It is aimed to teach the students some widely-used computational techniques such as molecular modeling, molecular docking and molecular dynamics simulations along with the parameters used to optimize simulations. In this way, students are expected to run a molecular dynamics simulation by their own.
Course Content
This course contains; Introduction to Quantum Chemistry,An overview to the Quantum Chemical Methods,Introduction to Statistical Mechanics,Molecular Dynamics,Force Fields,Solvation Models,Electrostatics in Molecular dynamics,Free Energy Calculations,Enhanced Sampling Techniques,Hybrid Simulation Methods : QM/MM calculations,Coarse Grained Potentials /Transferability of the Coarse Grained Potentials,Molecular Docking,Application of above-mentioned techniques to biological problems -I,Application of above-mentioned techniques to biological problems -II.
Dersin Öğrenme Kazanımları
Teaching Methods
Assessment Methods
1. Different aspects between molecular mechanics and quantum mechanics are understood and the student can decide which method is appropriate for solving a given biological problem.
10, 13, 14, 16, 19, 2, 21, 37
F
2. The force-fields as well as water models which are needed to perform a molecular dynamics simulation can be determined.
10, 13, 14, 16, 19, 2, 9
F
3. Knowledge can be gathered related to the basic commands used in Linux.
14, 16, 6, 9
E
4. A molecular dynamics simulation can be started on the clusters.
10, 14, 16, 2, 6, 9
5. Molecular dynamics simulations can be initiated and the results can be interpreted.
10, 14, 16, 19, 2, 20, 6
F
6. The optimum technique can be proposed to solve a problem related to computational biophysics.
10, 12, 13, 16, 2, 20, 21, 3, 4
F
Teaching Methods:
10: Discussion Method, 12: Problem Solving Method, 13: Case Study Method, 14: Self Study Method, 16: Question - Answer Technique, 19: Brainstorming Technique, 2: Project Based Learning Model, 20: Reverse Brainstorming Technique, 21: Simulation Technique, 3: Problem Baded Learning Model, 37: Computer-Internet Supported Instruction, 4: Inquiry-Based Learning, 6: Experiential Learning, 9: Lecture Method
Assessment Methods:
E: Homework, F: Project Task
Course Outline
Order
Subjects
Preliminary Work
1
Introduction to Quantum Chemistry
2
An overview to the Quantum Chemical Methods
3
Introduction to Statistical Mechanics
4
Molecular Dynamics
5
Force Fields
6
Solvation Models
7
Electrostatics in Molecular dynamics
8
Free Energy Calculations
9
Enhanced Sampling Techniques
10
Hybrid Simulation Methods : QM/MM calculations
11
Coarse Grained Potentials /Transferability of the Coarse Grained Potentials
12
Molecular Docking
13
Application of above-mentioned techniques to biological problems -I
14
Application of above-mentioned techniques to biological problems -II
Resources
1) Frenkel and Smit, Understanding Molecular Simulation : From Algorithms to Applications, , Academic Press, Computational Science Series
2) Allen and Tildesley, Computer Simulation of Liquids, Clarendon Press
3) Zhou, Molecular Modeling at the Atomic Scale, CRC Press, Taylor & Francis.
Course Contribution to Program Qualifications
Course Contribution to Program Qualifications
No
Program Qualification
Contribution Level
1
2
3
4
5
1
Develop and deepen knowledge in the same or in a different field to the proficiency level based on Bachelor level qualifications.
X
2
Conceive the interdisciplinary interaction which the field is related with.
X
3
Use of theoretical and practical knowledge within the field at a proficiency level and solve the problem faced related to the field by using research methods.
X
4
Interpret the knowledge about the field by integrating the information gathered from different disciplines and formulate new knowledge.
X
5
Independently conduct studies that require proficiency in the field.
X
6
Take responsibility and develop new strategic solutions as a team member in order to solve unexpected complex problems faced within the applications in the field.
X
7
Evaluate knowledge and skills acquired at proficiency level in the field with a critical approach and direct the learning.
X
8
Investigate, improve social connections and their conducting norms with a critical view and act to change them when necessary. Communicate with peers by using a foreign language at least at a level of European Language Portfolio B2 General Level.
X
9
Define the social and environmental aspects of engineering applications.
10
Audit the data gathering, interpretation, implementation and announcement stages by taking into consideration the cultural, scientific, and ethic values and teach these values.
X
Assessment Methods
Contribution Level
Absolute Evaluation
Rate of Midterm Exam to Success
50
Rate of Final Exam to Success
50
Total
100
ECTS / Workload Table
Activities
Number of
Duration(Hour)
Total Workload(Hour)
Course Hours
13
3
39
Guided Problem Solving
6
2
12
Resolution of Homework Problems and Submission as a Report
10
5
50
Term Project
0
0
0
Presentation of Project / Seminar
1
52
52
Quiz
0
0
0
Midterm Exam
6
5
30
General Exam
13
5
65
Performance Task, Maintenance Plan
0
0
0
Total Workload(Hour)
248
Dersin AKTS Kredisi = Toplam İş Yükü (Saat)/30*=(248/30)
8
ECTS of the course: 30 hours of work is counted as 1 ECTS credit.
