SIMULATING DRUG-TARGET INTERACTION USING LARGE SCALE MOLECULAR DYNAMICS AND FUZZY-ART
DOI:
https://doi.org/10.22159/ajpcr.2017.v10s1.19973Keywords:
Fuzzy-ARTMAP, Nil, Biomolecular interactionAbstract
The examination of bio-molecular associations between a complex drug compound and its target is of foremost significance for the improvement of new biomarkers or bioresponsive compounds. In this paper, we exhibited a combinatorial technique of simulation of molecular dynamics (MD) and fuzzy ART to focus on the coupling factors of in the molecular binding process and its intermediary transitioning state. Here, MD simulations divided into microsecond length enable us to watch a inter-molecular coupling events, taking after different dynamical pathways and accomplishing ordered binding assembly of molecules. Results form such simulations are used to evaluate parameters corresponding to its thermodynamic and molecular kinetic properties, getting a decent concurrence with accessible experimental information. Utilizing machine learning algorithms in conjunction with MD simulations could enhance the productive for identifying key parts of drug–target binding and localization.
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Durrant, J. & McCammon, J. A. Molecular dynamics simulations and drug discovery. BMC Biol. 9, 71 (2011).
Copeland, R. A., Pompliano, D. L. & Meek, T. D. Drug-target residence time and its im-plications for lead optimization. Nat. Rev. Drug Discov. 5, 730–739 (2006).
Jorgensen, W. L. Foundations of biomolecular modeling. Cell 155, 1199–1202 (2013).
Shan, Y. et al. How does a drug molecule find its target binding site? J. Am. Chem. Soc. 133, 9181–9183 (2011).
Dror, R. O. et al. Pathway and mechanism of drug binding to G-proteincoupled receptors. Proc. Natl Acad. Sci. USA 108, 13118–13123 (2011).
Pe´rez-Herna´ndez, G., Paul, F., Giorgino, T., De Fabritiis, G. & Noe´, F. Identification of slow molecular order parameters for Markov model construction. J. Chem. Phys. 139, 015102 (2013).
Bisignano, P. et al. Kinetic characterization of fragment binding in AmpC b-lactamase by high-throughput molecular simulations. J. Chem. Inf. Model 54, 362–366 (2014).
Buch, I., Giorgino, T. & De Fabritiis, G. Complete reconstruction of an enzymeinhibitor binding process by molecular dynamics simulations. Proc. Natl Acad. Sci. USA 108, 10184–10189 (2011).
Rinaldo-Matthis, A. et al. l-Enantiomers of transition state analogue inhibitors bound to human purine nucleoside phosphorylase. J. Am. Chem. Soc. 130, 842–844 (2007).
Hirschi, J. S., Arora, K., Brooks, 3rd C. L. & Schramm, V. L. Conformational dynamics in human purine nucleoside phosphorylase with reactants and transition-state analogues. J. Phys. Chem. B 114, 16263–16272 (2010).
Ho, M. C. et al. Four generations of transition-state analogues for human purine nuc-leoside phosphorylase. Proc. Natl Acad. Sci. USA 107, 4805–4812 (2010).
Gail A. Carpenter, Stephen Grossberg, and David B. Rosen. Fuzzy ART: Fast Stable Learning and Categorization of Analog Patterns by an Adaptive Resonance System." Neural Networks, 4(6):759-771, 1991.
Poggio, T. & Girosi, F. Networks for approximation and learning. Proc. IEEE 78, 1481–1497 (1990).
Miles, R. W., Tyler, P. C., Furneaux, R. H., Bagdassarian, C. K. & Schramm, V. L. One-third-the-sites transition-state inhibitors for purine nucleoside phosphorylase. Biochemi-stry 37, 8615–8621 (1998).
Lewandowicz, A., Tyler, P. C., Evans, G. B., Furneaux, R. H. & Schramm, V. L. Achieving the ultimate physiological goal in transition state analogue inhibitors for purine nucleoside phosphorylase. J. Biol. Chem. 278, 31465–31468 (2003).
A. Rai, S. Ramanathan and R. J. Kannan, "Quasi Opportunistic Supercomputing for Geospatial Socially Networked Mobile Devices," 2016 IEEE 25th International Conference on Enabling Technologies: Infrastructure for Collaborative Enterprises (WETICE), Paris, 2016, pp. 257-258. doi: 10.1109/WETICE.2016.65.
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