(in Polish) The novel drugs active in central nervous system - searching using in silico computational methods 1700-OG-EN-CNSdrug

Lectures
The main task of the lectures is to familiarize students with the ATC classification, physicochemical properties evaluation, eg.: aromaticity, rotatable bonds, polar surface area, logP, molecular weight, hydrogen bonds building potential.
Using proper databases of proteins and molecules.
Evaluation process of CNS-drug candidate using novel computational methods and molecular modelling.
Potential toxicity in silico assessment of invesigated compounds.

Laboratories:
The student will be involved in the in silico experiments which allow to determine pharmacological and physicochemical properties of compounds. The student will gather practical skills in the potential activity and toxicity assessment using molecular modelling methods, also obtain abilities to interpret the obtained results.

Total student workload

Contact hours with teacher: - participation in lectures: 10 hrs, - participation in laboratory: 22 hrs, - consultations with an academic teacher: 2 hrs, - completion of the test: 1 hr. The workload related to the activities requiring the direct participation of academic teachers is 35 hrs, which corresponds to 1.4 ECTS points. Self-study hours: - preparation for lectures: 6 hrs - preparation for labs: 12 hrs - reading literature: 10 hrs - preparation for test: 12 hrs The total workload related to the self-study hours is 40 hours, which corresponds to 1.6 ECTS point. Altogether: 75 hrs (3.0 ECTS)

Learning outcomes - knowledge

Student: W1: has basic knowledge about chemical structure of major substances active in central nervous system. C.W2. (pharmacy) W2: has specialist knowledge related to designing new drugs with defined properties and active in central nervous system. C.W13. (pharmacy) W3: has basic knowledge about structure, physicochemical and pharmacological properties relationship of organic compounds. C.W3. (pharmacy)

Learning outcomes - skills

Student: U1: is able to evaluate proper drug candidates based on chemical structure and their physicochemical properties. C.U3. (pharmacy) U2: can explain structure-activity relationship of organic compounds. B.U10. (pharmacy)

Learning outcomes - social competencies

Student: K1: understands the need for continually improve professional skills. K8. (pharmacy)

Teaching methods

Lectures: - informative (conventional) lecture with multimedia presentation - participatory lecture - problem-based lecture Laboratories: - performing experiments and problem analysis.

Type of course

elective course

Course coordinators

Łukasz Fijałkowski
Alicja Nowaczyk

Assessment criteria

Assessment methods:
- test (W1-W3, U1-U2)
The appropriate number of points from the final test is required.
Assessment criteria:
fail- 0-59%
satisfactory- 60-67%
satisfactory plus- 68-75%
good – 76-83%
good plus- 84-90%
very good- 91-100%

Bibliography

Primary literature:
1. Paroxetine—Overview of the molecular mechanisms of action. Kowalska, M.; Nowaczyk, J.; Fijałkowski, Ł.; Nowaczyk, A., International Journal of Molecular Sciences 2021, 22, (4),
2. Coumar, S. M. Molecular Docking for Computer-Aided Drug Design, Academic Press 2021.
3. Jensen J. H. Molecular Modeling Basics. CRC Press, 2017.
4. Singh D. B. Computer Aided Drug Design. Springer, 2020.
Supplementary literature:
1. Pirhadi, S., Sunseri, J., & Koes, D. R. (2016). Open source molecular modeling. Journal of Molecular Graphics and Modelling, 69, 127-143.
2. Transporter Proteins as Antitarget for Drug Cardiotoxicity. Kowalska, M.; Nowaczyk, J.; Nowaczyk, A., KV11. 1, NaV1. 5, and CaV1. 2 International Journal of Molecular Sciences 2020, 21, (21), 8099.
3. Sabe, V. T., Ntombela, T., Jhamba, L. A., Maguire, G. E., Govender, T., Naicker, T., & Kruger, H. G. (2021). Current trends in computer aided drug design and a highlight of drugs discovered via computational techniques: A review. European Journal of Medicinal Chemistry, 224, 113705.

Additional information

Additional information (registration calendar, class conductors, localization and schedules of classes), might be available in the USOSweb system:

Description of 1700-OG-EN-CNSdrug in USOSweb