Download Computer-Aided Drug Design and Discovery
Computer-Aided Drug Design and Discovery udemy video course download Pioneering the Future of Pharmaceutical Innovation. marries cutting-edge technology with life sciences, equipping learners to revolutionize drug development. By seamlessly integrating computational techniques with pharmaceutical knowledge, we empower you to make groundbreaking contributions to healthcare and therapeutics.
Benefits of Learning: Embarking on our Computer-Aided Drug Design and Discovery program offers an array of benefits:
- Accelerated Drug Discovery: Master the art of predicting molecular interactions, significantly expediting drug discovery timelines.
- Cost and Time Efficiency: Save resources by optimizing the drug development process through computational analysis.
- Precision and Accuracy: Learn to design targeted therapeutic agents with exceptional precision and accuracy.
- Innovation at the Forefront: Be at the forefront of shaping the future of pharmaceuticals by amalgamating technology and science.
What you’ll learn
- Accelerated Drug Discovery: Master the art of predicting molecular interactions, significantly expediting drug discovery timelines.
- Cost and Time Efficiency: Save resources by optimizing the drug development process through computational analysis.
- Precision and Accuracy: Learn to design targeted therapeutic agents with exceptional precision and accuracy.
- Innovation at the Forefront: Be at the forefront of shaping the future of pharmaceuticals by amalgamating technology and science.
Course content:
- Section 1: Module 1
- Lecture 1 Introduction of Drugs Part 1
- Lecture 2 Introduction of Drugs Discovery Part 2
- Lecture 3 History of Computer Aided Drug Discovery Part 3
- Lecture 4 Disease Mechanisms Part 4
- Lecture 5 Drug Mechanisms Part 5
- Lecture 6 Properties of Drug Part 6
- Lecture 7 Structure Based Drug Design Part 7
- Lecture 8 Target Selection Part 8
- Lecture 9 Library Generation Part 9
- Lecture 10 Virtual Screeing Part 10
- Lecture 11 Docking Screeing Part 11
- Lecture 12 Types of Resources Used Part 12
- Lecture 13 Drug Market Part 13
- Section 2: Module 2
- Lecture 14 Molecular Structures Part 1
- Lecture 15 Represent Structure Part 2
- Lecture 16 Common Molecular File Formats Part 3
- Lecture 17 Common Operation on Structures Part 4
- Lecture 18 Principal Part 5
- Lecture 19 Create Structers on MarvinSketch Part 6
- Lecture 20 Create Structers on MarvinSketch Part 7
- Section 3: Module 3
- Lecture 21 Compound Libraries Part 1
- Lecture 22 Chemical Universe Part 2
- Lecture 23 Create Structers on MarvinSketch Part 3
- Lecture 24 Purpose Part 4
- Lecture 25 Types of Libeary Part 5
- Lecture 26 Fragment Libraries Part 6
- Lecture 27 Combinatorial Libraries Part 7
- Lecture 28 Reaction Based Enumeration Part 8
- Lecture 29 Virtual Library Design Workflow Part 9
- Lecture 30 PubChem Database Part 10
- Lecture 31 PubChem Database Part 11
- Lecture 32 PubChem Database Part 12
- Section 4: Module 4
- Lecture 33 Smilib v2.0 Software – Create Your Own Combinatorial Library Part 1
- Lecture 34 Virtual Screening Part 2
- Lecture 35 Drug Likeness – Lipinski’s Rule Part 3
- Lecture 36 Other Ways to Screen Compound Libraries Part 4
- Lecture 37 Drug Likeness Tool Part 5
- Lecture 38 ADME T Properties Part 6
- Lecture 39 Interplaay of Properties Part 7
- Lecture 40 SwissADME Software Part 8
- Section 5: Module 5
- Lecture 41 Premise Part 1
- Lecture 42 Drug Target Identification Part 2
- Lecture 43 Druggable Proteome Part 3
- Lecture 44 Swiss Target Prediction Part 4
- Lecture 45 Therapeutic Target Database Part 5
- Lecture 46 Therapeutic Target Database Part 6
- Lecture 47 Structural Bioinformalites Part 7
- Lecture 48 Biomolecular Structures Part 8
- Lecture 49 Why Protein Structure is Important Part 9
- Lecture 50 Level of Protein Structure Part 10
Course details
- Video quality: MP4 | Video: h264, 1280 × 720
- Audio quality: Audio: AAC, 44.1 KHz, 2 Ch
- Video duration: 6h 12m
- Number of lessons: 5 sections, 50 lectures
- Language: English
- Compressed file size: 3.3 GB
