Targeted approach towards inhibition of telomere-hnRNP A1 interaction
Notice bibliographique
Résumé
A207 The heterogeneous nuclear ribonucleoparticule (hnRNP) A1 and A2 proteins associate with telomere ends (the cap structure), stimulate telomerase activity and are required for the viability of transformed human cells, irrespective of the status of telomerase expression or the length of the double-stranded telomeric repeat. We describe here our screening strategy for identifying small molecules capable of interfering with telomere capping by A1 and A2. Such small molecules are potentially promising novel anti-cancer agents predicted to be acutely cytotoxic to cancer cells, but innocuous to untransformed cells. In our first attempt, libraries were screened directly in a protein/DNA dissociation assay using a truncated version of the A1 protein: UP1 and a short telomeric DNA oligo. After examining 60,000 preselected compounds, no validated hits were identified. Only promiscuous inhibitors with the tendency to form aggregates in solution showed activity in vitro. A more selective screening approach was then undertaken. A large collection of compounds from different libraries was filtered to remove compound with undesired physicochemical properties and functional groups. This resulted in a database containing approximately 2 million compounds. Based on published X-ray crystallography structures, we chose to target the binding pocket that contacts the nucleotides TAG within the telomeric sequence TTAGGG. We resolved by X-ray diffraction the structure of isolated TAG oligonucleotide bound to UP1 and found this ligand exhibited the same network of interactions within the pocket as the full length telomeric repeat. We then designed a series of 2D and 3D pharmacophores based both on the protein binding site and the TAG ligand. The collection and sub-sets thereof were screened against these pharmacophores and several compounds were identified. The selected compounds were then docked in silico into the binding site and ranked using docking scores. The best compounds from each of these screens were obtained and screened. The present screening workflow consists of an initial disruption assay (to determine which compounds inhibit the targeted interaction), solubility assessment by nephelometry (to exclude insoluble compounds), binding studies to DNA and unrelated protein targets (to eliminate undesired binding activities), UP1 binding assessment using Surface Plasmon Resonance, cytotoxicity testing followed by in vivo target modulation. SAR studies were initiated on five compound classes that showed activity. A correlation between in vitro and in vivo activity was revealed for two closely related compound classes. Synthesis of analogues from these two classes is presently underway to increase potency. The virtual-HTS hybrid approach described here was critical for obtaining active and optimizable scaffolds, with the potential to develop potent inhibitors of telomere capping proteins.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,001 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».