Computational Generation of Substrate-Specific Molecular Cages

TL;DR

This paper introduces a computational method for designing substrate-specific molecular cages by modeling them as constrained graphs and optimizing their structure for efficient substrate binding.

Contribution

The authors develop an algorithm that constructs minimal molecular cages with specific binding patterns, advancing the design of substrate-targeted molecular structures.

Findings

Successfully designed cages with over a hundred atoms.

Developed an efficient algorithm for constructing minimal molecular cages.

Demonstrated the method's ability to generate substrate-specific molecular structures.

Abstract

In this paper, we propose a method to build molecular cages designed to capture a specific substrate. We model a cage as a graph of atoms with coordinates in space, and several constraints on their edges (degree, length and angle). We use a simple method to place binding patterns which are able to interact with certain parts of the substrate. We then propose an algorithm which considers all possible ways of connecting these binding patterns and try to construct the smallest possible molecular paths realizing these connections. We investigate many variants of our method in order to obtain the most efficient algorithm, able to build cages of more than a hundred atoms.