STORICO - Classes & Lectures 2018-21

“THE CHEMISTRY OF CNS MODULATORS: VALIUM WITHOUT SEDATION” - DOTT. SAMUELE MARAMAI

Description

This cycle of lessons will be focused on the modulation of γ-aminobutyric acid type A receptors (GABA_ARs) via the small molecule-protein interaction on the benzodiazepine (BZDs) allosteric binding site. γ-Aminobutyric acid (GABA) is the major inhibitory neurotransmitter within the central nervous system and GABA_ARs are responsible for the point-to-point transfer of information across the synapse, but they are also located extrasynaptically, where they exert a more modulatory and tonic inhibitory effect. The so-called classical BZDs, such as Diazepam, are non-selective positive allosteric modulators of GABA_ARs that potentiate the effects of GABA through the different receptor subtypes with equivalent affinity and efficacy. Starting from this point, this course will explore the design, synthesis and clinical development of novel GABA_ARs subunit-selective agents which could be used in place of BZDs to treat anxiety disorders, cognitive disfunctions and other neurological disorders. In addition, a discussion on the use of organic chemistry to address in vivo-related issues will be given.

Schedule:

Mercoledì 6 Luglio 2022 - 16.00-18.00

Giovedì 7 Luglio 2022 - 16.00-18.00

Mercoledì 13 Luglio 2022 - 16.00-18.00

Giovedì 14 Luglio 2022 - 16.00-18.00

 

Aula virtuale del docente:

https://unisi.webex.com/meet/samuele.maramai

 

Potrebbe essere attivata la modalità mista (sia online che in presenza), ma verrà eventualmente comunicato in seguito

INTRODUCTION TO DIGITAL MATERIAL DISCOVERY - DOTT. ALESSANDRO LANDI

Detailed programme
Le informazioni aggiornate sulle lezioni sono pubblicate nella pagina relativa alla didattica 2022/2023 https://www.dbcf.unisi.it/it/didattica/post-laurea/dottorati-di-ricerca/...

Main topics covered:
1st lesson. The materials challenge. Why designing better materials is so hard. Organic materials and their applications in electronics: solar cells, light-emitting diodes, transistor. New materials for new applications: materials with mixed ionic-electronics transport. Charge transfer and other microscopic processes determine the final performances of the device. What we can learn from (i) experiments and (ii) theory and how can we link the two? Three non-mutually exclusive approaches.

2nd lesson. Development of physical models. From molecular structure to molecular properties: what models can we use? Analysis of thermodynamical and kinetical aspects. Marcus theory, Fermi Golden Rule, Quantum Dynamics, Transient Localization Theory: choosing the most appropriate models for a given physical process.

3rd lesson. High-throughput virtual screening. Analysis of big databases. Databases of existing compounds vs virtual databases, opportunities and limits of the two. Reducing the computational effort: multi-stage screening. Development of approximate models to further lower the computational time: balancing speed and accuracy.

4th lesson. When machines can replace humans. Correlating complex properties to molecular structure: Machine learning approach. Choosing the appropriate training dataset: possible errors with biased data. Advantages and limits of Machine Learning: identifying novel correlations and extrapolating properties for materials not belonging to the dataset. Going beyond: “digital” does not necessarily mean “purely virtual”. Flexible automation for self-driving laboratories: experiments performed by robots.

Contacts:

Dott. Alessandro Landi

 

Abstract
Organic materials have the potential to be employed as active components of electrical or optical devices, like organic light-emitting diodes (OLED), organic photovoltaic (OPV), and components of flexible electronic devices like conductive inks.
The premise for their use in all these fields is that organic materials can be fine-tuned with exquisite precision to have the desired electronic characteristics and the processing characteristics required for fabrication. Indeed, developments of new materials have led to molecules showing appealing features (e.g., thermally activated delayed fluorescence, singlet fission and up-conversion) and applicability into novel domains like organic bioelectronics, neuromorphic and quantum computing. Unfortunately, developments of new materials historically relied on slow trial-and-error chemical tuning, together with very extensive labour to understand their physical principles.
However, true innovative breakthroughs in organic electronic materials requires the availability of reliable models allowing fast and realistic prediction of the properties of interest, in order to guide the in-silico discovery of new materials. Recently, this “Digital Material Discovery” has gained increased attention, but its wide application is still hindered by the fact that many different methodologies can be used to address the same series of questions (what can be computed, how the results are validated against experiment, how a dataset of candidates to be screened can be generated and how the results can be interpreted or used), often leading to a non-optimal workflow for the analysis of the property of interest.
It is thus clear that a good knowledge of advantages and drawbacks of the main methods used in computer aided material science is required to take full advantages of the opportunities of Digital Material Discovery. With this goal in mind, in this course, we will briefly describe the three main pillars of this field, i.e. the development of physical models, high-throughput screening and machine learning, which far from being mutually exclusive, can be finely integrated to take the best of each.
The main points covered by the course are:
• Thermodynamics and kinetics in organic electronics: why both matter
• Less is more or more is less? How to choose the most appropriate physical model for each material class
• Evaluating charge carrier mobility in organic crystals: comparison of Marcus theory, Fermi Golden Rule, Transient Localization Theory
• High-throughput virtual screening: opportunities and challenges
• Accuracy and speed: a delicate balance leads to new methodologies
• Machine learning: the answer to everything or a black-box tool preventing real insights?

