Concept

Quantitative structure–activity relationship

Related lectures (18)
Interrogating SAR in Medical Chemistry
Delves into the fundamentals of medicinal chemistry, emphasizing the interrogation of Structure-Activity Relationships (SAR) in drug design.
Identifying Drug Targets: Safety and Efficacy
Delves into identifying drug targets, ensuring efficacy, and maintaining safety in medical chemistry, covering genetic tests, chirality, stereochemistry, drug resistance, and drug-likeness rules.
Fragment-Based Drug Discovery: Concepts & Technologies
Covers the concepts and technologies of fragment-based drug discovery, exploring hit identification, lead optimization, and screening methods.
Interrogating SAR: Medicinal Chemistry
Covers medicinal chemistry basics, high-throughput screening, lead discovery milestones, and compound selectivity in drug optimization.
Identifying Correct Target in Medical Chemistry
Explores target identification, efficacy, and safety in medical chemistry, emphasizing the importance of on-target specificity and drug design.
Deep Generative Models in Drug Discovery
Explores the application of deep generative models in drug discovery, focusing on designing small molecules and optimizing molecular structures.
Fragment-Based Drug Discovery: Concepts & Technologies
Covers the concepts and technologies of fragment-based drug discovery, hit identification methods, and its application in target-based drug discovery.
Systems Biology of Metabolism
Explores Systems Biology, metabolic pathways, genome-scale models, and bioinformatic tools for predictive biochemistry in bioproduction.
The Cosmic Distance Ladder
Explores the Variable Universe through the Cosmic Distance Ladder, focusing on standard candles and the Hubble constant tension.
X-rays: From Discovery to Applications
Explores the historical perspective, properties, and applications of X-rays, including diffraction, atomic resolution, and spectral colors of elements.

Graph Chatbot

Chat with Graph Search

Ask any question about EPFL courses, lectures, exercises, research, news, etc. or try the example questions below.

DISCLAIMER: The Graph Chatbot is not programmed to provide explicit or categorical answers to your questions. Rather, it transforms your questions into API requests that are distributed across the various IT services officially administered by EPFL. Its purpose is solely to collect and recommend relevant references to content that you can explore to help you answer your questions.