We developed a new graphical-numerical method called TI2BioP (Topological Indices to BioPolymers) to estimate topological indices (TIs) from two-dimensional (2D) graphical approaches for the natural biopolymers DNA, RNA and proteins The methodology mainly turns long biopolymeric sequences into 2D artificial graphs such as Cartesian and four-color maps but also reads other 2D graphs from the thermodynamic folding of DNA/RNA strings inferred from other programs. The topology of such 2D graphs is either encoded by node or adjacency matrixes for the calculation of the spectral moments as TIs. These numerical indices were used to build up alignment-free models to the functional classification of biosequences and to calculate alignment-free distances for phylogenetic purposes. The performance of the method was evaluated in highly diverse gene/protein classes, which represents a challenge for current bioinformatics algorithms. TI2BioP generally outperformed classical bioinformatics algorithms in the functional classification of Bacteriocins, ribonucleases III (RNases III), genomic internal transcribed spacer II (ITS2) and adenylation domains (A-domains) of nonribosomal peptide synthetases (NRPS) allowing the detection of new members in these target gene/protein classes. TI2BioP classification performance was contrasted and supported by predictions with sensitive alignment-based algorithms and experimental outcomes, respectively. The new ITS2 sequence isolated from Petrakia sp. was used in our graphical-numerical approach to estimate alignment-free distances for phylogenetic inferences. Despite TI2BioP having been developed for application in bioinformatics, it can be extended to predict interesting features of other biopolymers than DNA and protein sequences. TI2BioP version 2.0 is freely available from http://ti2biop.sourceforge.net/.