Limits...
The ligand binding mechanism to purine nucleoside phosphorylase elucidated via molecular dynamics and machine learning.

Decherchi S, Berteotti A, Bottegoni G, Rocchia W, Cavalli A - Nat Commun (2015)

Bottom Line: These simulations are used to estimate kinetic and thermodynamic quantities, such as kon and binding free energy, obtaining a good agreement with available experimental data.In addition, we advance a hypothesis for the slow-onset inhibition mechanism of DADMe-immucillin-H against PNP.Combining extensive MD simulations with machine learning algorithms could therefore be a fruitful approach for capturing key aspects of drug-target recognition and binding.

View Article: PubMed Central - PubMed

Affiliation: 1] CONCEPT Lab, Istituto Italiano di Tecnologia, via Morego 30, 16163 Genova, Italy [2] BiKi Technologies s.r.l., via XX Settembre 33, 16121 Genova, Italy.

ABSTRACT
The study of biomolecular interactions between a drug and its biological target is of paramount importance for the design of novel bioactive compounds. In this paper, we report on the use of molecular dynamics (MD) simulations and machine learning to study the binding mechanism of a transition state analogue (DADMe-immucillin-H) to the purine nucleoside phosphorylase (PNP) enzyme. Microsecond-long MD simulations allow us to observe several binding events, following different dynamical routes and reaching diverse binding configurations. These simulations are used to estimate kinetic and thermodynamic quantities, such as kon and binding free energy, obtaining a good agreement with available experimental data. In addition, we advance a hypothesis for the slow-onset inhibition mechanism of DADMe-immucillin-H against PNP. Combining extensive MD simulations with machine learning algorithms could therefore be a fruitful approach for capturing key aspects of drug-target recognition and binding.

No MeSH data available.


Structures of the human PNP trimer and DADMe–immucillin-H.(a) PNP trimeric structure (PDB entry 3K8O): monomers corresponding to chains E, Q and Y are represented as ribbons in silver, blue and red, respectively. The catalytic sites are rather close to the interface between different monomers and can be recognized by the presence of the ligand and phosphate molecules. (b) Larger view of the PNP active site in the bound state with DADMe–immucillin-H (PDB entry 1RSZ). The main residues interacting with the ligand as well as the phosphate molecule and the ligand itself are represented in licorice mode. In green is shown the so-called ‘gate’ loop, formed by residues 240–256, and in yellow the α-helix, which makes intermittent contacts with the bound ligand and which is kinked at Gln269. (c) Two-dimensional structure of DADMe–immucillin-H. The torsional angles that are discussed in the text are explicitly reported.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
getmorefigures.php?uid=PMC4308819&req=5

f1: Structures of the human PNP trimer and DADMe–immucillin-H.(a) PNP trimeric structure (PDB entry 3K8O): monomers corresponding to chains E, Q and Y are represented as ribbons in silver, blue and red, respectively. The catalytic sites are rather close to the interface between different monomers and can be recognized by the presence of the ligand and phosphate molecules. (b) Larger view of the PNP active site in the bound state with DADMe–immucillin-H (PDB entry 1RSZ). The main residues interacting with the ligand as well as the phosphate molecule and the ligand itself are represented in licorice mode. In green is shown the so-called ‘gate’ loop, formed by residues 240–256, and in yellow the α-helix, which makes intermittent contacts with the bound ligand and which is kinked at Gln269. (c) Two-dimensional structure of DADMe–immucillin-H. The torsional angles that are discussed in the text are explicitly reported.

Mentions: In Fig. 1, we report the PNP trimer (Fig. 1a) along with a Two-dimensional sketch of DADME chemical structure (Fig. 1c). In our structural analysis, we will comment in particular on some key residues that we refer to as the binding site residues, namely His257, Asn243, Phe200, Pro198, Glu201 and Tyr88 (PDB entry 1RSZ, see Fig. 1a,b). A relevant secondary structure element is the α-helix made by residues 257–284. This α-helix is kinked at Gln269. A loop (residues 240–256) is located right before this α-helix. We will refer to it as the gate. The ligand comprises a purine and a dihydroxypyrrolidine ring connected via two bonds (see Fig. 1c). By flipped pose we mean a DADME conformation where the -C–N- dihedral angle between the dihydroxypyrrolidine and the purine ring differs from that of the crystallographic structure by about 120°.


