High-throughput binding affinity calculations at extreme scales
| dc.contributor.author | Dakka, Jumana | |
| dc.contributor.author | Turilli, Matteo | |
| dc.contributor.author | Wright, David | |
| dc.contributor.author | Zasada, Stefan | |
| dc.contributor.author | Balasubramanian, Vivek | |
| dc.contributor.author | Wan, Shunzhou | |
| dc.contributor.author | Coveney, Pete | |
| dc.contributor.author | Jha, Shantenu | |
| dc.contributor.ror | https://ror.org/02jjdwm75 | |
| dc.date.accessioned | 2026-02-26T17:57:13Z | |
| dc.date.issued | 2018-12-21 | |
| dc.description.abstract | Resistance to chemotherapy and molecularly targeted therapies is a major factor in limiting the effectiveness of cancer treatment. In many cases, resistance can be linked to genetic changes in target proteins, either pre-existing or evolutionarily selected during treatment. Key to overcoming this challenge is an understanding of the molecular determinants of drug binding. Using multi-stage pipelines of molecular simulations we can gain insights into the binding free energy and the residence time of a ligand, which can inform both stratified and personal treatment regimes and drug development. To support the scalable, adaptive and automated calculation of the binding free energy on high-performance computing resources, we introduce the High-throughput Binding Affinity Calculator (HTBAC). HTBAC uses a building block approach in order to attain both workflow flexibility and performance. | |
| dc.description.peerreviewed | Yes | |
| dc.description.status | Published | |
| dc.format | application/pdf | |
| dc.identifier.citation | Dakka, J., Turilli, M., Wright, D. W., Zasada, S. J., Balasubramanian, V., Wan, S., ... & Jha, S. (2018). High-throughput binding affinity calculations at extreme scales. BMC bioinformatics, 19(Suppl 18), 482. https://doi.org/10.1186/s12859-018-2506-6 | |
| dc.identifier.doi | https://doi.org/10.1186/s12859-018-2506-6 | |
| dc.identifier.issn | 1471-2105 | |
| dc.identifier.officialurl | https://link.springer.com/article/10.1186/s12859-018-2506-6 | |
| dc.identifier.uri | https://hdl.handle.net/20.500.14417/4181 | |
| dc.issue.number | 18 | |
| dc.journal.title | BMC Bioinformatics | |
| dc.language.iso | eng | |
| dc.page.total | 13 | |
| dc.publisher | Springer Nature | |
| dc.relation.department | Sci Tech (Data Science) | |
| dc.relation.entity | IE University | |
| dc.relation.school | IE School of Science & Technology | |
| dc.rights | Attribution 4.0 International | |
| dc.rights.accessRights | info:eu-repo/semantics/openAccess | |
| dc.rights.uri | http://creativecommons.org/licenses/by/4.0/ | |
| dc.subject.ods | ODS 3 - Salud y bienestar | |
| dc.subject.unesco | 33 Ciencias Tecnológicas::3306 Ingeniería y tecnología eléctricas | |
| dc.title | High-throughput binding affinity calculations at extreme scales | |
| dc.type | info:eu-repo/semantics/article | |
| dc.version.type | info:eu-repo/semantics/publishedVersion | |
| dc.volume.number | 19 | |
| dspace.entity.type | Publication | |
| relation.isAuthorOfPublication | 4c105a3d-3b6f-4801-b0a6-7593ef9017d2 | |
| relation.isAuthorOfPublication.latestForDiscovery | 4c105a3d-3b6f-4801-b0a6-7593ef9017d2 |
