Enhancing Opioid Bioactivity Predictions through Integration of Ligand-Based and Structure-Based Drug Discovery Strategies with Transfer and Deep Learning Techniques

The opioid epidemic has cast a shadow over public health, necessitating immediate action to address its devastating consequences. To effectively combat this crisis, it is crucial to discover better opioid drugs with reduced addiction potential. Artificial intelligence-based and other machine learning tools, particularly deep learning models, have garnered significant attention in recent years for their potential to advance drug discovery. However, using these tools poses challenges, especially when training samples are insufficient to achieve adequate prediction performance. In this study, we investigate the effectiveness of transfer learning in building robust deep learning models to enhance ligand bioactivity prediction for each individual opioid receptor (OR) subtype. This is achieved by leveraging knowledge obtained from pretraining a model using supervised learning on a larger data set of bioactivity data combined with ligand-based and structure-based molecular descriptors related to the entire OR subfamily. Our studies hold the potential to advance opioid research by enabling the rapid identification of novel chemical probes with specific bioactivities, which can aid in the study of receptor function and contribute to the future development of improved opioid therapeutics

Contact surfaces (shown for one protomer in dimeric arrangements) at the values of r indicated by dashed grey lines in Figure 2.

<p>The crystal structure contact surfaces are shown (on grey background) and additional distances are r = 3.12 nm, r = 3.64 nm and r = 4.60 nm for TM5,6/TM5,6 MOPr interface, and r = 3.80 nm, r = 4.00 nm and r = 4.60 nm for MOPr and KOPr at TM1,2,H8/TM1,2,H8, with the addition of r = 5.40 nm for KOPr.</p

PMFs calculated from the umbrella sampling, coarse-grained simulations for each of the different interfaces: MOPr TM1,2,H8/TM1,2,H8 is shown in red (error bars in pink), MOPr TM5,6/TM5,6 is shown in blue (error bars in light blue), and KOPr TM1,2,H8/TM1,2,H8 is in green (error bars in light green).

<p>The grayed region denoted ‘monomer’ is that in which the PMF curves were aligned to free-energy = 0. The dashed lines, shown at r = 3.12 nm, 3.64 nm, 3.80 nm, 4.00 nm, 4.60 nm, and 5.40 nm, indicate the values of separation at which the inter-protomer contacts were assessed.</p

Key results and methodological aspects of PMF curves in Figure 2.

<p>Key results and methodological aspects of PMF curves in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0090694#pone-0090694-g002" target="_blank">Figure 2</a>.</p

Interacting residues at key values of separation (r) in the PMF (shown by dashed lines in Figure 2).

<p>Cut-off value is shortest inter-protomer contact distance less than 4.8 Å between any atoms, for representative structures from the different simulation windows indicated by the dashed lines. Bolded residues are those present in the crystallographic KOPr and MOPr structures at the same cut-off values. *The interaction with this residue comes from the palmitoyl chain of the C3.55, which is not present in the crystallographic structures. Italicized residues are mentioned specifically in the text.</p

The crystallographic structures of the opioid receptors indicate putative interfacial interactions.

<p>A) Side view of crystallographic dimers. MOPr protomers interacting at a TM1,2,H8/TM1,2,H8 interface colored in red and pink from PDB ID: 4DKL. MOPr protomers interacting at a TM5,6/TM5,6 interface in blue and light blue, also from PDB ID 4DKL, and KOPr protomers interacting at a TM1,2,H8/TM1,2,H8 interface are shown in green and light green, from PDB ID: 4DJH. T4L is shown in gray in all cases. B) Extracellular view of crystallographic dimers, colored as above. Cyan overlay shows collective variables used to define the interface between protomer 1 and protomer 2 (P1 and P2). The PMF is calculated as a function of the separation <i>(r)</i> between the COMs of the TM regions of the two protomers. The orientation of the interface was maintained during the simulations by two harmonic restraints centered on the values of the angles, α and β. The angle α is the projection on the x, y plane of the angle calculated between the COM of the helix defining the interface, the COM of the helical bundle of the protomer bearing this helix (P1) and the COM of the adjacent protomer (P2). Angle β is the equivalent angle for the adjacent protomer.</p

How Oliceridine (TRV-130) Binds and Stabilizes a μ‑Opioid Receptor Conformational State That Selectively Triggers G Protein Signaling Pathways

Substantial attention has recently been devoted to G protein-biased agonism of the μ-opioid receptor (MOR) as an ideal new mechanism for the design of analgesics devoid of serious side effects. However, designing opioids with appropriate efficacy and bias is challenging because it requires an understanding of the ligand binding process and of the allosteric modulation of the receptor. Here, we investigated these phenomena for TRV-130, a G protein-biased MOR small-molecule agonist that has been shown to exert analgesia with less respiratory depression and constipation than morphine and that is currently being evaluated in human clinical trials for acute pain management. Specifically, we carried out multimicrosecond, all-atom molecular dynamics (MD) simulations of the binding of this ligand to the activated MOR crystal structure. Analysis of >50 μs of these MD simulations provides insights into the energetically preferred binding pathway of TRV-130 and its stable pose at the orthosteric binding site of MOR. Information transfer from the TRV-130 binding pocket to the intracellular region of the receptor was also analyzed, and was compared to a similar analysis carried out on the receptor bound to the classical unbiased agonist morphine. Taken together, these studies lead to a series of testable hypotheses of ligand–receptor interactions that are expected to inform the structure-based design of improved opioid analgesics

Hypothetical arrangements of B2AR dimers interacting with the Gs protein heterotrimer.

<p>The extracellular view of the B2AR-Gs protein complex (PDB ID: 3SN6) is shown with B2AR in grey cartoon representation, and the Gs heterotrimer, is shown in both cartoon and transparent surface (α is in orange, β is in cyan and γ is in pale blue). The first protomer of each of our minimum energy dimers for B2AR (Θ2 for TM4/3) is superimposed on the B2AR from the crystal structure 3SN6, and the position of the second protomer is shown in a green cartoon representation. An interface involving TM4 would favor an exclusive interaction of the dimer with the GαsAH subunit of the G protein, very close to the Gβ subunit when the interface is TM4/3 (panel A). In contrast, with TM1/H8 at the interface, the second protomer would not be involved in significant interactions with any of the G-protein subunits (in B).</p

Atomistic structural representations of representative minima of B1AR and B2AR homodimers for the different interfaces.

<p>Panel A shows a view from the cytoplasmic side of the minima Θ1 (dark shades) and Θ2 (lighter shades) for the B1AR (red/pink) and B2AR (blue/light blue) at the TM4/3 interface. The receptors are represented as helices with the loops removed for clarity, and are aligned on the left-most protomer. This panel highlights the small difference between the structures at the same separation but with slightly different angle minima. Panel B shows a view from the cytoplasmic side, of the minima extracted from the FES for the TM1/H8 interface. B1AR is shown in red and B2AR is shown in blue. The intracellular loops are omitted for clarity, and H8 and TM1 are highlighted to indicate the packing of the helices at the interface. Contacting residues are listed in <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1002649#pcbi.1002649.s006" target="_blank">Table S1</a> and depicted in <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1002649#pcbi.1002649.s004" target="_blank">Fig. S4</a>.</p

Results of the free energy calculations of adrenergic receptor dimers.

<p>Listed are the depths of the minima in the FES, along with the calculated dimerization constant (K_D), the standard free energy change ΔG_X°, and the estimated lifetime of each simulated B1AR and B2AR dimer. Confidence intervals are given in parentheses.</p