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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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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
Publisher : UI Scholars Hub

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

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
Prediction Methods of the Protein Subcellular Localization: A Systematic Reviews Parikesit, Arli Aditya; Patricia, Gabriella; Ratnasari, Nanda Risqia Pradana
Indonesian Journal of Life Sciences 2019: IJLS Vol 01 No .02
Publisher : Indonesia International Institute for Life Sciences

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (392.033 KB) | DOI: 10.54250/ijls.v1i2.20

Abstract

The prediction of protein subcellular localization (SCL) has been a long-running challenge in bioinformatics. Protein SCL is crucial for a protein to exercise its functions properly. The reliance of protein localization on signaling peptides and the information available in gene ontology (GO) databases makes it possible to use computational approaches to predict protein SCL. SCL methods can be classified as either sequence-based or annotation-based. Machine learning algorithms and classifiers are used in protein SCL prediction tools. This review presents a list of protein SCL predictors published in the last 5 years.
The Effects and Treatments for Usher Syndrome: A Review Heerlie, Devita Mayanda; Margaretha, Febrina; Fugaha, Daniel Ryan; Parikesit, Arli Aditya
Indonesian Journal of Life Sciences 2024: IJLS Vol 06 No.01
Publisher : Indonesia International Institute for Life Sciences

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54250/ijls.v6i01.184

Abstract

Usher syndrome is defined as the rare genetic disorder that affects both vision and auditory. Although the prevalence is really low, only about 4 to 17 per 100,000 people, it is noted to cover at least 50% of deaf-blindness cases. After reviewing the molecular genetics from several papers, there are several causative genes found with the most prevalent being MYO7A, and USH2A that cause USH type 1 and 2 respectively. Furthermore, other literature has found promising treatments that may help to slow down or prevent further degeneration of the syndrome.
In silico Screening of Potential Antidiabetic Phenolic Compounds from Banana (Musa spp.) Peel Against PTP1B Protein Pratama, Rico Alexander; Astina, Junaida; Parikesit, Arli Aditya
Journal of Tropical Biodiversity and Biotechnology Vol 8, No 3 (2023): December
Publisher : Universitas Gadjah Mada

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/jtbb.83124

Abstract

Type 2 diabetes mellitus (T2DM) is a global problem with increasing prevalence. The current treatments have made an immense progress  with some side effects, such as drug resistance, acute kidney toxicity, and increased risk of heart attack. Banana (Musa spp.) peel comprises 40% of banana fruit contains high phenolic compounds whilst some studies have suggested a correlation between phenolic compounds and antidiabetic activity. One of the novel protein targets that has been identified as a potential anti-diabetic treatment is PTP1B (PDB ID:2NT7). Therefore, this study aimed to screen the potential PTP1B inhibitor for antidiabetic treatment from phenolic compounds in banana peel. QSAR, molecular docking, ADME-Tox, and molecular dynamics analysis were deployed to examine forty-three phenolic compounds in banana peel. Eighteen ligands were screened by QSAR analysis and eight of them had a lower binding energy than the standard (ertiprotafib) in molecular docking, with urolithin A and chrysin were the lowest. Both passed Lipinski’s rule of five, had a good intestinal absorption, and no blood-brain barrier penetration, however, their mutagenicity, carcinogenicity, and irritation to the skin and eyes were still in questions. Molecular dynamics analysis found both of them were in a stable conformation with PTP1B. This study suggested a potential of urolithin A and chrysin as PTP1B inhibitor for antidiabetic treatment. Additionally, further experimentation is required to validate this finding.  
Troubled Helix – Tinjauan Multiperspektif Genetika dalam Bioetika Dito Anurogo; Arli Aditya Parikesit
Cermin Dunia Kedokteran Vol 48 No 3 (2021): Obstetri - Ginekologi
Publisher : PT Kalbe Farma Tbk.

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55175/cdk.v48i3.50

Abstract

Dalam review ini, dibahas tinjauan multiperspektif genetika dalam bioetika. Dikemukakan prinsip-prinsip etika mutakhir, seperti: reciprocity, mutuality, solidarity, citizenry, dan universality. Dibahas pula prinsip-prinsip etika dan pemeriksaan genetika, seperti: otonomi, privasi, kebaikan, nonmaleficence, keadilan. Didiskusikan pula perspektif etnokultural dalam layanan genetika, milestones guideline etika dan regulasi riset biomedis internasional, prinsip-prinsip etika menurut Universal Declaration on Bioethics and Human Rights 2005, hak asasi manusia dan etika profesional: apresiasi translasional, perspektif utilitarianisme, perspektif deontologi, “simalakama” pemeriksaan genetika, globalisasi bioetika, etika bioinformatika, dan riset eugenik. In this review, a multiperspective review of genetics in bioethics is discussed. The latest ethical principles are mentioned, such as: reciprocity, mutuality, solidarity, citizenry, and universality. The principles of ethics and genetic inquiry, such as: autonomy, privacy, kindness, nonmaleficence, justice was also discussed. Also discussed are multiperspective, ethnocultural perspectives in genetic services, milestones of ethical guidelines and international biomedical research regulations, ethical principles according to the Universal Declaration on Bioethics and Human Rights 2005, human rights and professional ethics: translational appreciation, utilitarianism perspective, deontological perspective, the “simulacra” of genetic examination, bioethics globalization, bioinformatics ethics, and eugenic research.
Revolution in Detecting Tuberculosis using Radiology with Application of Deep Learning Algorithm Putri Gabriella Angel Natalia Satya; Arli Aditya Parikesit
Cermin Dunia Kedokteran Vol 48 No 4 (2021): Dermatologi
Publisher : PT Kalbe Farma Tbk.

