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Her research team focuses on computational drug design, biomolecular simulation, cheminformatics and machine learning. They are pioneering the application of swarm intelligence, machine learning, and deep learning to solve problems in protein ligand docking, drug target identification, and prediction of biological activity and toxicity. They are interested in finding new chemical and biological agents with medicinal potential. To date, their computational methods PSOVina, AmPEP, GWOVina, BESTox, LigTMap, etc. have been used and regularly cited (https://app.cbbio.online/). Shirley has great interest in the biophysics of proteins, membranes and polymers. Using molecular dynamics simulations, she has studied the conformational dynamics and mode of action of peptides from nature that are antimicrobial, anticancer, and neurotoxic. She has identified novel antimicrobial and anticancer peptides from the genomes of microbes. She has been involved in the development of membrane lipid force fields and more recently in the modelling of self-assembling monolayers on biochips.
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mSystems (2023)
SUSTAINABILITYno. 6 (2023): 5341-5341
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2023 11th International Conference on Bioinformatics and Computational Biology (ICBCB)pp.136-140, (2023)
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