"Computer-assisted design, synthesis, and biological evaluation of active heterocyclic compounds targeting neurodegenerative, inflammatory, and oncological disorders."
The Drug Design & Synthesis Lab (DDSL) is an established academic research group in the Department of Pharmaceutical Sciences and Drug Research, Punjabi University, Patiala. Led by Dr. Yogita Bansal (Head and Professor), the laboratory focuses on rational computer-assisted drug design, chemical synthesis, and biological characterization of novel heterocyclic entities.
Our research philosophy bridges modern in-silico computational molecular modeling (2D/3D-QSAR, docking, molecular dynamics, ADMET, and machine learning) with benchtop organic synthesis of privileged heterocyclic scaffolds (benzimidazoles, coumarins, pyrazoles, indoles, and quinazolines). This integrated approach accelerates the discovery of potent, target-selective therapeutic leads with optimized pharmacokinetic profiles.
Core domains in computational drug design and medicinal chemistry
Structure-based and ligand-based virtual screening for lead discovery.
2D/3D-QSAR modeling, SMILES descriptors, and ML regression algorithms.
Receptor-ligand binding kinetics, MD simulations (100 ns+), and MM/GBSA.
Organic synthesis of benzimidazole, coumarin, and chromone hybrid scaffolds.
Target evaluation against BACE-1, VEGFR-2, AChE, IL-6, and TNF-α.
Overview of key cheminformatics software, machine learning algorithms, docking suites, and molecular descriptor calculators utilized at DDSL.
Interactive machine learning and QSAR prediction platform developed by Drug Design & Synthesis Lab, Punjabi University Patiala. Features real-time molecular structure parsing, descriptor calculations, and bioactivity predictions.
Lab's interactive in-house Streamlit web tool for SMILES-based molecular descriptor calculation and QSAR bioactivity scoring.
SMILES-based QSAR modeling software for bioactivity and toxicity prediction using Monte Carlo optimization.
Comprehensive molecular modeling suite for ligand-based and structure-based drug design and electrostatic surface analysis.
Open-source cheminformatics toolkit for chemical structure parsing, fingerprint generation, and 2D/3D depiction.
Molecular descriptor calculator capable of computing over 1,800 2D and 3D physical and topological descriptors.
Ensemble decision-tree learning method applied for robust QSAR bioactivity classification and regression.
Supervised learning algorithm utilizing kernel functions for non-linear bioactivity and IC50 prediction.
Optimized gradient boosting framework for high-performance quantitative structure-activity relationship modeling.
Gradient boosting decision tree library optimized for handling categorical chemical features and molecular fingerprints.
Open-source receptor-ligand docking software for automated binding affinity and conformation scoring.
Structure-based docking and scoring engine tailored for virtual screening of large compound libraries.
Atomic-level simulation of protein-ligand complex stability, conformational flexibility, and RMSD/RMSF tracking.
Molecular Mechanics/Generalized Born Surface Area method for precise binding free energy calculations.
Circular topological fingerprints used for molecular structural representation and high-throughput virtual screening.
166-bit structural keys encoding specific functional groups and sub-structural patterns for rapid chemical filtering.
Standard mathematical coefficient for calculating pairwise structural similarity between molecular entities.
Calculation of 0D, 1D, 2D, and 3D physical, chemical, and topological descriptors governing drug-likeness.
Peer-reviewed research articles and reviews by Dr. Yogita Bansal and researchers at DDSL
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Principal Investigator, research scholars, project fellows, and lab alumni
Research Focus: Computer-assisted design of biologically active compounds against inflammatory disorders, 2D/3D-QSAR modeling, and organic synthesis of Benzimidazole, Coumarin, and hybrid heterocyclic scaffolds.
3 Ph.D. scholars guided and currently pursuing advanced research in QSAR modeling, heterocyclic synthesis, and neurodegenerative disease targets.
Over 40 M.Pharm students have successfully completed their research dissertations in medicinal chemistry and computer-aided drug design.
DDSL alumni hold prominent academic, research, and industrial positions across pharmaceutical corporations and universities worldwide.
Official contact information for research collaborations and academic inquiries