Dermatophytosis is a potentially deadly fungal infection of the skin that can have major effects on both the patient's quality of life and the economy. The present work presents a computationally based in-silico approach for annotation of Trichophyton verrucosum hypothetical proteins and their potential therapeutic targets. Trichophyton verrucosum is a zoophilic dermatophyte fungus found worldwide. In rural areas, the fungus T. verrucosum is a common cause of human ringworm, which may be passed on either directly or indirectly from cattle to humans. There has been a significant rise in gene products due to genome sequencing projects, including Hypothetical Proteins (HP) with uncertain functions. Exploring and characterizing the actions of HPs is important in T.verrucosum, a dangerous fungus that causes disease in animals and can be transmitted to people. Many pipelines and web servers that incorporate multiple technologies are made accessible to achieve genome-wide identification of effector proteins. We have performed an NCBI search for hypothetical proteins identification. NCBI-CD and NCBI protein blast is used to identify the conserved domains and non-homologus proteins. The present research strategy will aid in structure prediction of different proteins, the discovery of binding sites, and drug design, allowing for a more in-depth examination of these proteins in wet laboratory experiments and helping in therapeutic development against T. verrucosum. In today's world, HPs might be a viable target for treating diseases linked to antibiotic resistance and drug resistance. This research of drug designing on hypothetical proteins will help farmers and animals to prevent from fungal disease.