# Course Identification

Topics in physical chemistry and biophysics

20232172

## Lecturers and Teaching Assistants

Prof. Hagen Hofmann

Amir Haluts

## Course Schedule and Location

2023

Second Semester

Tuesday, 14:15 - 16:00, FGS, Rm C

Sunday, 14:15 - 16:00, FGS, Rm A

**Tutorials**Sunday, 14:15 - 16:00, FGS, Rm A

18/04/2023

21/07/2023

## Field of Study, Course Type and Credit Points

Life Sciences: Lecture; Elective; Regular; 3.00 points

## Comments

(2) Cluster - Bio-related

## Prerequisites

## Restrictions

25

## Language of Instruction

## Attendance and participation

## Grade Type

## Grade Breakdown (in %)

100%

## Evaluation Type

**Examination**

## Scheduled date 1

15/08/2023

FGS, Rm C

0900-1100

N/A

## Scheduled date 2

31/08/2023

FGS, Rm A

0900-1100

N/A

## Estimated Weekly Independent Workload (in hours)

## Syllabus

The course is an introduction into the basic ideas in statistical thermodynamics. It is specifically designed for students in biology and biochemistry, but it will also refresh the knowledge of chemists. From the rules of probabilities over concepts such as entropy and free energy up to theories of protein folding, the lecture aims at providing basic knowledge in physical chemistry, useful sets of mathematical tools, and direct links to current topics in biophysics. Importantly, the lecture does not require a specific pre-knowledge in mathematics or physics.

Aim of the lecture: The first part provides a comprehensive overview about the forces that drive molecules to bind, dissolve, react, or to undergo conformational changes. A special focus is placed on the derivation of simple models to predict the behavior of molecules in chemistry and biology. The second part of the lecture describes how statistical concepts can be used to describe the behavior of proteins. Starting with polymer concepts for understanding disordered proteins and ending with theories in protein folding, the lecture makes you familiar with current topics in protein sciences.

Curriculum

- The rules of probabilities (Rules of Probabilities, Combinatorics, Distribution Functions, Averages and Standard Deviations)
- What is entropy? (Extremum Principles, Maximizing Multiplicity, Definition of Entropy, Maximum Entropy Method)
- What is free energy? (From Entropy to Free Energy, Heat Capacity, Thermodynamic Cycles, Maxwell Relations)
- Partition functions (Probability Distributions, The Boltzmann Law, What is a Partition Function, Thermodynamic Properties from Partition Functions)
- Solutions and mixtures (Lattice models, Chemical Potentials, Activity and Activity Coefficients)
- Phase transitions (When do liquids mix, Phase Separations, Critical Points)
- Cooperativity (Bistability, Landau Model, Ising Model, Helix-Coil Transitions, Nucleation)
- Binding equilibria (Binding Polynomials, Two-Site Model of Binding Cooperativity, Inhibitors, Rates from Binding Polynomials)
- Protein collapse I (Long-Chain Molecules, Distance Distributions, The Gaussian Chain)
- Protein collapse II (Protein Collapse as Coil-Globule transition, Mean-field theories of Coil-Globule transitions)
- Theories of protein folding (Heteropolymers, Specific Interactions, Entropy Catastrophy, The Energy Landscape Perspective, How likely are proteins)

## Learning Outcomes

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

- Link the rules of probability to thermodynamic quantities
- Compute free energies and entropies
- Use partition functions to describe complex equilibria
- Derive simple lattice models for problems in molecular biophysics
- Have a useful set of mathematical tools

## Reading List

Ken A Dill, Sarina Bromberg & Dirk Stigter "Molecular Driving Forces" Garland Science, New York