Over the last 50 years, several algorithms and approaches were introduced and improved to tackle the challenges of exploring a large and multidimensional conformational space. Optimisation algorithms are frequently used to guide the search in a conformational space of complex molecules such as proteins. It is a crucial step to access molecular properties corresponding to the most stable conformer. The optimisers are usually buried in docking software with limited tuning possibilities. We implement a Fireflies algorithm with Lévy flights distribution to search for the lowest energy conformations of peptides. The hyperparameters of this bio-inspired metaheuristics algorithm are tuned and its performance is compared with the state-of-the-art method. Our results show that the Fireflies-Lévy flights' algorithm is able to improve upon the genetic algorithm method with fewer energy evaluations. To the best of our knowledge, this is the first cheminformatics application that will open the door to additional nature-inspired metaheuristics to support the conformational analysis of large biomolecules.

Fireflies-Lévy flights algorithm for conformational optimization

ACS Spring Meeting 2021

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