Structure-Based Drug Discovery: SBDD Principles & Methods

Structure-Based

Drug Discovery

Decoding Molecular Architecture to Design Tomorrow's Medicines

Advanced Course in Medicinal Chemistry & Computational Biology

01 / 30

Academic Presentation | 2026

Table of Contents

Introduction to Drug Discovery

Fundamentals of Protein Structure

Target Identification & Validation

Structural Determination Methods (X-ray, NMR, Cryo-EM)

Molecular Docking & Virtual Screening

Fragment-Based Drug Discovery

Lead Optimization & SAR

Computational Tools & AI in SBDD

Case Studies & Success Stories

Challenges & Future Perspectives

02 / 30

Section 1: Introduction to Drug Discovery

From Disease Biology to Therapeutic Molecules

03 / 30

Academic Presentation | 2026

What is

Drug Discovery?

The rigorous, multi-disciplinary process of finding new candidate medications, moving from identifying initial disease targets to establishing safe and effective treatments.

Target Identification & Validation

Discovering specific biological mechanisms linked to disease pathology.

Hit to Lead & Lead Optimization

Screening vast compound libraries and chemically refining the best candidates.

Preclinical & Clinical Trials

Testing in laboratory models initially, followed by safely testing in human volunteers.

Regulatory Approval

Detailed review by health authorities to secure marketing authorization.

10,000

Compounds Screened

250

Preclinical Candidates

5

Clinical Trials

1

Approved Drug

04 / 30

Academic Presentation | 2026

Traditional

vs.

Structure-Based

Drug Discovery

Traditional / Phenotypic

Trial-and-error screening

Blind to molecular mechanisms

High attrition rates

Slow and expensive

Early aspirin discovery

Structure-Based (SBDD)

Rational, target-guided design

Uses 3D protein structures

Higher hit rates

Faster lead optimization

HIV protease inhibitors

SBDD reduces development costs by up to 50% and significantly improves clinical success rates.

05 / 30

HISTORY & MILESTONES OF

STRUCTURE-BASED DRUG DISCOVERY

1970s

First protein X-ray crystal structures solved

1980s

HIV crisis drives SBDD urgency

1994

FDA approves first SBDD drug (Saquinavir)

1996

Indinavir & Ritonavir trigger SBDD revolution

2001

Imatinib (Gleevec) cancer kinase inhibitor

2006

Cryo-EM revolution begins

2012

GPCR structures solved; new drug targets

2020s

AI/ML accelerates SBDD (AlphaFold breakthrough)

06 / 30

Academic Presentation | 2026

02

Fundamentals of Protein Structure

The Molecular Targets at the Heart of SBDD

07 / 30

Academic Presentation | 2026

Levels of Protein Structure

PRIMARY

Amino acid sequence; linear polypeptide chain; defined by genetic code

SECONDARY

α-helices and β-sheets; hydrogen bond stabilized; local folding motifs

TERTIARY

3D folded conformation of a single polypeptide; hydrophobic core; binding pockets formed here

QUATERNARY

Assembly of multiple polypeptide subunits; oligomeric complexes; allosteric sites

Binding pockets emerge at the tertiary/quaternary level — these are the targets for SBDD.

08 / 30

Binding Sites

& Pharmacophores

A specific 3D region of a protein with complementary shape and chemical properties to a ligand

Orthosteric (active) site

Allosteric site

Cryptic/hidden sites

Protein-protein interaction interfaces

Shape complementarity

Electrostatics

Hydrophobic contacts

H-bond donors/acceptors

09 / 30

Advanced Medicinal Chemistry

03

Target Identification <br/>& Validation

Finding the Right Biological Lock for Our Chemical Key

10 / 30

Major Drug Target Classes

ENZYMES

Kinases, proteases, phosphatases; inhibit catalytic activity; ~47% of all drug targets

