The main problem addressed in this work is the accurate reconstruction of molecular structures from a given value of a chemical property of interest, namely HOMO energy values. There are two related issues in reverse quantitative structure-activity relationship (reverse QSAR), the first one is the existence of a molecule with the given property value, and the second one is the choice of the most interesting structure in the case when several molecules with the same HOMO value exist. We assume a molecule exists for each given HOMO value. In an ideal case, we would have to deal with a differentiable mapping f from the space G of molecules to the space V of its real-valued HOMO values. Assume that v 0 is the desired HOMO value. Then, for a molecule g, we can introduce a loss function L v0 (g) = |v 0 -f (g)| p for some norm | • | p . In such a scenario, it would be possible to search for the optimal structure, by minimizing the L v using gradient descent methods. Unfortunately, since the space G of molecules is discrete, the mapping f is not differentiable, and we cannot apply the optimization approach directly. We use a VAE-type architecture to firstly map molecules from G to the corresponding latent space of the representations in R n for some n (encoder mapping E : G -→ R n ) and back from R n to G (decoder mapping D : R n -→ G). Next, we construct regression mapping f R : R n -→ V and apply the above mentioned optimization process to the function f R .