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Incorporating Target Protein Structure Flexibility and Dynamics in Computational Drug Discovery Using Ensemble-Based Docking Analysis

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A Simple and Resource-efficient Setup for the Computer-aided Drug Design Laboratory.

Loris Moretti^1,2, Luca Sartori^3,4

¹Drug Discovery Program, Department of Experimental Oncology, European Institute of Oncology, Via Adamello 16, 20139, Milan, Italy. loris.moretti.dc@gmail.com.

Molecular Informatics

|September 21, 2016

Summary

This summary is machine-generated.

Implementing high-throughput computing (HTC) is crucial for robust computer-aided drug design (CADD) research. This paper details the creation of a specialized computing facility to meet these demanding research needs.

Keywords:

Beowulf cluster Computational laboratory setup Computer-aided Drug Design environment GNU/Linux operating system High-throughput computing Molecular modelling

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Area of Science:

Computational chemistry and cheminformatics
Drug discovery and development
High-performance computing infrastructure

Background:

Computer-Aided Drug Design (CADD) research necessitates significant computational resources.
Single-computer setups lack the robustness and throughput required for modern drug discovery programs.
Existing solutions for specialized CADD computing environments are not widely standardized.

Purpose of the Study:

To describe the design and implementation of a dedicated computing facility for CADD.
To provide a comprehensive guide covering all aspects from facility layout to technical specifications.
To address the need for a robust and scalable computational environment in drug discovery.

Main Methods:

Detailed planning of the general layout and infrastructure for the computing facility.
Selection and integration of appropriate hardware and software components for high-throughput computing.
Consideration of network, storage, and power requirements for a dedicated research environment.

Main Results:

A fully realized computing facility tailored for CADD investigations.
Demonstration of a practical approach to implementing high-throughput computing for drug discovery.
Establishment of a robust computational environment capable of supporting extensive research.

Conclusions:

The successful realization of a specialized computing facility enhances CADD research capabilities.
This implementation provides a blueprint for other institutions seeking to build similar high-throughput computing environments.
Addressing the computational demands of drug discovery is essential for efficient research progression.