Abstract
Computer-aided drug design has become quite an important topic to study for modelling the drug for critical disease-causing proteins in reduced time and money. Nowadays, scientists are using bioinformatics in protein 3D structure prediction that is more convenient than conventional 2-D protein structure prediction. In this paper, new algorithms have been proposed on top of traditional GA and PSO that assumes a variable-length tree structure which represents a drug molecule and arranges essential functional groups in different positions of that drug. Once the geometry of the drug is obtained, its docking energy is minimized. We have also considered several inter-molecular forces for more accuracy. Results show that PSO performs better than the earlier GA methods. Nowadays, scientists are using bio-informatics in protein 3D structure prediction that is more convenient than conventional 2D protein structure prediction.
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Chatterjee, A., Roy, U.K., Haldar, D. (2018). Evolutionary Algorithms to Minimize Interaction Energy Between Drug Molecule and Target Protein in Streptococcus. In: Bhattacharyya, S., Gandhi, T., Sharma, K., Dutta, P. (eds) Advanced Computational and Communication Paradigms. Lecture Notes in Electrical Engineering, vol 475. Springer, Singapore. https://doi.org/10.1007/978-981-10-8240-5_39
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DOI: https://doi.org/10.1007/978-981-10-8240-5_39
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