The ligand binding mechanism to purine nucleoside phosphorylase elucidated via molecular dynamics and machine learning.

Decherchi S, Berteotti A, Bottegoni G, Rocchia W, Cavalli A - Nat Commun (2015)

Structures of the human PNP trimer and DADMe–immucillin-H.(a) PNP trimeric structure (PDB entry 3K8O): monomers corresponding to chains E, Q and Y are represented as ribbons in silver, blue and red, respectively. The catalytic sites are rather close to the interface between different monomers and can be recognized by the presence of the ligand and phosphate molecules. (b) Larger view of the PNP active site in the bound state with DADMe–immucillin-H (PDB entry 1RSZ). The main residues interacting with the ligand as well as the phosphate molecule and the ligand itself are represented in licorice mode. In green is shown the so-called ‘gate’ loop, formed by residues 240–256, and in yellow the α-helix, which makes intermittent contacts with the bound ligand and which is kinked at Gln269. (c) Two-dimensional structure of DADMe–immucillin-H. The torsional angles that are discussed in the text are explicitly reported.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4308819&req=5

f1: Structures of the human PNP trimer and DADMe–immucillin-H.(a) PNP trimeric structure (PDB entry 3K8O): monomers corresponding to chains E, Q and Y are represented as ribbons in silver, blue and red, respectively. The catalytic sites are rather close to the interface between different monomers and can be recognized by the presence of the ligand and phosphate molecules. (b) Larger view of the PNP active site in the bound state with DADMe–immucillin-H (PDB entry 1RSZ). The main residues interacting with the ligand as well as the phosphate molecule and the ligand itself are represented in licorice mode. In green is shown the so-called ‘gate’ loop, formed by residues 240–256, and in yellow the α-helix, which makes intermittent contacts with the bound ligand and which is kinked at Gln269. (c) Two-dimensional structure of DADMe–immucillin-H. The torsional angles that are discussed in the text are explicitly reported.
Mentions: In Fig. 1, we report the PNP trimer (Fig. 1a) along with a Two-dimensional sketch of DADME chemical structure (Fig. 1c). In our structural analysis, we will comment in particular on some key residues that we refer to as the binding site residues, namely His257, Asn243, Phe200, Pro198, Glu201 and Tyr88 (PDB entry 1RSZ, see Fig. 1a,b). A relevant secondary structure element is the α-helix made by residues 257–284. This α-helix is kinked at Gln269. A loop (residues 240–256) is located right before this α-helix. We will refer to it as the gate. The ligand comprises a purine and a dihydroxypyrrolidine ring connected via two bonds (see Fig. 1c). By flipped pose we mean a DADME conformation where the -C–N- dihedral angle between the dihydroxypyrrolidine and the purine ring differs from that of the crystallographic structure by about 120°.

Bottom Line: These simulations are used to estimate kinetic and thermodynamic quantities, such as kon and binding free energy, obtaining a good agreement with available experimental data.In addition, we advance a hypothesis for the slow-onset inhibition mechanism of DADMe-immucillin-H against PNP.Combining extensive MD simulations with machine learning algorithms could therefore be a fruitful approach for capturing key aspects of drug-target recognition and binding.

View Article: PubMed Central - PubMed

Affiliation: 1] CONCEPT Lab, Istituto Italiano di Tecnologia, via Morego 30, 16163 Genova, Italy [2] BiKi Technologies s.r.l., via XX Settembre 33, 16121 Genova, Italy.

ABSTRACT
The study of biomolecular interactions between a drug and its biological target is of paramount importance for the design of novel bioactive compounds. In this paper, we report on the use of molecular dynamics (MD) simulations and machine learning to study the binding mechanism of a transition state analogue (DADMe-immucillin-H) to the purine nucleoside phosphorylase (PNP) enzyme. Microsecond-long MD simulations allow us to observe several binding events, following different dynamical routes and reaching diverse binding configurations. These simulations are used to estimate kinetic and thermodynamic quantities, such as kon and binding free energy, obtaining a good agreement with available experimental data. In addition, we advance a hypothesis for the slow-onset inhibition mechanism of DADMe-immucillin-H against PNP. Combining extensive MD simulations with machine learning algorithms could therefore be a fruitful approach for capturing key aspects of drug-target recognition and binding.

No MeSH data available.