Graduate
  1. Physical Chemistry  1.1. Thermodynamics  1.1.1. Laws of Thermodynamics  1.1.2. Enthalpy and heat capacity  1.1.3. Entropy and free energy  1.1.4. Phase Equilibrium  1.1.5. Statistical thermodynamics  1.1.6. Thermodynamic cycle  1.1.7. Fugacity and activity  1.2. Quantum Chemistry  1.2.1. Principles of quantum mechanics  1.2.2. Schrödinger Equation  1.2.3. Particle in a box  1.2.4. Operators and eigenvalues  1.2.5. Atomic orbitals  1.2.6. Molecular orbital theory  1.2.7. Perturbation theory  1.2.8. Valence bond theory  1.2.9. Hybridization and chemical bonding  1.3. Chemical kinetics  1.3.1. Rate laws and reaction mechanisms  1.3.2. Collision theory  1.3.3. Transition state theory  1.3.4. Enzyme Kinetics  1.3.5. Chain Reactions and Polymerization  1.3.6. Photochemical reactions  1.4. Statistical mechanics  1.4.1. Partitioning functions  1.4.2. Molecular distribution functions  1.4.3. Boltzmann Distribution  1.4.4. Bose–Einstein and Fermi–Dirac statistics  1.5. Spectroscopy  1.5.1. Rotational Spectroscopy  1.5.2. Vibrational Spectroscopy  1.5.3. Electronic Spectroscopy  1.5.4. Nuclear magnetic resonance spectroscopy  1.5.5. Mass Spectrometry  1.5.6. Raman Spectroscopy  1.5.7. Electron paramagnetic resonance spectroscopy  1.6. Surface and colloidal chemistry  1.6.1. Absorption isotherm  1.6.2. Surface tension and wetting  1.6.3. Colloidal Stability  1.6.4. Catalysis  1.6.5. Emulsions and micelles  1.7. Electrochemistry  1.7.1. Nernst equation  1.7.2. Electrochemical cells  1.7.3. Conductivity and mobility  1.7.4. War  1.7.5. Fuel cells  1.7.6. Electrolysis
  2. Organic chemistry  2.1. Reaction mechanism  2.1.1. Nucleophilic substitution reactions  2.1.2. Electrophilic addition reactions  2.1.3. Elimination reactions  2.1.4. Rearrangement reactions  2.1.5. Radical reactions  2.1.6. Pericyclic reactions  2.2. Spectroscopy and structural determination  2.2.1. UV-Vis Spectroscopy  2.2.2. IR Spectroscopy  2.2.3. NMR Spectroscopy  2.2.4. Mass Spectrometry  2.2.5. X-ray crystallography  2.3. Stereoscopic  2.3.1. Chirality and optical activity  2.3.2. Structural analysis  2.3.3. Geometrical isomerism  2.3.4. Dynamic Stereochemistry  2.4. Organometallic Chemistry  2.4.1. Organolithium and organomagnesium reagents  2.4.2. Palladium-catalyzed cross-coupling reactions  2.4.3. Transition Metal Complexes  2.4.4. Metal–carbon bond  2.5. Polymer chemistry  2.5.1. Polymerization mechanism  2.5.2. Polymer Characteristics  2.5.3. Biodegradable Polymer  2.5.4. Conducting polymer  2.5.5. Supramolecular polymers  2.6. Medicinal chemistry  2.6.1. Drug design and development  2.6.2. Pharmacokinetics and pharmacodynamics  2.6.3. Structure-activity relationships  2.6.4. Molecular docking and drug screening
  3. Inorganic chemistry  3.1. Coordination chemistry  3.1.1. Crystal field theory  3.1.2. Ligand field theory  3.1.3. Spectrochemical Series  3.1.4. Chelation and stability  3.2. Organometallic Chemistry  3.2.1. Metal Carbonyls  3.2.2. Catalysis by organometallic complexes  3.2.3. Metallocenes  3.3. Bio-inorganic chemistry  3.3.1. Metalloproteins and enzymes  3.3.2. The role of metals in biological systems  3.3.3. Metal ion transport and storage  3.4. Solid state chemistry  3.4.1. Crystal Structures  3.4.2. Band theory of solids  3.4.3. Superconductors  3.4.4. Defects in the crystal  3.5. Lanthanides and Actinides  3.5.1. Electronic configuration in lanthanides and actinides  3.5.2. Coordination chemistry of the lanthanides  3.5.3. Magnetic Properties of Lanthanides
  4. Analytical chemistry  4.1. Chromatography  4.1.1. Gas Chromatography  4.1.2. High Performance Liquid Chromatography  4.1.3. Thin Layer Chromatography  4.2. Spectroscopic Techniques  4.2.1. Atomic absorption spectroscopy  4.2.2. X-ray diffraction  4.2.3. Inductively coupled plasma spectroscopy  4.3. Electroanalytical methods  4.3.1. Potentiometry  4.3.2. Voltammetry  4.3.3. Colometry  4.4. Mass Spectrometry  4.4.1. Ionization Technique  4.4.2. Fragmentation Pattern  4.5. Chemometrics  4.5.1. Multidisciplinary analysis  4.5.2. Machine Learning in Chemistry
  5. Theoretical and Computational Chemistry  5.1. Molecular dynamics simulation  5.1.1. Force fields and energy minimization  5.1.2. Monte Carlo simulation in molecular dynamics simulations  5.2. Quantum chemical methods  5.2.1. Hartree–Fock theory  5.2.2. Density functional theory  5.2.3. Semi-empirical methods  5.3. Computational drug design  5.3.1. Molecular Docking  5.3.2. QSAR Modeling  5.3.3. Virtual Screening
  6. Biochemistry  6.1. Enzyme Kinetics  6.1.1. Michaelis-Menten kinetics  6.1.2. Inhibition mechanism  6.2. Metabolism and Bioenergetics  6.2.1. Glycolysis  6.2.2. Citric acid cycle  6.2.3. Electron transport chain  6.3. molecular Biology  6.3.1. DNA replication and repair  6.3.2. Protein synthesis  6.3.3. Gene Regulation  6.4. Structural Biochemistry  6.4.1. Protein Folding  6.4.2. Membrane Biophysics
  7. Environmental Chemistry  7.1. Atmospheric Chemistry  7.1.1. Greenhouse gases  7.1.2. Ozone depletion  7.1.3. Air pollutants and smoke  7.2. Water Chemistry  7.2.1. pH and water hardness  7.2.2. Wastewater treatment  7.2.3. Aquatic Chemistry  7.3. Soil Chemistry  7.3.1. Heavy metal contamination  7.3.2. Soil pH and Buffering  7.3.3. Nutrient cycling  7.4. Toxicology and Chemical Safety  7.4.1. Toxicokinetics  7.4.2. Risk Assessment in Toxicology and Chemical Safety in Environmental Chemistry  7.4.3. Effects of pollutants on the environment