Detail Informations of the Course
Course Description
Course
Code
Semester
T+P (Hour)
Credit
ECTS
COMPUTATIONAL BIOPHYSICS : TOOLS and METHODS
BEBY1212982
Spring Semester
3+0
3
8
Course Program
Perşembe 10:00-10:45
Perşembe 11:00-11:45
Perşembe 12:00-12:45
Prerequisites Courses
Recommended Elective Courses
Language of Course
English
Course Level
Second Cycle (Master's Degree)
Course Type
Elective
Course Coordinator
Assoc.Prof. Özge ŞENSOY
Name of Lecturer(s)
Assoc.Prof. Özge ŞENSOY
Assistant(s)
Aim
It is aimed to teach the students some widely-used computational techniques such as molecular modeling, molecular docking and molecular dynamics simulations along with the parameters used to optimize simulations. In this way, students are expected to run a molecular dynamics simulation by their own.
Course Content
This course contains; Introduction to Quantum Chemistry,An overview to the Quantum Chemical Methods,Introduction to Statistical Mechanics,Molecular Dynamics,Force Fields,Solvation Models,Electrostatics in Molecular dynamics,Free Energy Calculations,Enhanced Sampling Techniques,Hybrid Simulation Methods : QM/MM calculations,Coarse Grained Potentials /Transferability of the Coarse Grained Potentials,Molecular Docking,Application of above-mentioned techniques to biological problems -I,Application of above-mentioned techniques to biological problems -II.
Dersin Öğrenme Kazanımları
Teaching Methods
Assessment Methods
1. Different aspects between molecular mechanics and quantum mechanics are understood and the student can decide which method is appropriate for solving a given biological problem.
10, 13, 14, 16, 19, 2, 21, 37
F
2. The force-fields as well as water models which are needed to perform a molecular dynamics simulation can be determined.
10, 13, 14, 16, 19, 2, 9
F
3. Knowledge can be gathered related to the basic commands used in Linux.
14, 16, 6, 9
E
4. A molecular dynamics simulation can be started on the clusters.
10, 14, 16, 2, 6, 9
5. Molecular dynamics simulations can be initiated and the results can be interpreted.
10, 14, 16, 19, 2, 20, 6
F
6. The optimum technique can be proposed to solve a problem related to computational biophysics.
10, 12, 13, 16, 2, 20, 21, 3, 4
F
Teaching Methods:
10: Discussion Method, 12: Problem Solving Method, 13: Case Study Method, 14: Self Study Method, 16: Question - Answer Technique, 19: Brainstorming Technique, 2: Project Based Learning Model, 20: Reverse Brainstorming Technique, 21: Simulation Technique, 3: Problem Baded Learning Model, 37: Computer-Internet Supported Instruction, 4: Inquiry-Based Learning, 6: Experiential Learning, 9: Lecture Method
Assessment Methods:
E: Homework, F: Project Task
Course Outline
Order
Subjects
Preliminary Work
1
Introduction to Quantum Chemistry
2
An overview to the Quantum Chemical Methods
3
Introduction to Statistical Mechanics
4
Molecular Dynamics
5
Force Fields
6
Solvation Models
7
Electrostatics in Molecular dynamics
8
Free Energy Calculations
9
Enhanced Sampling Techniques
10
Hybrid Simulation Methods : QM/MM calculations
11
Coarse Grained Potentials /Transferability of the Coarse Grained Potentials
12
Molecular Docking
13
Application of above-mentioned techniques to biological problems -I
14
Application of above-mentioned techniques to biological problems -II
Resources
1) Frenkel and Smit, Understanding Molecular Simulation : From Algorithms to Applications, , Academic Press, Computational Science Series
2) Allen and Tildesley, Computer Simulation of Liquids, Clarendon Press
3) Zhou, Molecular Modeling at the Atomic Scale, CRC Press, Taylor & Francis.
Course Contribution to Program Qualifications
Course Contribution to Program Qualifications
No
Program Qualification
Contribution Level
1
2
3
4
5
1
Develop and deepen knowledge in the same or in a different field to the proficiency level based on Bachelor level qualifications.
X
2
Conceive the interdisciplinary interaction which the field is related with.
X
3
Use of theoretical and practical knowledge within the field at a proficiency level and solve the problem faced related to the field by using research methods.
X
4
Interpret the knowledge about the field by integrating the information gathered from different disciplines and formulate new knowledge.
X
5
Independently conduct studies that require proficiency in the field.
X
6
Take responsibility and develop new strategic solutions as a team member in order to solve unexpected complex problems faced within the applications in the field.
X
7
Evaluate knowledge and skills acquired at proficiency level in the field with a critical approach and direct the learning.
X
8
Investigate, improve social connections and their conducting norms with a critical view and act to change them when necessary. Communicate with peers by using a foreign language at least at a level of European Language Portfolio B2 General Level.
X
9
Define the social and environmental aspects of engineering applications.
10
Audit the data gathering, interpretation, implementation and announcement stages by taking into consideration the cultural, scientific, and ethic values and teach these values.
