## 2 Materials and Methods  
### Dataset and Calculation of Topological Descriptors  
We created our PTML-MLP model by following a series of steps that were explained in detail in recent studies [35; 46]. Consequently, here, we focused only on those features in which our work differs from previous reports. We downloaded a single tab-based file from the online database named ChEMBL [55; 56]. Such a file contained chemical data regarding the compounds in the form of SMILES (Simplified Molecular Input Line Entry System) codes. The same file also had biological information. In this sense, the anticancer activity of each compound reported in the biological assays was GI\({}_{50}\), i.e., the concentration of a compound that reduced total cell growth by 50% in a given lung cancer cell line. It is important to emphasize that all the GI\({}_{50}\) values of the compounds present in our dataset were determined by employing the sulforhodamine B (SRB) assay with a test time of 48 h. In our dataset, we eliminated different entries with missing data (SMILES codes, activity values, measurement units, and duplicates). We also deleted repeated entries (compounds predicted more than one time against the same lung cancer cell line); we kept only the entry of the repeated compound with the lowest \(\text{GI}_{50}\) value. We annotated as active [_ALC(e)_ = 1] only those molecules with \(\text{GI}_{50}\leq 2000\) nM against a defined lung cancer cell line. The remaining compounds were annotated as inactive [_ALC(e)_ = \(-1\)]. It should be highlighted that _ALC(e)_ was a dichotomic variable specifying the anticancer activity of the \(i\)th compound under the experimental condition _ej_. At the same time, each experimental condition _ej_ involved two elements, namely, the type of cancer cell line (_ct_) and the mutability (_mb_) of the lung cancer cell line. In the case of _ct_, it had nine labels corresponding to nine different lung cancer cell lines. In the case of _mb_, three labels were assigned according to the values of the tumor mutational burden (TMB) [57, 58]. Notice that TMB \(>10\) is a common threshold used to analyze the susceptibility of cancers to immunotherapy [59]. However, recent reports indicate that this may not be an adequate threshold across multiple types of cancer [60, 61], thus suggesting that different TMB thresholds should be used. Therefore, in this study, in terms of mutability (element _mb_), among the nine lung cancer cell lines, four were labeled as exhibiting \"low\" mutability (TMB \(\leq\) 40 mutations per million bases), three were annotated as having \"intermediate\" mutability (40 < TMB < 85), and the other two were labeled as displaying \"high\" mutability (TMB \(\geq\) 85). In that manner, the element _mb_ reflected (at least indirectly) the potential sensitivity of the different lung cancer cell lines to immunotherapy. Then, a *.txt file containing SMILES codes of the chemicals was employed as the entry by the MODESLAB v1.5 software [62], from which four families of topological descriptors (_TD_) were computed. Such families were the bond-based spectral moments [_SM_(_PP_)_k_], the atom-based connectivity indices [_X_(_SG_)_m_], the atom-based valence connectivity indices [_X_(_NG_)_m_], and the bond-based connectivity indices [_e_(_SG_)_m_]. In the case of _SM_(_PP_)_k_, they were calculated with order \(k\) from 1 to 7 [_k_ is the maximum number of bonds present in a fragment without counting bond multiplicity], being weighted by physicochemical properties _PP_ such as hydrophobic contribution (_Hyd_), topological polar surface area (_Psa_), molar refractivity contribution (_Mol_), atomic weights (_Ato_), etc. In the case of _X_(_NG_)_m_, _X_(_NG_)_m_, and _e_(_SG_)_m_, they were computed with order \(m\) from 1 to 6 [_m_ is the exact number of bonds present in a fragment without counting bond multiplicity] for four types of subgraphs/generic fragments (_SG_): paths (_P_), clusters (_C_), path-clusters (_PC_), and chains/rings (_Ch_).