Ligand-Based Modeling of CXC Chemokine Receptor 4 and Identification of Inhibitors of Novel Chemotypes as Potential Leads towards New Anti-COVID-19 Treatments

BACKGROUND

Chemokines are involved in several human diseases and in different stages of COVID-19 infection and play critical role in the pathophysiology of the associated acute respiratory disease syndrome, a major complication leading to death among COVID-19 patients. In particular, CXC chemokine receptor 4 (CXCR4) was found to be highly expressed in COVID-19 patients.

METHODS

We herein describe a computational workflow based on combining pharmacophore modeling and QSAR analysis towards the discovery of novel CXCR4 inhibitors. Subsequent virtual screening identified two promising CXCR4 inhibitors from the National Cancer Institute (NCI) list of compounds. The most active hit showed in vitro IC50 value of 24.4 µM.

RESULTS AND CONCLUSION

These results prove the validity of the QSAR model and associated pharmacophore models as means to screen virtual databases towards new CXCR4 inhibitors as leads for the development of new COVID-19 therapies.

Combining selectivity and affinity predictions using an integrated Support Vector Machine (SVM) approach: An alternative tool to discriminate between the human adenosine A(2A) and A(3) receptor pyrazolo-triazolo-pyrimidine antagonists binding sites

G Protein-coupled receptors (GPCRs) selectivity is an important aspect of drug discovery process, and distinguishing between related receptor subtypes is often the key to therapeutic success. Nowadays, very few valuable computational tools are available for the prediction of receptor subtypes selectivity. In the present study, we present an alternative application of the Support Vector Machine (SVM) and Support Vector Regression (SVR) methodologies to simultaneously describe both A(2A)R versus A(3)R subtypes selectivity profile and the corresponding receptor binding affinities. We have implemented an integrated application of SVM-SVR approach, based on the use of our recently reported autocorrelated molecular descriptors encoding for the Molecular Electrostatic Potential (autoMEP), to simultaneously discriminate A(2A)R versus A(3)R antagonists and to predict their binding affinity to the corresponding receptor subtype of a large dataset of known pyrazolo-triazolo-pyrimidine analogs. To validate our approach, we have synthetized 51 new pyrazolo-triazolo-pyrimidine derivatives anticipating both A(2A)R/A(3)R subtypes selectivity and receptor binding affinity profiles.

Pyrido[2,3-e]-1,2,4-triazolo[4,3-a]pyrazin-1-one as a new scaffold to develop potent and selective human A3 adenosine receptor antagonists. Synthesis, pharmacological evaluation, and ligand-receptor modeling studies

The paper describes a new class of human (h) A(3) adenosine receptor antagonists, the 2-arylpyrido[2,3-e]-1,2,4-triazolo[4,3-a]pyrazin-1-one derivatives (PTP), either 4-oxo (1-6, series A) or 4-amino-substituted (7-20, series B). In both series A and B, substituents able to act as hydrogen bond acceptors (OMe, OH, F, COOEt) were inserted on the 2-phenyl ring. In series B, cycloalkyl and acyl residues were introduced on the 4-amino group. Some of the new derivatives showed high hA(3) AR affinities (K(i) < 50 nM) and selectivities vs both hA(1) and hA(2A) receptors. The selected 4-benzoylamino-2-(4-methoxyphenyl)pyrido[2,3-e]-1,2,4-triazolo[4,3-a]pyrazin-1-one (18), tested in an in vitro rat model of cerebral ischemia, proved to be effective in preventing the failure of synaptic activity induced by oxygen and glucose deprivation in the hippocampus. Molecular docking of this new class of hA(3) AR antagonists was carried out to depict their hypothetical binding mode to our refined model of hA(3) receptor.

Highlights on the development of A(2A) adenosine receptor agonists and antagonists

Although significant progress has been made in the past few decades demonstrating that adenosine modulates a variety of physiological and pathophysiological processes through the interaction with four subtypes of a family of cell-surface G-protein-coupled receptors, clinical evaluation of some adenosine receptor ligands has been discontinued. Major problems include side effects due to the wide distribution of adenosine receptors, low brain penetration (which is important for the targeting of CNS diseases), short half-life of compounds, or a lack of effects, in some cases perhaps due to receptor desensitization or to low receptor density in the targeted tissue. Currently, three A(2A) adenosine receptor agonists have begun phase III studies. Two of them are therapeutically evaluated as pharmacologic stress agents and the third proved to be effective in the treatment of acute spinal cord injury (SCI), while avoiding the adverse effects of steroid agents. On the other hand, the great interest in the field of A(2A) adenosine receptor antagonists is related to their application in neurodegenerative disorders, in particular, Parkinson's disease, and some of them are currently in various stages of evaluation. This review presents an update of medicinal chemistry and molecular recognition of A(2A) adenosine receptor agonists and antagonists, and stresses the strong need for more selective ligands at the A(2A) human subtype.

Linear and nonlinear 3D-QSAR approaches in tandem with ligand-based homology modeling as a computational strategy to depict the pyrazolo-triazolo-pyrimidine antagonists binding site of the human adenosine A2A receptor

The integration of ligand- and structure-based strategies might sensitively increase the success of drug discovery process. We have recently described the application of Molecular Electrostatic Potential autocorrelated vectors (autoMEPs) in generating both linear (Partial Least-Square, PLS) and nonlinear (Response Surface Analysis, RSA) 3D-QSAR models to quantitatively predict the binding affinity of human adenosine A3 receptor antagonists. Moreover, we have also reported a novel GPCR modeling approach, called Ligand-Based Homology Modeling (LBHM), as a tool to simulate the conformational changes of the receptor induced by ligand binding. In the present study, the application of both linear and nonlinear 3D-QSAR methods and LBHM computational techniques has been used to depict the hypothetical antagonist binding site of the human adenosine A2A receptor. In particular, a collection of 127 known human A2A antagonists has been utilized to derive two 3D-QSAR models (autoMEPs/PLS&RSA). In parallel, using a rhodopsin-driven homology modeling approach, we have built a model of the human adenosine A2A receptor. Finally, 3D-QSAR and LBHM strategies have been utilized to predict the binding affinity of five new human A2A pyrazolo-triazolo-pyrimidine antagonists finding a good agreement between the theoretical and the experimental predictions.

