Učni načrt predmeta

Predmet:
Biomolekularne simulacije
Course:
Biomolecular Simulations
Študijski program in stopnja /
Study programme and level		 Študijska smer /
Study field		 Letnik /
Academic year		 Semester /
Semester
Nanoznanosti in nanotehnologije, 3. stopnja 1 1
Nanosciences and Nanotechnologies, 3rd cycle 1 1
Vrsta predmeta / Course type
Izbirni
Univerzitetna koda predmeta / University course code:
NANO3-789
Predavanja
Lectures		 Seminar
Seminar		 Vaje
Tutorial		 Klinične vaje
work		 Druge oblike
študija		 Samost. delo
Individ. work		 ECTS
15 15 15 105 5

*Navedena porazdelitev ur velja, če je vpisanih vsaj 15 študentov. Drugače se obseg izvedbe kontaktnih ur sorazmerno zmanjša in prenese v samostojno delo. / This distribution of hours is valid if at least 15 students are enrolled. Otherwise the contact hours are linearly reduced and transfered to individual work.

Nosilec predmeta / Course leader:
prof. dr. Janez Mavri
Sodelavci / Lecturers:
Jeziki / Languages:
Predavanja / Lectures:
Slovenščina, angleščina / Slovenian, English
Vaje / Tutorial:
Pogoji za vključitev v delo oz. za opravljanje študijskih obveznosti:
Prerequisites:

Zaključen študij druge stopnje s področja naravoslovja ali tehnologije ali zaključen študij druge stopnje na drugih področjih z znanjem osnov s področja predmeta.

Completed second cycle studies in natural sciences or technologies or completed second cycle studies in other fields with knowledge of fundamentals in the field of this course.

Vsebina:
Content (Syllabus outline):

- Časovno odvisna in časovno neodvisna Schrödingerjeva enačba
- Polje sile
- Kemijske reakcije v plinski fazi
- Molekulska dinamika in Monte Carlo simulacija
- Refinement: Vključitev eksperimentalnih podatkov
- Kako izračunati razlike v prostih energijah
- Kemijska reakcija v encimski okolici
- Simulacija nuklearnega tuneliranja
- Design inhibitorjev na osnovi strukture prehodnega stanja
- Modelna študija i) Simulacija kemijskega koraka monoaminske oksidaze
- Modelna študija ii) Simulacija prenosa protona z integracijo po poti v encimskem centru
- Modelna študija iii) Simulacija reakcije v vodni raztopini

- Time-dependent and time-independent Schrödinger equation
- Force field
- Chemical reactions in the gas phase
- Molecular dynamics and the Monte Carlo simulation
- Refinement: Incorporation of experimental data
- How to calculate free energy differences
- Chemical reaction in an enzymatic environment
- Simulation of nuclear tunneling
- Design of inhibitors on the basis of the transition-state structure
- Model study i) Simulation of chemical step of monoamine oxidase
- Model study ii) Path integral simulation of proton transfer in the enzyme center
- Model study iii) Simulation of a chemical reaction in aqueous solution

Temeljna literatura in viri / Readings:

- Warshel, A. (1991): Computer modeling of chemical reactions in enzymes and solutions. J. Wiley
- Field, M.J. (2002): Simulating enzyme reactions: Challenges and Perpectives. J. Comp. Chem. 23, str:
48 - 58.
- https://www.nobelprize.org/nobel_prizes/chemistry/laureates/2013/warshel-lecture.html

Cilji in kompetence:
Objectives and competences:

Študent bo dobil vpogled v probleme biomolekularnih simulacij: kvantno mehanske metode, metode na osnovi molekulske mehanike, ki omogočajo termično povprečenje, modeliranje kemijskih reakcij v raztopinah, encimatske reakcije in načrtovanje inhibitorjev. Sestavni del predmeta je praktično delo z računalnikom.

Splošne kompetence:
- obvladanje raziskovalnih metod, postopkov inprocesov, razvoj kritične in samokritične presoje,
- sposobnost uporabe znanja v praksi,
- razvoj komunikacijskih sposobnosti in spretnosti, posebej komunikacije v mednarodnem okolju,
- kooperativnost, delo v skupini (in v mednarodnem okolju)

Predmetnospecifične kompetence:
- Predmet pripravlja študente za uporabo znanja s področja biomolekularnih simulacij.

Students will gain insight into the problems of intermolecular simulations: quantum-mechanical methods, molecular mechanics-based methods enabling thermal averaging, the modelling of chemical reactions in solutions, enzymatic reactions and the planning of inhibitors. Practical work involving the use of computers constitutes an integral part of this course.

General Competences:
- The student will master research methods, procedures and processes
- The student will develop critical thinking
- The student will develop communications skills to present research achievement in the international environment
- Work in team (in international environment)

Course Specific Competences:
- This course prepares students to apply knowledge of biomolecular simulations.

Predvideni študijski rezultati:
Intendeded learning outcomes:

Študent bo dobil vpogled v probleme biomolekularnih simulacij.
Študent bo sposoben uporabljati pridobljeno znanje v svojem raziskovalnem delu.

The student will gain insight into the problems of intermolecular simulations.
Students will be able to apply the obtained knowledge in their research work.

Metode poučevanja in učenja:
Learning and teaching methods:

Predavanja, seminarji, konzultacije, laboratorijsko delo

Lectures, Seminar work, Consultations, Laboratory work

Načini ocenjevanja:
Delež v % / Weight in %
Assesment:
Seminar
50 %
Seminar
Ustni izpit
50 %
Oral exam
Reference nosilca / Lecturer's references:
1. V. Smrkolj, D. Pregeljc, H. Kavčič, N. Umek, J. Mavri, Micro-pharmacokinetics of lidocaine and bupivacaine transfer across a myelinated nerve fiber, Computers in Biology and Medicine 165 (2023) 107375.
2. A. Prah, D. Pregeljc, J. Stare, J. Mavri, Brunner syndrome caused by point mutation explained by multiscale simulation of enzyme reaction, Sci Rep 12(2022) 21889.
3. A. Prah, M. Purg, J. Stare, R. Vianello, J. Mavri, How Monoamine Oxidase A Decomposes Serotonin: An Empirical Valence Bond Simulation of the Reactive Step, J. Phys. Chem. B, 124 (2020) 8259−8265.
4. M.Z. Brela, A. Prah, M. Boczar, J. Stare, J. Mavri, Path Integral Calculation of the Hydrogen/Deuterium Kinetic Isotope Effect in Monoamine Oxidase A Catalyzed Decomposition of Benzylamine, Molecules 24 (2019) 4359.
5. M. Sencanski, S. Glisic, M. Šnajder, N. Veljkovic, N. Poklar Ulrih, J. Mavri, M. Vrecl, Computational design and characterization of nanobodyderived peptides that stabilize the active conformation of the β2-adrenergic receptor (β2-AR), Scientific Reports 9 (2019) 16555.