Desain Vaksin Multiepitop Monkeypox berbasis Imunoinformatika sebagai Pengembangan Kandidat Vaksin di Indonesia

Abstract

Monkeypox (Mpox) merupakan penyakit zoonosis yang disebabkan oleh virus Monkeypox (MPXV) dan telah menjadi darurat kesehatan global. Hingga saat ini belum tersedia vaksin yang dikembangkan khusus untuk MPXV, terutama di Indonesia. Penelitian ini bertujuan merancang kandidat vaksin multiepitop berbasis imunoinformatika serta menyesuaikannya dengan profil alel HLA dominan di Indonesia. Melalui metode imunoinformatika, dilakukan karakterisasi protein, prediksi dan seleksi epitop, desain vaksin, pemodelan 3D, molecular docking, dan imunosimulasi. Hasil penelitian menunjukkan bahwa protein H3L merupakan antigen unggul. Vaksin desain yang tersusun atas 353 asam amino bersifat stabil, hidrofilik, non-alergenik, dan non-toksik. Population coverage terhadap populasi Indonesia mencapai 99,45%. Vaksin menunjukkan afinitas tinggi terhadap TLR3 dan TLR4, serta mampu menginduksi respons imun humoral dan seluler yang kuat dalam simulasi. Vaksin multiepitop berbasis imunoinformatika yang dirancang berpotensi menjadi kandidat vaksin MPXV yang efektif dan aman untuk populasi Indonesia, namun masih memerlukan validasi eksperimental lebih lanjut.

Monkeypox (Mpox) is a zoonotic disease caused by the Monkeypox virus (MPXV) and has become a global health emergency. To date, no vaccine specifically developed for MPXV is available, particularly in Indonesia. This study aimed to design a multiepitope vaccine candidate based on immunoinformatics while adapting it to the dominant HLA allele profile of the Indonesian population. Using immunoinformatics methods, protein characterization, epitope prediction and selection, vaccine design, 3D modeling, molecular docking, and immun simulation were performed. The results showed that the H3L protein was the superior antigen. The designed vaccine, composed of 353 amino acids, was stable, hydrophilic, non-allergenic, and non-toxic. Population coverage for the Indonesian population reached 99.45%. The vaccine demonstrated high affinity for TLR3 and TLR4 and was able to induce strong humoral and cellular immune responses in the simulation. The immunoinformatics-based multiepitope vaccine designed in this study has the potential to be an effective and safe MPXV vaccine candidate for the Indonesian population, although further experimental validation is still required.