Background: Hypertension is a worldwide epidemic that has been recognized as the most leading global risk for mortality, with its prevalence associated with increased blood pressure, concomitant risks of cardiovascular and kidney diseases, and major commonality in individuals advanced in age. With the current treatment options for hypertension management, there is still a need to develop therapies that directly target receptors that aid in hypertension treatment. Methodology: The study focused on the in-silico profiling of the reported compounds from Areca catechu L. (fam. Arecaceae) towards the n-domain and c-domain angiotensin converting enzyme (ACE) receptor models. Bioisosteric replacement was used to create bioisosteres investigated for similar binding affinity. Results: Some A. catechu compounds exhibited favorable binding energies towards the n- and c-domain receptor models of ACE, binding in the same ACE ligand binding site as lisinopril, benazepril, and sampatrilat via similar interactions and amino acid residues. The majority of A. catechu compounds with favorable ACE binding energies belong to the phytochemical classes of flavonoids, polyphenols and phenolics, glycosides, and steroids. After in silico toxicity and pharmacokinetic profiling, the bioisosteres Leuco-DM02-39, Leuco-DM02-66, Leuco-DM05-60, Querc-DM09-63, and Querc-DM14-31 with binding energies higher than their parent compounds and comparable to lisinopril, benazepril, and sampatrilat were deemed the best. Conclusion A. catechu compounds have the potential to target ACE n-domain and c-domain receptor models. Three leucocyanidin and two quercetin bioisosteres exhibited favorable binding to the n-domain and c-domain ACE receptor models and could be further optimized to derive a promising antihypertensive agent through ACE inhibition.
Peptidyl-Dipeptidase A ; Areca ; Hypertension

Background: Breast cancer is one of the leading causes of deaths in women worldwide, affecting nearly 7.8 million people. In 2020 in the Philippines, there were around 150,000 Filipinos who were newly diagnosed with the disease. The complex pathogenesis of breast cancer in addition to the emergence of resistance to therapy makes the treatment very challenging. Compounds that can antagonize the effects of estradiol towards ER-α, especially the mutant Y537S type are sought for. Objectives: The focus of this study was the in-silico assessment of the reported secondary metabolites from Phaseolus vulgaris L. (fam. Fabaceae) towards the wild-type and mutant ER-α. Bioisosteric replacement was conducted to generate analogs that can possibly have a comparable binding affinity as estradiol towards estrogen receptors alpha. Results: Majority of the secondary metabolites present in Phaseolus vulgaris L. belong to the group of phytoestrogens, phytosterols, and plant hormones. These groups of compounds exhibited favorable binding energies toward the wild-type and mutant (Y537S) estrogen receptors alpha. Moreover, they bind to the same ligand binding pocket as estradiol, involving similar interactions and amino acid residues. Conclusion Compounds from Phaseolus vulgaris L. can potentially target ER-α. Four gibberellin A19 analogs were generated that exhibited favorable binding towards the wild- and mutant- ER-α and may be further optimized to obtain a promisin gcompound against breast cancer.
Breast Neoplasms ; Molecular Docking Simulation

Background: Malaria remains to be one of the major health problems in tropical areas of the world. It puts at least one-third of the world population at risk of infection and afflicts over 200 million people worldwide, approximately 7000 of whom are Filipinos. In spite of available drugs, malarial chemotherapy is still insufficient. The increased resistance of Plasmodium falciparum strains to existing antimalarial drugs prompts the discovery of new therapeutic agents for malaria. Objective: This study aimed to uncover, through molecular docking technique, new chemical entities that can be developed as new drugs for malaria. Methodology: In this study, 2,527 approved and 5,755 experimental drugs from DrugBank and 4,687 natural compounds from Analyticon MEGx database were docked against Plasmodium falciparum aspartate transcarbamoylase (PfATC) and oritidine-5'-monophosphate decarboxylase (PfOMPDC), two key enzyme targets involved in the de novo biosynthesis pathway of the pathogen. Results: A total of 39 compounds (1 approved drug, 19 experimental drugs, 19 natural products) had larger binding energy (BE) values than the known ligands 2,3-naphthalenediol (BE = -7.0 kcal/mol) and uridine 5- PfATC monophosphate (BEPfOMPDC = -9.0 kcal/mol). The top 3 hits were natural products: dihydrotrichotetronine (BEPfATC = -21 kcal/mol, BE = -18 kcal/mol), ginkgolide A (BE = -19 kcal/mol, BE = -15 kcal/mol), and PfOMPDC PfATC PfOMPDC ginkgolide C (BE = -16 kcal/mol, BE = -16 kcal/mol). Conclusion Based on calculated binding energy and ADMET properties, dihydrotrichotetronine, ginkgolide A, and ginkgolide C are the best natural product candidates for further development as dual inhibitors for both PfATC and PfOMPDC enzymes. Furthermore, myricetin (BE = -9 kcal/mol, BE = -10 kcal/mol) and PfATC PfOMPDC tolcapone (BE = -9.1 kcal/mol, BE = -9.2 kcal/mol) may also be repurposed as anti-malarial drugs.
Malaria

Background: The biological activity of a compound is assumed to be encoded in its chemical composition and geometric structure, from which physico-chemical, electrotopological, and graph theory-derived properties can be determined. Objective: This study aimed to identify the molecular descriptors derived from Dragon® 6 software that can discriminate compounds as drug or nondrug Methodology: Over 4000 molecular properties were obtained for approximately 2000 known drugs and 2000 nondrugs on which Linear Discriminant Analysis was performed. Results: Compounds can be discriminated between drug and nondrug with 81% accuracy using only two molecular descriptors, the information index HVcpx and the topological index MDDD. Conclusion A “Rule of Three” (HVcpx ≤ 3 and MDDD ≥ 30) seems to confer druglikeness in compounds. This rule can be used as additional filter in high throughput screening of compounds in any drug discovery research.
Discriminant Analysis ; Drug Discovery