TÜRKÇE
ENGLISH
Information
| Unit | INSTITUTE OF MEDICAL SCIENCES |
| TRANSLATIONAL MEDICINE (PhD) (ENGLISH) (INTERDISCIPLINARY) | |
| Code | Trans639 |
| Name | Molecular Docking |
| Term | 2025-2026 Academic Year |
| Term | Fall and Spring |
| Duration (T+A) | 1-4 (T-A) (17 Week) |
| ECTS | 6 ECTS |
| National Credit | 3 National Credit |
| Teaching Language | Türkçe |
| Level | Belirsiz |
| Type | Normal |
| Mode of study | Yüz Yüze Öğretim |
| Catalog Information Coordinator | Doç. Dr. Yasemin SAYGIDEĞER |
| Course Instructor |
Doç. Dr. Yasemin SAYGIDEĞER
(Bahar)
(A Group)
(Ins. in Charge)
Biolog ERMAN SALİH İSTİFLİ (Bahar) (A Group) (Asst. Ins.) |
Course Goal / Objective
The aim is to enable students to learn molecular docking methods both theoretically and practically, and to apply these approaches in drug design and biomedical research with a scientific and critical perspective.
Course Content
This course covers the fundamental principles of molecular docking, docking types and modes, conformational space search algorithms, target protein and ligand preparation, and AutoDock-based applications.
Course Precondition
Knowledge in biochemistry (completing the course Trans609 or 649)
Resources
online available tools Autoduck etc
Notes
Will be provided during the course
Course Learning Outcomes
| Order | Course Learning Outcomes |
|---|---|
| LO01 | The ability to compare and interpret traditional and modern (computer-aided) approaches in the drug design and discovery process. |
| LO02 | The ability to utilize fundamental knowledge from molecular biology and biochemistry (protein structure, ligand-receptor interactions) by integrating it with computer science. |
| LO03 | The ability to explain the fundamental principles and limitations of molecular modeling and simulation methods. |
| LO04 | The ability to define a scientific problem (e.g., screening new drug candidates) and develop solution strategies by selecting and using appropriate bioinformatics tools and databases (PDB, PubChem). |
| LO05 | The ability to use a computer software (AutoDock) at a basic level for a specific scientific purpose and to interpret the obtained quantitative/non-quantitative outputs (binding energy, interaction diagrams). |
| LO06 | Gaining the skill to work and communicate within an interdisciplinary team (chemistry, biology, computer science). |
| LO07 | The ability to follow current developments in science and technology (new algorithms, software) and to improve oneself with an awareness of the necessity of lifelong learning. |
Relation with Program Learning Outcome
| Order | Type | Program Learning Outcomes | Level |
|---|---|---|---|
| PLO01 | Bilgi - Kuramsal, Olgusal | Develops and deepens the current and advanced level knowledge of translational medicine via unique thoughts or researches at a level of proficiency, find out original definitions that will bring innovation in the field of translational medicine. | |
| PLO02 | Bilgi - Kuramsal, Olgusal | Conceives the interdisciplinary interactions related to translational medicine; analyzes synthesizes and evaluates original and new thoughts. | 3 |
| PLO03 | Bilgi - Kuramsal, Olgusal | Explains the usage of tool, devices and instruments requiered for knowledge and technologies about translational medicine and its related disciplines. | |
| PLO04 | Bilgi - Kuramsal, Olgusal | Defines frequently used statistical methods in translational medicine and related disciplines, uses statistical softwares effectively. | |
| PLO05 | Beceriler - Bilişsel, Uygulamalı | Uses both theoretical and practical knowledge at an advanced level in the studies related to translational medicine. | |
| PLO06 | Beceriler - Bilişsel, Uygulamalı | Develops a new thoughts, method and designment/application which brings innovation in translational medicine or implements a known thoughts, method and designment/application in different fields, investigates, comprehends, designs, adapts, implements an original topic. | 4 |
| PLO07 | Beceriler - Bilişsel, Uygulamalı | Writes the report of his/her research which he/she participated, | |
| PLO08 | Beceriler - Bilişsel, Uygulamalı | Makes necessary investigations by using tool, devices and instrument required for knowledge and technologies about translational medicine and related disciplines at an advanced level, develops a new and creative solution (device, method, treatment, drug) for the problems. | |
| PLO09 | Beceriler - Bilişsel, Uygulamalı | Uses statistical software in the field of Translational Medicine effectively, chooses statistical methods correctly, calculates and interprets correctly. | |
| PLO10 | Yetkinlikler - Bağımsız Çalışabilme ve Sorumluluk Alabilme Yetkinliği | Maintains the organization of Translational Medicine laboratories and develops solutions in case of encountering unforeseen complex situations during laboratory working hours. | |
| PLO11 | Yetkinlikler - Bağımsız Çalışabilme ve Sorumluluk Alabilme Yetkinliği | Conducts scientific studies in translational medicine and related fields independently or as a team member. | 3 |
