A Comprehensive Computational Framework for Materials Design, Ab Initio Modeling, and Molecular Docking

TL;DR

This paper introduces an integrated computational framework combining stochastic simulation, ab initio modeling, and molecular docking to accelerate materials and molecular design across scientific domains.

Contribution

It presents a novel, comprehensive workflow that unifies multiple computational tools and techniques for systematic investigation of chemical and material properties.

Findings

The framework enables efficient exploration of high-dimensional chemical spaces.

It demonstrates applicability to drug development and materials science.

Open-source tools make the approach scalable and cost-effective.

Abstract

To facilitate rational molecular and materials design, this research proposes an integrated computational framework that combines stochastic simulation, ab initio quantum chemistry, and molecular docking. The suggested workflow allows systematic investigation of structural stability, binding affinity, and electronic properties across biological and materials science domains by utilizing complementary tools like Avogadro for molecular construction and visualization, AutoDock for docking and interaction analysis, and ORCA for high-level electronic structure computations. Uncertainty, configurational sampling, and optimization in high-dimensional chemical spaces are addressed by combining Monte Carlo-based and annealing-inspired techniques. The work shows how materials science ideas such as polymer design, thin films, crystalline lattices, and bioelectronic systems can be applied to drug development. On-device, open-source computational methods are viable, scalable, and economical, as demonstrated by comparative platform analysis. All things considered, the findings highlight the need of an integrated, repeatable computational pipeline for speeding up de novo molecule assembly and materials architecture while lowering experimental risk and expense.