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Abstract

Near linear scaling fragment based quantum chemical calculations are becoming increasingly popular for treating large systems with high accuracy and is an active field of research. However, it remains difficult to set up these calculations without expert knowledge. To facilitate the use of such methods, software tools need to be available to support these methods and help to set up reasonable input files which will lower the barrier of entry for usage by non-experts. Previous tools relies on specific annotations in structure files for automatic and successful fragmentation such as residues in PDB files. We present a general fragmentation methodology and accompanying tools called FragIt to help setup these calculations. FragIt uses the SMARTS language to locate chemically appropriate fragments in large structures and is applicable to fragmentation of any molecular system given suitable SMARTS patterns. We present SMARTS patterns of fragmentation for proteins, DNA and polysaccharides, specifically for D-galactopyranose for use in cyclodextrins. FragIt is used to prepare input files for the Fragment Molecular Orbital method in the GAMESS program package, but can be extended to other computational methods easily.FragIt: A Tool to Prepare Input Files for Fragment Based Quantum Chemical CalculationsA rational in silico drug-target flexibility complement methodology-design for the generation of a peptide-mimic novel pharmacoelement binding to the amino acid conserved sequences of the active loop of a Haemophilus influenzae porin P2.FragIt: A Tool to Prepare Input Files for Fragment Based Quantum Chemical Calculations. Haemophilus influenzae type b (Hib) is one of the leading causes of invasive bacterial infection in young children. It is characterized by inflammation that is mainly mediated by cytokines and chemokines. One of the most abundant components of the Hib outer membrane is the P2 porin, which has been shown to induce the release of several inflammatory cytokines. A synthetic peptide corresponding to loop L7 of the porin activates JNK and p38 mitogen-activated protein kinase (MAPK) pathways. It has also been reported that a novel use of the complementary peptide approach to design a peptide that is able to bind selectively to the protein P2, thereby reducing its activity. In this in silico study we used of higher levels of our complement conserved structure ligand based binding pocket drug interactive theory to increase the accuracy of protein-ligand binding affinity predictions, resulting in better hit identification success rates as well as more efficient lead optimization processes. Here, we discovered for the first time the GENEA-Poriflunzaten-5567 a Peptide-mimic novel pharmacoelements complementary to the active loop of porin P2 from Haemophilus influenzae for the annotated modulation of its activity using a rational in silico drug-target flexibility complement methodology-design to Prepare Input Files for Fragment Based Quantum Chemical Calculations for the generation of a peptide-mimic novel pharmacoelement binding to the amino acid conserved sequences of the active loop Haemophilus influenzae porin P2.

Keywords

combined-application;knowledge-based;scoring;physical;-forcefield;-based hit-scoring;functions; rational; in silico drug-target; flexibility; complement; methodology-design; peptide-mimic; novel pharmacoelement; amino acid; conserved sequences; active loop; Haemophilus influenzae; porin P2;. Input Files; Fragment Based; Quantum Chemical Calculations;

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) A rational in silico drug-target flexibility complement methodology-design to Prepare Input Files for Fragment Based Quantum Chemical Calculations for the generation of a peptide-mimic novel pharmacoelement binding to the amino acid conserved sequences of the active loop Haemophilus influenzae porin P2.

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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