Growth performance of Indonesian three-breed cross chicken associated with growth hormone and insulin-like growth factor 2 genes.

Background and Aim: Poultry, such as chickens, is an important source of animal protein, producing eggs and meat. Local chickens are able to adapt to the hot weather and become more resistant to disease. However, it has relatively slow growth and low egg production. These problems can be overcome through holding selection and crossing. Local chicken productivity is slow and low based on chicken growth. There is a need to examine the factors that influence growth and productivity. Therefore, this study aimed to evaluate crossbreed chicken growth performance, including body weight (BW), BW gain, feed intake, and feed conversion. Materials and Methods: DNA was extracted from 40 chickens with the growth hormone (GH) gene and 40 chickens with the insulin-like growth factor 2 (IGF2) gene, followed by a polymerase chain reaction. Genotyping was performed using restriction fragment length polymorphism analysis. In animal selection and phenotypic data collection, 80 chickens from Sentul, Kampung, and Kedu were used to produce the second-generation three-crossbreed chickens (F2) using the GH gene. Results: Growth hormone is a very relevant gene in chicken performance traits. Growth hormone and IGF2 genes regulate chicken production. This study presents the second-generation growth features of three-crossbreed chickens derived from Sentul, Kampung, and Kedu, all of which are native to Indonesia (F2). A statistically significant (p = 0.05) improvement in BW, weight gain, feed intake, and feed conversion over a 12-week period was observed when the animals were allowed free access to regular feed. Analysis of variance results indicated a significant (p = 0.0001) interaction between the 12-week period and GH and IGF2 gene sensitivities of different chicken breeds. Conclusion: Crossbreed chicken growth performance increased within 12 weeks. This study highlighted the need to improve the productivity and breeding of domestic crossbred chickens to contribute to the Indonesian conservation and genetic diversity program.

Assessment of Antitumor and Antiproliferative Efficacy and Detection of Protein-Protein Interactions in Cancer Cells from 3D Tumor Spheroids.

When compared to two-dimensional (2D) cell cultures, 3D spheroids have been considered suitable in vitro models for drug discovery research and other studies of drug activity. Based on different 3D cell culture procedures, we describe procedures we have used to obtain 3D tumor spheroids by both the hanging-drop and ultra-low-attachment plate methods and to analyze the antiproliferative and antitumor efficacy of different chemotherapeutic agents, including a peptidomimetic. We have applied this method to breast and lung cancer cell lines such as BT-474, MCF-7, A549, and Calu-3. We also describe a proximity ligation assay of the cells from the spheroid model to detect protein-protein interactions of EGFR and HER2. © 2022 Wiley Periodicals LLC. Basic Protocol 1: Growth of 3D spheroids using the hanging-drop method Basic Protocol 2: Growth of spheroids using ultra-low-attachment plates Support Protocol 1: Cell viability assay of tumor spheroids Support Protocol 2: Antiproliferative and antitumor study in 3D tumor spheroids Support Protocol 3: Proximity ligation assay on cells derived from 3D spheroids.

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

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 ß-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.

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

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 ER 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 ERß rs4986938 G/A and endometriosis was found significantly different (p=0.015; p=0.034). CONCLUSION: Estradiol level and ERß expression increases, polymorphism genotypes and alleles of ERß rs4986938 G/A gene and allele frequency of ERα rs9340799 A/G gene have roles in endometriosis.

Hepatoprotective effect of Pandanus odoratissimus seed extracts on paracetamol-induced rats.

CONTEXT: Pandanus odoratissimus 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 P. odoratissimus 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 P. odoratissimus (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: Pandanus odoratissimus 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 (p < 0.05). Moreover, P. odoratissimus significantly decreased total bilirubin and direct bilirubin levels (p < 0.05). It significantly blocked the decline of serum albumin and protein levels (p < 0.05). Histopathological changes amplified paracetamol-induced liver damage and the hepatoprotective effect of P. odoratissimus in the liver. DISCUSSION AND CONCLUSIONS: Pandanus odoratissimus 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.

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

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.

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

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.

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

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 (e.g. Notepad++) or by molecule visualization softwares (e.g., YASARA View). These structures could be used further in virtual screening campaigns in the early stage of drug discovery projects.

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

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.

Broad Spectrum Peptide Vaccine Design Against Hepatitis C Virus.

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.