What is he best known for?
The fields of study he is best known for:
- Organic chemistry
- Pharmacology
- Opioid
His primary areas of study are Pharmacology, Antagonist, Opioid, Opioid receptor and Stereochemistry.
His Pharmacology study combines topics from a wide range of disciplines, such as -Naloxone, Narcotic antagonist, Naltrexone and Opiate.
His work in the fields of Antagonist, such as Naltrindole, δ-opioid receptor and Competitive antagonist, overlaps with other areas such as Kappa.
His biological study spans a wide range of topics, including Endocrinology and Physical dependence.
When carried out as part of a general Opioid receptor research project, his work on Norbinaltorphimine is frequently linked to work in Bivalent, therefore connecting diverse disciplines of study.
His study in Stereochemistry is interdisciplinary in nature, drawing from both Structure–activity relationship, Opioid peptide and κ-opioid receptor.
His most cited work include:
- International Union of Pharmacology. XII. Classification of opioid receptors (617 citations)
- Naltrindole, a highly selective and potent non-peptide δ opioid receptor antagonist (519 citations)
- Binaltorphimine and nor-binaltorphimine, potent and selective k-opioid receptor antagonists (471 citations)
What are the main themes of his work throughout his whole career to date?
His scientific interests lie mostly in Stereochemistry, Pharmacology, Receptor, Opioid and Opioid receptor.
His research investigates the connection with Stereochemistry and areas like Opioid antagonist which intersect with concerns in Norbinaltorphimine.
His Pharmacology research includes elements of Agonist, -Naloxone, μ-opioid receptor and Antagonist.
He interconnects Ligand and In vivo in the investigation of issues within Receptor.
In his study, Enkephalin is strongly linked to Endocrinology, which falls under the umbrella field of Opioid.
His research integrates issues of Competitive antagonist, Affinity label, Narcotic antagonist and Receptor antagonist in his study of Opioid receptor.
He most often published in these fields:
- Stereochemistry (38.78%)
- Pharmacology (35.29%)
- Receptor (30.28%)
What were the highlights of his more recent work (between 2003-2021)?
- Pharmacology (35.29%)
- Agonist (22.22%)
- Opioid (30.07%)
In recent papers he was focusing on the following fields of study:
His main research concerns Pharmacology, Agonist, Opioid, Receptor and Opioid receptor.
His Pharmacology study focuses on Morphine in particular.
His studies in Agonist integrate themes in fields like Enzyme-linked receptor, Endocrinology, Receptor antagonist and Conditioned place preference.
His study looks at the relationship between Opioid and fields such as Antagonist, as well as how they intersect with chemical problems.
His Receptor research is multidisciplinary, incorporating perspectives in Pharmacophore, Stereochemistry and In vivo.
His Opioid receptor research integrates issues from Potency and δ-opioid receptor.
Between 2003 and 2021, his most popular works were:
- A heterodimer-selective agonist shows in vivo relevance of G protein-coupled receptor dimers (296 citations)
- Effects of κ-opioid receptor ligands on intracranial self-stimulation in rats (235 citations)
- Opioid-induced tolerance and dependence in mice is modulated by the distance between pharmacophores in a bivalent ligand series (221 citations)
In his most recent research, the most cited papers focused on:
- Organic chemistry
- Biochemistry
- Opioid
Opioid, Pharmacology, Agonist, Receptor and Opioid receptor are his primary areas of study.
His studies in Pharmacology integrate themes in fields like Oxymorphone and Oxycodone.
His Agonist research incorporates themes from Antagonist and Heteromer.
His Receptor course of study focuses on Structure–activity relationship and Cannabinoid, Drug tolerance and Cannabinoid receptor.
Philip S. Portoghese combines subjects such as G protein-coupled receptor, Stereochemistry, In vivo and Receptor antagonist with his study of Opioid receptor.
His Stereochemistry research incorporates elements of Opioid antagonist and Naltrexone.
This overview was generated by a machine learning system which analysed the scientist’s
body of work. If you have any feedback, you can
contact us
here.
