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Mechanistic models in biology offer a quantitative framework for describing and analyzing biological processes. These models enable the integration of accumulated knowledge and support the accurate prediction and optimization of biologically active compounds. In this study, we provide an overview of several widely used mechanistic models related to growth and decay, highlighting their properties that can be effectively applied in molecular docking. We propose a novel approach that integrates mechanistic modeling with docking analysis, offering a statistically robust method for optimizing bioactive analogs. This approach has the potential to facilitate the design of new compounds with improved pharmacokinetic profiles.

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Intelligent Analysis of Mechanistic Models and Docking in Biomolecule Research

  • 会议论文

  • 发表日期：

    2025年

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  • Fatima Sapundzhi,
  • Slavi Georgiev,
  • Meglena Lazarova,
  • Ivan Altaparmakov,
  • Venelin Todorov,
  • Antonina Ivanova

摘要

Mechanistic models in biology offer a quantitative framework for describing and analyzing biological processes. These models enable the integration of accumulated knowledge and support the accurate prediction and optimization of biologically active compounds. In this study, we provide an overview of several widely used mechanistic models related to growth and decay, highlighting their properties that can be effectively applied in molecular docking. We propose a novel approach that integrates mechanistic modeling with docking analysis, offering a statistically robust method for optimizing bioactive analogs. This approach has the potential to facilitate the design of new compounds with improved pharmacokinetic profiles.