Judul: Prediction of T-Cell Epitope Candidate Targeting Conserved-KRAS for Cancer Vaccine using Reverse Vaccinology Approach
Abstrak: Kanker merupakan penyebab kematian kedua terbesar di dunia. Sebanyak 9.6 juta kematian manusia di dunia disebabkan oleh kanker. Kurang lebih sepertiga penderita kanker mengalami mutasi gen KRAS. Mutasi gen KRAS banyak terjadi pada kanker pankreas (90%), kanker kolon (30-40%), dan kanker paru (15-25%). Pendekatan reverse vaccinology dapat mempermudah pengembangan vaksin penyakit yang sebelumnya sulit dan tidak mungkin diproduksi. Penelitian ini bertujuan untuk merancang kandidat epitop sel-T dengan target conserved-KRAS sebagai imunoterapi kanker. KSFEDIHHY merupakan kandidat epitop terbaik yang dihasilkan dari rangkaian penelitian yang dilakukan. Kandidat epitop ini memiliki skor imunogenisitas yang baik, diprediksi dapat berikatan dengan banyak supertipe HLA, bersifat non-alergen dan non-toksik. KSFEDIHHY dapat berikatan dengan HLA B*57:01 dengan affinitas -7.8 kkal/mol. Prediksi ikatan antara peptida dan HLA yang telah dilakukan baik berdasarkan sekuens maupun berdasarkan struktur ini menunjukkan KSFEDIHHY potensial untuk dikembangkan sebagai kandidat epitop untuk vaksin kanker., Cancer is the second cause of death in the world. There are 9.6 million deaths caused by cancer. Approximately one third of cancer patients have the KRAS gene mutation. KRAS gene mutations occur mostly in pancreatic cancer (90%), colon cancer (30-40%), and lung cancer (15-25%). The reverse vaccinology approach can ease the difficulties and impossiblities to produce vaccine. This study aims to design T-cell epitopes candidate targeting the conserved-KRAS as cancer immunotherapy. KSFEDIHHY is the best epitope candidate from a series of assays conducted. This candidate epitope has a good immunogenicity score, predicted to be able to bind with many HLA supertypes, non-allergenic and non-toxic. KSFEDIHHY can make a complex with HLA B*57:01 with binding affinity -7.8 kcal/mol. Prediction analysis for both sequence-based and structure-based shows that KSFEDIHHY has the potential to be developed as an epitope candidate for cancer vaccines.
Keyword: reverse vaccinology, HLA class I, T-cell epitope

Judul: Virtual screening of Ligands with Epidermal Growth Factor Receptor Protein as Candidate Targeted Therapy for Lung Cancer
Abstrak: Salah satu cara pengobatan kanker paru-paru yaitu melalui metode terapi target dengan mekanisme pemberian obat ke molekul spesifik yaitu sel kanker. Penelitian ini dimaksudkan untuk menemukan kandidat obat terapi kanker paru- paru melalui metode komputasi dengan melihat nilai energi afinitas dan pengujian toksisitasnya. Sebanyak 250 struktur EGFR (tipe wildtype dan mutasi) sebagai protein target akan dilakukan virtual screening dan penambatan molekul dengan ligan dari database zinc20 sejumlah 131.328 ligan. Hasil dari virtual screening tersebut didapatkan delapan belas struktur ligan terbaik yaitu tujuh ligan yang berinteraksi dengan struktur EGFR tipe wildtype dengan nilai energi afinitasnya sebesar -9,76 kcal/mol hingga -9,32 kcal/mol. Sebanyak sebelas ligan yang berinteraksi dengan struktur mutasi dengan nilai energi afinitas -9,11 kcal/mol hingga -8,08 kcal/mol. Terdapat lima ligan yang berinteraksi dengan baik di struktur wildtype dan mutasi yaitu ligan dengan rumus kimia C24H16F2N2O4, C20H13F2N5O4,C23H27N5O4,C19H21N5O4S2, dan C22H26ClN5O2. Struktur reseptor dari protein EGFR yang paling banyak berikatan dengan ligan terbaik adalah struktur dengan kode 3W33,3W2S, dan 4LI5. Jenis asam amino yang sama pada struktur wildtype dan mutasi yang muncul yaitu pada ikatan hidrofobik adalah Asp855 dan pada ikatan hidrogen adalah Val726 dan Leu718., One of the treatments for lung cancer is through targeted therapy, which involves the administration of drugs to specific molecules, namely cancer cells. This research aims to discover potential lung cancer therapy candidates through computational methods by examining the affinity energy values and conducting toxicity testing. A total of 250 EGFR structures (wildtype and mutations) as target proteins will undergo virtual screening and molecular docking with ligands from the zinc20 database, consisting of 131.328 ligands. The results of the virtual screening identified eighteen top ligand structures, including seven ligands that interacted with the wildtype EGFR structure with affinity energy values ranging from -9,76 kcal/mol to -9,32 kcal/mol. Eleven ligands interacted with the mutation structure with affinity energy values from -9,11 kcal/mol to -8,08 kcal/mol. Five ligands showed good interaction with both wildtype and mutation structures, namely C24H16F2N2O4,C20H13F2N5O4,C23H27N5O4, C19H21N5O4S2, and C22H26ClN5O. As for the receptor structure of the EGFR protein that bound most to the top ligands, the structures with the codes 3W33, 3W2S, and 4LI5 were predominant. The same amino acids that appeared in both wildtype and mutation structures in hydrophobic bonds were Asp855, and in hydrogen bonds is Val726 and Leu718.
Keyword: kanker paru-paru, EGFR, docking, energi afinitas, interaksi ligan-protein

Judul: Model Input-output dalam Masalah Network Flow
Abstrak: Production process is a process, which is done by industry, to transform input into output. According to the type of output and its activity, industry can be classified into various sectors, which are connected to each other. Therefore, a model to analyze the connection among sections is needed. The model is known as input-output model (IO model). IO model presents an IO table, which shows informations about the transaction between goods and services in each economic sector. Furthermore, the IO model also shows that the amount of all input is the same as the amount of all output. In this paper, the transaction of each economic sector in IO table is analyzed using network flow theory. The formulated network flow problem implies that each sector represents partly as a producer and also as a consumer. This paper also solves a minimum cost circulation problem.
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