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55175/cdk.v48i4.70

Abstract

Radiology is a medical examination of internal body parts using data imaging to interpret an illness. Many illnesses can be detected using this medical discipline; one of the diseases is tuberculosis caused by Mycobacterium tuberculosis bacteria. The supreme ability of Artificial Intelligence and Machine learning has amazed the radiologist in analyzing big data-based information. A better deep learning algorithm can lead radiologist to accurate results. This article will review ten (10) research papers that use a deep learning algorithm in the application to detect tuberculosis by data processing technique. The goal is to know the best type of data processing in deep learning to detect TB. Radiologi adalah pemeriksaan bagian dalam tubuh menggunakan data pencitraan untuk interpretasi suatu penyakit. Banyak penyakit dapat dideteksi menggunakan disiplin medis ini; salah satunya adalah tuberkulosis yang disebabkan oleh bakteri Mycobacterium tuberculosis yang menyerang paru. Ahli radiologi tertarik atas kemampuan Artificial Intelligence dan Machine Learning untuk analisis data yang akurat. Artikel ini akan mengulas sepuluh (10) makalah penelitian aplikasi algoritma deep learning untuk deteksi tuberkulosis menggunakan teknik pengolahan data
Use of Artificial Intelligence in the Diagnostics of Autism Spectrum Disorder Gabriele Mustika Kresnia; Arli Aditya Parikesit
Cermin Dunia Kedokteran Vol 49 No 6 (2022): Nutrisi
Publisher : PT Kalbe Farma Tbk.

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55175/cdk.v49i6.246

Abstract

Autism Spectrum Disorder (ASD) is a neurologic development disorder; it is listed in the Diagnostic and Statistical Manual of Mental Disorders, 5th Edition (DSM-V). Early diagnosis is critical in improving the life quality of individuals affected by ASD. Several studies show that Artificial Intelligence can be used in the diagnosis of ASD through biological means such as observing patient EEG data and surveying their genome. Articles were searched in the PUBMED database, ScienceDirect, and Springer Link between 2019 - 2020. Four papers were selected for review. The papers devised models that can accurately predict ASD in affected individuals, though some are based on old data and/or require testing on larger datasets to determine accuracy. As ASD diagnosis usually cannot be achieved before the individual shows symptoms, AI has the potential to improve ASD diagnosis in affected individuals. Further study to confirm the models and test on larger, more recent datasets would be required to develop more accurate models and achieve even better results. Autism spectrum disorder (ASD) merupakan salah satu gangguan perkembangan saraf yang tercantum pada Diagnostic and Statistical Manual of Mental Disorders, 5th Edition (DSM-V). Diagnosis dini sangat penting untuk meningkatkan kualitas hidup individu ASD. Beberapa penelitian menunjukkan bahwa kecerdasan buatan dapat digunakan untuk diagnosis ASD melalui metode berbasis biologis seperti mengamati data EEG pasien dan mensurvei genomnya. Review ini berbasis pencarian data antara tahun 2019 – 2020 di database PUBMED, ScienceDirect, dan Springer Link. Empat makalah kunci dipilih untuk ditinjau. Makalah-makalah tersebut mampu merancang model yang dapat memprediksi ASD secara akurat, meskipun beberapa aspek implementasinya didasarkan pada data usang dan/ atau memerlukan pengujian pada kumpulan data yang lebih besar untuk menentukan akurasi. Mengingat diagnosis ASD biasanya tidak dapat dilakukan sebelum individu menunjukkan gejala, kecerdasan buatan berpotensi meningkatkan ketepatan diagnosis ASD. Masih diperlukan studi lanjutan untuk mengkonfirmasi model dan pengujian pada kumpulan data yang lebih besar dan lebih baru untuk mengembangkan model yang memiliki presisi lebih baik dan hasil lebih akurat.
Drug Repurposing Option for COVID-19 with Structural Bioinformatics of Chemical Interactions Approach Arli Aditya Parikesit; Rizky Nurdiansyah
Cermin Dunia Kedokteran Vol 47 No 3 (2020): Dermatologi
Publisher : PT Kalbe Farma Tbk.

