Efficient GPU Implementation of AutoDock Vina

July 25, 2020
Events, ACS2020, Featured

At the American Chemical Society Fall 2020 Virtual Meeting & Expo, several Atomwise members and partners were selected to present their research and work. Learn what our Atoms have been working on below and visit Atomwise at ACS Fall 2020 Virtual Meeting & Expo for other presentation sessions. 


AMAdrian Morrison, PhD 
Atomwise

Atomwise Collaborators: ...Izhar Wallach, PhD

Title: Efficient GPU Implementation of AutoDock Vina

Division: COMP

 

 

Abstract

A key step in virtual high throughput screenings (VHTS) of small molecules for structure based drug discovery is the docking procedure that aims to find most likely binding modes of trial ligands to target proteins. One of the foremost tools for this procedure today is AutoDock Vina and its efficient parallel implementation, Smina. Here, we introduce the CUina program, a new implementation of Smina for Graphics Processing Units based on the NVIDIA CUDA platform. CUina implements the key features of Smina, namely flexible ligand docking by sampling and optimizing on the Vina scoring surface, but has been rewritten from the ground up with algorithms tailored for the idiosyncrasies of GPU architectures. We have found that CUina generates poses of equivalent quality as Smina and for reduced cost on popular cloud platforms. Today, GPU architectures provide the computational engine for ubiquitous machine learning methods so CUina is harmonious with ML based VHTS workflows. Herein we describe implementation details and present pose quality and software performance benchmarks.

 


Poster Presentation

On-demand Poster (click for hi-resolution)

morrison_gpu_vina_acs_f2020_preview

On-demand audio recording


 

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