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Abstract

Geometric modeling of biomolecules plays an essential role in the conceptualization of biolmolecular structure, function, dynamics and transport. Qualitatively, geometric modeling offers a basis for molecular visualization, which is crucial for the understanding of molecular structure and interactions. Quantitatively, geometric modeling bridges the gap between molecular information, such as that from X-ray, NMR and cryo-EM, and theoretical/mathematical models, such as molecular dynamics, the Poisson-Boltzmann equation and the Nernst-Planck equation. In this work, we present a family of variational multiscale geometric models for macromolecular systems. Our models are able to combine multiresolution geometric modeling with multiscale electrostatic modeling in a unified variational framework. We discuss a suite of techniques for molecular surface generation, molecular surface meshing, molecular volumetric meshing, and the estimation of Hadwiger’s functionals. Emphasis is given to the multiresolution representations of biomolecules and the associated multiscale electrostatic analyses as well as multiresolution curvature characterizations. The resulting fine resolution representations of a biomolecular system enable the detailed analysis of solvent-solute interaction, and ion channel dynamics, while our coarse resolution representations highlight the compatibility of protein-ligand bindings and possibility of protein-protein interactions.In silico discovery of a Asn-Ile-Ile-Gly-Val-Ser-Tyr peptide mimetic high free energy recored chemical analog molecule CFTR targeted binding sites as a future mutant corrector against over-expressed cystic fibrosis pathological post-transcripts.Multiscale geometric modeling of macromolecules II: Lagrangian representation.Abstract: Cystic Fibrosis (CF) is the most common lethal autosomal recessive disorder in Caucasia population, affecting approximately 30,000 people in the United States and ∼70,000 worldwide. While there is yet no cure for CF, aggressive treatment including mucus thinners, antibiotics, anti-inflammatories and bronchodilators along with physical therapy and proper nutritional repletion, can lengthen and improve the quality of life of CF patients. Peptides derived from mutant CFTR protein which inhibit intracellular degradation and/or retention of mutant CFTR proteins have been clinially used. Methods of inhibiting intracellular degradation and/or retention of mutant CFTR protein by administering peptides having an amino acid sequence corresponding to mutant CFTR amino acid sequences have also been reported in other studies. Further, methods of preventing cellular retention and degradation of an otherwise membrane bound protein by competitively inhibiting intracellular degradation (proteolysis) and retention which would otherwise retain or degrade synthesized mutant proteins prior to arrival of the protein at the cell surface have previously been tested. In our project we conducted a fragment-ligand based structure drug discovery procedure through a ligand-based high throughput screening of 150,000 chemically diverse compounds and of more than 1,500 analogs of active compounds yielded several classes of CFTR corrector multi-targeted to the conserved cystic fibrosis over-expressed nucleic acid binding sites mutant domains. Previous biochemical studies also suggested a mechanism of action involving improved CFTR folding at the ER increased stability at the cell surface. Previous reffered biologically active peptides have been used to inhibit intracellular degradation (proteolysis) and/or retention processes to treat or cure Cystic Fibrosis disease. Peptides are short-lived and typically involve short amino acid stretches bearing few “hot spots”, thus the identification of molecules able to mimic them may produce important lead compounds for the treatment of CF. Here, we have for the first time discovered Multiscale geometric Lagrangian representation modeling of an in silico discovery of a Asn-Ile-Ile-Gly-Val-Ser-Tyr peptide mimetic high free energy recored chemical analog molecule CFTR targeted binding sites as a future mutant corrector against over-expressed cystic fibrosis pathological post-transcripts.

Keywords

In silico discovery; Asn-Ile-Ile-Gly-Val-Ser-Tyr peptide mimetic; high free energy; recored chemical analog molecule; CFTR targeted; binding sites; future mutant corrector; over-expressed; cystic fibrosis; pathological post-transcripts; Multiscale geometric modeling; Lagrangian representation, variational multiscale modeling, Multiresolution surface, Energy functional, Meshing, Curvature, Electrostatics.

Article Type

Research Article – Abstract

Publication history

Received: Sep 20, 2017
Accepted: Sep 25, 2017
Published: Oct 01, 2017

Citation

Grigoriadis Ioannis, Grigoriadis George, Grigoriadis Nikolaos, George Galazios (2017) Multiscale geometric Lagrangian representation modeling of an in silico discovery of a Asn-Ile-Ile-Gly-Val-Ser-Tyr peptide mimetic high free energy recored chemical analog molecule CFTR targeted binding sites as a future mutant corrector against over-expressed cystic fibrosis pathological post-transcripts.

Authors Info

Grigoriadis Nikolaos
Department of IT Computer Aided Personalized Myoncotherapy, Cartigenea-Cardiogenea, Neurogenea-Cellgenea, Cordigenea-HyperoligandorolTM,
Biogenea Pharmaceuticals Ltd,
Thessaloniki, Greece;

Grigoriadis Ioannis
Department of Computer Drug Discovery Science, BiogenetoligandorolTM,
Biogenea Pharmaceuticals Ltd,
Thessaloniki, Greece;

Grigoriadis George
Department of Stem Cell Bank and ViroGeneaTM,
Biogenea Pharmaceuticals Ltd,
Thessaloniki, Greece;

George Galazios
Professor of Obstetrics and Gynecology,
Democritus University of Thrace,
Komotini, Greece;

E-mail: biogeneadrug@gmail.com

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