What is he best known for?
The fields of study he is best known for:
Ruben Abagyan mostly deals with Docking, Biochemistry, Computational biology, Protein structure and Receptor.
The concepts of his Docking study are interwoven with issues in Binding site and Ligand.
When carried out as part of a general Biochemistry research project, his work on G protein-coupled receptor, Chemokine receptor, Peptide sequence and Fungal protein is frequently linked to work in Lanosterol, therefore connecting diverse disciplines of study.
His Computational biology research incorporates themes from DOCK, Allosteric regulation and Bioinformatics.
His work deals with themes such as PTX3, Serum amyloid P component, Acute-phase protein, Protein–protein interaction and Innate immune system, which intersect with Protein structure.
His studies in Receptor integrate themes in fields like Immunohistochemistry, Plasma protein binding, Pharmacology, Cell biology and Mutagenesis.
His most cited work include:
- METLIN: a metabolite mass spectral database. (1436 citations)
- Structures of the CXCR4 chemokine GPCR with small-molecule and cyclic peptide antagonists. (1391 citations)
- ICM—a new method for protein modeling and design: applications to docking and structure prediction from the distorted native conformation (1241 citations)
What are the main themes of his work throughout his whole career to date?
The scientist’s investigation covers issues in Docking, Biochemistry, Protein structure, Computational biology and Stereochemistry.
The Docking study combines topics in areas such as Homology modeling and Binding site.
Biochemistry and Biophysics are frequently intertwined in his study.
The Protein structure study which covers Crystallography that intersects with Side chain.
His Computational biology study incorporates themes from Small molecule and Bioinformatics, Drug discovery.
He interconnects Pharmacology and Cell biology in the investigation of issues within Receptor.
He most often published in these fields:
- Docking (24.76%)
- Biochemistry (20.63%)
- Protein structure (14.56%)
What were the highlights of his more recent work (between 2015-2021)?
- Biochemistry (20.63%)
- Docking (24.76%)
- Computational biology (14.81%)
In recent papers he was focusing on the following fields of study:
His primary areas of study are Biochemistry, Docking, Computational biology, Drug and Receptor.
As part of his studies on Biochemistry, Ruben Abagyan often connects relevant subjects like Bacteria.
His Docking study is related to the wider topic of Stereochemistry.
Ruben Abagyan has included themes like G protein-coupled receptor, Bioinformatics, Drug discovery, Orphan receptor and Binding site in his Computational biology study.
His Binding site study combines topics from a wide range of disciplines, such as Protein structure and Sequence alignment.
His Receptor study combines topics in areas such as Small molecule and Cell biology.
Between 2015 and 2021, his most popular works were:
- Structure of CC chemokine receptor 2 with orthosteric and allosteric antagonists (142 citations)
- Structure of CC Chemokine Receptor 5 with a Potent Chemokine Antagonist Reveals Mechanisms of Chemokine Recognition and Molecular Mimicry by HIV. (85 citations)
- An electrostatic mechanism for Ca(2+)-mediated regulation of gap junction channels. (80 citations)
In his most recent research, the most cited papers focused on:
His main research concerns Stereochemistry, Computational biology, Receptor, Biochemistry and Transporter.
Specifically, his work in Stereochemistry is concerned with the study of Docking.
His study in the field of Protein–ligand docking and Lead Finder also crosses realms of Template, Serotonin 1A Receptor and 5-HT1A receptor.
His Computational biology research incorporates themes from RNA, Transcription factor, Sequence alignment and Bioinformatics.
The concepts of his Receptor study are interwoven with issues in Pharmacology and Cell biology.
His Searching the conformational space for docking and Molecular Docking Simulation study in the realm of Protein structure connects with subjects such as Static electricity.
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