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All Journal Bioma : Berkala Ilmiah Biologi Eksakta : Berkala Ilmiah Bidang MIPA Contagion: Scientific Periodical Journal of Public Health and Coastal Health Health Information : Jurnal Penelitian Narra J Pharmaceutical Sciences and Research (PSR) Makara Journal of Science Indonesian Journal of Medical Chemistry and Bioinformatics International Journal of Science and Environment Eduvest - Journal of Universal Studies
Erlina, Linda
Department Of Medical Chemistry, Faculty Of Medicine, Universitas Indonesia
Aerospace Engineering Agriculture, Biological Sciences & Forestry Astronomy Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Dentistry Education Energy Engineering Environmental Science Health Professions Immunology & microbiology Materials Science & Nanotechnology Mathematics Mechanical Engineering Medicine & Pharmacology Neuroscience Nursing Physics Public Health Social Sciences

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Epigenetic Diet to Modulate Immune Response against SARS-CoV-2 Andika, Andika; Ahdyani, Risa; Erlina, Linda; Azminah, Azminah; Yanuar, Arry
Pharmaceutical Sciences and Research Vol. 7, No. 2
Publisher : UI Scholars Hub

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Abstract

The COVID-19 pandemic has spread to various parts of the world and caused many deaths. The victims are infected by SARS-CoV-2, a new type of coronavirus that has appeared since December 2019 and caused respiratory symptoms, fever, coughing, and shortness of breath. In addition to social distancing, wearing masks and washing hands, diet is important as a defense of the body against SARS-CoV-2. In this review, researchers conducted epigenetic diet studies that could potentially inhibit SARS-CoV-2, and can be consumed and used on a daily basis.
Pharmacophore-Based Virtual Screening from Indonesian Herbal Database to Find Putative Selective Estrogen Receptor Degraders Prawiningrum, Aisyah F; Paramita, Rafika Indah; Erlina, Linda
Indonesian Journal of Medical Chemistry and Bioinformatics Vol. 1, No. 1
Publisher : UI Scholars Hub

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Abstract

Most breast cancer cases are luminal subtypes which are estrogen receptor-sensitive or progesterone receptor-sensitive. Common treatments include surgery and adjuvant endocrine therapy by prescribing selective estrogen receptor degraders (SERD). SERD is a type of medication that inhibits estrogen receptor (ER) activity by degrading it, and as a result, downregulating it. The current FDA-approved SERD can only be administered through intramuscular injection. The aim of this study is to find orally non-toxic and bioavailable herbal alternatives of SERDs in Indonesian Herbal Database by doing virtual screening using LigandScout. The hit compounds were further analyzed using a molecular docking tool, AutoDock. Three compounds that gave the best results in molecular docking, namely kuwanon T, mulberrin, and curcumin, were analyzed in terms of their toxicity and drug-likeness. Based on toxicity and drug-likeness study, curcumin is considered to be the best candidates for SERD alternatives. This result is further supported by molecular dynamic simulation outcome in which curcumin is the most stable while binding with estrogen receptors.
Pharmacophore Modeling, Molecular Docking, and ADMET Approach for Identification of Anti-Cancer Agents Targeting the C-Jun N-Terminal Kinase (JNK) Protein Nur Ayu Ramadanti; Linda Erlina; Rafika Indah Paramita; Aryo Tedjo; Fadillah Fadillah; Surya Dwira
EKSAKTA: Berkala Ilmiah Bidang MIPA Vol. 24 No. 01 (2023): Eksakta : Berkala Ilmiah Bidang MIPA (E-ISSN : 2549-7464)
Publisher : Faculty of Mathematics and Natural Sciences (FMIPA), Universitas Negeri Padang, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24036/eksakta/vol24-iss01/391

Abstract

One of the most prevalent cancers in Indonesia is breast cancer, based on Indonesia's pathological-based registration.    Breast cancer is a complex, heterogeneous disease classified into hormone-receptor-positive, human epidermal growth factor receptor-2 overexpressing (HER2+) and triple-negative breast cancer (TNBC) based on histological features. Patients with HR+, HER2- Early Breast Cancer (EBC) do not experience recurrence or recurrence for a long time with currently available standard therapy [11]. However, up to 30% of patients with high-risk clinical and/or pathological features may experience a relapse in the first few years. This results in the need for research and development regarding updates in medicine both in terms of treatment and targets and drug compounds used. The c-Jun N-terminal kinase (JNK) protein functions in signaling and influences the apoptotic pathway as well as cancer cell survival. In this study, an insilico screening experiment of inhibitory compounds was carried out on the JNK protein receptor target by screening compounds and molecular docking of compounds for breast cancer therapy.Two novel herbal compounds, Mangostin and ent-Copalyl Dyphospate, have the potential to be turned into medicines that may cause apoptosis through JNK protein targets according to an in-silico-based molecular simulation technique
Molecular Simulation for Screening Bioactive Compounds as Potential Candidate for Alzheimer’s Disease Immanuelle Kezia; Linda Erlina; Ninik Mudjihartini; Fadilah Fadilah
EKSAKTA: Berkala Ilmiah Bidang MIPA Vol. 24 No. 02 (2023): Eksakta : Berkala Ilmiah Bidang MIPA (E-ISSN : 2549-7464)
Publisher : Faculty of Mathematics and Natural Sciences (FMIPA), Universitas Negeri Padang, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24036/eksakta/vol24-iss02/401

