What is Medicinal Chemistry (section 6)

 Section 6: Screening and Drug Design

In the journey of drug discovery, once a disease target (such as an enzyme or receptor) is identified, scientists begin the next big task: finding the right compound that can interact with this target to treat the disease. This process involves screening and drug design.

In this section, you will learn how scientists search for potential drug candidates, how they evaluate their effectiveness, and how they design better versions using chemical knowledge.

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1. What is Screening?

Screening means testing a large number of chemical compounds to see which ones interact with the disease target. The aim is to find a "hit" — a compound that shows a desirable effect.

There are two major types of screening:

• High-Throughput Screening (HTS)
• Virtual Screening (Computer-based)

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2. High-Throughput Screening (HTS)

HTS is a laboratory technique where thousands of compounds are tested quickly using automated machines. The process includes:

1. A target molecule (like an enzyme) is placed in many small test tubes or wells.
2. Different chemicals are added to each well.
3. A machine measures the reaction in each well.
4. Wells showing a positive result (good reaction) are noted.

HTS helps identify many hit compounds in a short time. These hits become candidates for further study.

Example:

• Testing thousands of small molecules against a cancer protein to find which ones stop it from working.

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3. Virtual Screening

Virtual screening uses computers and software to simulate how different chemical compounds might bind to the target. It is based on:

• The 3D structure of the target
• Chemical databases with millions of molecules
• Mathematical models and algorithms

Virtual screening helps shortlist promising compounds before actual lab testing, saving time and money.

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4. What is a "Hit" and a "Lead"?

• A Hit is a compound that shows desired activity in screening (but may still be weak or non-specific).
• A Lead is an improved version of the hit, after changes are made to make it stronger, safer, and more specific.

Hit → Lead → Drug Candidate

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5. Lead Optimization

Lead optimization is the process of modifying the chemical structure of a lead compound to improve:

• Potency (stronger action)
• Selectivity (acts only on the target)
• Solubility (dissolves well in body fluids)
• Absorption (can enter the bloodstream)
• Metabolism (not destroyed too quickly)
• Toxicity (should be safe)

Medicinal chemists use knowledge of Structure–Activity Relationship (SAR) to make these changes.

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6. Structure–Activity Relationship (SAR)

SAR is a method where scientists study how changing the chemical structure of a compound affects its biological activity.

Example:

• Replacing a hydrogen atom with a methyl group might increase the potency.
• Changing the position of a functional group may improve absorption.

This trial-and-error method is guided by chemical logic and is essential in making a better drug.

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7. Computer-Assisted Drug Design (CADD)

CADD uses software to:

• Visualise the target and drug in 3D
• Simulate how well a drug will bind (docking studies)
• Predict drug properties like solubility, toxicity, etc.

CADD makes drug design faster and reduces the number of failed compounds.

Two types:

1. Structure-based Design: When the 3D structure of the target is known.
2. Ligand-based Design: When structure is unknown but active compounds are known.

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8. Molecular Docking

Molecular docking is a CADD technique where:

• The drug molecule is fitted into the binding site of the target protein.
• The computer scores how strong the binding is.
• The best-fitting compounds are selected for lab testing.

It is like matching puzzle pieces — the better the fit, the more effective the drug may be.

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9. Pharmacophore Modelling

A pharmacophore is the part of the molecule responsible for its action. It includes:

• Hydrogen bond donors and acceptors
• Hydrophobic groups
• Aromatic rings
• Charged groups

By identifying the pharmacophore, scientists can design new compounds with similar activity.

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10. QSAR – Quantitative Structure–Activity Relationship

QSAR is a mathematical model that predicts the activity of new compounds based on known data.

Steps in QSAR:

1. Collect data of known compounds.
2. Identify physicochemical properties (e.g., log P, molecular weight, electronic charge).
3. Use statistical methods to build equations.
4. Use the model to predict activity of new compounds.

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11. Lipinski’s Rule of Five (Drug-Likeness)

To decide if a compound is likely to become a good oral drug, it should follow Lipinski’s Rule of Five:

Rule	Limit
Molecular weight	< 500 Daltons
Log P (lipid solubility)	< 5
Hydrogen bond donors	≤ 5
Hydrogen bond acceptors	≤ 10

Compounds that break more than one of these rules are likely to have poor absorption.

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12. ADMET Studies

ADMET stands for:

• Absorption
• Distribution
• Metabolism
• Excretion
• Toxicity

In drug design, these properties are checked early using computer models or lab tests to avoid problems later.

Example:

• A drug that is not absorbed well or is toxic to the liver will likely fail in clinical trials.

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13. Summary Table – Drug Screening & Design Tools

Technique	Purpose
High-Throughput Screening	Find hits from large chemical libraries
Virtual Screening	Use computer models to select hits
SAR	Study effect of structure changes
CADD	Design drugs using 3D models
Molecular Docking	Simulate drug binding to target
QSAR	Predict drug activity from structure
Lipinski’s Rule of Five	Evaluate drug-likeness
ADMET Profiling	Predict pharmacokinetic properties

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14. Advantages of Modern Screening and Design

• Faster identification of good candidates
• Lower cost of development
• Fewer toxic compounds
• More accurate predictions
• Better success rate in clinical trials

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15. Limitations

• Computer predictions are not always accurate.
• Good in-vitro results don’t always work in the human body.
• Requires skilled chemists and high-tech labs.
• Costly in early stages

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Conclusion

Screening and drug design are the heart of medicinal chemistry. They help scientists find the best compounds and turn them into life-saving drugs. With the help of computers, chemical logic, and biological understanding, modern drug design is faster, smarter, and more successful than ever before.