Graduate → Organic chemistry → Medicinal chemistry ↓


Structure-activity relationships


In the vast and complex field of medicinal chemistry, it is important to understand the structure-activity relationship (SAR). This concept is one of the main principles that underlies the design and optimization of drug compounds. By systematically modifying the structure of chemical compounds and observing their biological activities, chemists attempt to optimize these molecules to achieve the desired therapeutic effects.

Introduction to structure-activity relationships

The basic premise of SAR revolves around the idea that the biological activity of a compound – how it interacts with biological receptors or enzymes – depends on its molecular structure. This implies that even small changes in molecular structure can lead to significant differences in activity.

Factors affecting activity include:

  • Functional groups and their orientation
  • Electronic delivery
  • Hydrophobic/hydrophilic balance
  • Stereoscopic

Historical context and development of the SAR

The concept of SAR came about in the early 20th century when scientists began to realize that subtle differences in chemical structure could lead to different therapeutic effects. This notion became more sophisticated with the development of receptor theory in pharmacology, which hypothesized the existence of specific sites in the body where drugs bind to exert their effects.

Initial foundation

The work of Paul Ehrlich, who used dye compounds to stain specific cells and bacteria, paved the way. Ehrlich's "magic bullet" theory proposed that specific chemicals could target specific pathogens, leading to targeted drug therapy. His innovations highlighted the importance of molecular structure in determining biological activity.

Mechanisms supporting SAR

The mechanisms by which SAR operates are multifaceted, integrating chemistry, biology, and biophysics. Here's a closer look:

Functional group

The presence and orientation of functional groups significantly affect the pharmacokinetics and pharmacodynamics of the molecule. Consider the conversion of an alcohol group to an ether or ester, which can increase membrane permeability by increasing lipophilicity.

R-OH → ROR' or R-COOR'

Electronic effects

Electronic effects affect how the molecule engages in chemical interactions. For example, electron-withdrawing groups can make phenol more acidic, affecting its bioavailability:

Phenol (C6H5OH) with NO2 group: C6H4(NO2)OH

The incorporation of electron-rich or electron-deficient groups can affect the affinity of a molecule for a biological target.

Hydrophobic/hydrophilic balance

Solubility and partitioning properties are important when designing drugs. The optimal balance between hydrophobic and hydrophilic properties ensures that the drug can cross cell membranes but remain soluble in bodily fluids.

Hydrophobic Hydrophilic

The partition coefficient (log P) of a molecule helps balance these characteristics.

Stereoscopic

Stereochemically different compounds, known as stereoisomers, often display very different biological activities. An excellent example of this is provided by the enantiomers of the drug thalidomide:

(+) Enantiomer: Sedative effects (-) Enantiomer: Teratogenic effects

Techniques for studying SAR

Quantitative structure-activity relationship (QSAR)

QSAR takes SAR a step further by applying mathematical and statistical methods to quantitatively predict the biological activity of compounds. It involves the use of descriptors, which are numerical values given the properties of molecules such as lipophilicity, molecular weight, topological indices, and quantum mechanics-derived properties.

Activity = f(descriptor_1, descriptor_2, ..., descriptor_n)

Computer aided drug design (CADD)

Modern advances have allowed computer simulations to predict and optimize SAR prior to experimental synthesis. The methods used are as follows:

  • Molecular docking
  • Molecular dynamics simulation
  • Homology modeling
Molecule Receptor

Case studies and applications

Case study: Non-steroidal anti-inflammatory drugs (NSAIDs)

NSAIDs such as aspirin, ibuprofen and naproxen are classic examples of SAR action. While all have similar anti-inflammatory effects, differences in their chemical structures cause differences in their mechanism of action and side-effect profile.

(Aspirin) C9H8O4 (Ibuprofen) C13H18O2 (Naproxen) C14H14O3

Subtle changes in side chains alter receptor interaction, half-life, and specificity, affecting the therapeutic use of each drug.

Case study: β-lactam antibiotics

The SAR of β-lactam antibiotics such as penicillins and cephalosporins illustrates how bacterial resistance can be combated by altering the β-lactam ring and adjacent structures.

Penicillin core: R-C9H11N2O4S Cephalosporin core: R-C14H14N2O4S

Conclusion and future perspectives

Understanding SAR is critical for the rational design of new drugs. As researchers deepen their understanding of SAR, taking advantage of modern technologies such as machine learning and artificial intelligence, the future of medicinal chemistry may see even greater efficiency in drug development, lower costs, and personalized medicine.

The discovery of SARs is expanding the boundaries of possibility in drug design, ultimately improving healthcare outcomes globally.


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Structure-activity relationships

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