Abstract

Alzheimer’s disease is one of the neurodegenerative diseases that afflict the elderly. One of the symptoms is a loss cognitive ability due to neuronal death caused by amyloid plaque accumulation. Alzheimer’s disease is one of the most expensive diseases to treat. Drugs for Alzheimer’s treatment only treat the symptoms, not the disease itself. Several pathways, including the mitochondrial cascade, can be used to develop drugs for Alzheimer’s disease, according to NIH guidelines. Caspase3 is a protein that involved in the mitochondrial cascade, specifically in apoptosis. Alzheimer’s therapy may be more effective if caspase3 is targeted. Indonesia is a rich country, particularly in medicinal plants. We used the Structure-Based Drug Design approaches to screen bioactive compounds in Indonesian medicinal plant to find the best compound candidate. In addition, we performed ADMETOX prediction, molecular docking, and molecular dynamic simulation on forty 3D structures of bioactive compounds and donepezil as an FDA approved Alzheimer’s drug. We discovered Miraxanthin-V had a higher binding affinity than donepezil using molecular simulation. As a result, we can conclude that Miraxanthin-V has a high potential of neuroprotective by inhibiting apoptosis.
Ligand Based Pharmacophore Modelling, Virtual Screening, Molecular Docking, and ADMETOX of Natural Compounds as Antibiotic Candidates against Urinary Tract Infections (UTI) Windy Dwininda; Linda Erlina; Rafika Indah Paramita; Fadillah Fadillah; Surya Dwira; Jaka Fajar Fatriansyah
EKSAKTA: Berkala Ilmiah Bidang MIPA Vol. 24 No. 02 (2023): Eksakta : Berkala Ilmiah Bidang MIPA (E-ISSN : 2549-7464)
Publisher : Faculty of Mathematics and Natural Sciences (FMIPA), Universitas Negeri Padang, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24036/eksakta/vol24-iss02/404

Abstract

The use of antibiotic drugs requires close supervision that patients take antibiotics according to the rules. Irregular antibiotic use led to increased ADR cases (Antibiotic Drug-resistant). ADR is when an individual becomes resistant to an antibiotic drug that cannot kill bacteria. The high number of ADR cases prompted drug discovery to be implemented in analysis for Antibiotic candidates with good effectiveness through the Molecular Docking approach. The search for candidate test compounds as antibiotics were performed using the pharmacophore modelling method and molecular docking. And piperine, withaferin, has some of the same amino acids Ala101, Val103, Glu166, Trp165, and Leu102. Based on the prediction of the promising potential test ligand compound is Corosolic acid. In addition to assessing drug-likeness, pharmacokinetic and toxicity parameters, corosolic acid also has the lowest binding energy among other compounds. Through a textual bioinformatics approach, molecular docking simulations can be used as a first step in the search for new drug candidates in silico by considering various aspects, starting from the physicochemical properties of protein-ligand compounds and the environment. Analysis during the docking process to ADMETOX is an analysis to see the effectiveness and in silico compound safety.  
Comparasion of Microbiome Composition in Acne Vulgaris Using Metagenomic Shotgun and 16s Rrna Zahra Zahra; Linda Erlina
Contagion: Scientific Periodical Journal of Public Health and Coastal Health Vol 5, No 3 (2023): CONTAGION
Publisher : Universitas Islam Negeri Sumatera Utara, Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30829/contagion.v5i3.15393

