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Computational Chemistry Commons

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Articles 1 - 7 of 7

Full-Text Articles in Computational Chemistry

Design And In Silico Modeling Of Heterocyclic-Based Xanthone Derivatives As Potential Anticancer Agents Through Tyrosine Kinase Inhibition, Yehezkiel Steven Kurniawan, Ervan Yudha, Nela Fatmasari, Radite Yogaswara, Harno Dwi Pranowo, Eti Nurwening Sholikhah, Jumina Jumina Mar 2026

Design And In Silico Modeling Of Heterocyclic-Based Xanthone Derivatives As Potential Anticancer Agents Through Tyrosine Kinase Inhibition, Yehezkiel Steven Kurniawan, Ervan Yudha, Nela Fatmasari, Radite Yogaswara, Harno Dwi Pranowo, Eti Nurwening Sholikhah, Jumina Jumina

Makara Journal of Science

Cancer is one of the deadliest diseases nowadays, and tyrosine kinase receptors play crucial roles in cancer cell survival, differentiation, proliferation, and migration. This study designed and developed a new inhibitor from heterocyclic-based xanthone derivatives to target two tyrosine kinase receptors, epidermal growth factor receptor (EGFR) and platelet-derived growth factor receptor (PDGFR), through in silico screening. Eighteen heterocyclic-based xanthones were evaluated through molecular docking for both receptors. All heterocyclic-based xanthones gave the root mean square deviation (RMSD) value lower than 2.00 Å. Xanthone with isobenzothiazole substituent (iBzThio) was found as the most potent inhibitor with binding energies of -10.60 and …


Investigating The In Vitro Antimicrobial Potential And Comprehensive Computational Studies Of New Schiff Base Derivatives, Abrar Hussain, Shahzaib Akhter, Hammad Nasir, Khurram Shahzad, Muhammad Arfan, Sand Hyun Park Jan 2026

Investigating The In Vitro Antimicrobial Potential And Comprehensive Computational Studies Of New Schiff Base Derivatives, Abrar Hussain, Shahzaib Akhter, Hammad Nasir, Khurram Shahzad, Muhammad Arfan, Sand Hyun Park

Chemistry & Biochemistry Faculty Publications

Antimicrobial resistance (AMR) is a growing global health threat driven by multidrug-resistant bacteria (Staphylococcus aureus, Pseudomonas aeruginosa), and fungi (Candida albicans, and C. parapsilosis). This study evaluated six novel Schiff base derivatives (HSB-1 to HSB-6) through integrated in vitro antimicrobial activity and comprehensive computational studies. In vitro disk diffusion assay demonstrated the largest zones of inhibition against S. aureus for HSB-6 and HSB-1 (15–17 mm), activity against P. aeruginosa for HSB-5 and HSB-6 (12 mm), and moderate antifungal activity for HSB-4 (8–11 mm). Molecular docking results correlated with the in vitro findings with the binding energy ΔG = −12.3 kcal/mol …


Microplastic Degradation Using Laccase Enzyme From Trametes Hirsuta: In The Silico Study, Hanzhola Gusman Riyanto, Diana Sylvia Dec 2025

Microplastic Degradation Using Laccase Enzyme From Trametes Hirsuta: In The Silico Study, Hanzhola Gusman Riyanto, Diana Sylvia

Makara Journal of Science

Microplastics are a serious global problem that arises worldwide because of their widespread use. Exposure to microplastics can negatively affect human and environmental health. In this study, we used molecular docking methods with MOE software (version 2014.0901) to investigate the interaction between the laccase enzyme and several microplastic compounds as a preliminary study of microplastic degradation using enzymes. The Quantitative Structure Analysis Relationship (QSAR) analysis revealed that all microplastic ligands had higher Pa values than Pi, indicating that the laccase enzyme may be biologically active. The findings of the present study show that polyamide (PA) has the lowest binding energy …


Quantitative Structure-Activity Relationship, Pharmacokinetics, Drug-Likeness, Toxicity, And Molecular Docking Studies Of 4-N-(Methyl)-4-Aminoquinoline Derivatives As Antimalarial Compounds, Muhamad Jalil Baari, Devi Hardiyanti Dec 2025

Quantitative Structure-Activity Relationship, Pharmacokinetics, Drug-Likeness, Toxicity, And Molecular Docking Studies Of 4-N-(Methyl)-4-Aminoquinoline Derivatives As Antimalarial Compounds, Muhamad Jalil Baari, Devi Hardiyanti

Makara Journal of Science

Antimalarial drug resistance has encouraged various innovations to develop novel drug compounds that are effective, feasible, and safe, adhering to health standards. One way to do that is by observing and predicting the biological activity of drug compounds using quantitative structure–activity relationship (QSAR) analysis. In this study, QSAR analysis was conducted on the 4-N-(methyl)-4-aminoquinoline derivatives, which effectively inhibit the growth of Plasmodium falciparum as a source of malaria. The research stages involved molecular structure modeling, molecular geometry optimization using the AM1 semi-empirical method, and QSAR descriptor calculations, including electronic (atomic charges (q), HOMO and LUMO energies, polarizability (α), …


Rational Design Of Small Molecules Targeting Mitochondrial Redox Proteins, Matheus Barbosa Belchior Jan 2025

Rational Design Of Small Molecules Targeting Mitochondrial Redox Proteins, Matheus Barbosa Belchior

Graduate Theses, Dissertations, and Problem Reports (ETD)

Reactive oxygen species play a crucial role in many cellular processes. Despite being a natural byproduct of cellular metabolism, overexpression of these species causes damage to the cell, leading to cell dysfunction. Central to the regulation of these highly reactive molecule is the mitochondria. Impairment in its function has been associated with oxidative stress within the cell. Herein, a ligand-based and structure-based approach to design new small molecules to inhibit mitochondrial redox proteins associated with oxidative stress and reactive oxygen species. In the first project two molecules were synthesized and characterized as potential monoamine oxidase B inhibitors. Results showed two …


De Novo Drug Design Using Transformer-Based Machine Translation And Reinforcement Learning Of An Adaptive Monte Carlo Tree Search, Dony Ang, Cyril Rakovski, Hagop S. Atamian Jan 2024

De Novo Drug Design Using Transformer-Based Machine Translation And Reinforcement Learning Of An Adaptive Monte Carlo Tree Search, Dony Ang, Cyril Rakovski, Hagop S. Atamian

Biology, Chemistry, and Environmental Sciences Faculty Articles and Research

The discovery of novel therapeutic compounds through de novo drug design represents a critical challenge in the field of pharmaceutical research. Traditional drug discovery approaches are often resource intensive and time consuming, leading researchers to explore innovative methods that harness the power of deep learning and reinforcement learning techniques. Here, we introduce a novel drug design approach called drugAI that leverages the Encoder–Decoder Transformer architecture in tandem with Reinforcement Learning via a Monte Carlo Tree Search (RL-MCTS) to expedite the process of drug discovery while ensuring the production of valid small molecules with drug-like characteristics and strong binding affinities towards …


Identification Of Peptide Sequence To Block Dengue Virus Transmission Into Cells Via In Silico And In Vitro Assays, Arumugam Aathe Cangaree Jul 2020

Identification Of Peptide Sequence To Block Dengue Virus Transmission Into Cells Via In Silico And In Vitro Assays, Arumugam Aathe Cangaree

Student Works (2020-2029)

Dengue virus (DV) infection has become main public wellbeing concerns, affecting approximately 390 million people worldwide. This fact was reported by the World Health Organization. Yet, there is no commercial antiviral treatment for DV infection. Therefore, the development of potent and non-toxic anti-DV, as a complement for the existing treatment strategies, are urgently needed. Herein, we investigate a series of low molecular weight peptides inhibitors by aiming the cellular entry process as the promising approach to block DV infection. The peptides were designed based on previously reported peptide sequence, DN58opt (TWWCFYFCRRHHPFWFFYRHN), to identify minimal effective inhibitory sequence via molecular docking …