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Syllabus ( BENG 466 )


   Basic information
Course title: Structural Bioinformatics and Computational Drug Design
Course code: BENG 466
Lecturer: Assist. Prof. Onur SERÇİNOĞLU
ECTS credits: 5
GTU credits: 3 ()
Year, Semester: 4, Spring
Level of course: First Cycle (Undergraduate)
Type of course: Departmental Elective
Language of instruction: English
Mode of delivery: Face to face , Group study , Lab work
Pre- and co-requisites: Min CC required from BENG212 and BENG451
Professional practice: No
Purpose of the course: This courses is intended to teach bioengineering undergraduate students how to investigate sequence, structure and function relationships in proteins, identify new drug candidates, perform protein dynamics simulations using structural bioinformatics software either available online or installed locally. The courses is comprised of theoretical classes and laboratory sessions that complement each other.
   Learning outcomes Up

Upon successful completion of this course, students will be able to:

  1. Visualize three dimensional structures of proteins using scientific software

    Contribution to Program Outcomes

    1. Acquire knowledge on biological, chemical, physical and mathematical principles which constitute the basis of bioengineering applications
    2. Acquire knowledge on current bioengineering applications from the industrial and scientific aspects
    3. Acquire knowledge for research methods which are required to develop novel application methods
    4. Design processes for the investigation of bioengineering problems, collect data, analyze and interpret the results.
    5. Combine, Interpret, and analyze different subfields of bioengineering

    Method of assessment

    1. Homework assignment
    2. Laboratory exercise/exam
  2. Conduct basic analyses of biomolecular simulation trajectories

    Contribution to Program Outcomes

    1. Acquire knowledge on current bioengineering applications from the industrial and scientific aspects
    2. Acquire knowledge for research methods which are required to develop novel application methods
    3. Apply mathematical analysis and modeling methods for bioengineering design and production processes.

    Method of assessment

    1. Homework assignment
    2. Laboratory exercise/exam
  3. Generate structural models of protein-small molecule interactions

    Contribution to Program Outcomes

    1. Convert biological, chemical, physical and mathematical principles into novel applications for the benefit of society,
    2. Apply mathematical analysis and modeling methods for bioengineering design and production processes.
    3. Conduct and develop bioengineering applications for relevant sectors such as health and agricultural industry.
    4. Design processes for the investigation of bioengineering problems, collect data, analyze and interpret the results.

    Method of assessment

    1. Homework assignment
    2. Laboratory exercise/exam
  4. Identify drug candidate small molecules using virtual screening

    Contribution to Program Outcomes

    1. Acquire knowledge on current bioengineering applications from the industrial and scientific aspects
    2. Acquire knowledge for research methods which are required to develop novel application methods
    3. Convert biological, chemical, physical and mathematical principles into novel applications for the benefit of society,
    4. Apply mathematical analysis and modeling methods for bioengineering design and production processes.
    5. Combine, Interpret, and analyze different subfields of bioengineering
    6. Work effectively in multi-disciplinary research teams

    Method of assessment

    1. Homework assignment
    2. Laboratory exercise/exam
  5. Define the basic concepts used in structure and ligand-based drug discovery with computational methods.

    Contribution to Program Outcomes

    1. Acquire knowledge on biological, chemical, physical and mathematical principles which constitute the basis of bioengineering applications
    2. Acquire knowledge on current bioengineering applications from the industrial and scientific aspects
    3. Acquire knowledge for research methods which are required to develop novel application methods

    Method of assessment

    1. Written exam
   Contents Up
Week 1: Introduction to structural bioinformatics: sequence, structure, function relationships in proteins
Week 2: Introduction to drug discovery and development, computer-aided drug design
Week 3: Introduction to chem- and bio-informatics databases
Week 4: Querying ChEMBL and Protein Data Bank programmatically
Homework I
Week 5: Molecular filtering, similarity, and clustering
Week 6: Ligand-based pharmacophore models
Homework II
Week 7: Binding site comparisons
Week 8: Prediction of interactions between drug candidates and protein structures: molecular docking simulations
Homework III
Week 9: Virtual screening via molecular docking simulations
Mid-term Exam
Week 10: Visualization and analysis of protein-ligand interactions
Week 11: Protein dynamics: classical molecular dynamics simulation (preparation)
Week 12: Protein dynamics: classical molecular dynamics simulation (production)
Week 13: Basic analyses of molecular dynamics simulation trajectories
Week 14: Advanced analyses of molecular dynamics simulation trajectories
Homework IV
Week 15*: -
Week 16*: Final Exam
Textbooks and materials: Textbooks:
G. Petsko, Ringe, D., Protein Structure and Function, 2003, Wiley-Blackwell
A. Leach, Molecular Modeling: Principles and Applications, 2nd Ed., 2002, Pearson
N. Ben-Tal, Kessel, A., Introduction to Proteins: Structure, Function, and Motion, Second Edition, 2018, CRC Press
K. Merz, D. Ringe, C.H. Reynolds (ed.), Drug Design: Structure- and Ligand-Based Approaches, 2010, Cambridge University Press
Other tutorials and papers
Recommended readings: A. Liljas, L. Liljas, J. Piskur, Textbook of Structural Biology, 2009, WSPC
I. Bahar, R. L. Jernigan, Protein Actions: Principles and Modeling, 2017, Garland Science


  * Between 15th and 16th weeks is there a free week for students to prepare for final exam.
Assessment Up
Method of assessment Week number Weight (%)
Mid-terms: 8 20
Other in-term studies: 0
Project: 0
Homework: 3,4,5,6,7,9, 10, 13, 14 40
Quiz: 0
Final exam: 16 40
  Total weight:
(%)
   Workload Up
Activity Duration (Hours per week) Total number of weeks Total hours in term
Courses (Face-to-face teaching): 1 14
Own studies outside class: 1 14
Practice, Recitation: 3 12
Homework: 6 4
Term project: 0 0
Term project presentation: 0 0
Quiz: 0 0
Own study for mid-term exam: 3 5
Mid-term: 2 1
Personal studies for final exam: 3 5
Final exam: 2 1
    Total workload:
    Total ECTS credits:
*
  * ECTS credit is calculated by dividing total workload by 25.
(1 ECTS = 25 work hours)
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