Abstract

Acne vulgaris is a common skin disease in adolescents and young adults. One factor that plays a role in the development of acne vulgaris is changes in the composition of the microbiome in the skin. The microbiome is the community of microorganisms that live on the surface of the skin and plays an important role in maintaining the ecological balance of the skin. Research on microbiome composition in acne vulgaris has been conducted using various analytical methods, including shotgun metagenomics and 16S rRNA. The aim of this study was to compare the microbiome composition in acne vulgaris using shotgun metagenomics and 16S rRNA. This research method is a literature review while data collection techniques are carried out by library studies obtained from 3 databases Pubmed, Google Scholar and Science Direct. The collected data were then analyzed using qualitative analysis. The results showed that some of the most common bacteria in acne vulgaris, such as Propionibacterium acnes, Staphylococcus epidermidis, and Staphylococcus aureus. In recent years, microbiota screening has been developed using NGS techniques using metagenomic whole genome shotgun and 16S rRNA DNA sequencing analysis. NGS techniques have been able to determine the microbiota of facial skin, and differentiate the bacterial abundance of acne-prone and healthy skin.Keywords : 16s rRNA, Acnes Vulgaris, Microbiome, NGS
Metabolite Biomarker Discovery for Lung Cancer Using Machine Learning Fajarido, Ariski; Erlina, Linda; Tedjo, Aryo; Fadilah, Fadilah; Arozal, Wawaimuli
Indonesian Journal of Medical Chemistry and Bioinformatics Vol. 3, No. 1
Publisher : UI Scholars Hub

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Abstract

Lung cancer is the leading cause of cancer death worldwide. About 2.1 million lung cancer patients were diagnosed in 2018, accounting for about 11.6% of all newly diagnosed cancer cases. For lung cancer, blood is the first choice as a source of screening biomarker candidates. Blood biomarkers provide a snapshot of the patient's entire body, including the primary tumor, metastatic disease, immune response, and peritumoral stroma. However, sputum sampling, bronchial lavage or aspiration, exhaled breath (EB), and airway epithelial sampling represent unique samples for lung cancer and other airway cancers as potential sources for alternative biomarkers. Metabolites are products of cell metabolism that are unique biomarkers in a disease. In this article, we aim to find metabolite biomarkers using machine learning. Metabolite data were obtained from Metabolomic workbench, while detection and identification were performed in silico. From 82 samples, controls and cancers, we found 158 metabolites and analyzed them. From the analysis, we found 3 metabolites that play an important role in lung cancer and found 1 metabolite that is the most influential. From there we found that glutamic acid is one of the best biomarker candidates we provide for detecting lung cancer. However, this simulation still needs to be improved in order to find other biomarkers that can provide a better detection of lung cancer
The Whole Genome Sequencing Of Mycobacterium Tuberculosis For Drug Resistance Prediction Puspitasari, Melya; Andriansjah, Andriansjah; Erlina, Linda
Health Information : Jurnal Penelitian Content Digitized
Publisher : Poltekkes Kemenkes Kendari

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Abstract

Whole-genome sequencing (WGS) has shown tremendous potential in rapid diagnosis of drug-resistant tuberculosis (TB). In the current study, we performed WGS on drug-resistant Mycobacterium tuberculosis isolates obtained from Shanghai (n = 137) and Russia (n = 78). We aimed to characterise the underlying and high-frequency novel drug-resistance-conferring mutations, and also create valuable combinations of resistance mutations with high predictive sensitivity to predict multidrug- and extensively drug-resistant tuberculosis (MDR/XDR-TB) phenotype using a bootstrap method. Most strains belonged to L2.2, L4.2, L4.4, L4.5 and L4.8 lineages. We found that WGS could predict 82.07% of phenotypically drug-resistant domestic strains. The prediction sensitivity for rifampicin (RIF), isoniazid (INH), ethambutol (EMB), streptomycin (STR), ofloxacin (OFL), amikacin (AMK) and capreomycin (CAP). The mutation combination with the highest sensitivity for MDR prediction was rpoB S450L + rpoB H445A/P + katG S315T + inhA I21T + inhA S94A, with a sensitivity of 92.17%, and the mutation combination with highest sensitivity for XDR prediction was rpoB S450L + katG S315T + gyrA D94G + rrs A1401G, with a sensitivity of 92.86%. The molecular information presented here will be of particular value for the rapid clinical detection of MDR- and XDR-TB isolates through laboratory diagnosis.
Identification of Antiviral Compounds against Hepatitis C Virus (HCV) targeting NS3 Protein by Pharmacophore Modeling, Molecular Docking, and ADMET Approach Rahayu, Ratih; Erlina, Linda; Ratnoglik, Suratno Lulut; Yasmon, Andi; Fadilah; Paramita, Rafika Indah
EKSAKTA: Berkala Ilmiah Bidang MIPA Vol. 24 No. 04 (2023): Eksakta : Berkala Ilmiah Bidang MIPA (E-ISSN : 2549-7464)
Publisher : Faculty of Mathematics and Natural Sciences (FMIPA), Universitas Negeri Padang, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24036/eksakta/vol23-iss04/448

