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All Journal HAYATI Journal of Biosciences Jurnal Teknologi Industri Pertanian Indonesian Journal of Biotechnology Journal of Agromedicine and Medical Sciences Journal of Tropical Biodiversity and Biotechnology Manajemen Pendidikan BERITA BIOLOGI JURNAL BIOLOGI INDONESIA Jurnal Teknologi Laboratorium Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Chimica et Natura Acta Indonesian Journal of Chemistry Jurnal Sinergitas PkM & CSR FaST : Jurnal Sains dan Teknologi Walisongo Journal of Chemistry Menara Perkebunan Jurnal Teknik Informatika (JUTIF) Bioinformatics and Biomedical Research Journal Cermin Dunia Kedokteran Indonesian Journal of Life Sciences Makara Journal of Science Makara Journal of Technology Biosaintifika: Journal of Biology & Biology Education Jurnal Bioteknologi & Biosains Indonesia (JBBI) Cermin Dunia Kedokteran Kesmas: Jurnal Kesehatan Masyarakat Nasional (National Public Health Journal) Jurnal Bioteknologi & Biosains Indonesia Berita Biologi
Arli Aditya Parikesit
Department Of Bioinformatics, School Of Life Sciences, Indonesia International Institute For Life Sciences (i3l), Jakarta, Indonesia
Agriculture, Biological Sciences & Forestry Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Health Professions Immunology & microbiology Industrial & Manufacturing Engineering Materials Science & Nanotechnology Mechanical Engineering Medicine & Pharmacology Public Health Social Sciences Other

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Journal : Makara Journal of Science

 1 
Protein Annotation of Breast-cancer-related Proteins with Machine-learning Tools Parikesit, Arli Aditya; Agustriawan, David; Nurdiansyah, Rizky
Makara Journal of Science Vol. 24, No. 2
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One of the primary contributors to the mortality of women is breast cancer. Several approaches are used to cure it, but recurrence occurs in 79% of the cases because the underlying mechanism of the protein molecules is not carefully ex-amined. The goal of this research was to use machine-learning tools is to elucidate conserved regions and to obtain functional annotations of breast-cancer-related proteins. The sequences of five breast-cancer-related proteins (BRCA2, BCAR1, BCAR3, BCAR4, and BRMS1) and their annotations were retrieved from the UniProt and TCGA databases, respectively. Conserved regions were extracted using CLUSTALX. We constructed a phylogenetic tree using the MEGA 7.0. SUPERFAMILY database to obtain fine-grained domain annotation. The tree revealed that the BRCA2 and BCAR4 protein sequences are located in a clade, which indicates that they have overlapping functions. Several protein domains were identified, including the SH2 and Ras GEF domains in BCAR3, the SH3 domain in BCAR1, and the BRCA2 helical domain, the nucleic-acid-binding protein, and tower domain. We found that no protein domains could be annotated for BCAR4 or BRMS1, which may indicate the presence of a disordered protein state. We suggest that each protein has distinct functionalities that are complementary in regulating the progression of breast cancer, although further study is necessary for confirmation. This protein-domain annotation project could be leveraged by the complete integration of mapping with respect to gene and disease ontology. This type of leverage is vital for obtaining biochemical insights regarding breast cancer.