Scouting human A3 adenosine receptor antagonist binding mode using a molecular simplification approach: from triazoloquinoxaline to a pyrimidine skeleton as a key study

The concept of molecular simplification as a drug design strategy to shorten synthetic routes, while keeping or enhancing the biological activity of the lead drug, has been applied to design new classes of human A3 adenosine receptor (AR) antagonists. Over the past decade, we have focused a part of our research on the study of AR antagonists belonging to strictly correlated classes of tricyclic compounds. One of these classes is represented by the 2-aryl-1,2,4-triazolo[4,3-a]quinoxalin-1-one derivatives, either 4-amino or 4-oxo-substituted, which were intensively investigated by evaluating the effect of different substituents on the 2-phenyl ring and on the 4-amino group. Using an in silico molecular simplification approach, a new series of easily synthesizable 2-amino/2-oxoquinazoline-4-carboxamido derivatives have been discovered, presenting high affinity and selectivity against human A3 AR.

New 2-arylpyrazolo[3,4-c]quinoline derivatives as potent and selective human A3 adenosine receptor antagonists. Synthesis, pharmacological evaluation, and ligand-receptor modeling studies

This paper reports the study of some 2-arylpyrazolo[3,4-c]quinolin-4-ones, 4-amines, and 4-amino-substituted derivatives designed as human A3 adenosine receptor (AR) antagonists. Most of the herein reported compounds showed a nanomolar affinity toward the hA3 receptor subtype and different degrees of selectivity that resulted to be strictly dependent on the presence and nature of the substituent on the 4-amino group. Bulky and lipophilic acyl groups, as well as the benzylcarbamoyl residue, afforded highly potent and selective hA3 receptor antagonists. The selected 4-diphenylacetylamino-2-phenylpyrazoloquinoline (25) and 4-dibenzoylamino-2-(4-methoxyphenyl)pyrazoloquinoline (36), tested in an in vitro rat model of cerebral ischemia, prevented the irreversible failure of synaptic activity induced by oxygen and glucose deprivation in the hippocampus. The observed structure-affinity relationships of this class of antagonists were also exhaustively rationalized using the recently published ligand-based homology modeling (LBHM) approach.

Pyrazolo-triazolo-pyrimidines as adenosine receptor antagonists: Effect of the N-5 bond type on the affinity and selectivity at the four adenosine receptor subtypes

In the last few years, many efforts have been made to search for potent and selective human A₃ adenosine antagonists. In particular, one of the most promising human A₃ adenosine receptor antagonists is represented by the pyrazolo-triazolo-pyrimidine family. This class of compounds has been strongly investigated from the point of view of structure-activity relationships. In particular, it has been observed that fundamental requisites for having both potency and selectivity at the human A₃ adenosine receptors are the presence of a small substituent at the N⁸ position and an unsubstitued phenyl carbamoyl moiety at the N⁵ position. In this study, we report the role of the N⁵-bond type on the affinity and selectivity at the four adenosine receptor subtypes. The observed structure-activity relationships of this class of antagonists are also exhaustively rationalized using the recently published ligand-based homology modeling approach.

Pyrazolo-triazolo-pyrimidines as adenosine receptor antagonists: A complete structure-activity profile

In the last 5 years, many efforts have been conducted searching potent and selective human A(3) adenosine antagonists. In this field several different classes of compounds, possessing very good affinity (nM range) and with a broad range of selectivity, have been proposed. Recently, our group synthesized a new series of pyrazolo-triazolo-pyrimidines bearing different substitutions at the N(5) and N(8) positions, which have been described as highly potent and selective human A(3) adenosine receptor antagonists. The present review summarizes available data and provides an overview of the structure-activity relationships found for this class of human A(3) adenosine receptor antagonists.

4-amido-2-aryl-1,2,4-triazolo[4,3-a]quinoxalin-1-ones as new potent and selective human A3 adenosine receptor antagonists. synthesis, pharmacological evaluation, and ligand-receptor modeling studies

A structural investigation on some 4-amido-2-phenyl-1,2-dihydro-1,2,4-triazolo[4,3-a]quinoxalin-1-one derivatives, designed as human A3 adenosine receptor (hA3 AR) antagonists, is described. In the new derivatives, some acyl residues with different steric bulk were introduced on the 4-amino group, and their combination with the 4-methoxy group on the 2-phenyl moiety, and/or the 6-nitro/6-amino substituent on the fused benzo ring, was also evaluated. Most of the new derivatives were potent and selective hA3 AR antagonists. SAR analysis showed that hindering and lipophilic acyl moieties not only are well tolerated but even ameliorate the hA3 affinity. Interestingly, the 4-methoxy substituent on the appended 2-phenyl moiety, as well as the 6-amino group, always exerted a positive effect, shifting the affinity toward the hA3 receptor subtype. In contrast, the 6-nitro substituent exerted a variable effect. An intensive molecular modeling investigation was performed to rationalize the experimental SAR findings.