Details

Autor(en) / Beteiligte

• Albuquerque, Ana Camila Campelo
• Bezerra, Katyanna Sales
• de Fátima Vianna, Jéssica
• Batista, Sabrynna Oliveira
• de Lima Neto, José Xavier
• de Oliveira Campos, Daniel Melo
• Oliveira, Jonas Ivan Nobre
• Galvão, Douglas Soares
• Fulco, Umberto Laino

Titel

In Silico Evaluation of the Binding Energies of Androgen Receptor Agonists in Wild-Type and Mutational Models

Ist Teil von

• The journal of physical chemistry. B, 2023-06, Vol.127 (22), p.5005-5017

Ort / Verlag

United States: American Chemical Society

Erscheinungsjahr

2023

Quelle

MEDLINE

Beschreibungen/Notizen

• Anabolic androgenic steroids (AAS) are substances with androgenic and anabolic characteristics. Among the many side effects of hormone therapy with AAS, the following stand out: heart problems, adrenal gland disorders, aggressive behavior, increased risk of prostate cancer, problems related to lack of libido and impotence. Such substances vary in the relationship between androgenic activity, and the activation of the androgen receptor (AR) is of fundamental importance for the singularity of the action of each AAS. In this sense, our study evaluates the aspects that comprise the interactions of testosterone agonists (TES), dihydrotestosterone (DHT) and tetrahydrogestrinone (THG) in complex with the AR. In addition, we also evaluated the impact of ligand–receptor affinity differences in a mutation model. We apply computational techniques based on density functional theory (DFT) and use, as methodology, Molecular Fractionation with Conjugate Caps (MFCC). The energetic specificities present in the interaction between the analyzed complexes attest that the highest affinity with the AR receptor is found for AR–THG, followed by AR–DHT, AR–TES and AR-T877A–DHT, respectively. Our results also show the differences and equivalences between the different agonists, in addition to evaluating the difference between the DHT ligand in complex with the wild-type and mutant receptor, presenting the main amino acid residues that involve the interaction with the ligands. The computational methodology used proves to be an operative and sophisticated choice to help in the search for pharmacological agents for various therapies that have androgen as a target.