Fungal infections have retained their status as a significant human health threat, resulting in the publication of the first fungal priority pathogens list by the World Health Organization. Thus, the development of new antifungals is essential in the mainstream of drug design to combat fungal infections. Computer-aided calculations have become a necessary part of works devoted to new drug design. Virtual libraries of structural files for both low-molecular electrophilic phytochemicals and proteins from Saccharomyces cerevisiae and Candida albicans have been created based on experimental databases as well as using the AlphaFold resource for some proteins with unsolved 3D structures. During the virtual screening process, many affine interactions were identified as having binding energies calculated using the Autodock Vina program of no more than -9 kcal/mol. In particular, ixerin D (Pubchem code CID101553163) from dandelion was predicted to bind to proteins with PDB structures codes 3of7, 5t94, 4uuy, 2cnq, 2zeu, and 3bnu, demonstrating the possibility of covalent modifications of CYS453. Inuloxin (CID102194603) was bound in silico to the protein with PDB code 5TZ1 and lactucin (CID442266) to the protein with PDB code 1IYL. Similar affine interactions of an unsaturated ketone (CID5318099) from Helichrysum and Orthosiphon aristatus were predicted using modeled protein structures with Uniprot database codes A0A1D8PEV1, A0A1D8PSE5, P29717, Q59U61, Q59YG2, Q5A5N0, A0A1D8PN96, and Q59Q43. These results have provided valuable insights into the possible repurposing of well-known phytochemicals with the aim of developing new tools for yeast infection management. The work was supported by the BRFFR (Belarus) grant X23MH-005.