(in Polish) Wstęp do biofizyki dla fizyków 1100-WBF
Course Topics – Lectures
Block I – What Is Biophysics (2h)
Definition and scope of biophysics
Origins of biophysics
Interdisciplinary nature of biophysics
Block II – Chemical Foundations of Biomolecules (5h)
1. Chemical foundations of biological matter
Valency of biogenic elements
Orbital hybridization and molecular geometry
Types of chemical bonds (covalent and noncovalent)
2. Organic chemistry as the foundation of biomolecules
Role of carbon in the chemistry of biological compounds
Basic functional groups and their properties
Stability and diversity of organic compounds
3. Biomolecules – structural overview (without functional biochemistry)
Proteins – amino acids and levels of protein structure
Nucleic acids – chemical structure of DNA and RNA
Lipids – amphiphilicity and self-organization
Saccharides – chemical structure and structural roles
4. Water and ions in biological systems
Physicochemical properties of water
Hydration and ion–molecule interactions
Role of metal ions in stabilizing biological structures
5. Stabilization of biomolecular structures
Interactions stabilizing biomolecular structures
Introduction to the energy landscape of biomolecules
Hierarchy of biomolecular structures
Block III – Theoretical and Computational Foundations of Molecular Biophysics (6h)
1. Energy and interactions in biomolecular systems
Potential energy as a function of configuration
Free energy and entropy (qualitative approach)
Electrostatic interactions in biomolecules
Electrostatic screening and the role of the aqueous environment
2. Molecular mechanics and dynamics
Molecular mechanics as an approximate description of biomolecular systems
Force fields: applicability and limitations
Molecular dynamics as a description of atomic motion
Timescales of molecular simulations
3. Stochastic description and the environment
Brownian motion and diffusion
Stochastic dynamics – conceptual framework
Monte Carlo methods – applications in molecular biophysics
Molecular electrostatics and hydrodynamics (intuitive approach)
Block IV – Protein–Ligand Interactions and Fundamentals of Drug Design (4h)
1. Protein–ligand interactions
Ligand binding sites
Mechanisms of protein–ligand interactions
2. Properties of interactions
Binding affinity
Interaction selectivity
3. Fundamentals of drug design
Introduction to structure-based drug design
Block V – Experimental Methods in Molecular Biophysics (3 h)
1. Structural methods
X-ray crystallography
NMR spectroscopy
Cryo-electron microscopy (cryo-EM)
2. Spectroscopic and calorimetric methods
Spectroscopic methods for studying biomolecular structure and dynamics
Calorimetric methods for analyzing interactions and stability
3. Applications and limitations of biophysical methods
Selection of methods for specific research problems
Limitations related to resolution, sensitivity, and data interpretation
Block VI – Computational Methods and Machine Learning in Biophysics (10 h)
1. Introduction to machine learning in biophysics
Machine learning tasks
Biophysical datasets
Machine learning algorithms
Data processing associated with machine learning
2. Neural networks
Fundamentals of neural networks
Major modern neural network architectures
Graph neural networks
Molecular feature extraction using neural networks
3. Protein folding
Protein folding as a computational problem
Historical approaches
AlphaFold as a tool for protein folding
Components of AlphaFold
Prediction of multimer structures
Protein–ligand structure prediction
Protein language models
4. RNA structure
Characteristics of RNA folding
Methods for RNA structure prediction
Practical Classes (Exercises)
1. Seeing proteins (biophysics laboratory) – pass based on attendance and active participation
2. Crystallography in practice (biophysics laboratory) – pass based on attendance and active participation
3. Hydration shells around proteins – computational methods – graded report
4. Ligand docking – computational methods – graded report
5. Prediction of molecular properties using machine learning (tabular data) – pass based on attendance and active participation
6. Introduction to neural networks – pass based on attendance and active participation
7. Protein structure prediction with AlphaFold – pass based on attendance and active participation
8. Protein structure prediction with ESMFold – pass based on attendance and active participation
9. RNA structure prediction – pass based on attendance and active participation
Mode
Course coordinators
Learning outcomes
Knowledge (W)
Upon completion of the course, the student:
