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Introduction To Cheminformatics And Medicinal Chemistry

Posted By: ELK1nG
Introduction To Cheminformatics And Medicinal Chemistry

Introduction To Cheminformatics And Medicinal Chemistry
Last updated 7/2022
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz
Language: English | Size: 1.44 GB | Duration: 2h 52m

Understand the underlying chemistry of drug development and use free softwares to analyze molecules

What you'll learn
Units to describe biological activity
An overview of drug discovery
An introduction to cheminformatics
The SMILES representation of chemical structures
Small molecule databases
Physical chemical features that may influence oral bioavailability of drugs
Softwares to analyze physical chemical features of compounds
Strategies to change the structure of bioactive compounds
Requirements
Very basic knowledge of chemistry and biology
Description
Hi! In this course, I'm going to introduce some concepts and tools of Medicinal Chemistry and Cheminformatics! Cheminformatics can be understood as an interdisciplinary field. It encompasses the theoretical knowledge of chemistry and the application of informatics. This area is applied in several fields, such as drug development, environmental science, and material science. In this course, we are going to focus on the part of cheminformatics applied to drug discovery. In this introductory course, you'll gain knowledge of chemical databases, drawing of molecular structures, and softwares to analyze physicochemical and structural features of molecules to predict their pharmacokinetic properties, bioactivity, or safety profile.Medicinal chemistry, on the other hand, is an area where chemistry and pharmacology intersect, and it is directly involved in the process of rational drug development. Its main difference from the traditional drug discovery process is the emphasis on the chemical properties and structure of the chemical compounds investigated to generate possible insights into their biological activities. Medicinal chemistry, therefore, provides the rationale for choosing molecules, deducing their possible pharmacokinetic properties, such as plasma concentration, or biological activity, based on their functional groups, molecular weight, cLogP, etc. You may like this course if you are interested in…Understanding how molecules can be represented in a linear format fileKnowing how to use chemical databasesKnowing about physicochemical features that may help to predict oral availability of drug candidatesUsing free softwares to analyze the structure of molecules to predict physicochemical featuresUsing free softwares to analyze the structure of molecules to predict biological activityKnowing how proteins are relevant to the process of drug discoveryContributing to the field of biochemistry and protein design by playing Foldit

Overview

Section 1: Introduction

Lecture 1 Course overview

Lecture 2 Cheminformatics and medicinal chemistry

Lecture 3 Units of biological activity

Lecture 4 The representation of molecular structures as SMILES

Section 2: Chemical databases

Lecture 5 Chemical databases: an overview

Lecture 6 PUBCHEM

Lecture 7 PUBCHEM Sketcher

Lecture 8 ZINC database

Lecture 9 CHEMspider

Lecture 10 Exercise

Section 3: ADMET concepts

Lecture 11 Intro to ADME concepts

Lecture 12 Physico-chemical descriptors of bioavailability

Lecture 13 Software of analysis: Molinspiration

Lecture 14 Software of analysis: SwissADMET

Lecture 15 Software of analysis: Pro-Tox-II

Lecture 16 Exercise

Section 4: Structure and biological activity

Lecture 17 Introduction to the section

Lecture 18 Combinatorial library

Lecture 19 Fragment based approach

Lecture 20 Peptidomimetics

Lecture 21 Biososterism

Lecture 22 Software of analysis: SwissBioisostere

Section 5: Studies with proteins

Lecture 23 Introduction to proteins

Lecture 24 PDB database: part 1

Lecture 25 PDB database: part 2

Lecture 26 Molecular docking studies

Lecture 27 Molecular docking with SwissDock

Lecture 28 Introduction fo Foldit: part 1

Lecture 29 Introduction fo Foldit: part 2

Lecture 30 Exercise

Section 6: Bonus section

Lecture 31 Bonus lecture

Lecture 32 Artificial intelligence in drug discovery

Students of biology,Students of chemistry,Students of pharmacy,Students of biotechnology,Professionals of the above areas,Professionals or students of related areas