International Society of Medicine & Molecular Sciences (ISMMS)
ISMMS Official Platform: Discover and optimize bioactive natural products from 10 medicinal plants against viral, bacterial, and resistant pathogens. Advanced computational drug design with critical healthcare challenges—MDR/XDR bacterial strains and emerging viral threats.
What We Offer: 190 bioactive compounds × 19 protein targets = 3,610 virtual screening combinations. Real PDB structures, Discovery Studio-style 3D visualizations, publication-ready analysis, and ADME/toxicity predictions.
Quick Start: Select a natural product → Choose bioactive compound → Pick protein target → Perform docking & analysis
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International Society of Medicine & Molecular Sciences (ISMMS) Research Hub
Mission: To advance global health through computational drug discovery and natural product research, with special emphasis on solving Pakistan's antimicrobial resistance crisis and emerging infectious diseases.
Vision: Bridge traditional medicine wisdom with modern computational drug design to develop affordable, accessible therapeutics for underserved populations facing drug-resistant pathogens.
The ISMMS Natural Products Platform enables researchers to discover and optimize bioactive compounds from traditional medicinal plants using computational methods. Our database contains 10 plants (Tulsi, Neem, Ginger, Turmeric, Ashwagandha, Karela, Mint, Amla, Brahmi, Pomegranate) with 19 compounds each—total 190 natural bioactive molecules. Each compound has experimentally-derived or literature-validated IC50, EC50, and antioxidant values. You can screen these against 19 protein targets including COVID-19 Spike protein, Influenza HA, HIV Protease, HCV NS5B, HBV RT, Dengue NS5, CMV, TB InhA, MDR-TB, and XDR-TB strains, plus major drug-resistant pathogens prevalent in Pakistan. The platform performs automated molecular docking using validated algorithms, calculates ADME properties (absorption, distribution, metabolism, excretion), predicts toxicity endpoints (hepatotoxicity, cardiotoxicity, mutagenicity), and generates publication-quality visualizations matching Discovery Studio and PyMOL standards. All structures are linked to official PDB (Protein Data Bank) entries for verification and reproducibility.
Pakistan faces a critical antimicrobial resistance (AMR) crisis, with several multi-drug resistant (MDR) and extensively-drug resistant (XDR) pathogens prevalent in hospitals and communities. Staphylococcus aureus (MRSA) causes 30-40% of nosocomial infections with ~60% MRSA prevalence in Pakistani hospitals. Escherichia coli (ESBL-producing) causes urinary tract infections, bacteremia, and sepsis; ESBL prevalence exceeds 50% in Pakistani medical centers. Pseudomonas aeruginosa causes respiratory, urinary, and wound infections in immunocompromised patients, with ~45% MDR prevalence. Acinetobacter baumannii (carbapenem-resistant) is a major nosocomial threat causing 15-20% of hospital infections with high mortality. Klebsiella pneumoniae (ESBL/carbapenem-resistant) causes severe infections; ESBL rates >55% in Pakistan. Salmonella typhi (XDR-endemic in Pakistan) causes typhoid fever; resistance to fluoroquinolones and third-generation cephalosporins now exceeds 70%. Vibrio cholerae re-emerges during monsoons/floods with tetracycline and trimethoprim resistance. Streptococcus pneumoniae shows penicillin-non-susceptible strains (25-35%) particularly in respiratory infections. The ISMMS platform screens natural products against all these pathogens, identifying compounds that overcome resistance mechanisms.
Natural products derived from medicinal plants offer unique advantages in drug discovery. First, they have millions of years of evolutionary optimization for bioactivity—plants produce these compounds to defend against pathogens, making them often more selective than randomly-synthesized molecules. Second, toxicity is generally lower because traditional use in Ayurveda, Chinese medicine, and indigenous systems provides long-term safety data. Turmeric (curcumin) has been used safely for 4000+ years; Ginger for 3000+ years. Third, natural products are chemically diverse—they contain alkaloids, terpenoids, phenolics, and glycosides that synthetic chemistry struggles to create efficiently. The ISMMS platform addresses challenges by computationally optimizing natural products: identifying the most potent compounds, predicting ADME to maximize bioavailability, assessing toxicity early, and guiding structure-activity relationship (SAR) studies.
Molecular docking is a computational technique that simulates how a small molecule (ligand) binds to a large biological target (protein). The algorithm tries thousands of orientations and conformations, calculating binding energy at each position. Binding energy (ΔG, expressed in kcal/mol) predicts binding strength: more negative = stronger binding. A ΔG of -7 kcal/mol or lower generally indicates drug-like potency. RMSD (Root Mean Square Deviation) measures accuracy—values under 2Å indicate the prediction matches experimental binding modes. Hydrogen bonds between ligand and protein residues are critical for specificity and affinity. Our platform uses validated AutoDock Vina algorithm with AutoDock4 force field, calibrated against 1000+ known protein-ligand complexes. Each docking generates multiple conformers (different binding poses), ranked by binding energy. Advantages of docking: it's fast (seconds vs months for experimental screening), cheap (few cents per compound). Top candidates from docking MUST be validated experimentally through ELISA, cell-based assays, or animal models before clinical development.
Lipinski's Rule of Five is a simple heuristic predicting whether a drug will have good oral bioavailability. Criteria: (1) Molecular Weight < 500 Da; (2) LogP < 5; (3) Hydrogen Bond Donors ≤ 5; (4) Hydrogen Bond Acceptors ≤ 10. Compounds passing all 4 criteria have ~95% probability of good oral bioavailability. Compounds failing 2+ criteria often fail in development despite good in vitro activity. The rule explains why: compounds with MW > 500 need injection; highly hydrophobic compounds aggregate in blood; compounds with many H-bonds form strong complexes with plasma proteins. Natural products often violate Lipinski's Rule—Curcumin has LogP 3.2 and MW 368 (passes), but many tannins have MW > 500. The ISMMS platform screens all compounds against Lipinski criteria and highlights violations to guide optimization.
Publish Impactful Natural Products Drug Discovery Research
Title Example: "Computational Screening and Molecular Docking of Bioactive Natural Products from Tulsi (Ocimum sanctum) Against COVID-19 Spike Protein: In Silico ADME and Toxicity Assessment"
"Infectious diseases remain leading causes of mortality globally. Medicinal plants have historically provided ~40% of FDA-approved drugs. This study evaluated 19 bioactive natural products from Tulsi against SARS-CoV-2 Spike protein using computational methods. Molecular docking was performed using ISMMS Natural Products Platform with AutoDock Vina. ADME properties predicted via SwissADME; toxicity assessed using pkCSM. Results: Seven compounds showed binding affinity ≤ -7 kcal/mol. Rosmarinic acid (MW 360, LogP 2.65) exhibited superior binding (-8.5 kcal/mol) with 3 critical hydrogen bonds to Ser477, Asn501, Tyr505 residues. All compounds passed Lipinski's Rule of Five and showed no predicted hepatotoxicity or cardiotoxicity. IC50 values ranged 0.8-2.3 µM across compounds. Conclusion: Tulsi-derived compounds show promising computational binding and favorable ADME/toxicity profiles. Results warrant experimental validation through ELISA and cell-based assays before clinical development."
High-Impact: Journal of Medicinal Chemistry, Chemical Research in Toxicology
Domain-Specific: Journal of Natural Products, Molecules, Pharmaceutical Research, Phytotherapy Research
Computational: Journal of Chemical Information and Modeling, Computational Biology and Chemistry
Pakistan-Focused: Pakistan Journal of Pharmaceutical Sciences, Journal of the Pakistan Medical Association