Study of peptide fingerprints of parasite proteins and drug-DNA interactions with Markov-Mean-Energy invariants of biopolymer molecular-dynamic lattice networks.

Since the advent of Molecular Dynamics (MD) in the science of biopolymers with research by Karplus et al. on the dynamics of proteins, MD has become the leading established, computational techniques to investigate the structure and function of complex biomolecules and their interactions.

 MD trajectory analysis (MDTs) remains, however, Multi-species Recombinant Proteins the biggest challenge and requires a lot of knowledge, experience, and effort. Here, we introduce a new class invariants for MDTs based on the spatial distribution of the mean-Energy ξk values ​​(L) in 2D Euclidean space representation of the MDTs.

Forces of the MD track procedure to fold into a 2D Cartesian coordinate system using the procedure step-by-step driven by simple rules. The ξk (L) value is the invariants of matrix Markov (1Π), which represents the probability of transition between the two countries in the new 2D space; associated with MDTs graphic representation similar to a grid network (LNS) of DNA and protein sequences. 

We also introduced a new algorithm to perform phylogenetic analysis of peptides by MDTs not a polypeptide sequence. In the first experiment, we describe the algorithm to 35 peptides present in Peptide Mass Fingerprinting (PMF) from Leishmania infantum new proteins studied in this work. We report, with the first time, 2D electrophoresis isolation, characterization MALDI TOF Mass Spectroscopy, and Mascot search results for this PMF. 

In a second experiment, we built LNS to 422 MDTs obtained in the simulation of DNA-Drug Docking 57 furocoumarins anticancer interaction with DNA oligonucleotides. We calculate ξk (L) respective values ​​for all LNS and use them as input to train a new classifier with accuracy = 85.44% and 84.91% in the training and validation respectively. 

The new model can be used as a scoring Ovine Recombinant Proteins to guide the docking studies of DNA-drug in the design of new coumarin drugs for PUVA therapy. New phylogenetic analysis algorithms encode different information from sequence similarity and can be used to analyze the MDTs obtained in docking or modeling experiments for each class of biopolymers. Works opens new perspectives in the analysis and application of MD in polymer science.