Unit CHEMOINFORMATICS

Course
Chemical sciences
Study-unit Code
55062305
Curriculum
In all curricula
Teacher
Gabriele Cruciani
Teachers
  • Gabriele Cruciani
  • Laura Goracci (Codocenza)
Hours
  • 14 ore - Gabriele Cruciani
  • 48 ore (Codocenza) - Laura Goracci
CFU
6
Course Regulation
Coorte 2021
Offered
2022/23
Learning activities
Affine/integrativa
Area
Attività formative affini o integrative
Academic discipline
CHIM/06
Type of study-unit
Opzionale (Optional)
Type of learning activities
Attività formativa monodisciplinare
Language of instruction
Italian
Contents
The aim is to provide a general framework for the definition of chemioinformatics and its applications in the chemical, biological, analytical and pharmaceutical fields. In the frontal lessons, basic knowledge of organic chemistry, computational and analytical chemistry are needed while in the laboratory hours one will ask the student to apply the knowledge to actual and very current problems.
Reference texts
Material provided by teacher
Educational objectives
The course will show the relevance of chemioinformatics in chemical research. Although chemioinformatics methods are mainly applied in the chemical-pharmaceutical field, the student will be sensitized to the possibility of applying such methodologies to various fields of chemistry.
The course should allow the student to acquire the following basic knowledge:
Know the definition of chemioinformatics and its historical evolution;
Understand the importance of chemioinformatics in various chemical research fields, with particular attention to drug discovery procedures.
Know the economic aspects of chemioinformatics, which allows to reduce the cost of the survey.
Know the basics of chemioinformatics.
Know the basics of drug metabolism and the methods associated with that research field.
Know chemioinformatics methodologies to be applied to the study of drug human metabolism.
Understand the basic principles of designing drugs and classical methods associated with this field of research.
Know chemioinformatics methodologies to be applied to drug design.
Understand the basic principles of lipidomics and classical methods associated with this field of research.
Know chemioinformatics methodologies to apply to lipidomics.
Understand the basic principles of the analysis of food and classical methods associated with this field of research.
Know chemioinformatics methodologies to be applied in the field of food chemistry.

The main skills (ie the ability to apply the acquired knowledge) will be:
To be able to understand the potential field of application of chemioinformatics.
Being able to use automated sample preparation tools (EpMotion, Heppendorf)
Being able to conduct biocatalysis experiments to study the metabolism of P450 cytochrome drugs.
To be able to apply chemioinformatics procedures for the analysis of enzymatic biocatalysis data.
Be able to carry out MSMS fragmentation studies to identify drug metabolites
Be able to apply chemioinformatics procedures for drug design and for virtual screening methods
To be able to apply methods for the extraction of lipids
To be able to apply chemioinformatics procedures for lipidomic data analysis
Be able to carry out multivariate statistical analysis studies on experimental data.
Prerequisites
It is required the knowledge of the elements of molecular design and organic chemistry.
Teaching methods
The course is organized with theoretical frontal lessons and practical experience in the lab, to facilitate the student in learning chemioinformatics.
In the front lessons of 2 hours each, held in the classroom, the basic principles of chemioinformatics will be illustrated. In addition, chemical, analytical and pharmaceutical issues will also be introduced, which will then be studied by students in practical sessions.
In practical activities, students will be required to implement the chemoinformatics tools described in frontal lessons. In particular, given a problem, they will have to do bibliographic research to acquire all the elements necessary to select and evaluate the best chemioinformatics tools, they will have to apply these tools to the best of their possibilities under the supervision of the teacher and will then describe in written reports particular successes and criticality of the chemioinformatics used.
Theoretical lessons are highly recommended, while lessons for laboratory activities are compulsory.
Other information
contacts

Gabriele Cruciani:
email: gabriele.cruciani@unipg.it
phone: (+39) 0755855629

Laura Goracci:
email: laura.goracci@unipg.it
phone: (+39) 0755855632
Learning verification modality
The final test includes the evaluation of written reports on laboratory activities and an oral test. The written reports must contain a brief explanation of the experimental problem addressed, a discussion on the experimental techniques used and a final part that shows the conclusions obtained experimentally. The oral exam will involve the formulation of 3-4 questions over a period of 30-40 minutes. The test is aimed at ascertaining the student's ability to use the tools he has acquired in the course and to connect the acquired knowledge to solve practical problems.
The overall assessment of the exam will take into account the following aspects: correctness and adequacy of responses, processing skills and conceptual connection, mastery and language skills, according to the following percentages: 60%, 30%, 10%.

For info on facilities for special needs students visit: https://www.unipg.it/en/international-students/general-information/facilities-for-special-needs-students
Extended program
The course provides theoretical frontal lessons and practical experience in the lab, so as to facilitate the student in learning chemioinformatics.
Definition of Chemioinformatica. History of Chemioinformatics. Comparison between classical methodologies and chemioinformatics methodologies.
Chemioinformatics applied to metabolic studies. Introduction to drug metabolism studies in drug discovery. Classical experimental methods for the study of metabolism. Matrices for in vitro metabolism study. Criticism of classical methodologies in high-throughput approaches.
Chemioinformatics solutions for metabolism studies in drug discovery.
Chemioinformatics applied to drug design. Introduction to drug design in drug discovery. Classic Methodologies for Identifying Drug Applicants. Criticism of classical methodologies in high-throughput approaches. Chemioinformatics solutions for molecular design.
Chemioinformatics applied to lipidomics. Introduction to lipidomics. Classical experimental methods for targeted and untargeted lipidomics. Criticism of classical methodologies of lipid identification in high-throughput approaches. Chemioinformatics solutions for lipidomics.
Chemioinformatics applied to food chemistry analysis. Survey on a specific food product. Identification of issues associated with the safety and potential contamination of the product concerned. Treatment of experimental data with chemioinformatics approaches for the analysis of the food product being investigated.
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