ECTS - University of Pisa
| Modules | Area | Type | Hours | Teacher(s) | |
| ADVANCED COMPUTER-AIDED DRUG DESIGN | CHIM/08 | LEZIONI | 58 |
|
Lo studente avrà acquisito conoscenze in merito alle tecniche avanzate di Computer-aided Drug Design.
The student will acquire knowledge about the computational chemistry applied to the Drug Discovery field.
La verifica delle conoscenze sarà oggetto della valutazione della tesina sperimentale che gli studenti porteranno a termine alla fine del corso.
The student will be assessed on his/her demonstrated ability to carry out a full computational research study.
Methods:
Lo studente saprà utilizzare il software di studi computazionali
The student who completes the course successfully will be able to demonstrate a solid knowledge of the advanced understanding of ligand-protein interactions. He/she will be familiar with a broad range of ligand- and structure-based computational methods and finally he/she will be able to perfom computational modeling tasks using state of the art software
Lo studente dovrà preparare e presentare una relazione scritta che riporti i risultati dello studio computazionale che porterà a termine.
The abilities acquired by student will be verified by means of the development of a small research study.
Lo studente potrà acquisire e/o sviluppare capacità di problem-solving e imparare ad utilizzare applicativi scientifici informatici
Durante le sessioni di laboratorio saranno valutati i risultati ottenuti dalle attività svolte
Chimica computazionale di base
Basis of computational chemistry. Furthermore, a good command of the English language is required, since lectures are given in English.
Delivery: face to face
Attendance: Mandatory
Learning activities:
Teaching methods:
AIM
The course aims at providing the students with understanding of computational modeling in the area of drug discovery. After finishing the course the students will have:
• Advanced understanding of ligand-protein interactions.
• Be familiar with a range of ligand and structure based computational methods.
• Performed computational modeling tasks using state of the art software.
DESCRIPTION
Although no single drug has been designed solely by computer techniques, the contribution of these methods to drug discovery is no longer a matter of dispute. Allthe world’s major pharmaceutical and biotechnology companies use computational design tools. Computer-aided drug design represents computational methods and resources that are used to facilitate the design and discovery of new therapeutic solutions. Digital repositories, containing detailed information on drugs and other useful compounds, are goldmines for the study of chemical reactions capabilities. Design libraries, with the potential to generate molecular variants in their entirety, allow the selectionand sampling of chemical compounds with diverse characteristics. Fold recognition, for studying sequence-structure homology between protein sequences and structures, are helpful for inferring binding sites and molecular functions. Virtual screening, the in-silico analog of high-throughput screening, offers great promise for systematic evaluation of huge chemical libraries to identify potential lead candidates that can be synthesized and tested. In this course the bases of the computer-aided drug design will be explored, and the lectures will be accompanied by laboratory exercises.
COURSE OUTLINE
a) Molecular dynamic simulations;
b) Pharmacophore-based drug desig;
c) QSAR, 3D-QSAR and in silico ADME studies
d) Artificial intelligence methods applied to the drug discovery field.
AIM
The course aims at providing the students with understanding of computational modeling in the area of drug discovery. After finishing the course the students will have:
• Advanced understanding of ligand-protein interactions.
• Be familiar with a range of ligand and structure based computational methods.
• Performed computational modeling tasks using state of the art software.
DESCRIPTION
Although no single drug has been designed solely by computer techniques, the contribution of these methods to drug discovery is no longer a matter of dispute. Allthe world’s major pharmaceutical and biotechnology companies use computational design tools. Computer-aided drug design represents computational methods and resources that are used to facilitate the design and discovery of new therapeutic solutions. Digital repositories, containing detailed information on drugs and other useful compounds, are goldmines for the study of chemical reactions capabilities. Design libraries, with the potential to generate molecular variants in their entirety, allow the selectionand sampling of chemical compounds with diverse characteristics. Fold recognition, for studying sequence-structure homology between protein sequences and structures, are helpful for inferring binding sites and molecular functions. Virtual screening, the in-silico analog of high-throughput screening, offers great promise for systematic evaluation of huge chemical libraries to identify potential lead candidates that can be synthesized and tested. In this course the bases of the computer-aided drug design will be explored, and the lectures will be accompanied by laboratory exercises.
COURSE OUTLINE
a) Molecular dynamic simulations;
b) Pharmacophore-based drug desig;
c) QSAR, 3D-QSAR and in silico ADME studies
d) Artificial intelligence methods applied to the drug discovery field.
Non viene consigliato alcun testo, ma il materiale necessario verrà reso disponibile durante lo svolgimento del modulo
There are not recommended readings. The teacher will supply the material during the lessons.
Valutazione di una Tesina
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