INNOVATIVE STRATEGIES FOR THE DEVELOPMENT OF NEW PHARMACOLOGICAL TOOLS - PROF. GABRIELE CARULLO

1. PROTACs in Medicinal Chemistry
1.1. PROTAC technology (First Lesson) – 16 Maggio 2022 ore 16.00 – 18.00
1.2. PROTAC technology: case studies (Second Lesson) – 18 Maggio 2022 ore 16.00 – 18.00

2. Green Chemistry approaches for the synthesis of bioactive compounds (Third Lesson) – 25 Maggio 2022 ore 16.00 – 18.00

3. Precision Medicine for Rare Diseases: Synthetic Lethality at a Glance (Fourth Lesson) – 30 Maggio 2022 ore 16.00 – 18.00

 

CONTATTI:

e-mail: gabriele.carullo@unisi.it

Webex room: https://unisi.webex.com/meet/gabriele.carullo

 Locandina del corso

STRUTTURA, FUNZIONE ED INTERAZIONI DI PROTEINE-STRUCTURE, FUNCTION AND INTERACTIONS OF PROTEINS - PROF.SSA CECILIA POZZI

Contenuti: Lo scopo del corso è di fornire nozioni avanzate su struttura, funzione ed interazioni di proteine negli organismi viventi. I principali argomenti trattati durante il corso sono: struttura proteica; enzimi e loro inibizione; metallo-proteine; sintesi proteica in procarioti ed eucarioti; interazioni proteina-proteina e proteina-DNA/RNA; struttura dei ribosomi; proteine di membrana.

Programma delle lezioni: Il corso si terrà indicativamente nel periodo maggio-giugno, secondo il calendario delle lezioni riportato di seguito.

Data	Orario	Aula
06/05/2022	14:30	15
12/05/2022	14:30	15
19/05/2022	14:30	15
26/05/2022	14:30	15
01/06/2022	14:30	16
09/06/2022	14:30	16
16/06/2022	14:30	16
23/06/2022	14:30	16

La pagina Moodle per il Corso è https://elearning.unisi.it/course/view.php?id=7997. Successivamente ad ogni lezione il materiale didattico verrà caricato nella pagina. I partecipanti al corso sono pregati di registrarsi nella pagina Moodle e riceveranno comunicazioni relative direttamente mediante la mailing list dei partecipanti.

 

Per partecipare al corso potete contattare direttamente il docente tramite email: cecilia.pozzi@unisi.it o pozzi4@unisi.it

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Contents: The main goal of the course is to provide advanced knowledge about structure, function and interactions of proteins in living organisms. The main topics of the course are: protein structure; enzymes and their inhibition; metallo-proteins; protein synthesis in prokaryotes and eukaryotes; protein-protein interactions and protein-DNA/RNA interactions; structures of ribosomes; membrane proteins.

Program of the lessons: the course will be held in the period May-June. The class schedule for the course is provided below.

Date	Time	Classroom
06/05/2022	14:30	15
12/05/2022	14:30	15
19/05/2022	14:30	15
26/05/2022	14:30	15
01/06/2022	14:30	16
09/06/2022	14:30	16
16/06/2022	14:30	16
23/06/2022	14:30	16

 

 

The Moodle page for the course is https://elearning.unisi.it/course/view.php?id=7997. After each lesson you will find the course material uploaded on the page. Participants to the course are kindly asked to register on the Moodle page so you will receive related communications directly through the participant mailing list.

