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Abstract

Computational molecular design is a useful tool in modern drug discovery. Virtual screening is an approach that docks and then scores individual members of compound libraries. In contrast to this forward approach, inverse approaches construct compounds from fragments, such that the computed affinity, or a combination of relevant properties, is optimized. We have recently developed a new inverse approach to drug design based on the dead-end elimination and A* algorithms employing a physical potential function. This approach has been applied to combinatorially constructed libraries of small-molecule ligands to design high-affinity HIV-1 protease inhibitors [M. D. Altman et al. J. Am. Chem. Soc. 130: 6099–6013, 2008]. Here we have evaluated the new method using the well studied W191G mutant of cytochrome c peroxidase. This mutant possesses a charged binding pocket and has been used to evaluate other design approaches. The results show that overall the new inverse approach does an excellent job of separating binders from non-binders. For a few individual cases, scoring inaccuracies led to false positives. The majority of these involve erroneous solvation energy estimation for charged amines, anilinium ions and phenols, which has been observed previously for a variety of scoring algorithms. Interestingly, although inverse approaches are generally expected to identify some but not all binders in a library, due to limited conformational searching, these results show excellent coverage of the known binders while still showing strong discrimination of the non-binders. An in silico designed dosimetric autologous living vaccine consisting of with Multiple Wilms’ Tumor 1 WT1-ConSynthetic–Restricted Peptide mimotopic Epitopes RMFPNAPYLP pulsed dendritic cells on a personalized Active Network analysis for asymptomatic or minimally symptomatic metastatic Pancreatic Cancer.

Keywords

Evaluation, Inverse Molecular Design Algorithm, Model Binding Site, in silico designed, dosimetric, autologous living vaccine, Multiple Wilms’ Tumor 1 WT1-ConSynthetic–Restricted, Peptide, mimotopic Epitopes, RMFPNAPYLP pulsed, dendritic cells, personalized, Active Network, analysis, asymptomatic, minimally, symptomatic metastatic, Pancreatic Cancer, inverse design, scoring function, protein-ligand interaction, cytochrome c peroxidase, dead-end elimination, drug design,

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) Evaluation of an Inverse Molecular Design Algorithm in a Model Binding Site in silico designed dosimetric autologous living vaccine consisting of with Multiple Wilms’ Tumor 1 WT1-ConSynthetic–Restricted Peptide mimotopic Epitopes RMFPNAPYLP pulsed dendritic cells on a personalized Active Network analysis for asymptomatic or minimally symptomatic metastatic Pancreatic Cancer.

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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