QSAR for RNases and theoretic–experimental study of molecular diversity on peptide mass fingerprints of a new Leishmania infantum protein

Abstract

The toxicity and low success of current treatments for Leishmaniosis determines the search of new peptide drugs and/or molecular targets in Leishmania pathogen species (L. infantum and L. major). For example, Ribonucleases (RNases) are enzymes relevant to several biologic processes; then, theoretical and experimental study of the molecular diversity of Peptide Mass Fingerprints (PMFs) of RNases is useful for drug design. This study introduces a methodology that combines QSAR models, 2D-Electrophoresis (2D-E), MALDI-TOF Mass Spectroscopy (MS), BLAST alignment, and Molecular Dynamics (MD) to explore PMFs of RNases. We illustrate this approach by investigating for the first time the PMFs of a new protein of L. infantum. Here we report and compare new versus old predictive models for RNases based on Topological Indices (TIs) of Markov Pseudo-Folding Lattices. These group of indices called Pseudo-folding Lattice 2D-TIs include: Spectral moments pi ( k )(x,y), Mean Electrostatic potentials xi ( k )(x,y), and Entropy measures theta ( k )(x,y). The accuracy of the models (training/cross-validation) was as follows: xi ( k )(x,y)-model (96.0%/91.7%)>pi ( k )(x,y)-model (84.7/83.3) > theta ( k )(x,y)-model (66.0/66.7). We also carried out a 2D-E analysis of biological samples of L. infantum promastigotes focusing on a 2D-E gel spot of one unknown protein with M<20, 100 and pI <7. MASCOT search identified 20 proteins with Mowse score >30, but not one >52 (threshold value), the higher value of 42 was for a probable DNA-directed RNA polymerase. However, we determined experimentally the sequence of more than 140 peptides. We used QSAR models to predict RNase scores for these peptides and BLAST alignment to confirm some results. We also calculated 3D-folding TIs based on MD experiments and compared 2D versus 3D-TIs on molecular phylogenetic analysis of the molecular diversity of these peptides. This combined strategy may be of interest in drug development or target identification.

QSAR Models for Proteins of Parasitic Organisms, Plants and Human Guests: Theory, Applications, Legal Protection, Taxes, and Regulatory Issues

“…For instance, in a recent work our group recognized that the toxicity and low success of current treatments for Leishmaniosis determines the search of new peptide drugs and/or molecular targets in Leishmania pathogen species (L. infantum and L. major). In this sense, we decided to invetigate the molecular diversity of Ribonucleases (RNases) using MARCH-INSIDE [104]. RNAses are enzymes relevant to several biologic processes; then, theoretical and experimental study of the molecular diversity of Peptide Mass Fingerprints (PMFs) of RNases is useful for drug design.…”

MOZART, a QSAR Multi-Target Web-Based Tool to Predict Multiple Drug–Enzyme Interactions

“…This methodology has been used since 1962 when Hansch published the first QSAR study [ 13 ]. This approach may predict different properties such as toxicity, physical properties, drug activity, enzyme function, or even the toxicity or properties of nanoparticles [ 14 , 15 , 16 , 17 , 18 , 19 , 20 , 21 , 22 , 23 ] using specific features of the molecules, also called molecular descriptors (MD). QSAR methodology has been used together with docking in the development of new drugs.…”

Enhanced QSAR Model Performance by Integrating Structural and Gene Expression Information

“…With the assumption that structurally similar molecules have similar biological properties, quantitative structure-activity relationship (QSAR)-based in silico approaches have played an essential role in risk assessment [1,2], drug discovery and development [3], and classification of active compounds in many biological research projects [4,5,6]. One of the primary examples would be separation of chemicals into subgroups with different toxic responses using global QSAR models [7].…”