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Course Unit Code	Course Unit Title	Type of Course Unit	Year of Study	Semester	Number of ECTS Credits
KIMS4812	COMPUTER-AİDED DRUG DESİGN		4	8	4,00

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Lisans

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Language of Instruction

Turkish

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Objectives of the Course

The aim of this course is to introduce computer-aided methods used in drug discovery and to teach molecular modeling, structure-based design, and ligand-based approaches.

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Name of Lecturer(s)

Assist. Prof. Dr. Hatice ARI

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Learning Outcomes

1	Explains the basic steps of the drug discovery process.
2	Compares ligand- and structure-based design approaches.
3	Applies molecular docking and pharmacophore modeling.
4	Evaluates QSAR and virtual screening methods.
5	Analyzes software used in drug design.

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Mode of Delivery

Formal Education

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Prerequisities and Co-Requisities

None

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Recommended Optional Programme Components

None

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Content of the Course

Drug discovery process, target identification, ligand- and structure-based drug design, molecular docking, pharmacophore modeling, QSAR (quantitative structure–activity relationships), virtual screening, molecular dynamics simulations, and software applications.

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Weekly Detailed Course Contents

Week	Subjects (Theoretical)	Teaching Methods	Preparatory
1	Introduction to drug design	Lecture, definition and historical overview	Read about the history and basic concepts of drug design.
2	Target identification and validation	Case study, target analysis	Research target identification methods.
3	Principles of ligand-based design	Conceptual lecture, analogy task	Read basic articles on ligand-based design techniques.
4	Principles of structure-based design	Slide presentation, comparative summary table	Compare structure-based and ligand-based approaches.
5	Molecular docking methods	Software demo, docking practice	Watch and study an example of molecular docking.
6	Pharmacophore modeling	Modeling exercise, structure drawing	Review pharmacophore modeling steps and examine example structures.
7	Introduction to QSAR analysis	Group activity, QSAR example resolution	Research fundamental QSAR parameters.
8	Virtual screening strategies	Literature analysis, algorithm overview	Study algorithms related to virtual screening.
9	Introduction to molecular dynamics simulations	Practical lecture, simulation walkthrough	Read brief resources on molecular dynamics.
10	ADMET predictions	Discussion, ADMET software demo	Explore ADMET prediction tools and parameters.
11	Introduction to drug design software (e.g., Autodock)	Computer lab, program usage	Review usage guides for Autodock or equivalent software.
12	Software applications and result interpretation	Data analysis, result comparison	Interpret virtual screening results from previous studies.
13	Student project presentations	Student presentations, feedback session	Prepare project files and give first presentations.
14	General review	General review	Finalize presentations and conduct full course review.

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Text Book / Material / Recommended Resources

Leach, A. R. (2001). Molecular Modelling: Principles and Applications. Gasteiger, J., & Engel, T. (2003). Chemoinformatics: A Textbook. Current journal articles and software manuals.

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Planned Learning Activities and Teaching Methods

None

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Assessment Methods and Criteria

Term (or Year) Learning Activities	Quantity	Weight
Midterm Examination	1	50
Quiz	1	50
Total		100
End Of Term (or Year) Learning Activities	Quantity	Weight
Final Examination	1	100
Total		100
Term (or Year) Learning Activities		40
End Of Term (or Year) Learning Activities		60

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Work Pacement(s)

None

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Workload Calculation

Activities	Number	Time (hours)	Total Work Load (hours)
Midterm Examination	1	1	1
Final Examination	1	1	1
Quiz	1	1	1
Attending Lectures	14	2	28
Self Study	14	3	42
Individual Study for Mid term Examination	3	3	9
Individual Study for Final Examination	4	4	16
Individual Study for Quiz	2	2	4
Total Work Load (hours)			102

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Contribution of Learning Outcomes to Programme Outcomes

	PO 1	PO 2	PO 3	PO 4	PO 5	PO 6	PO 7	PO 8	PO 9	PO 10	PO 11	PO 12	PO 13	PO 14	PO 15
LO 1	3			2	3					5
LO 2	3			2	3					5
LO 3	3		3	2	3					5
LO 4	3			2	3					5
LO 5	3		3	2	3					5