10 research outputs found
Supervised Molecular Dynamics (SuMD) as a Helpful Tool To Depict GPCR–Ligand Recognition Pathway in a Nanosecond Time Scale
Supervised MD (SuMD) is a computational
method that allows the
exploration of ligand–receptor recognition pathway investigations
in a nanosecond (ns) time scale.
It consists of the incorporation of a tabu-like supervision algorithm
on the ligand–receptor approaching distance into a classic
molecular dynamics (MD) simulation
technique. In addition to speeding up the acquisition of the ligand–receptor
trajectory, this implementation facilitates the characterization
of multiple binding events (such as meta-binding, allosteric, and
orthosteric sites) by taking advantage of the all-atom MD simulations
accuracy of a GPCR–ligand complex embedded into explicit lipid–water
environment
Supervised Molecular Dynamics (SuMD) as a Helpful Tool To Depict GPCR–Ligand Recognition Pathway in a Nanosecond Time Scale
Supervised MD (SuMD) is a computational
method that allows the
exploration of ligand–receptor recognition pathway investigations
in a nanosecond (ns) time scale.
It consists of the incorporation of a tabu-like supervision algorithm
on the ligand–receptor approaching distance into a classic
molecular dynamics (MD) simulation
technique. In addition to speeding up the acquisition of the ligand–receptor
trajectory, this implementation facilitates the characterization
of multiple binding events (such as meta-binding, allosteric, and
orthosteric sites) by taking advantage of the all-atom MD simulations
accuracy of a GPCR–ligand complex embedded into explicit lipid–water
environment
Supervised Molecular Dynamics (SuMD) as a Helpful Tool To Depict GPCR–Ligand Recognition Pathway in a Nanosecond Time Scale
Supervised MD (SuMD) is a computational
method that allows the
exploration of ligand–receptor recognition pathway investigations
in a nanosecond (ns) time scale.
It consists of the incorporation of a tabu-like supervision algorithm
on the ligand–receptor approaching distance into a classic
molecular dynamics (MD) simulation
technique. In addition to speeding up the acquisition of the ligand–receptor
trajectory, this implementation facilitates the characterization
of multiple binding events (such as meta-binding, allosteric, and
orthosteric sites) by taking advantage of the all-atom MD simulations
accuracy of a GPCR–ligand complex embedded into explicit lipid–water
environment
Supervised Molecular Dynamics (SuMD) as a Helpful Tool To Depict GPCR–Ligand Recognition Pathway in a Nanosecond Time Scale
Supervised MD (SuMD) is a computational
method that allows the
exploration of ligand–receptor recognition pathway investigations
in a nanosecond (ns) time scale.
It consists of the incorporation of a tabu-like supervision algorithm
on the ligand–receptor approaching distance into a classic
molecular dynamics (MD) simulation
technique. In addition to speeding up the acquisition of the ligand–receptor
trajectory, this implementation facilitates the characterization
of multiple binding events (such as meta-binding, allosteric, and
orthosteric sites) by taking advantage of the all-atom MD simulations
accuracy of a GPCR–ligand complex embedded into explicit lipid–water
environment
Perturbation of Fluid Dynamics Properties of Water Molecules during G Protein-Coupled Receptor–Ligand Recognition: The Human A<sub>2A</sub> Adenosine Receptor as a Key Study
Recent
advances in structural biology revealed that water molecules
play a crucial structural role in the protein architecture and ligand
binding of G protein-coupled receptors. In this work, we present an
alternative approach to monitor the time-dependent organization of
water molecules during the final stage of the ligand–receptor
recognition process by means of membrane molecular dynamics simulations.
We inspect the variation of fluid dynamics properties of water molecules
upon ligand binding with the aim to correlate the results with the
binding affinities. The outcomes of this analysis are transferred
into a bidimensional graph called water fluid dynamics maps, that
allow a fast graphical identification of protein “hot-spots”
characterized by peculiar shape and electrostatic properties that
can play a critical role in ligand binding. We hopefully believe that
the proposed approach might represent a valuable tool for structure-based
drug discovery that can be extended to cases where crystal structures
are not yet available, or have not been solved at high resolution
Bridging Molecular Docking to Membrane Molecular Dynamics To Investigate GPCR–Ligand Recognition: The Human A<sub>2A</sub> Adenosine Receptor as a Key Study
G protein-coupled
receptors (GPCRs) represent the largest family
of cell-surface receptors and about one-third of the actual targets
of clinically used drugs. Following the progress made in the field
of GPCRs structural determination, docking-based screening for novel
potent and selective ligands is becoming an increasingly adopted strategy
in the drug discovery process. However, this methodology is not yet
able to anticipate the “bioactive” binding mode and
discern it among other conformations. In the present work, we present
a novel approach consisting in the integration of molecular docking
and membrane MD simulations with the aim to merge the rapid sampling
of ligand poses into in the binding site, typical of docking algorithms,
with the thermodynamic accuracy of MD simulations in describing, at
the molecular level, the stability a GPCR-ligand complex embedded
into explicit lipid–water environment. To validate our approach,
we have chosen as a key study the human A<sub>2A</sub> adenosine receptor
(hA<sub>2A</sub> AR) and selected four receptor–antagonist
complexes and one receptor–agonist complex that have been recently
crystallized. In light of the obtained results, we believe that our
novel strategy can be extended to other GPCRs and might represent
a valuable tool to anticipate the “bioactive” conformation
of high-affinity ligands
Deciphering the Complexity of Ligand–Protein Recognition Pathways Using Supervised Molecular Dynamics (SuMD) Simulations
Molecular
recognition is a crucial issue when aiming to interpret
the mechanism of known active substances as well as to develop novel
active candidates. Unfortunately, simulating the binding process is
still a challenging task because it requires classical MD experiments
in a long microsecond time scale that are affordable only with a high-level
computational capacity. In order to overcome this limiting factor,
we have recently implemented an alternative MD approach, named supervised
molecular dynamics (SuMD), and successfully applied it to G protein-coupled
receptors (GPCRs). SuMD enables the investigation of ligand–receptor
binding events independently from the starting position, chemical
structure of the ligand, and also from its receptor binding affinity.
