3 research outputs found
Discovery of Potent and Selective CB2 Agonists Utilizing a Function-Based Computational Screening Protocol
Nowadays, the identification of agonists and antagonists
represents
a great challenge in computer-aided drug design. In this work, we
developed a computational protocol enabling us to design/screen novel
chemicals that are likely to serve as selective CB2 agonists. The
principle of this protocol is that by calculating the ligand–residue
interaction profile (LRIP) of a ligand binding to a specific target,
the agonist–antagonist function of a compound is then able
to be determined after statistical analysis and free energy calculations.
This computational protocol was successfully applied in CB2 agonist
development starting from a lead compound, and a success rate of 70%
was achieved. The functions of the synthesized derivatives were determined
by in vitro functional assays. Moreover, the identified potent CB2
agonists and antagonists strongly interact with the key residues identified
using the already known potent CB2 agonists/antagonists. The analysis
of the interaction profile of compound 6, a potent agonist,
showed strong interactions with F2.61, I186, and F2.64, while compound 39, a potent antagonist, showed strong interactions with L17,
W6.48, V6.51, and C7.42. Still, some residues including V3.32, T3.33,
S7.39, F183, W5.43, and I3.29 are hotspots for both CB2 agonists and
antagonists. More significantly, we identified three hotspot residues
in the loop, including I186 for agonists, L17 for antagonists, and
F183 for both. These hotspot residues are typically not considered
in CB1/CB2 rational ligand design. In conclusion, LRIP is a useful
concept in rationally designing a compound to possess a certain function
Discovery of Potent and Selective CB2 Agonists Utilizing a Function-Based Computational Screening Protocol
Nowadays, the identification of agonists and antagonists
represents
a great challenge in computer-aided drug design. In this work, we
developed a computational protocol enabling us to design/screen novel
chemicals that are likely to serve as selective CB2 agonists. The
principle of this protocol is that by calculating the ligand–residue
interaction profile (LRIP) of a ligand binding to a specific target,
the agonist–antagonist function of a compound is then able
to be determined after statistical analysis and free energy calculations.
This computational protocol was successfully applied in CB2 agonist
development starting from a lead compound, and a success rate of 70%
was achieved. The functions of the synthesized derivatives were determined
by in vitro functional assays. Moreover, the identified potent CB2
agonists and antagonists strongly interact with the key residues identified
using the already known potent CB2 agonists/antagonists. The analysis
of the interaction profile of compound 6, a potent agonist,
showed strong interactions with F2.61, I186, and F2.64, while compound 39, a potent antagonist, showed strong interactions with L17,
W6.48, V6.51, and C7.42. Still, some residues including V3.32, T3.33,
S7.39, F183, W5.43, and I3.29 are hotspots for both CB2 agonists and
antagonists. More significantly, we identified three hotspot residues
in the loop, including I186 for agonists, L17 for antagonists, and
F183 for both. These hotspot residues are typically not considered
in CB1/CB2 rational ligand design. In conclusion, LRIP is a useful
concept in rationally designing a compound to possess a certain function
Photoredox-Catalyzed Redox-Neutral Decarboxylative C–H Acylations of Coumarins with α‑Keto Acid
A novel and green photocatalytic strategy for the synthesis
of
C-4-acylated coumarins with α-keto acids and 3-nitrocoumarin
has been developed. This operationally simple protocol works under
mild reaction conditions, providing convenient access to 4-acyl coumarin
derivatives. The control experimental results showed that the nitro
radical produced by the cleavage of the C–N bond acts as an
electron acceptor to complete the photocatalytic cycle, achieving
a redox-neutral reaction