Publications by authors named "Vivitri Dewi Prasasty"

8 Publications

  • Page 1 of 1

Prediction of human-Streptococcus pneumoniae protein-protein interactions using logistic regression.

Comput Biol Chem 2021 Jun 24;92:107492. Epub 2021 Apr 24.

Faculty of Biology, Universitas Nasional, Jakarta, 12520, Indonesia. Electronic address:

Streptococcus pneumoniae is a major cause of mortality in children under five years old. In recent years, the emergence of antibiotic-resistant strains of S. pneumoniae increases the threat level of this pathogen. For that reason, the exploration of S. pneumoniae protein virulence factors should be considered in developing new drugs or vaccines, for instance by the analysis of host-pathogen protein-protein interactions (HP-PPIs). In this research, prediction of protein-protein interactions was performed with a logistic regression model with the number of protein domain occurrences as features. By utilizing HP-PPIs of three different pathogens as training data, the model achieved 57-77 % precision, 64-75 % recall, and 96-98 % specificity. Prediction of human-S. pneumoniae protein-protein interactions using the model yielded 5823 interactions involving thirty S. pneumoniae proteins and 324 human proteins. Pathway enrichment analysis showed that most of the pathways involved in the predicted interactions are immune system pathways. Network topology analysis revealed β-galactosidase (BgaA) as the most central among the S. pneumoniae proteins in the predicted HP-PPI networks, with a degree centrality of 1.0 and a betweenness centrality of 0.451853. Further experimental studies are required to validate the predicted interactions and examine their roles in S. pneumoniae infection.
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http://dx.doi.org/10.1016/j.compbiolchem.2021.107492DOI Listing
June 2021

Polymorphisms of Estrogen Receptor-α and Estrogen Receptor-β Genes and its Expression in Endometriosis.

Turk J Pharm Sci 2021 Feb;18(1):91-95

Universitas Indonesia, Faculty of Medicine, Department of Medical Biology, Depok, Indonesia.

Objectives: Endometriosis is a common gynecological disorder, characterized by the presence of endometrial-like tissue in the extrauterine location. The increasing estradiol concentration can influence endometriosis risk and estrogen receptor (ER) activity. Polymorphism in ER causes gene expression alteration and influences hormone-receptor interaction. This research aims to determine ER genetic polymorphisms in endometriosis pathogenesis.

Materials And Methods: This study was performed on case-control polymorphisms, which compared 83 women with endometriosis and 76 women without endometriosis. However, the samples used for gene expression analysis and estrogen level measurement were obtained from 18 women with endometriosis and 18 women without endometriosis. Polymerase chain reaction-restriction fragment length polymorphism was used to determine ER genetic polymorphisms. Chi-square, Mann-Whitney test, Spearman's correlation (p), t-independent, and two-tailed tests were used to analyze the data.

Results: Association between the allele ERα rs9340799 A/G and endometriosis was significantly different (p=0.012), whereas rs2234693 T/C polymorphism showed no association with endometriosis. The correlation between the genotype frequencies of allele ERβ rs4986938 G/A and endometriosis was found significantly different (p=0.015; p=0.034).

Conclusion: Estradiol level and ERβ expression increases, polymorphism genotypes and alleles of gene and allele frequency of gene have roles in endometriosis.
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http://dx.doi.org/10.4274/tjps.galenos.2019.94914DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7957307PMC
February 2021

Hepatoprotective effect of seed extracts on paracetamol-induced rats.

Pharm Biol 2021 Dec;59(1):31-39

Faculty of Biotechnology, Atma Jaya Catholic University of Indonesia, Jakarta, Indonesia.

Context: Linn. (Pandanaceae) seed extract is known to have antioxidant activities. However, the potential hepatoprotective effect is still unclear.

Objective: To investigate the hepatoprotection aspect of methanol extract towards paracetamol-induced rats.

Materials And Methods: Thirty male Sprague-Dawley rats were randomly divided into six equal groups: one group served as the healthy control and five groups with hepatotoxicity (hepatotoxic control and 4 treatment groups). The oral treatment of paracetamol-induced hepatotoxicity of 3 g/kg using three different concentrations of (300, 600 and 900 mg/kg), and silymarin (200 mg/kg) groups were administered once a day for 14 days. Enzyme activities and protein levels in serum were determined in rats at the end of the treatments. The histopathology of rat livers was observed under an electron microscope with 10× magnification.