In this article, we present an extension of the SuMD application domain
including different types of proteins in comparison with GPCRs. In
particular, we have deeply analyzed the ligand–protein recognition
pathways of six different case studies that we grouped into two different
classes: globular and membrane proteins. Moreover, we introduce the
SuMD-Analyzer tool that we have specifically implemented to help the
user in the analysis of the SuMD trajectories. Finally, we emphasize
the limit of the SuMD applicability domain as well as its strengths
in analyzing the complexity of ligand–protein recognition pathways
Exploring the Directionality of 5‑Substitutions in a New Series of 5‑Alkylaminopyrazolo[4,3‑<i>e</i>]1,2,4-triazolo[1,5‑<i>c</i>]pyrimidine as a Strategy To Design Novel Human A<sub>3</sub> Adenosine Receptor Antagonists.
The structure–activity relationship (SAR) of new
5-alkylaminopyrazoloÂ[4,3-<i>e</i>]Â1,2,4-triazoloÂ[1,5-<i>c</i>]Âpyrimidines as antagonists
of the A<sub>3</sub> adenosine receptor (AR) was explored with the
principal aim to establish the directionality of 5-substitutions inside
the orthosteric binding site of the A<sub>3</sub> AR. All the synthesized
compounds showed affinity for the hA<sub>3</sub> AR from nanomolar
to subnanomolar range. In particular, the most potent and selective
antagonist presents an (<i>S</i>) α-phenylethylamino
moiety at the 5 position (<b>26</b>, <i>K</i><sub>i</sub> hA<sub>3</sub> = 0.3 nM). Using an in silico receptor-driven
approach, we have determined the most favorable orientation of the
substitutions at the 5 position of the pyrazoloÂ[4,3-<i>e</i>]Â1,2,4-triazoloÂ[1,5-<i>c</i>]Âpyrimidine (PTP) scaffold,
opening the possibility for further derivatizations aimed at directing
the N<sup>5</sup> position toward the extracellular environment
Exploring the Directionality of 5‑Substitutions in a New Series of 5‑Alkylaminopyrazolo[4,3‑<i>e</i>]1,2,4-triazolo[1,5‑<i>c</i>]pyrimidine as a Strategy To Design Novel Human A<sub>3</sub> Adenosine Receptor Antagonists.
The structure–activity relationship (SAR) of new
5-alkylaminopyrazoloÂ[4,3-<i>e</i>]Â1,2,4-triazoloÂ[1,5-<i>c</i>]Âpyrimidines as antagonists
of the A<sub>3</sub> adenosine receptor (AR) was explored with the
principal aim to establish the directionality of 5-substitutions inside
the orthosteric binding site of the A<sub>3</sub> AR. All the synthesized
compounds showed affinity for the hA<sub>3</sub> AR from nanomolar
to subnanomolar range. In particular, the most potent and selective
antagonist presents an (<i>S</i>) α-phenylethylamino
moiety at the 5 position (<b>26</b>, <i>K</i><sub>i</sub> hA<sub>3</sub> = 0.3 nM). Using an in silico receptor-driven
approach, we have determined the most favorable orientation of the
substitutions at the 5 position of the pyrazoloÂ[4,3-<i>e</i>]Â1,2,4-triazoloÂ[1,5-<i>c</i>]Âpyrimidine (PTP) scaffold,
opening the possibility for further derivatizations aimed at directing
the N<sup>5</sup> position toward the extracellular environment
Exploring the Directionality of 5‑Substitutions in a New Series of 5‑Alkylaminopyrazolo[4,3‑<i>e</i>]1,2,4-triazolo[1,5‑<i>c</i>]pyrimidine as a Strategy To Design Novel Human A<sub>3</sub> Adenosine Receptor Antagonists.
The structure–activity relationship (SAR) of new
5-alkylaminopyrazoloÂ[4,3-<i>e</i>]Â1,2,4-triazoloÂ[1,5-<i>c</i>]Âpyrimidines as antagonists
of the A<sub>3</sub> adenosine receptor (AR) was explored with the
principal aim to establish the directionality of 5-substitutions inside
the orthosteric binding site of the A<sub>3</sub> AR. All the synthesized
compounds showed affinity for the hA<sub>3</sub> AR from nanomolar
to subnanomolar range. In particular, the most potent and selective
antagonist presents an (<i>S</i>) α-phenylethylamino
moiety at the 5 position (<b>26</b>, <i>K</i><sub>i</sub> hA<sub>3</sub> = 0.3 nM). Using an in silico receptor-driven
approach, we have determined the most favorable orientation of the
substitutions at the 5 position of the pyrazoloÂ[4,3-<i>e</i>]Â1,2,4-triazoloÂ[1,5-<i>c</i>]Âpyrimidine (PTP) scaffold,
opening the possibility for further derivatizations aimed at directing
the N<sup>5</sup> position toward the extracellular environment