Study of interaction energies between residues of the active site of Hsp90 and geldanamycin analogues using quantum mechanics/molecular mechanics methods.

Background: Heat shock protein (Hsp90KDa) is a molecular chaperone involved in the process of cellular oncogenesis, hence its importance as a therapeutic target. Geldanamycin is an inhibitor of Hsp90 chaperone activity, which binds to the ATP binding site in the N-terminal domain of Hsp90. However, geldanamycin has shown hepatotoxic damage in clinical trials; for this reason, its use is not recommended. Taking advantage that geldanamycin binds successfully to Hsp90, many efforts have focused on the search for similar analogues, which have the same or better biological response and reduce the side effects of its predecessor; 17-AAG and 17-DMAG are examples of these analogues. Methods: In order to know the chemical factors influencing the growth or decay of the biological activity of geldanamycin analogues, different computational techniques such as docking, 3DQSAR and quantum similarity were used.  Moreover, the study quantified the interaction energy between amino acids residues of active side and geldanamycin analogues, through hybrid methodology (Autodock-PM6) and DFT indexes. Results: The evaluation of interaction energies showed that the interaction with Lys58 residue is essential for the union of the analogues to the active site of Hsp90, and improves its biological activity. This union is formed through a substituent on C-11 of the geldanamycin macrocycle. A small and attractor group was found as the main steric and electrostatic characteristic that substituents on C11 need in order to interact with Lys 58; behavior was observed with hydroxy and methoxy series of geldanamycin analogues, under study. Conclusion: This study contributes with new hybrid methodology (Autodock-PM6) for the generation of 3DQSAR models, which to consider the interactions between compounds and amino acids residues of Hsp90´s active site in the alignment generation. Additionally, quantum similarity and reactivity indices calculations using DFT were performed to know the non-covalent stabilization in the active site of these compounds.

Método acoplado Autodock-PM6 para seleccionar la mejor pose en estudios de acoplamiento molecular / Autodock-PM6 method to choose the better pose in molecular docking studies / A Autodock-PM6 metodo pra seleccionar o melhor pose en estudios de acoplamiento molecular

El acoplamiento molecular (conocido como docking) es una técnica de mecánica molecular ampliamente utilizada para predecir energías y modos de enlace entre ligandos y proteínas, información de gran utilidad en el estudio de nuevos compuestos con efectos terapéuticos. No obstante, los resultados obtenidos mediante esta técnica tienden a la subjetividad, debido a que los programas utilizados para llevarla a cabo proporcionan más de un criterio de selección de la mejor pose. En la presente investigación se aplicó el método semiempírico PM6 a los resultados del acoplamiento, obteniendo con ello mejorías en el proceso de selección de la mejor pose pues se obtuvieron poses con alta probabilidad de unión al sitio activo de su receptor y con energías de unión menores a las reportadas por los criterios de selección ofrecidos por el programa de docking.

The acoplamiento molecular (conocido como docking) es una técnica de mecánica molecular ampliamente utilizada para predecir energías y modos de enlace entre ligandos y proteínas, lo que proporciona información de gran utilidad para el estudio de nuevos compuestos con efectos terapéuticos. No obstante, los resultados obtenidos mediante esta técnica tienden a la subjetividad, debido a que los programas utilizados para llevarla a cabo proporcionan más de un criterio de selección de la mejor pose. En la presente investigación, se aplicó el método semiempírico PM6 a los resultados del acoplamiento, obteniendo con ello mejorías en el proceso de selección de la mejor pose al observarse finalmente poses con alta probabilidad de unión al sitio activo de su receptor y con energías de unión menores a las reportadas por los criterios de selección ofrecidos por el programa de docking.

El acoplamiento molecular (conocido como docking) es una técnica de mecánica molecular ampliamente utilizada para predecir energías y modos de enlace entre ligandos y proteínas, lo que proporciona información de gran utilidad para el estudio de nuevos compuestos con efectos terapéuticos. No obstante, los resultados obtenidos mediante esta técnica tienden a la subjetividad, debido a que los programas utilizados para llevarla a cabo proporcionan más de un criterio de selección de la mejor pose. En la presente investigación, se aplicó el método semiempírico PM6 a los resultados del acoplamiento, obteniendo con ello mejorías en el proceso de selección de la mejor pose al observarse finalmente poses con alta probabilidad de unión al sitio activo de su receptor y con energías de unión menores a las reportadas por los criterios de selección ofrecidos por el programa de docking.

CoMFA, LeapFrog and blind docking studies on sulfonanilide derivatives acting as selective aromatase expression regulators.

Aromatase, the enzyme responsible for estrogen biosynthesis, is an attractive target in the treatment of hormone-dependent breast cancer. In this manuscript, the structure-based drug design approach of sulfonanilide analogues as potential selective aromatase expression regulators (SAERs) is described. Receptor-independent CoMFA (Comparative Molecular Field Analysis) maps were employed for generating a pseudocavity for LeapFrog calculation. A robust model, using 45 and 10 molecules in the training and test sets, respectively, was developed producing statistically significant results with cross-validated and conventional correlation coefficients of 0.656 and 0.956, respectively. This model was used to predict the activity of newly proposed molecules as SAERs candidates being two magnitude orders more potent than the previously reported compounds. Also in the present study, the computational blind docking method using eHiTS is tested on molecules study group and COX-2 enzyme. Future perspectives of the method in the screening of SAERs candidates with no COX-2 inhibitory activity are discussed.

Three-dimensional quantitative structure-activity relationship studies on novel series of benzotriazine based compounds acting as Src inhibitors using CoMFA and CoMSIA.

Comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) were performed on a series of benzotriazine derivatives, as Src inhibitors. Ligand molecular superimposition on the template structure was performed by database alignment method. The statistically significant model was established of 72 molecules, which were validated by a test set of six compounds. The CoMFA model yielded a q(2)=0.526, non cross-validated R(2) of 0.781, F value of 88.132, bootstrapped R(2) of 0.831, standard error of prediction=0.587, and standard error of estimate=0.351 while the CoMSIA model yielded the best predictive model with a q(2)=0.647, non cross-validated R(2) of 0.895, F value of 115.906, bootstrapped R(2) of 0.953, standard error of prediction=0.519, and standard error of estimate=0.178. The contour maps obtained from 3D-QSAR studies were appraised for activity trends for the molecules analyzed. Results indicate that small steric volumes in the hydrophobic region, electron-withdrawing groups next to the aryl linker region, and atoms close to the solvent accessible region increase the Src inhibitory activity of the compounds. In fact, adding substituents at positions 5, 6, and 8 of the benzotriazine nucleus were generated new compounds having a higher predicted activity. The data generated from the present study will further help to design novel, potent, and selective Src inhibitors as anticancer therapeutic agents.