Molecular Orbital Analysis provides early insight into a compound’s electronic stability, reactivity, and binding potential before costly simulations or experiments are run. By identifying where a molecule donates and accepts electrons, this tool helps prioritize drug-like candidates, reduce chemical risk, and guide rational optimization decisions early in discovery.
Electron stability is a key principle that determines how easily a molecule participates in unwanted chemical rations in biological and chemical environments, which impacts safety, metabolism, and robustness. A drug candidate must survive different environments such as the bloodstream, metabolic enzymes, and off-target biomolecules, in which electronic stability will be greatly tested. Revilico’s Molecular Orbital Analysis Engine proves to be an effective tool where a user will be able to screen for electron stability and reactivity in a high throughput manner which will have a strong influence in assessing chemical stability, metabolic liability risk, redox / charge-transfer tendencies, and SAR interpretation across analogs. Before diving into the workflow, we need to have a basic understanding of Density Functional Theory (DFT). A general explanation of what DFT is trying to solve is that we want to understand where electrons are in a molecule (probability distribution of the electron field) and how strongly they are held, partly because electrons determine bonding, reactivity, stability, and charge transfer. The main issue is that with the number of electron interactions we have to track, it becomes almost impossible even for moderately sized molecules to calculate these interactions 1 by 1 using Schrodinger’s equation. The solution is that with DFT, we will model the molecule using the overall electron cloud (electron density) instead of accounting for each electron as a point calculation. Diving deeper in the theory DFT is based on solving the many-electron Schrodinger equation denoted by the following equation: Where the equation will scale catastrophically (O(n!) where n is the number of atoms) with the number of electrons and will become computationally intractable for real drug-like molecules. The DFT solution will replace the many-electron wavefunction (Psi) with the electron density p(r) which depends on three spatial coordinates, regardless of system size. The total energy is written as a functional of this density: Where T[p] is the approximated kinetic energy, V_ext[p] is the electron-nuclear attraction, J[p] is the classical electron-electron repulsion, and E_xc[p] is the exchange correlation energy. In practice DFT is solved using Kohn-Sham orbitals which satisfy: Electron density is reconstructed as When running the engine, we will convert our SMILES string and convert them into 3D molecular structures. We will then run geometry optimization where we will relax the molecule into a low energy structure so artificial strain does not distort the energy calculations. You can think of this as a calibration or preprocessing step. We will then run our DFT calculations which will determine the electron energy, a set of molecular orbitals, and the energy of each orbital. From these calculations we can identify our HOMO (highest-energy orbital that is occupied) and LUMO (lowest-energy orbital that is unoccupied). Calculating the difference between our HOMO and LUMO will measure the minimum energy cost to promote an electron from the most weakly held occupied state to the most empty state.
Interactive HOMO-LUMO Viewer
Explore molecular orbital analysis results in an interactive 3D viewer. Toggle HOMO and LUMO orbital isosurfaces, adjust opacity and isosurface levels, and view orbital energies and HOMO-LUMO gap values.- Orbital Visualization — View HOMO (red/pink) and LUMO (blue) isosurfaces overlaid on the molecular structure.
- Interactive Controls — Toggle orbitals on/off, adjust opacity and isosurface level for detailed exploration.
- Energy Analysis — Review HOMO energy, LUMO energy, and HOMO-LUMO gap for each molecule.