W1. knows the scope and position of biophysics within the natural sciences and understands its interdisciplinary character
W2. understands the chemical and physical foundations of biomolecular structure and stability
W3. is familiar with the basic concepts of energetics and dynamics of molecular processes in biological systems
W4. understands the hierarchy of biomolecular structures and the structure–function relationship
W5. knows the physical basis of protein–ligand interactions and the principles of drug design
W6. is familiar with the main experimental and computational methods used to study the structure and dynamics of biomolecules
W7. has basic knowledge of the applications of molecular simulations and machine learning in biophysics
Skills (U)
Upon completion of the course, the student is able to:
U1. interpret biological processes in terms of energy, dynamics, and physical interactions
U2. apply simplified physical models to describe biomolecular systems
U3. distinguish between different levels of biomolecular description and select appropriate research methods for a given scale of the problem
U4. critically analyze the limitations of models, approximations, and biophysical data
U5. understand and interpret results of structural, simulation-based, and computational studies presented in the scientific literature
U6. identify areas of application of computational methods and machine learning in biophysics
Social Competences (K)
Upon completion of the course, the student:
K1. understands the importance of an interdisciplinary approach in research on complex biological systems
K2. is aware of the limitations of their own knowledge and the need for collaboration with representatives of other disciplines
K3. demonstrates readiness to further develop competencies in the application of physics to the life sciences
Assessment criteria
Assessment Criteria
Condition for Admission to the Examination
Admission to the examination is granted only to students who have successfully completed all practical classes предусмотрed in the course syllabus.
1. Examination (70%)
The examination consists of two parts:
a) Multiple-choice test
The test is the primary component of the examination and must be passed in order to pass the course.
The passing threshold for the test is above 50%.
The multiple-choice test allows for a maximum grade of good (4.0).
A result of at least 80% in the test qualifies the student to attempt the open-ended questions.
b) Open-ended questions
The examination includes three open-ended questions, assessed qualitatively.
Only students who have obtained at least 80% in the multiple-choice test are admitted to the open-ended questions.
The open-ended questions assess in-depth understanding of the material, as well as the ability to analyze and synthesize knowledge.
A very good (5.0) grade for the examination may be awarded exclusively on the basis of the quality of answers to the open-ended questions.
c) Bonus for reports (for students with a test result ≥ 80%)
Students who have obtained at least 80% in the multiple-choice test and have completed the open-ended questions may receive an increase of the examination grade by 0.5 in the case of very good report grades.
This bonus cannot independently result in a very good (5.0) grade.
The maximum examination grade is determined by the quality of the answers to the open-ended questions.
2. Reports (30%)
During the course, students prepare two reports.
Each report is graded using the standard grading scale.
The reports assess the ability to analyze data, interpret results, and apply theoretical knowledge in practice.
Reports graded as satisfactory (3.0) do not increase the final course grade above the examination grade.
3. Final Course Grade
The final course grade is calculated as a weighted average of the examination grade (70%) and the grades from the two reports (30%).
Half grades (e.g., 3.5, 4.5) are permitted.
Passing the examination is a prerequisite for passing the course.
The final course grade may not be higher than the final examination grade, including any bonus for very good reports; the highest possible grade is 5!.
4. Final Grade Scale
3,00–3,24 → 3,0
3,25–3,74 → 3,5
3,75–4,24 → 4,0
4,25–4,74 → 4,5
4,75–5,00 → 5,0
Bibliography
Recommended literature for individual topics will be indicated during the lectures.
Lecture presentations (slides) will be made available to students in electronic form after the classes.
Additional information
Additional information (registration calendar, class conductors, localization and schedules of classes), might be available in the USOSweb system: