The proposed model allows the prediction of important chemical property values, namely the HOMO energy levels, which are otherwise costly to compute. While our model performs on the same level of accuracy as the current state-of-the-art regression models, the junction tree variational autoencoder coupled with a regression algorithm also allows to create new molecular structures with desired HOMO value. We have proposed two strategies for performing the guided search for such structures and experimentally shown that our model produces molecules with desirable target properties.