This book collects contributions published in the Special Issue "From a Molecule to a Drug: Chemical Features Enhancing Pharmacological Potential" and dealing with successful stories of drug improvement or design using classic protocols, quantum mechanical mechanistic investigation, or hybrid approaches such as QM/MM or QM/ML (machine learning). In the last two decades, computer-aided modeling has strongly supported scientists' intuition to design functional molecules. High-throughput screening protocols, mainly based on classical mechanics' atomistic potentials, are largely employed in biology and medicinal chemistry studies with the aim of simulating drug-likeness and bioactivity in terms of efficient binding to the target receptors. The advantages of this approach are quick outcomes, the possibility of repurposing commercially available drugs, consolidated protocols, and the availability of large databases. On the other hand, these studies do not intrinsically provide reactivity information, which requires quantum mechanical methodologies that are only applicable to significantly smaller and simplified systems at present. These latter studies focus on the drug itself, considering the chemical properties related to its structural features and motifs. Overall, such simulations provide necessary insights for a better understanding of the chemistry principles that rule the diseases at the molecular level, as well as possible mechanisms for restoring the physiological equilibrium.
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Hardcover. Zustand: Fine. 1st Edition. Hardcover, vii + 223 pages, NOT ex-library. Likely unread, book is clean and bright throughout with unmarked text, free of inscriptions and stamps, firmly bound. Issued without a dust jacket. -- This collection of scientific papers focuses on how specific chemical and structural features of a molecule can be optimized to improve its effectiveness as a medicine. Core Themes and Content -- The book explores the transition from a basic chemical compound to a viable drug candidate through various advanced methodologies: - Computer-Aided Molecular Design [it highlights how scientists use computational modeling, including Artificial Intelligence (AI) and machine learning, to predict how a molecule will interact with biological targets]; - Structure-Activity Relationships (SAR) [a primary focus is on rationalizing how changing a molecule's structure affects its biological response, solubility, and toxicity]; - Drug Repurposing [the text discusses strategies for finding new therapeutic uses for existing, approved drugs to reduce development time and costs]; - Quantum Mechanical (QM) Studies [it addresses the need for high-level simulations (like QM/MM or QM/ML) to understand the reactive chemistry of drugs, which simpler models often miss]. The volume includes research on a wide variety of substances, such as: - Natural Compounds [studies on antioxidants like carrageenan, polyphenols (kaempferol), and seafood-derived peptides]; - Synthetic Derivatives [the editors' own work on selenoderivatives of fluoxetine (Prozac) designed to enhance antioxidant capacity while maintaining antidepressant effects]; - Therapeutic Agents [investigations into lithium salts with reduced toxicity and the potential of fucoidan against atherosclerosis]. This book is intended for medicinal chemists, pharmacologists, and computational biologists looking for modern "success stories" in drug improvement and rational design. Bestandsnummer des Verkäufers 012707
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