Abstract: Embodiments of the invention include systems and methods that enable the identification of candidate proteins that have desired features of a target protein. An example method comprises receiving first and second input proteins. The method further comprises applying a first machine learning model to the first and second input proteins to generate corresponding fragments. The method further comprises applying a second machine learning model to the fragments, wherein applying the second machine learning model comprises generating an encoded representation in a multidimensional space for each of the fragments. The method also comprises generating a similarity score between the fragments from the first input and the second input. The method then comprises generating a hierarchical scale of similarity between the first and second inputs according to the similarity score and selecting candidate proteins based on the hierarchical scale.

Abstract: An antifungal composition showing broad antifungal activity includes at least one peptidic fragment with antifungal activity. The composition has a broad antifungal spectrum and could be used as a food, cosmetic, coating and/or paint, or to enhance the antifungal properties of other antifungal agents in these products, or any other application where broad antifungal activity is required. Several peptidic fragments and their possible modifications to ensure optimal activity are detailed. Methods for producing and formulating the antifungal composition are also disclosed.