Applied Chemistry to Drug Design

Code:

Q3021

Acronym:

Q3021

Level:

300

Keywords
Classification	Keyword
OFICIAL	Chemistry

Instance: 2023/2024 - 2S

Active?	Yes
Responsible unit:	Department of Chemistry and Biochemistry
Course/CS Responsible:	Bachelor in Chemistry

Cycles of Study/Courses

Acronym	No. of Students	Study Plan	Curricular Years	Credits UCN	Credits ECTS	Contact hours	Total Time
L:BQ	20	Official Study Plan	3	-	6	48	162
L:Q	34	study plan from 2016/17	3	-	6	48	162

Teaching language

Suitable for English-speaking students

Objectives

The student must develop a broad knowledge of the entire drug discovery and development pipeline, from identifying the target to the market entry, including economic and legal aspects and registration of patents.
Given a biological target, the student should also be able to identify a lead compound. To predict its binding pose and optimize computationally the energy of interaction between the two species when the target structure is known. Estimate the energetic contribution of the solvent in the receptor-ligand equilibrium and the role of hydrophobicity and flexibility. The student must know the requirements of a drug to have good absorption, distribution, metabolism, and excretion properties. In short, the student must have the capacity, on an autonomous basis, to make consistent and relevant proposals of ligands with good affinity for the target, with favorable pharmacokinetic properties, and with viability for commercial development.

Learning outcomes and competences

To choose a hit/lead compound from an extensive database; to predict its binding pose; to improve the affinity of the hit/lead compound; to predict and improve the pharmacokinetic properties of the hit/lead; to work with all intervenients in the drug discovery and development process.

Working method

Presencial

Pre-requirements (prior knowledge) and co-requirements (common knowledge)

Not applicable

Program

1. Introduction to Drug Design
1.1. What is a drug?
1.2. The origin of drugs.
1.3. Drug formulation, different formulations, and their strengths and weaknesses.
1.4. The multiple names of a drug: internal name, IUPAC name, generic name, and commercial name.
1.5. Drug likeliness. ADME-tox properties.

2. Drug Discovery and Development Pipeline.
2.1. Discovery and development pipeline and its segmentation into standard phases
2.2. Target identification. Importance and methodologies.
2.3. Pharmacophores and hit compounds. Methods to find hit compounds: serendipity, screening, and rational design.
2.4. Hit-to-Lead optimization. Combinatorial chemistry, parallel synthesis, and rational modification.
2.5. Measuring the biological activity. Sinergy between design and assays.
2.6. Pre-development and development. Clinical trials. Post-Comercial survey.
2.7. Scientific, technical, and economic reasons for drug discontinuation.
2.8. Marketing of a drug. Legal aspects.
2.9. Patents.

3. Absorption, Distribution, Metabolism, and Excretion
3.1. Pharmacokinetics and Pharmacodynamics. Relation with drug dose.
3.2. Bioavailability. The relation between bioavailability and the amount of drug available at the target site.
3.3. Transport Across Biological Membranes.
3.4. Absorption. Barriers to absorption. Molecular properties that modulate absorption.
3.5. Distribution. Molecular properties that influence the rate and extent of drug distribution.
3.6. Metabolism and excretion. Half-life of a drug.

4. Quantitative Structure-Activity Relationships (QSAR)
4.1. Introduction to QSAR.
4.2. Stages for building a QSAR model. Iterative nature of the derivation of the model.
4.3. Compound Selection. Property diversity, range of values for the descriptors, and range of activity of the selected compounds. Interpolation and extrapolation.
4.4. Identification and selection of the most relevant set of descriptors.
4.5. Correlation between descriptors.
4.6. Derivation of the mathematical model.
4.7. Complexity of the mathematical model and overfitting.
4.8. Evaluation of the fit and the statistical significance of the model.
4.9. Evaluation of the predictive capability of the model.

Practical Classes
1. The ABL-Tyrosine Kinase.
2. VMD visualisation PyMOL.
3. Virtual screening and molecular docking using the software HADDock and SwissDock.
4. Optimization of the energy of interaction of the selected hit compounds.
5. Prediction of bioavailability using the Lipinski and Veber rules.
6. Prediction of the toxicity of the hit compounds.
7. Writing of report.

Mandatory literature

Graham Patrick; An Introduction to Medicinal Chemistry, 2009

Teaching methods and learning activities

Classical lectures, centred in the professor, with smaller interventions from the students.

The laboratory classes will follow the problem-based learning paradigm, centred on the students, where the professor will help and guide the student through its search for knowledge, motivated by the necessity to solve the problem it has in hand.

Software

http://www.swissdock.ch/
https://pymol.org/2/
https://www.bonvinlab.org/software/haddock2.2/
http://www.swissadme.ch/
Osiris Property Explorer - http://www.organic-chemistry.org/prog/peo
Marvin Property Plugin - http://www.chemaxon.com/marvin/sketch/index.php

Evaluation Type

Distributed evaluation with final exam

Assessment Components

designation	Weight (%)
Exame	75,00
Participação presencial	25,00
Total:	100,00

Amount of time allocated to each course unit

designation	Time (hours)
Estudo autónomo	90,00
Frequência das aulas	48,00
Trabalho escrito	24,00
Total:	162,00

Eligibility for exams

The student must assist to 75% of the practical classes at least.

Calculation formula of final grade

The final classification will be the weighted average of the result of the theoretical exam (50%) and the practical classification (50%). The practical classification will be calculated as a weighted average of the continuous evaluation during the practical classes (25%) and the classification of an examination concerning the work developed during the semester in the practical classes (25%), to be done together with the lectures examination.
To be approved in the course, the student needs a minimum grade of 7 in the theoretical exam.

Classification improvement

The student can repeat the written examinations within the calendar and rules defined by the Conselho Pedagógico. The practical classification can not be improved.