Quantitative structure activity relationships as useful tools for the design of new adenosine receptor ligands. 1. Agonist.
In order to minimize expensive drug failures it is essential to determine the potential biological activity of new candidates as early as possible. In view of the large libraries of nucleoside analogues that are now being handled in organic synthesis, the identification of a drugs biological activity is advisable even before synthesis and this can be achieved using predictive biological activity methods. In this sense, computer aided rational drug design strategies like 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 traditional QSAR applications in the development of new agonist molecules with affinity toward adenosine receptors is scarce. This review attempts to summarize the current level of knowledge concerning computational affinity predictions for adenosine receptors using QSAR models based on knowledge of the agonist ligands. Several computational protocols and different 2D and 3D descriptors have been described in the literature for these targets, but more effort is still required in this area.
González
Maykel Pérez
MP
Service Unit, Experimental Sugar Cane Station, Villa Clara, Cuba. mpgonzalez76@yahoo.es
Terán
Carmen
C
Teijeira
Marta
M
Helguera
Aliuska Morales
AM
D000241:Adenosine / Q000031:analogs & derivatives* / Q000737:chemistry / Q000627:therapeutic use*; D015195:Drug Design; D006801:Humans; D008024:Ligands; D058906:Purinergic P1 Receptor Agonists; D021281:Quantitative Structure-Activity Relationship; D043684:Receptor, Adenosine A3 / Q000502:physiology; D018047:Receptors, Purinergic P1 / Q000502:physiology
D008024:Ligands; D058906:Purinergic P1 Receptor Agonists; D043684:Receptor, Adenosine A3; D018047:Receptors, Purinergic P1; D000241:Adenosine