Synthesis and in vitro Activity of Eugenyl Benzoate Derivatives as BCL-2 Inhibitor in Colorectal Cancer with QSAR and Molecular Docking Approach.

OBJECTIVE: This study is aimed to acquiring new compounds of Eugenyl benzoate (2-methoxy-4-(prop-2-en-1-yl)phenyl benzoate) derivatives that can inhibit HT29 colorectal cancer cells. METHODS: In this research, we used several chemical reactions to synthesize novel compounds, such as Esterification, Demethylation, Halohydrin, and Sharpless reaction. Cytotoxicity assays were performed to test the inhibitory activity of compounds against HT29 colon cancer cells. QSAR analysis were carried out to analyse the relationship of chemical structure of the novel compounds with their cytotoxic activity. RESULT: Ten novel compounds were successfully synthesized and tested in vitro against the HT29 cell. The IC50 of the novel compounds were between 26.56 µmol/ml - 286.81 µmol/ml which compound 4-[(2S)-2,3-dihydroxypropyl]-2-methoxyphenyl 2-hydroxybenzoate (9) showed as best active compound as BCL-2 inhibitors better than other synthesized compounds and Eugenol as well. QSAR analysis of the in vitro results gave a Log equation: 1/IC50 = -0.865-0.210 (LogP)2 + 1,264 (logP)-0.994 CMR (n = 10; r = 0.706; SE: 0.21; F = 0.497, sig = 7.86). The equation shows the log variable P and CMR affect IC50. The properties of hydrophobicity (log P) are more instrumental than the ones of steric (CMR). CONCLUSION: The active compound (9) given best activities as BCL-2 inhibitors than other eugenol derivatives. QSAR indicates the logP and CMR have effect on its colorectal cytotoxic activity which the hydrophobicity parameter (logP) plays more role than the steric parameter (CMR).

Whole genome sequencing data of Candida krusei, the pathogen causing Candidaemia, from Department of Parasitology Culture Collection, Faculty of Medicine Universitas Indonesia.

Candida krusei is a Candida non-albicans species with a high prevalence, which causes candidaemia. Current treatment guidelines include fluconazole as a primary therapeutic option for the treatment of these infections; however, it is only a fungistatic against Candida spp., and both inherent and acquired resistance to fluconazole have been reported. C. krusei species is also reported as the only Candida sp. which has an intrinsic resistance factor to fluconazole. Therefore, in dealing with antifungal resistance, it is necessary to develop new antifungal agents that are efficient in the treatment of fungal infections, especially those caused by C. krusei. The purpose of this study was to investigate the genome of clinical C. krusei isolates and correlate the resistant phenotypes with mutations in resistance genes. A total of 16 samples of C. krusei from clinical samples from hospitals in Jakarta were used in the experiment. All colonies were extracted using the QIAamp DNA Mini Kit. The library was prepared using the Illumina DNA Prep Kit. The sequencing process was carried out on the Illumina MiSeq Platform using a 2x301 paired-end configuration. FASTQ raw files are available under the BioProject Accession Number PRJNA819536 and Sequence Read Archive Accession Numbers SRR18739949 and SRR18739964.

Virtual screening of Indonesian herbal compounds as COVID-19 supportive therapy: machine learning and pharmacophore modeling approaches.

BACKGROUND: The number of COVID-19 cases continues to grow in Indonesia. This phenomenon motivates researchers to find alternative drugs that function for prevention or treatment. Due to the rich biodiversity of Indonesian medicinal plants, one alternative is to examine the potential of herbal medicines to support COVID therapy. This study aims to identify potential compound candidates in Indonesian herbal using a machine learning and pharmacophore modeling approaches. METHODS: We used three classification methods that had different decision-making processes: support vector machine (SVM), multilayer perceptron (MLP), and random forest (RF). For the pharmacophore modeling approach, we performed a structure-based analysis on the 3D structure of the main protease SARS-CoV-2 (3CLPro) and repurposed SARS, MERS, and SARS-CoV-2 drugs identified from the literature as datasets in the ligand-based method. Lastly, we used molecular docking to analyze the interactions between the 3CLpro and 14 hit compounds from the Indonesian Herbal Database (HerbalDB), with lopinavir as a positive control. RESULTS: From the molecular docking analysis, we found six potential compounds that may act as the main proteases of the SARS-CoV-2 inhibitor: hesperidin, kaempferol-3,4'-di-O-methyl ether (Ermanin); myricetin-3-glucoside, peonidin 3-(4'-arabinosylglucoside); quercetin 3-(2G-rhamnosylrutinoside); and rhamnetin 3-mannosyl-(1-2)-alloside. CONCLUSIONS: Our layered virtual screening with machine learning and pharmacophore modeling approaches provided a more objective and optimal virtual screening and avoided subjective decision making of the results. Herbal compounds from the screening, i.e. hesperidin, kaempferol-3,4'-di-O-methyl ether (Ermanin); myricetin-3-glucoside, peonidin 3-(4'-arabinosylglucoside); quercetin 3-(2G-rhamnosylrutinoside); and rhamnetin 3-mannosyl-(1-2)-alloside are potential antiviral candidates for SARS-CoV-2. Moringa oleifera and Psidium guajava that consist of those compounds, could be an alternative option as COVID-19 herbal preventions.