Navigator also provides access to AI models that accelerate stages of discovery workflows. These include high-quality embedding models, both general-purpose and conditioned on target, disease, or both, for comparison, prioritisation, and downstream analysis.
The product offers unprecedented practical insight into energy-landscape data and allows it to be analysed in new ways. It supports qualitative interpretation of molecular systems while exposing quantitative access points for reproducible computational work.
When offered as part of a pilot, DOHD ROTU structural biologists guide teams through the process. Minimal prior knowledge of energy-landscape methodology is required.
