Volatile Sulfur Compounds (VSCs) are organic compounds that were recently characterized for their contribution to the odor, flavor, and therapeutic effects of Cannabis sativa L. However, the biochemical pathways underlying VSC biosynthesis in Cannabis sativa remain incompletely characterized. Here, we report a systematic computational approach to identify candidate protein homologs of key biosynthetic enzymes in the proteome of a Cannabis sativa cultivar GMO (also known as Garlic, Mushroom, Onions). Through profile Hidden Markov Model (HMM) searches of reference sequences from eight VSC-producing plant species, including garlic (Allium sativum), onion (Allium cepa), hops (Humulus lupulus), passionfruit (Passiflora edulis), grape (Vitis vinifera), durian (Durio zibethinus), jackfruit (Artocarpus heterophyllus), and horseradish (Armoracia rusticana). From Pfam database, we retrieved HMM profiles of protein domains present in nine target enzyme classes including myrosinase, lipoxygenase (LOX), γ-glutamyl transpeptidase (GGT), glutathione S-transferase (GST), alcohol dehydrogenase (ADH), alliinase, cysteine synthase (IRC7), methionine γ-lyase (MGL), and cystathionine γ-synthase. Using HMMER with optimized parameters, we searched the proteome of the cannabis cultivar GMO and identified a significant number of candidates based on the protein domain presence and its statistical significance. Additionally, we retrieved amino-acid sequences of all target enzymes. From this pool of candidate enzymes, we chose the candidate that has a significant homolog of the target enzyme present in the proteome and shows the presence of the protein domain. Our analysis identified high-confidence homologs for all nine target enzyme classes. These results provide the first systematic catalog of candidate VSC biosynthases and sulfur metabolism genes in the Cannabis sativa cultivar GMO. This study creates a foundation for experimental validation and metabolic engineering efforts to identify and enhance VSC metabolite production.