Results: significantly decreased the serum glutamic-oxaloacetic transaminase (SGOT), serum glutamic pyruvic transaminase (SGPT), alkaline phosphatase (ALP) and γ-glutamyl transferase (GGT) activities in induced-paracetamol rat serum ( < 0.05). Moreover, significantly decreased total bilirubin and direct bilirubin levels ( < 0.05). It significantly blocked the decline of serum albumin and protein levels ( < 0.05). Histopathological changes amplified paracetamol-induced liver damage and the hepatoprotective effect of in the liver.

Discussion And Conclusions: improved the hepatoprotective effect in a concentration-dependent manner by reducing related hepatic enzyme and protein markers, suggesting as a useful agent in hepatotoxicity treatment, and it can be generalized to a broader study population in different hepatotoxic animal models.
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http://dx.doi.org/10.1080/13880209.2020.1865408DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7801105PMC
December 2021

The validation of molecular interaction among dimer chitosan with urea and creatinine using density functional theory: In application for hemodyalisis membrane.

Int J Biol Macromol 2021 Jan 10;168:339-349. Epub 2020 Dec 10.

Department of Chemistry, Faculty of Mathematics and Natural Sciences, Bandung Institute of Technology, 40132 Bandung, Indonesia.

The formation of chitosan dimer and its interaction with urea and creatinine have been investigated at the density functional theory (DFT) level (B3LYP-D3/6-31++G**) to study the transport phenomena in hemodialysis membrane. The interaction energy of chitosan-creatinine and chitosan-urea complexes are in range -4 kcal/mol < interaction energy <-20 kcal/mol which were classified in medium hydrogen bond interaction. The chemical reactivity parameter proved that creatinine was more electrophilic and easier to bind chitosan than urea. The energy gap of HOMO-LUMO of chitosan-creatinine complex was lower than chitosan-urea complex that indicating chitosan-creatinine complex was more reactive and easier to transport electron than chitosan-urea complex. Moreover, the natural bond orbital (NBO) analysis showed a high contribution of hydrogen bond between chitosan-creatinine and chitosan-urea. The chitosan-creatinine interaction has a stronger hydrogen bond than chitosan-urea through the interaction O18-H34....N56 with stabilizing energy = -13 kcal/mol. The quantum theory atom in molecule (QTAIM) also supported NBO data. All data presented that creatinine can make hydrogen bond interaction stronger with chitosan than urea, that indicated creatinine easier to transport in the chitosan membrane than urea during hemodialysis process.
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http://dx.doi.org/10.1016/j.ijbiomac.2020.12.052DOI Listing
January 2021

Structure-based discovery of novel inhibitors of Mycobacterium tuberculosis CYP121 from Indonesian natural products.

Comput Biol Chem 2020 Apr 17;85:107205. Epub 2020 Jan 17.

Faculty of Biology, Universitas Nasional, Jakarta, 12520, Indonesia.

Tuberculosis (TB) continues to be a serious global health threat with the emergence of multidrug-resistant tuberculosis (MDR-TB) and extremely drug-resistant tuberculosis (XDR-TB). There is an urgent need to discover new drugs to deal with the advent of drug-resistant TB variants. This study aims to find new M. tuberculosis CYP121 inhibitors by the screening of Indonesian natural products using the principle of structure-based drug design and discovery. In this work, eight natural compounds isolated from Rhoeo spathacea and Pluchea indica were selected based on their antimycobacterial activity. Derivatives compound were virtually designed from these natural molecules to improve the interaction of ligands with CYP121. Virtual screening of ligands was carried out using AutoDock Vina followed by 50 ns molecular dynamics simulation using YASARA to study the inhibition mechanism of the ligands. Two ligands, i.e., kaempferol (KAE) and its benzyl derivative (KAE3), are identified as the best CYP121 inhibitors based on their binding affinities and adherence to the Lipinski's rule. Results of molecular dynamics simulation indicate that KAE and KAE3 possess a unique inhibitory mechanism against CYP121 that is different from GGJ (control ligand). The control ligand alters the overall dynamics of the receptor, which is indicated by changes in residue flexibility away from CYP121 binding site. Meanwhile, the dynamic changes caused by the binding of KAE and KAE3 are isolated around the binding site of CYP121. These ligands can be developed for further potential biological activities.
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http://dx.doi.org/10.1016/j.compbiolchem.2020.107205DOI Listing
April 2020

Data of small peptides in SMILES and three-dimensional formats for virtual screening campaigns.