COVID-19 In Silico Drug with Zingiber officinale Natural Product Compound Library Targeting the Mpro Protein Wijaya, Renadya Maulani; Hafidzhah, Muhammad Aldino; Kharisma, Viol Dhea; Ansori, Arif Nur Muhammad; Parikesit, Arli Aditya
Makara Journal of Science Vol. 25, No. 3
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Coronavirus disease 2019 (COVID-19), which is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has become a worldwide pandemic. Ginger (Zingiber officinale) is a rhizome, which is commonly used for culinary and medicinal purposes. In Indonesia, ginger is taken as traditional medicine by processing it into a drink known as jamu. The present study aimed to assess and evaluate the bioactive compounds in ginger that can be used in drug design for treating COVID-19. The crystal structure of the SARS-CoV-2 main protease (Mpro) was generated from a protein sequence database, i.e., Protein Data Bank, and the bioactive compounds in ginger were derived from the existing compounds library. Mpro is involved in polyprotein synthesis, including viral maturation and nonstructural protein gluing, making it a potential antiviral target. Furthermore, the bioactive compounds in ginger were analyzed using Lipinski’s rule of five to determine their drug-like molecular properties. Moreover, molecular docking analysis was conducted using the Python Prescription 0.8 (Virtual Screening Tool) software, and the interaction between SARS-CoV-2 Mpro and the bioactive compounds in ginger was extensively examined using the PyMOL software. Out all of the 16 bioactive compounds that were docked successfully, 4-gingerol, which has the lowest binding energy against SARS-CoV-2 Mpro, as per the virtual screening results, was proven to have the most potential as a viral inhibitor of SARS-CoV-2
STUDI IN SILICO MODIFIKASI POS TRANSLASI DISAIN VAKSIN CHIMERIC BERBASIS VIRUS LIKE PARTICLES HUMAN PAPILLOMAVIRUS DENGAN KAPSID VIRION L1 Tambunan, Usman Sumo Friend; Parikesit, Arli Aditya; Tochary, Theo A.; Sugiono, Dedy
Makara Journal of Science Vol. 11, No. 2
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Computational Study of Post Translation Modification in Chimeric Virus Like Particles Vaccine of Human Papilloma Virus with Virion Capsid L1. The Human Papillomavirus (HPV) infection has a tight correlation with the incidence of cervical cancer. Chimeric virus like particles (cVLP) has been developed as vaccine candidate for preventing cervical cancer. cVLPs are improvement of Virus Like Particles (VLP) by substituting the epitope of L1 HPV -18 and -52 protein to L1 HPV -16 protein. They are ANN1, ANN2, HMM1, and HMM2. The impact of post translation modification will be determined. Based on In Silico study, the dominant post translation modification is glycosylation
Molecular Simulation of B-Cell Epitope Mapping from Nipah Virus Attachment Protein to Construct Peptide-Based Vaccine Candidate: A Reverse Vaccinology Approach Kharisma, Viol Dhea; Dian, Farida Aryani; Burkov, Pavel; Scherbakov, Pavel; Derkho, Marina; Sepiashvili, Ekaterina; Sucipto, Teguh Hari; Parikesit, Arli Aditya; Murtadlo, Ahmad Affan Ali; Jakhmola, Vikash; Zainul, Rahadian
Makara Journal of Science Vol. 27, No. 2
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There are no specific drugs or vaccines for Nipah virus (NiV), which is a new Paramyxovirus that infects swine and humans. This study was conducted to investigate B-cell epitope mapping of the NiV attachment glycoprotein and to construct peptide-based vaccine candidates using the reverse vaccinology approach. To generate the linear B-cell epitope, the NiV isolates were extractad from GenBank, NCBI, using the IEDB web server; peptide modeling was conducted using PEP-FOLD3; docking was conducted using PatchDock and FireDock; and in silico cloning was designed using SnapGene. Various peptides were successfully identified from the NiV attachment glycoprotein based on B-cell epitope prediction, allergenicity prediction, similarity prediction, and toxicity prediction. An in silico cloning design of the pET plasmic was also developed. The peptide “RFENTTSDKGKIPSKVIKSYYGTMDIKKINEGLLD” (1G peptide) is predicted to be a potential candidate for the NiV vaccine as it has several good vaccine characteristics. It increases the immune response of B cells through activation, differentiation into plasma cells, the formation of memory cells, and it may increase IgM/IgG antibody titres for viral neutralization. However, the results of this study should be further verified through in vivo and in vitro analyses
Development of a Multi-Epitope Peptide Vaccine Against Monkeypox Virus: Immunoinformatics Analysis for South East Asian HLA Alleles Chandra, Nelson; Herdiansyah, Mochammad Aqilah; Kharisma, Viol Dhea; Ansori, Arif Nur Muhammad; Parikesit, Arli Aditya
Makara Journal of Science Vol. 29, No. 1
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The monkeypox virus (MPXV), a DNA virus causing zoonotic disease, poses major global public health challenges, with mortality rates between 3%–6%. Although smallpox vaccines provide partial cross-protection, there is a critical need for a dedicated, effective monkeypox (mpox) vaccine. This study aimed to design a multi-epitope peptide-based vaccine specifically adapted to the HLA allele profiles common in Southeast Asian populations, where MPXV cases are rising. Using immunoinformatics, we screened for and detected B and T cell epitopes from the MPXV cell surface antigen and IFN-alpha/beta receptor proteins. The vaccine design was validated through a rigorous evaluation of its antigenicity, immunogenicity, allergenicity, and toxicity to ensure both safety and efficacy. Key epitopes were mapped to HLA alleles including HLA-A*11:01, HLA-A*24:02, and HLA-B*15:02, which are highly prevalent in Southeast Asia populations. Molecular docking analyses demonstrated stable interactions between the vaccine construct and TLR3/TLR4 immune receptors, suggesting a robust immune response activation. Additionally, molecular dynamics simulations confirmed the structural stability of the vaccine-receptor complex. This immunoinformatics-driven multi-epitope vaccine design offers a promising candidate for combating MPXV, with high projected coverage and immuno-genic potential for Southeast Asian populations. Validation in laboratory and clinical settings is recommended to con-firm these findings.
