A New Optimized Hybridization Approach for in silico High Throughput Molecular Docking on FPGA Platform

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BACKGROUND: The development process of a new drug should be a subject of continuous evolution and rapid improvement as drugs are essential to treat a wide range of diseases of which many are life-threatening. The advances in technology resulted in a novel track in drug discovery and development known as in silico drug design. The molecular docking phase plays a vital role in in silico drug development process. In this phase, thousands of 3D conformations of both the ligand and receptor are generated and the best conformations that create the most stable drug-receptor complex are determined. The speed in finding accurate and high-quality complexes depends on the efficiency of the search function in the molecular docking procedure.

OBJECTIVE: The objective of this research is to propose and implement a novel hybrid approach called hABCDE to replace the EMC searching part inside the BUDE docking algorithm. This helps in reaching the best solution in a much accelerated time and higher solution quality compared to using the ABC and DE algorithms separately.

METHODS: In this work, we have employed a new approach of hybridization between the Artificial Bee Colony (ABC) algorithm and the Differential Evolution (DE) algorithm as an alternative searching part of the Bristol University Docking Engine (BUDE) in order to accelerate the search for higher quality solutions. Moreover, the proposed docking approach was implemented on Field Programmable Gate Array (FPGA) parallel platform using Vivado High-Level Synthesis Tool (HLST) in order to optimize and enhance the execution time and overall efficiency. The NDM-1 protein was used as a model receptor in our experiments to demonstrate the efficiency of our approach.

RESULTS: The NDM-1 protein was used as a model receptor in our experiments to demonstrate the efficiency of our approach. The results showed that the execution time for the BUDE with the new proposed hybridization approach was improved by 9,236 times.

CONCLUSION: Our novel approach was significantly effective to improve the functionality of docking algorithms (Bristol University Docking Engine (BUDE)).

Medienart:

E-Artikel

Erscheinungsjahr:

2024

2023

Erschienen:

2024

Enthalten in:

Zur Gesamtaufnahme - volume:20

Enthalten in:

Current computer-aided drug design - 20(2023), 3 vom: 23., Seite 236-247

Sprache:

Englisch

Beteiligte Personen:

Jarrah, Amin [VerfasserIn]
Lababneh, Jawad [VerfasserIn]

Links:

Volltext

Themen:

Artificial bee colony algorithm
BUDE
Differential evolution algorithm
FPGA
Journal Article
Molecular docking
Optimization
Parallel processing
Proteins
Vivado HLS

Anmerkungen:

Date Completed 01.11.2023

Date Revised 01.11.2023

published: Print

Citation Status MEDLINE

doi:

10.2174/1573409919666230503094411

funding:

Förderinstitution / Projekttitel:

PPN (Katalog-ID):

NLM363217401