Data Brief 2019 Dec 4;27:104607. Epub 2019 Oct 4.

Faculty of Pharmacy, Sanata Dharma University, Paingan, Maguwoharjo, Sleman, Depok, Yogyakarta, 55282, Indonesia.

The data presented in this article are structures of dipeptides, tripeptides and tetrapeptides constructed from all possible combinations of 20 natural and common amino acids. In total, the data contains 168400 peptides. The structures are available in their simplified molecular-input line-entry system (SMILES) and three-dimensional (3D) formats. The type of data are text files, which could be accessed and modified either by text editor applications ( Notepad++) or by molecule visualization softwares (, YASARA View). These structures could be used further in virtual screening campaigns in the early stage of drug discovery projects.
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http://dx.doi.org/10.1016/j.dib.2019.104607DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6806445PMC
December 2019

Peptide-Based Subunit Vaccine Design of T- and B-Cells Multi-Epitopes against Zika Virus Using Immunoinformatics Approaches.

Microorganisms 2019 Jul 31;7(8). Epub 2019 Jul 31.

Faculty of Biology, Universitas Nasional, Jakarta 12520, Indonesia.

The Zika virus disease, also known as Zika fever is an arboviral disease that became epidemic in the Pacific Islands and had spread to 18 territories of the Americas in 2016. Zika virus disease has been linked to several health problems such as microcephaly and the Guillain-Barré syndrome, but to date, there has been no vaccine available for Zika. Problems related to the development of a vaccine include the vaccination target, which covers pregnant women and children, and the antibody dependent enhancement (ADE), which can be caused by non-neutralizing antibodies. The peptide vaccine was chosen as a focus of this study as a safer platform to develop the Zika vaccine. In this study, a collection of Zika proteomes was used to find the best candidates for T- and B-cell epitopes using the immunoinformatics approach. The most promising T-cell epitopes were mapped using the selected human leukocyte antigen (HLA) alleles, and further molecular docking and dynamics studies showed a good peptide-HLA interaction for the best major histocompatibility complex-II (MHC-II) epitope. The most promising B-cell epitopes include four linear peptides predicted to be cross-reactive with T-cells, and conformational epitopes from two proteins accessible by antibodies in their native biological assembly. It is believed that the use of immunoinformatics methods is a promising strategy against the Zika viral infection in designing an efficacious multiepitope vaccine.
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http://dx.doi.org/10.3390/microorganisms7080226DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6722788PMC
July 2019

Broad Spectrum Peptide Vaccine Design Against Hepatitis C Virus.

Curr Comput Aided Drug Des 2019 ;15(2):120-135

Faculty of Biotechnology, Atma Jaya Catholic University of Indonesia, Jakarta, Indonesia.

Background: Hepatitis C virus (HCV) infection is a global burden. There is no peptide vaccine found as modality to cure the disease is available due to the weak cellular immune response and the limitation to induce humoral immune response.

Methods: Five predominated HCV subtypes in Indonesia (1a, 1b, 1c, 3a, and 3k) were aligned and the conserved regions were selected. Twenty alleles of class I MHC including HLA-A, HLA-B, and HLAC types were used to predict the potential epitopes by using NetMHCPan and IEDB. Eight alleles of HLA-DRB1, together with a combination of 3 alleles of HLA-DQA1 and 5 alleles of HLA-DQB1 were utilized for Class II MHC epitopes prediction using NetMHCIIPan and IEDB. LBtope and Ig- Pred were used to predict B cells epitopes. Moreover, proteasome analysis was performed by NetCTL and the stability of the epitopes in HLA was calculated using NetMHCStabPan for Class I. All predicted epitopes were analyzed for its antigenicity, toxicity, and stability. Population coverage, molecular docking and molecular dynamics were performed for several best epitopes.

Results: The results showed that two best epitopes from envelop protein, GHRMAWDMMMNWSP (E1) and PALSTGLIHLHQN (E2) were selected as promising B cell and CD8+ T cell inducers. Other two peptides, LGIGTVLDQAETAG and VLVLNPSVAATLGF, taken from NS3 protein were selected as CD4+ T cell inducer.

Conclusion: This study suggested the utilization of all four peptides to make a combinational peptide vaccine for in vivo study to prove its ability in inducing secondary response toward HCV.
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http://dx.doi.org/10.2174/1573409914666181003151222DOI Listing
July 2019