Before Memmo my notes were scattered across PDFs. Now a workspace pulls everything into one place — I see exactly what's still left to study.
Up-to-date reference surveying the latest advances in the structural understanding of protein-protein interactions and developments in drug discovery and therapeutics
Targeting Protein–Protein Interactions for Drug Discovery provides a systematic and comprehensive overview of protein-protein interactions (PPIs), reviewing foundational concepts, advanced methodologies, and emerging therapeutic strategies, reflecting the multidisciplinary nature of PPI research.
This book discusses computational methods for predicting PPI structures, with a special emphasis on protein docking and deep learning-based approaches, diverse chemical scaffolds for PPI modulation, including foldamers as inhibitors of aberrant PPIs and sulfonyl-γ-AApeptides as novel modulators, and the development and application of stapled peptides as modulators of intracellular PPIs, offering enhanced stability, binding affinity, and cellular permeability.
Readers will also find information on cyclic peptides, focusing on their unique conformational stabilization and therapeutic potential across a range of diseases, small molecule inhibitors targeting BCL-family proteins, revealing their potential in cancer therapy, molecular glues as activators for PPIs, categorized into degraders, stabilizers, and inhibitors based on their biological effects, and the targeting of the APC–Asef interaction for drug discovery in colorectal cancer therapy, offering a case study of specificity and clinical relevance.
Targeting Protein–Protein Interactions for Drug Discovery explores sample topics including:
Exploring both classical and novel approaches to PPI characterization and modulation, Targeting Protein–Protein Interactions for Drug Discovery offers a comprehensive reference for researchers aiming to unlock the therapeutic potential of PPIs along with educators and students engaged in the study of cellular mechanisms, drug discovery, and biotechnology.
Before Memmo my notes were scattered across PDFs. Now a workspace pulls everything into one place — I see exactly what's still left to study.
Memmo's summaries are gold before exams. I don't have to re-read 800 pages two weeks before — just the important parts.
The AI chat has saved me the night before an exam more than once. I just keep asking until I get it — no waiting on a study group to reply.
The quizzes hit exactly what I need to know. Memmo tracks what I get stuck on — so I only practice what's worth it.
Flashcards with spaced repetition are magic. Memmo knows when I'm about to forget something and brings it back.
The AI podcasts are my favorite. I listen on my way to school and get a recap without sitting at a computer.
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