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55175/cdk.v47i3.359

Abstract

The SARS-CoV-2 virus is the pathogenic agent that caused the COVID-19 disease. The epicenter of this disease is the city of Wuhan, China. It is already categorized as “pandemic” by WHO, as many countries already affected with the infections, including recently Indonesia. Although the standard RT-PCR and DNA sequencing protocols has already developed for diagnostic, no drugs are available to cure this disease until today. The anti-malaria drug of chloroquine phosphate was repurposed, as well as other anti-viral drugs. In this regard, a structural bioinformatics pipeline was utilized to validate the claim in the computational realm. Within the sphere of the online molecular docking method, it was found that all the tested repurposed drugs attached accordingly with the SARS-CoV-2 protease enzyme that plays a role in viral replication. The repurposed drugs could be proposed as drug candidates for COVID-19, after clinical trials or further laboratory testing. Virus SARS-CoV-2 adalah patogen penyebab penyakit COVID-19. Episentrum penyakit ini adalah kota Wuhan, Tiongkok. WHO mengeluarkan peringatan ‘pandemi’ karena banyak negara sudah terkena infeksi, termasuk Indonesia. Meskipun protokol RT-PCR dan sekuensing DNA standar telah dikembangkan untuk tujuan diagnostik, hingga saat ini tidak ada obat untuk menyembuhkan penyakit ini. Obat anti-malaria chloroquine phosphate dicoba, bersama dengan beberapa obat anti-virus. Alur analisis bioinformatika struktural digunakan untuk validasi di ranah komputasi. Dalam lingkup metode molecular docking secara online, ditemukan bahwa obat tersebut tertambat dengan enzim protease SARS-CoV-2 yang berperan dalam replikasi virus. Obat ini dapat diusulkan sebagai kandidat obat untuk COVID-19, setelah pengujian laboratorium dan uji klinis lebih lanjut.
The Role of Bioinformatics in Personalized Medicine: Your Future Medical Treatment Margareta Deidre Valeska; Gabriella Patricia Adisurja; Stefanus Bernard; Renadya Maulani Wijaya; Muhammad Aldino Handzhah; Arli Aditya Parikesit
Cermin Dunia Kedokteran Vol 46 No 12 (2019): Kardiovakular
Publisher : PT Kalbe Farma Tbk.

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55175/cdk.v46i12.399

Abstract

Bioinformatics is beneficial in personalized medicine. Two methods stand out, the randomized algorithm and computer assisted drug design (CADD). This article will discuss application, pitfalls, and future of those two methods. Suggestion to improve the clarity of the bioinformatics research in the field of personalized medicine will also be reviewed. Bioinformatika berperan sangat penting dalam personalized medicine. Dua metode penting dalam kajian ini adalah randomized algorithm dan computer assisted drug design (CADD). Kajian ini membahas aplikasi, kekurangan, dan masa depan kedua metode tersebut. Saran-saran untuk meningkatkan efek riset bioinformatika dalam kajian personalized medicine juga akan ditelaah.
Kontribusi Aplikasi Medis dari Ilmu Bioinformatika Berdasarkan Perkembangan Pembelajaran Mesin (Machine Learning) Terbaru Arli Aditya Parikesit
Cermin Dunia Kedokteran Vol 45 No 9 (2018): Infeksi
Publisher : PT Kalbe Farma Tbk.

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55175/cdk.v50i9.729

Abstract

Berkembangnya ilmu bioinformatika merupakan konsekuensi banyaknya data eksperimen laboratorium para peneliti biologi molekuler ataupun biomedis. Selain pengembangan basis data terpusat yang merupakan kompetensi inti ilmu bioinformatika, pendekatan komputasi lain seperti pembelajaran mesin juga dikembangkan, sehingga data tersebut dapat diolah menjadi informasi yang berguna bagi dunia kesehatan. Kajian ini akan menelaah perkembangan pendekatan pembelajaran mesin pada ilmu bioinformatika, dan aplikasinya pada dunia kesehatan terutama pada informatika kanker dan virus. Masa depan aplikasi medis dengan ilmu bioinformatika menarik karena melibatkan berbagai pendekatan baru seperti kecerdasan buatan dan biologi sistem. The development of bioinformatics science is a consequence of the massive data generation of laboratory experiments conducted by molecular biology and biomedical researchers. In addition to the development of a centralized database that is the core competence of bioinformatics science, other computing approaches such as machine learning are also developed so that the data can be processed into useful information for the human health. This review will examine the development of machine learning approaches in bioinformatics science, and its application to the human health, especially in cancer and virus informatics. The future of medical applications with bioinformatics science is exciting as it involves various new approaches such as artificial intelligence and system biology.
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