GPCRs

G-protein coupled receptors; ~34% of FDA-approved drugs; 7-transmembrane helices

ION CHANNELS

Voltage/ligand-gated channels; CNS, cardiac targets

NUCLEAR RECEPTORS

Transcription factor regulation; steroid hormones, cancer

PROTEIN-PROTEIN INTERACTIONS

Challenging; large flat surfaces; emerging frontier

NUCLEIC ACIDS

DNA/RNA targeting; antivirals, oncology

11 / 30

Target Validation Strategies

Genetic Validation

Knockout/knockin models, CRISPR screens, human genetics (GWAS)

Biochemical Validation

In vitro binding assays, enzymatic activity, SPR, ITC

Cell-Based Validation

Knockdown/overexpression, phenotypic rescue experiments

In Vivo Validation

Animal models, disease-relevant endpoints

Clinical Biomarker

Target engagement confirmed in patients

Key Validation Criteria

Druggability

Disease Linkage

Selectivity Potential

Structural Data Availability

Druggable

Disease-Relevant

Structurally Characterized

Good Target

12 / 30

Target Validation Overview

04

Structural Determination Methods

Visualizing Proteins at Atomic Resolution

13 / 30

X-ray Crystallography

Gold standard for protein structure determination since the 1950s

Protein expression & purification

Crystal growth

(key bottleneck)

X-ray diffraction data collection (synchrotron)

Phase determination (MR, SAD, MAD)

Model building & refinement

Deposition to Protein Data Bank (PDB)

High resolution (1-3 Å), well-established, large structures possible

Requires crystallization, static snapshots, difficult for membrane proteins

14 / 30

Cryo-EM and NMR Spectroscopy

Cryo-EM

No crystallization needed

Maintains near-native conditions

Awarded Nobel Prize in 2017

Ideal for large macromolecular complexes

Achieves sub-2 Ångström resolution

NMR Spectroscopy

Measures solution state dynamics

Optimal for small proteins (< 50 kDa)

Reveals conformational flexibility

Yields detailed chemical shift data

15 / 30

05

Molecular Docking & Virtual Screening

Computational Prediction of Ligand-Target Interactions

16 / 30

Academic Presentation | 2026

What is docking?

Computational method predicting preferred orientation and binding affinity of a small molecule within a protein binding site

Two Main Components

SEARCH ALGORITHM

explores conformational space (rigid, semi-flexible, fully flexible)

Genetic algorithms, Monte Carlo, systematic search

SCORING FUNCTION

ranks poses by predicted binding affinity

Force-field based, empirical, knowledge-based, ML-based

AutoDock, Glide, GOLD, Vina, rDock

Protein flexibility, solvation, entropy, scoring accuracy

17 / 30

Virtual Screening Workflow

Compound Library

~10M+

Druglikeness Filter

~1M

Pharmacophore Screening

~100K

Molecular Docking

~10K

Re-scoring

~1K

Experimental Validation

5-20 hits

18 / 30

Academic Presentation | 2026

Fragment-Based Drug Discovery (FBDD)

Building Potent Drugs from Small Molecular Fragments

19 / 30

Fragment-Based Drug Discovery (FBDD)

FBDD uses very small molecules (150-300 Da) as starting points, identified by weak but efficient binding, then grown or linked into drug-like leads.

Better chemical space coverage

Higher ligand efficiency

Fewer compounds to screen (~1,000-10,000 vs millions)

20 / 30

07

Lead Optimization &

Structure-Activity Relationships

Fine-Tuning Molecules for Potency, Selectivity & Safety

21 / 30

Structure-Activity Relationships (SAR)

SAR describes how structural modifications to a molecule affect its biological activity at a target.

Bioisosteric replacements

maintain activity while improving ADMET

Scaffold hopping

change core while retaining pharmacophore

Matched molecular pairs (MMP) analysis

Free-Wilson analysis

Activity cliffs

small structural change causes large potency jump

22 / 30

Academic Presentation | 2026

40%

of all drug candidate failures in clinical trials are directly attributed to poor ADMET properties.

23 / 30

Academic Presentation | 2026