Search for new antagonist ligands for adenosine receptors from QSAR point of view. How close are we?

Abstract

In view of the large libraries of nucleoside analogues that are now being handled in organic synthesis, the identification of drug biological activity is advisable prior to synthesis and this can be achieved by employing predictive biological property methods. In this sense, Quantitative Structure-Activity Relationships (QSAR) or docking approaches have emerged as promising tools. Although a large number of in silico approaches have been described in the literature for the prediction of different biological activities, the use of QSAR applications to develop adenosine receptor (AR) antagonists is not common as for the case of the antibiotics and anticancer compounds for instance. The intention of this review is to summarize the present knowledge concerning computational predictions of new molecules as adenosine receptor antagonists.

The A3 adenosine receptor as multifaceted therapeutic target: pharmacology, medicinal chemistry, and in silico approaches

“…In such a computational approach, the activity of a compound is a cumulative influence of different structural features, the so‐called “molecular descriptors”, which are chosen to construct a theoretical model since they are important in the molecular recognition of hA 3 AR. These include for example the topological and electrostatic potential descriptors that contain pertinent information specific to each individual compound . Subsequently, the model constructed through the use of such descriptors could also assist in the optimization of the structure of lead compounds and in the discovery of new potent adenosine ligands with improved pharmacological profiles .…”

“…These include for example the topological and electrostatic potential descriptors that contain pertinent information specific to each individual compound. 312 Subsequently, the model constructed through the use of such descriptors could also assist in the optimization of the structure of lead compounds and in the discovery of new potent adenosine ligands with improved pharmacological profiles. 313,314 The following sections illustrate some examples of QSAR studies (Table VIII) carried out on certain groups of derivatives that have been identified as potent hA 3 AR agonists or antagonists.…”

Pharmacophoric Models and 3D QSAR Studies of the Adenosine Receptor Ligands

“…The current review is complementary to a recently published review [23]. Although Gonzales et al mainly discussed the use of classical QSAR applications to develop AR antagonists, we provide a collection of results in which pharmacophoric models or 3D QSAR studies have been used for the optimization of existing antagonists or for the development of novel structures endowed with AR affinity.…”

“…HipHop works by finding the chemical features shared by a set of active molecules or training set. In order to obtain specific pharmacophores for A 2A and A 2B ARs to be used for the identification of selective A 2A /A 2B antagonists, Wei and co-authors accurately chose the two training sets by collecting antagonists with high affinity and selectivity toward the receptor subtypes under study (13,(19)(20)(21)(22)(23)(24)(25)(26)(27) in Chart 3).…”

Structural Analysis of Flavonoids and Related Compounds - A Review of Spectroscopic Applications

“…However, exact mechanisms for many of the actions attributed to flavonoids have not yet been established, but the relationship between their activity and the presence of specific functional groups in the molecules is undeniable. Moreover, each role attributed to flavonoids has been linked to different structural features -for example, while antioxidant activity depends essentially on the number and location of OH groups in the molecules, their antagonist effect towards adenosine receptors depends more on the overall planarity than on the hydroxyl groups; in fact, the latter even appear to be counter-productive (González et al, 2007).…”