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PROGETTAZIONE E SVILUPPO DEL FARMACO
Module MODULO 1 CHIMICA FARMACEUTICA

Academic Year 2026/2027 - Teacher: SALVATORE GUCCIONE

Expected Learning Outcomes

The course aims to introduce students to the main molecular modelling techniques applied to rational drug design, with particular emphasis on the methods employed, their theoretical foundations, and their respective fields of application.
Students will acquire a basic understanding of the main computational methods available and their theoretical foundations, of the molecular properties that can be calculated and their associated level of accuracy, as well as of the criteria for selecting the most appropriate approach depending on the molecular system and the property or scientific problem under investigation.
The course will cover both ligand-based and structure-based approaches to drug design. Within the ligand-based approaches, the concepts of structure–activity and structure–property relationships will be introduced, together with the quantitative characterization of molecules through molecular descriptors and their application to the study and prediction of physicochemical and biological properties. Structural and topological, electronic, steric, and lipophilic descriptors will be considered, together with properties such as molecular mass and volume, polar surface area, lipophilicity, hydrogen-bonding capacity, charge, conformational flexibility, and other properties relevant to biological activity and the pharmacokinetic characteristics of compounds. The concepts of molecular similarity, molecular fingerprints, and quantitative structure–activity relationship (QSAR) models will also be introduced.
Particular attention will be devoted to structure-based approaches, which rely on knowledge of the three-dimensional structure of the biological target. The principles of molecular structure and recognition, ligand–receptor interactions, and binding-site analysis will be presented. The main methodologies used in structure-based drug design will be introduced, with particular emphasis on molecular docking, including its theoretical foundations, protein and ligand preparation, binding-pose generation, scoring functions, and critical evaluation of the results. The basic principles of molecular dynamics will also be briefly introduced as a tool for studying protein and ligand–receptor complex flexibility and conformational evolution, as well as for analysing the stability of molecular interactions. The limitations and main sources of error associated with docking and molecular dynamics procedures will be highlighted, together with the importance of validating computational protocols.
Specific molecular modelling software and computational tools will be presented through practical examples and case studies related to the design and optimization of bioactive compounds. The successes, potential applications, and limitations of the different computational approaches will be discussed, highlighting the importance of selecting appropriate methods, descriptors, and molecular models according to the scientific question and the system under investigation.
Knowledge and understanding:
Students will acquire basic knowledge of the main computational approaches to molecular modelling and rational drug design, understanding their theoretical foundations, main applications, and limitations. Molecular descriptors, ligand-based and structure-based approaches, molecular docking, and the principles of molecular dynamics will be addressed.
Applying knowledge and understanding:
Students will be able to apply the main molecular modelling methods to the characterization and analysis of molecular systems, selecting appropriate approaches and descriptors according to the property or scientific problem under investigation, and critically interpreting the results obtained using computational tools.

Course Structure

Frontal Lessons.

Lectures, with attendance requirements (70%) in accordance with the Academic Regulations (R.D.A.).

According to  "Regolamento Didattico di Ateneo (R.D.A.) i.e. University Didactic Regulations attendance of  lessons   is mandatory.

Attending the supplementary seminars that are organized  is also strongly recommended.

Should teaching be carried out in mixed mode or remotely, it may be necessary to introduce changes with respect to previous statements, in line with the programme planned and outlined in the syllabus.

Information for students with disabilities and/or Specific Learning Disorders (SLD):

To ensure equal opportunities and in compliance with current legislation, students concerned may request an individual meeting with the instructor in order to discuss and arrange any appropriate compensatory and/or exemption measures, taking into account the learning objectives and the student’s specific needs.

Students may also contact the departmental CInAP (Centro per l’Integrazione Attiva e Partecipata – Services for Students with Disabilities and/or Specific Learning Disorders) faculty contact person, Prof. Santina Chiechio, at santina.chiechio@unict.it.

Required Prerequisites

Organic Chemistry, Biochemistry

Attendance of Lessons

Frontal Lessons.

According to  "Regolamento Didattico di Ateneo (R.D.A.) i.e. University Didactic Regulations attendance of  lessons   is mandatory.

Should teaching be carried out in mixed mode or remotely, it may be necessary to introduce changes with respect to previous statements, in line with the programme planned and outlined in the syllabus.

Learning assessment may also be carried out on line, should the conditions require it.


Detailed Course Content

Specific Contents

•     Process of action of drugs. Pharmacodynamics: molecular targets: interactions between bio-active molecules and drug targets. Pharmacokinetics: adsorption, distribution, metabolism, elimination.

•     Introduction to basic principles of protein-ligand interactions and a number of concepts in modern drug discovery.

•     Rational drug design and introduction to computational methods.

•     Conformational analysis: Geometry optimization and Energy Minimization methods. Quantum- and Molecular-mechanics methods (Force Field).

•     Commercial(Cambridge Structural Database: CSD) and non-profit (Protein Brookaven Databank: PDB) crystallographic databases.

•     Structure based methods, binding site analysis, dock¬ing, scoring functions and virtual screening.

•     Application of docking techniques to the prediction of drug-target interactions.

•     MIF methods : GRID, CoMFA.

•     Ligand based design approaches including “traditional” (2D) QSAR (QSPR), 3D-QSAR (CoMFA, HASL) , Pharmacophore modelling.

•     Introduction to chemioinformatics and Drug Development.

•     Chemical and Drug Databases.

•     Property calculations and property filtering.

•     Molecular Similarity.

•     Prediction of ADME (Administration-Distribution-Metabolism-Excretion) and  toxicity of Drug molecule.

•     Structural Bioinformatics in Drug Development (Protein Homology modeling).

•     Molecular Dynamics.

 TEXTBOOKS AND OTHER RESOURCES

Due to the cutting edge nature of this course and the rapid advances made in the field , a single primary text which adequately covers the content of this  course has not been identified.  Therefore each lecturer will provide the student with additional resources to supplement their lecture material. These resources will take the form of text  books, journal articles (if available links to the electronic form of  these resources will be provided) or web based resources. 

Textbook Information

Class Notes; Chemometry booklet;  useful readings suggested from the teacher.



Course Planning

 SubjectsText References
1See Course Programme.Principles of molecular modelling and computer-aided drug design; molecular descriptors and ligand-based approaches, structure–activity relationships (SAR), QSAR and molecular similarity.Structure-based approaches: molecular recognition, ligand–target interactions, molecular docking and scoring functions; introduction to the principles of molecular dynamics and their applications in drug design.Lesson Notes and Booklets/Articles provided by the Professor.

Learning Assessment

Learning Assessment Procedures

Assessment: written examination consisting of 5 questions, with a duration of 80 minutes.

Assessment criteria:

  • 18–23/30: at least 3 out of 5 questions correctly answered, based on the accuracy, completeness and relevance of the responses;
  • 24–27/30: 4 out of 5 questions correctly answered, based on the accuracy, completeness and relevance of the responses;
  • 28–30/30: all 5 questions correctly answered, based on the accuracy, completeness and relevance of the responses.

The assessment of learning outcomes may also be conducted remotely, should circumstances require it.


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