 

To attend the course please contact directly the lecturer by email: cecilia.pozzi@unisi.it or pozzi4@unisi.it

 

 

DETERMINATION OF PROTEIN STRUCTURE AND DYNAMIC BY NMR SPECTROSCOPY

For further information, please contact: Prof.ssa Daniela Valensin

 

Nuclear NMR spectroscopy is widely used to determine structural and dynamic properties of proteins. In this course, the basic NMR approach used for structure calculation will be discussed. Both theoretical and practical aspects of 2D and 3D NMR spectra will be presented. The advantages and disadvantages of this technique will be considered as well.

POST HF METHODS: MULTICONFIGURATIONAL AND PERTURBATIVE METHODS

For further information, please contact: Prof. Luca De Vico

 

Course Content

The course will start a brief re-cap of the Hartree-Fock (HF) method, mostly to put all students on the same page and familiarize with a common way of expressing equations.
The pitfalls of HF will be illustrated, and consequently the possible solution offered by Multiconfigurational Self-Consistent Field (MC-SCF) methods will be introduced and described. Among MC-SCF methods, we will focus mostly on CASSCF and RASSCF methods. We will see how it is possible to use MC-SCF methods to describe not ground state, but also electronically excited states of molecular systems.
Finally, we will see how MC-SCF methods necessitate an ulterior refinement to be able to predict correctly electronic state energy differences, that is to simulate absorption spectra in the UV-VIS. Perturbative methods will be described, in particular CASPT2, MS-CASPT2 and XMS-CASPT2.
A brief hands-on experience will conclude the course. During these exercises the student will use their own laptop to access the Department computational resources and perform a series of calculations to employ and  compare the various techniques described during the course.

LIFE CYCLE ASSESSMENT: METHODOLOGY AND APPLICATION FOR ENERGY AND CHEMICAL PROCESSES

For further information, please contact: Prof.ssa Maria Laura Parisi

 

Course content

The course will illustrate the fundamental concepts concerning sustainability and the interaction of industrial and environmental systems. Focusing on the basic principles of the Life Cycle Assessment, the course will provide  insight of the methodological aspects underlying the implementation of an environmental footprint calculation of products and processes, also through practice exercises.
The course will take place in the second half of May 2020. The foreseen timetable would be organized with lessons twice a week, to be agreed upon with students.

STRUCTURE, FUNCTION AND INTERACTIONS OF PROTEINS

For further information, please contact Prof.ssa Cecilia Pozzi

 

Course content

The four levels in the protein structure. Post-translational modifications and their role.
Mechanisms of enzymatic reactions and mechanisms of inhibition. Metallo-proteins.
Structural and functional role of metals in metallo-enzymes. Protein synthesis in prokaryotes. Protein synthesis in eukaryotes.
Main features of protein-protein interactions (PPIs), functional and structural implications.
Main features of protein-DNA and protein-RNA interactions. Structures of ribosomes and functional mechanisms in protein synthesis. Main characteristics of membrane proteins, channels and receptors.

CHEMICAL SENSORS AND BIOSENSORS

The course will be held in the period march-june 2020.

For more information, please contact Dott. Marco Consumi

 

 

Course Content

Definitions, theoretical background, components of a sensing system.

Transducers: electrochemical, optical, thermal and mass transducers.

Receptor part: mechanism of chemical and biological recognition;

Sensor analytical performance;

Ion‐selective electrodes (ISEs);

Optical sensors and biosensors: techniques of optical detection, absorptiometry, UV‐visible absorption spectroscopy; reflectometry, luminescence spectroscopy, light scattering techniques, direct and indirect methods, indicator-based systems.

Mass and thermal sensors: piezo‐electric effect, surface acoustic waves, thermal sensors. Application of chemical sensors and biosensors: industrial processes, environmental and biomedical applications.

ANALYTICAL DETERMINATION OF NUTRACEUTICAL COMPONENTS IN FOOD MATRICES - DOTT.SSA GABRIELLA TAMASI

The course will be held from March 2020 and will last 24 hours.

For more information, please contact Dr Gabriella Tamasi

 

Course content:

The course aims to present an up-to-date overview on the forefront analytical methods for characterizing food matrices, particularly vegetables, as regards antioxidant and bioactive components. The first part will be dedicated to classify the main families of bioactive minor components in foods/vegetables (polyphenols, terpenoids, glycoalkaloids, lignans, …). Then, the main analytical techniques to identify and quantify the nutraceutical species will be investigated. Both targeted and untargeted approaches will be discussed. Statistic and chemiometric tools will be proposed to address cultivar and geographical characterizations. The course will also aim to explore new research challenges in food quality and safety control, valorization of production chain (from the fields to the market) and valorization of agricultural and agro-industrial by-products. Innovation in extraction protocols will be also investigated.