TY - BOOK ID - 138428834 TI - From a Molecule to a Drug: Chemical Features Enhancing Pharmacological Potential AU - Ribaudo, Giovanni AU - Orian, Laura PY - 2022 PB - Basel MDPI - Multidisciplinary Digital Publishing Institute DB - UniCat KW - SARS-CoV-2 KW - benzoic acid derivatives KW - gallic acid KW - molecular docking KW - reactivity parameters KW - selenoxide elimination KW - one-pot KW - imine-enamine KW - reaction mechanism KW - DFT calculations KW - selenium KW - anti-inflammatory drugs KW - QSAR KW - pain management KW - cyclooxygenase KW - multitarget drug KW - cannabinoid KW - neuropathic pain KW - clopidogrel KW - NMR study KW - oxone KW - peroxymonosulfate KW - sodium halide KW - thienopyridine KW - drug discovery KW - precision medicine KW - pharmacodynamics KW - pharmacokinetics KW - coronavirus SARS-CoV-2 KW - COVID-19 KW - 3-chymotrypsin-like protease KW - pyrimidonic pharmaceuticals KW - molecular dynamics simulations KW - binding free energy KW - β-carrageenan KW - antioxidant activity KW - Box-Behken KW - extraction KW - Eucheuma gelatinae KW - physic-chemistry KW - rheology KW - quercetin KW - quercetin 3-O-glucuronide KW - cisplatin KW - nephrotoxicity KW - cytoprotection KW - lithium therapy KW - neurocytology KW - toxicology KW - neuroprotection KW - chemoinformatics KW - big data KW - methadone hydrochloride KW - pharmaceutical solutions KW - drug compounding KW - high performance liquid chromatography KW - stability study KW - microbiology KW - fucoidan KW - alginate KW - L-selectin KW - E-selectin KW - MCP-1 KW - ICAM-1 KW - THP-1 macrophage KW - monocyte migration KW - protein binding KW - breast milk KW - M/P ratio KW - statistical modeling KW - molecular descriptors KW - chromatographic descriptors KW - affinity chromatography KW - anti-ACE KW - anti-DPP-IV KW - gastrointestinal digestion KW - in silico KW - molecular dynamics KW - paramyosin KW - seafood KW - target fishing KW - n/a UR - https://www.unicat.be/uniCat?func=search&query=sysid:138428834 AB - 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. ER -