We analyzed the ability of S4 to explore the chemical space, in terms of generating structurally diverse and bioactive molecules. To this end, we employed a commonly-used strategy with CLMs, that is, varying the sampling temperature (T ) to control chemical diversity . T affects which elements of a string are generated by a weighted random sampling (equation (3)). When T → 0 the most likely element (based on the CLM prediction) is selected as the next element of the sequence, while the higher the T , the more random the selections. T = 1 corresponds to using the CLM predictions as the sampling probability of each element at each generation step.