Computational Drug Design

Lecturers: Dr. Tobias Hüfner, Dr. Jayashrita Debnath, Dr. Balázs Fábián

Course open to all interested students.
Every Tuesday 14:00 – 16:00 (s.t.) during the Winter Semester

Contact the lecturers directly:
Tobias Hüfner: tobias.huefner@biophys.mpg.de
Jayashrita Debnath: Jayashrita.Debnath@biophys.mpg.de
Balázs Fábián: Balazs.Fabian@biophys.mpg.de

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Content Covered (incl. practicals)

• 1. Introduction to computational drug design
• 2. Ligand-based approachees
  • a. (Quantitative) structure-activity relationship (SAR & QSAR)
  • b. Pharmacophore modeling
• 3. Bioinformatics approaches (target recognition and structural modeling)
  • a. Sequence alignments and searches
  • b. Gene identification and prediction
  • c. Homology modeling
• 4. Structure-based approaches
  • a. Molecular docking
    • i. Ligand docking: theory and scoring functions
    • ii. Virtual screening
    • iii. Protein-protein docking and interaction
  • b. Molecular dynamics simulation
    • i. Introduction into molecular dynamics
    • ii. Estimation of ligand binding affinity
• 5. Free energy perturbation
• 6. Enhance sampling methods

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Topics for Student Presentations

QSAR

• 1. QSAR modeling using partial least square (PLS)
• 2. Application of neural networks in QSAR

Modeling

• 1. Profile based methods and applications to sequence alignment
• 2. Threading for protein structure prediction
• 3. Using co-evolution for protein structure prediction

Docking

• 1. Protein-protein interface prediction using 3D structure and residue conservation
• 2. Induced-fit docking

MD simulation

• 1. Thermodynamic integration (TI) for free energy calculation
• 2. Non-equilibrium simulation
• 3. Advanced methods in enhanced sampling
• 4. Metadynamics

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Course Documentation

Lecture 1, 2020.11.03 (PDF) password protected

Lecture 2, 2020.11.10 (PDF) password protected

Lecture 3, 2020.11.17 (PDF) password protected

Lecture 4, 2020.11.24 (PDF) password protected

Lecture 5+6, 2020.12.01 (PDF) password protected

Lecture 7, 2020.12.16 (PDF) password protected

Lecture 8, 2021.01.12 (PDF) password protected

Lecture 9, 2021.01.19 (PDF) password protected

Lecture 10, 2021.01.26 (PDF) password protected

Lecture 11, 2021.02.02 (PDF) password protected

Lecture 12, 2021.02.09 (PDF) password protected