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Application of I TASSER, trRosetta, UCSF Chimera, HADDOCK server, and HEX loria for De Novo and In Silico Design of Proteins
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Perspective of drug design with high-performance computing.

Zhe Li1, Hui Li2, Kunqian Yu2

  • 1Guangdong Provincial Key Laboratory of New Drug Design and Evaluation, School of Pharmaceutical Sciences, Sun Yat-Sen University, China.

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Computational drug design accelerates discovery using high-performance computing. This review covers applications, advances, and future directions for faster drug development.

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Area of Science:

  • Computational chemistry
  • Pharmacology
  • Bioinformatics

Background:

  • Drug discovery is a lengthy and expensive process.
  • Computational methods offer potential to streamline drug development.
  • High-performance computing (HPC) is crucial for complex simulations.

Purpose of the Study:

  • To summarize applications of computational drug design.
  • To review recent advances in the field.
  • To outline future directions for accelerating drug discovery.

Main Methods:

  • Literature review of computational drug design.
  • Analysis of high-performance computing applications in drug discovery.
  • Synthesis of current trends and future prospects.

Main Results:

  • Computational drug design encompasses various applications like virtual screening and molecular modeling.
  • Recent advances include AI/ML integration and improved simulation techniques.
  • HPC enables faster and more accurate predictions.

Conclusions:

  • Computational drug design, powered by HPC, is vital for efficient drug discovery.
  • Continued advancements in algorithms and computing power will further accelerate the process.
  • Interdisciplinary collaboration is key to realizing the full potential of computational approaches.