Congestion game scheduling for virtual drug screening optimization.

Abstract:

:In virtual drug screening, the chemical diversity of hits is an important factor, along with their predicted activity. Moreover, interim results are of interest for directing the further research, and their diversity is also desirable. In this paper, we consider a problem of obtaining a diverse set of virtual screening hits in a short time. To this end, we propose a mathematical model of task scheduling for virtual drug screening in high-performance computational systems as a congestion game between computational nodes to find the equilibrium solutions for best balancing the number of interim hits with their chemical diversity. The model considers the heterogeneous environment with workload uncertainty, processing time uncertainty, and limited knowledge about the input dataset structure. We perform computational experiments and evaluate the performance of the developed approach considering organic molecules database GDB-9. The used set of molecules is rich enough to demonstrate the feasibility and practicability of proposed solutions. We compare the algorithm with two known heuristics used in practice and observe that game-based scheduling outperforms them by the hit discovery rate and chemical diversity at earlier steps. Based on these results, we use a social utility metric for assessing the efficiency of our equilibrium solutions and show that they reach greatest values.

journal_name

J Comput Aided Mol Des

authors

Nikitina N,Ivashko E,Tchernykh A

doi

10.1007/s10822-017-0093-7

subject

Has Abstract

pub_date

2018-02-01 00:00:00

pages

363-374

issue

2

eissn

0920-654X

issn

1573-4951

pii

10.1007/s10822-017-0093-7

journal_volume

32

pub_type

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