| PLO12 | Yetkinlikler - Bağımsız Çalışabilme ve Sorumluluk Alabilme Yetkinliği | Writes the report of his/her research in which he/she participated, publishes in a national or international reputed journal (indexing in SCI, SCI-Expanded, SSCI, or AHCI), and presents it at scientific meetings. | 3 |
| PLO13 | Yetkinlikler - Öğrenme Yetkinliği | Follows evidence-based practices and conducts research on professional practices that will create evidence in their field. | |
| PLO14 | Yetkinlikler - Öğrenme Yetkinliği | Applies the principles of advanced professional development and lifelong learning in the field of Translational Medicine. | |
| PLO15 | Yetkinlikler - İletişim ve Sosyal Yetkinlik | Communicate current developments and studies within the field to both professional and non-professional groups systematically using written, oral and visual techniques by supporting with quantitative and qualitative data. | |
| PLO16 | Bilgi - Kuramsal, Olgusal | Learns how to teach a concept, subject, phenomenon or case related to Translational Medicine. | |
| PLO17 | Belirsiz | Communicate and discuss orally, in written and visually with peers by using a foreign language at least at a level of European Language Portfolio B2 General Level. | |
| PLO18 | Yetkinlikler - Alana Özgü Yetkinlik | Audit the data gathering, interpretation, implementation and announcement stages by taking into consideration the cultural, scientific, and ethic values and uses these issues for social strategy, implementation plans and frame of quality processes. | 1 |
| PLO19 | Yetkinlikler - Alana Özgü Yetkinlik | Knows the importance of ethical principles and ethical committees for the individual and society, acts ethically. | |
| PLO20 | Yetkinlikler - Alana Özgü Yetkinlik | Increases the awareness of society about translational medicine. |
Week Plan
| Week | Topic | Preparation | Methods |
|---|---|---|---|
| 1 | Introduction to Molecular Docking | Review basic biochemistry knowledge related to the concepts of protein, ligand, and drug design. | Öğretim Yöntemleri: Anlatım, Tartışma |
| 2 | Traditional and Modern Drug Design | Research the traditional stages of the drug discovery process. | Öğretim Yöntemleri: Grup Çalışması, Tartışma |
| 3 | Molecular Docking Technique | Extract the general workflow diagram of molecular docking from a provided article. | Öğretim Yöntemleri: Anlatım, Soru-Cevap, Tartışma |
| 4 | Molecular Docking Types | To list the types of protein–ligand interactions (e.g., hydrogen bonding, hydrophobic interactions, etc.). | Öğretim Yöntemleri: Gösteri, Alıştırma ve Uygulama |
| 5 | Molecular docking modes | To list the types of protein–ligand interactions (e.g., hydrogen bonding, hydrophobic interactions, etc.). | Öğretim Yöntemleri: Gösterip Yaptırma, Bireysel Çalışma |
| 6 | Conformational Space Search Algorithms | Consider the countless possible 3D shapes (conformations) a ligand can adopt during binding and attempt to understand why finding the optimal binding mode within this vast sea of possibilities is a challenging problem. | Öğretim Yöntemleri: Gösterip Yaptırma, Grup Çalışması, Bireysel Çalışma |
| 7 | Pose Selection | Predict the types of information (coordinates, energy score) that might be present in a docking output file. | Öğretim Yöntemleri: Gösterip Yaptırma, Grup Çalışması, Bireysel Çalışma |
| 8 | Mid-Term Exam | Ölçme Yöntemleri: Ödev |
|
| 9 | Docking Target (Receptor) Structure | Visit the Protein Data Bank (PDB) website, search for a protein structure, and examine it. | Öğretim Yöntemleri: Gösterip Yaptırma, Grup Çalışması |
| 10 | Preparation of the receptor | To download the structure with PDB ID 1HSG (HIV-1 protease inhibitor complex) from the Protein Data Bank, to record key quality metrics such as resolution, R-free value, missing amino acid residues, and the presence of bound ligands, and to develop a preliminary assessment of its suitability as a docking target. | Öğretim Yöntemleri: Gösterip Yaptırma, Bireysel Çalışma |
| 11 | Obtaining Ligand Molecules | Attempt to download the 3D structure of a simple molecule from chemical databases such as PubChem or ZINC. | Öğretim Yöntemleri: Gösterip Yaptırma, Bireysel Çalışma |
| 12 | AutoDock Software | Visit the official AutoDock website to learn about the software's features and versions. | Öğretim Yöntemleri: Anlatım, Gösterip Yaptırma |
| 13 | Protein Preparation | Research the concept and purpose of the "grid box" | Öğretim Yöntemleri: Anlatım, Gösterip Yaptırma, Bireysel Çalışma |
| 14 | Student presentations | Preparing presentation | Öğretim Yöntemleri: Soru-Cevap |
| 15 | Article discussion | reading articles | Öğretim Yöntemleri: Tartışma, Soru-Cevap |
| 16 | Term Exams | Ölçme Yöntemleri: Ödev |
|
| 17 | Term Exams | Ölçme Yöntemleri: Performans Değerlendirmesi |
Student Workload - ECTS
| Works | Number | Time (Hour) | Workload (Hour) |
|---|---|---|---|
| Course Related Works | |||
| Class Time (Exam weeks are excluded) | 14 | 3 | 42 |
| Out of Class Study (Preliminary Work, Practice) | 14 | 6 | 84 |
| Assesment Related Works | |||
| Homeworks, Projects, Others | 1 | 6 | 6 |
| Mid-term Exams (Written, Oral, etc.) | 1 | 8 | 8 |
| Final Exam | 1 | 16 | 16 |
| Total Workload (Hour) | 156 | ||
| Total Workload / 25 (h) | 6,24 | ||
| ECTS | 6 ECTS | ||