Co-Authors Adi Sofyan Ansori, Muhammad Albert Widjaja Aldino Hafidzhah, Muhammad Alhussain, Shaheer Alyaa Farrah Dibha Angelique, Priscilla Arif Nur Muhammad Ansori Bernard, Stefanus Bhat, Nausheen Burkov, Pavel Chandra, Nelson David Agustriawan Dedy Sugiono Deidre Valeska, Margareta Derkho, Marina Dian, Farida Aryani Didik Huswo Utomo Dito Anurogo Dito Anurogo Dito ANUROGO Dito Anurogo Dito Anurogo Dito Anurogo Dito Anurogo, Dito Ema Utami Ezra Bernandus Wijaya Fugaha, Daniel Ryan Gabriela, Vania Gabriele Mustika Kresnia Gabriella Patricia Adisurja Hafidzhah, Muhammad Aldino Heerlie, Devita Mayanda Herdiansyah, Mochammad Aqilah Hutapea, Hotma Martogi Lorensi Imron Imron Jakhmola, Vikash Jeremias Ivan Josephine, Evalina Junaida Astina Karimah, Nihayatul Karimah, Nihayatul Kharisma, Viol Dhea KUSRINI Kusrini, Kusrini Maksim Rebezov Margareta Deidre Valeska Margaretha, Febrina Maria Kiseleva Maulani Wijaya, Renadya Miko Wahyono, Tri Yunis Muhammad Aldino Hafidzhah Muhammad Aldino Handzhah Muhammad Hermawan Widyananda Murtadlo, Ahmad Affan Ali Nadezhda Kenijz Natalia Satya, Putri Gabriella Angel Nelda Aprilia Salim Nihayatul Karimah Patricia Adisurja, Gabriella Patricia, Gabriella Posa, Gabrielle Ann Villar Prakoso, Muhammad Ja'far Pratama, Rico Alexander Putri Gabriella Angel Natalia Satya Rahadian Zainul Ramanto, Kevin Nathanael Ratnasari, Nanda Risqia Pradana Renadya Maulani Wijaya Ridarto, Afif Maulana Yusuf Riza A PUTRANTO Rizky Nurdiansyah Rizky, Wahyu Choirur Ryan Fugaha, Daniel Ryan Wijaya Ryan Wijaya, Ryan Satrio Wibowo Scherbakov, Pavel Sepiashvili, Ekaterina Shemuel, Josia Sofy Permana Sri Wahyuningsih Stefanus Bernard Sudaryo, Mondastri Korib Sugiono, Dedy Svetlana Artyukhova Tambunan, Usman Sumo Friend Teguh Hari Sucipto, Teguh Hari Theo A Tochary Tochary, Theo A. Usman Sumo Friend Tambunan Utomo, Didik Huswo Utomo, Didik Huswo Vikash Jakhmola Viol Dhea Kharisma Wicaksono, Adhityo Wijaya, Renadya Maulani Yanuargi, Bayu Yulia Matrosova