Abstract

Hepatitis C Virus (HCV) is a world health problem. HCV infection is initiated by various structural and non-structural proteins. The HCV NS3 protein has an important function in viral replication. The N-terminal domain of NS3 acts as a protease to process most of the viral polypeptides. NS3 also acts as an RNA helicase and NTPase and triggers liver fibrosis which accelerates the development of liver disease. Thus, this study aims to provide information on potential new antiviral candidates against HCV that target the NS3 protein. This study was conducted in-silico with a ligand-based and structure-based pharmacophore model to the cavity of the active protein site generated after virtual screening and molecular docking. The results of this study showed that three compounds, namely stigmasterol, gamma-mangostin, and erycristagallin, were found as HCV antiviral candidates that target the NS3 protein with a lower binding affinity than the native ligand. The binding energy of each compound is -9.23 Kcal/mol, -8.58 Kcal/mol, and -8.17 Kcal/mol. Based on ADMET analysis, the three compounds have high absorption in the small intestine. The cytotoxicity analysis of stigmasterol compounds is not potentially mutagenic, and the LD50 value of stigmasterol is also lower than other compounds.
Structure-Based Virtual Screening and Molecular Docking on the Indonesian Herbal Compound as a Promising Insulin Receptor (INSR) Inhibitor to Suppress Tumor Growth Candraningrum, Veronica Hesti; Erlina, Linda; Paramita, Rafika Indah; Fadillah, Fadillah; Dwira, Surya; Fatriansyah, Jaka Fajar
EKSAKTA: Berkala Ilmiah Bidang MIPA Vol. 24 No. 04 (2023): Eksakta : Berkala Ilmiah Bidang MIPA (E-ISSN : 2549-7464)
Publisher : Faculty of Mathematics and Natural Sciences (FMIPA), Universitas Negeri Padang, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24036/eksakta/vol23-iss04/452

Abstract

A healthy cell maintains a homeostasis condition of glucose level, whereas cancer cells do not. Increased glucose uptake is a hallmark of cancer cells that helps them survive, proliferate, and spread. INSR is one of key feature that take part in glucose metabolism through insulin signaling. To block the entry of glucose into cells, researchers were aiming to disrupt the insulin signaling pathway as the upstream activation in glucose metabolism by inhibiting insulin receptor (INSR) using Indonesian herbal compounds. The approach during the screening was structure-based drug discovery (SBDD) method where INSR was determined as the macromolecules. Some parameters such as binding affinity, constant inhibition, drug-likeness, pharmacokinetics, and toxicity were applied to help the search of potential inhibitor. According to the test results, Heterophylin, Sanggenofuran A, and Epigallocatechin-3-O-caffeate had the strongest molecular binding activity against the INSR protein. Heterophylin is discovered in jackfruit fruit trees and Sanggenofuran A is present in mulberry trees. While Epigallocatechin-3-O-caffeate, is abundantly found in green tea plant
Co-Authors . Andriansjah Abiyyi, Mohammad Wildan Adisti Dwijayanti Ahdyani, Risa Aisyah Latiefah Andi Rosilala Andi Yasmon Andika Andika Andrias Bayu Fariska Ari Estuningtyas Ari Estuningtyas, Ari Arleni Bustami Arry Yanuar Arsianti, Ade Aryo Tedjo Azizah, Norma N. Azminah Azminah Candraningrum, Veronica Hesti Cendani, Gabriella Regita Cristina, Artha Uli Dwirini Retno Fadilah Fadilah Fadilah Fadillah Fadillah Fadillah Fadillah Fajarido, Ariski Fariska, Andrias Bayu Fatriansyah, Jaka Fajar Frans Dany Frans Dany, Frans Harimurti, Putri Saskia Hashim, Najihah M. Ida Neni Haryanti Immanuelle Kezia Insani, Fauzi Azhar Kezia, Immanuelle Kusmardi Liviandari, Regina Monica, Maria Diyan Nabilah Dwi Septiani Nihayah, Silviatun Ninik Mudjihartini Nur Ayu Ramadanti Paramita, Rafika Indah Prawiningrum, Aisyah F Puspitasari, Melya Rafika Indah Paramita Rahayu, Ratih Rahmat Apipi Ratih Rinendyaputri Ratih Rinendyaputri Regina Liviandari Reni Paramita Rohmatul Fajriyah Rosa, Feby Lilia Septelia I. Wanandi Sri S. Ningsih, Sri S. Sugito, Syailendra Karuna Suratno Lulut Ratnoglik Surya Dwira Syahrani, Resda Akhra Wawaimuli Arozal Windy Dwininda Zahra Zahra