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DOI 10.3390/ijms22147489

Медицинская библиотека · International journal of molecular sciences · 2021

AMIDE v2: High-Throughput Screening Based on AutoDock-GPU and Improved Workflow Leading to Better Performance and Reliability.

Darme Pierre, Dauchez Manuel, Renard Arnaud, Voutquenne-Nazabadioko Laurence, Aubert Dominique, Escotte-Binet Sandie, Renault Jean-Hugues, Villena Isabelle, Steffenel Luiz-Angelo, Baud Stéphanie

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Аннотация

Molecular docking is widely used in computed drug discovery and biological target identification, but getting fast results can be tedious and often requires supercomputing solutions. AMIDE stands for AutoMated Inverse Docking Engine. It was initially developed in 2014 to perform inverse docking on High Performance Computing. AMIDE version 2 brings substantial speed-up improvement by using AutoDock-GPU and by pulling a total revision of programming workflow, leading to better performances, easier use, bug corrections, parallelization improvements and PC/HPC compatibility. In addition to inverse docking, AMIDE is now an optimized tool capable of high throughput inverse screening. For instance, AMIDE version 2 allows acceleration of the docking up to 12.4 times for 100 runs of AutoDock compared to version 1, without significant changes in docking poses. The reverse docking of a ligand on 87 proteins takes only 23 min on 1 GPU (Graphics Processing Unit), while version 1 required 300 cores to reach the same execution time. Moreover, we have shown an exponential acceleration of the computation time as a function of the number of GPUs used, allowing a significant reduction of the duration of the inverse docking process on large datasets.

Для цитирования: Darme Pierre, Dauchez Manuel, Renard Arnaud, Voutquenne-Nazabadioko Laurence, Aubert Dominique, Escotte-Binet Sandie, Renault Jean-Hugues, Villena Isabelle, Steffenel Luiz-Angelo, Baud Stéphanie. AMIDE v2: High-Throughput Screening Based on AutoDock-GPU and Improved Workflow Leading to Better Performance and Reliability.. International journal of molecular sciences. 2021. DOI: 10.3390/ijms22147489.

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