Introduction To Drug Design| QSAR | Combinatorial Chemistry | Medicinal Chemistry 6th Semester

The lecture begins by distinguishing Unit 5 from previous units, noting that rather than covering disease-specific drug classifications, this unit focuses entirely on drug design methodology. The instructor contextualizes the topic by explaining that a new drug typically takes 12–15 years to reach the market, passing through preclinical (animal testing) and multiple phases of clinical trials before commercialization.

Drug design is defined as a systematic, knowledge-based process of discovering and developing new chemical compounds that interact with biological targets to produce desired therapeutic effects. Key features include a rational/scientific approach (avoiding trial and error), target-based processes (identifying enzymes or receptors involved in disease), bioactive molecule development, use of computational tools (QSAR, pharmacophore modeling, molecular docking), and continuous optimization of drug properties like potency, selectivity, ADME, and toxicity.

Two main drug design approaches are covered: Structure-Based Drug Design (SBDD) is used when the 3D structure of the biological target (receptor or enzyme) is known. Scientists identify the target, locate its active site, design small molecules that fit the active site, study binding interactions (hydrogen bonds, hydrophobic forces, electrostatic interactions), calculate binding energy (lower energy = better fit), and iteratively optimize the lead compound. HIV protease inhibitors are given as a real-world example. Ligand-Based Drug Design (LBDD) is used when the target's 3D structure is unknown but known ligands that bind to it are available. Scientists collect all known ligands, analyze their common structural features, build pharmacophore or QSAR models, and design new molecules with similar features.

Pro-drug design is reviewed from a previous unit. Pro-drugs are inactive or minimally active forms of drugs that become active after enzymatic or chemical metabolism. They are designed to improve solubility, chemical stability, taste/smell, reduce irritation, improve absorption, reduce first-pass metabolism, enable targeted delivery, and reduce toxicity. Examples include valacyclovir (prodrug of acyclovir), fosphenytoin, levodopa (prodrug of dopamine), and capecitabine (prodrug of 5-fluorouracil). Pro-drugs are classified into carrier-linked (including double prodrugs, macromolecular, site-specific, and mutual prodrugs) and bioprecursors.

QSAR (Quantitative Structure-Activity Relationship) is explained as an extension of SAR where the relationship between chemical structure and biological activity is expressed mathematically. Three key parameters are discussed: (1) Partition Coefficient (log P) measures lipophilicity/hydrophobicity. An optimal moderate log P value (log P₀) gives maximum biological activity — too low means poor membrane permeation, too high means the drug gets stuck in the membrane. The parabolic graph of log P vs. biological activity is explained in detail. (2) Hammett's Electronic Parameter (σ) quantifies whether a substituent is electron-withdrawing (positive σ, increases acidity, stabilizes negative charge) or electron-donating (negative σ, decreases acidity) using benzoic acid as the reference compound. Examples with NO₂ (σ = +0.78) and CH₃ (σ = -0.17) are provided. (3) Taft's Steric Parameter (Es) measures the bulkiness of substituents. More negative Es values indicate bulkier groups with more steric hindrance, which impedes receptor binding. It is measured by comparing hydrolysis rates of esters with different substituents.

Hansch Analysis combines all three parameters (log P, σ, Es) into a single mathematical equation: log(1/C) = k₁·log P + k₂·σ + k₃·Es + k₄, allowing quantitative prediction of biological activity from chemical structure without laboratory testing.

Pharmacophore Modeling involves identifying essential 3D structural features of drug molecules (hydrogen bond donors/acceptors, hydrophobic groups, aromatic rings, charged groups) responsible for biological activity. It has two types mirroring drug design approaches: ligand-based and structure-based pharmacophore models. Applications include new drug design, lead optimization, and activity prediction.

Molecular Docking is a computational technique that predicts the preferred orientation (binding pose) of a drug molecule when it binds to its target receptor. The process involves preparing 3D structures, identifying the active site, using algorithms to try various orientations, scoring each pose based on binding energy (lower score = better), and finalizing the best pose. Two types are rigid docking (no conformational changes) and flexible docking (ligand can adjust conformation). Applications include drug discovery, lead optimization, and binding affinity prediction.

Combinatorial Chemistry is a technique for rapidly creating large numbers of different chemical compounds simultaneously by combining different sets of chemical building blocks (e.g., combining 3 acids with 3 amines in one reaction yields 9 different compounds at once). The compounds form a 'library' that is then screened to identify the most active 'hit' compounds for further development. Two synthesis methods are solid-phase synthesis (reactions on a resin bead, used for peptide synthesis) and solution-phase synthesis (reactants dissolved in solvent, used for small organic molecules). The primary purpose is to accelerate drug discovery by increasing the diversity of compounds tested in a shorter time.