The first type of techniques we discuss focuses on conformer sampling in transition metal chemistry. The exploration of low-energy chemical space is essential for the investigation of quantitative structure-activity relationships (QSAR) because the functional characteristics of molecules are largely determined by the most stable configuration. In addition, conformer sampling also plays a crucial role in several different types of computational analyses, such as docking, pharmacophore searching, and receptor-based virtual screening. Moreover, ligand conformations have profound effects on catalytic activities. However, capturing reasonable conformer ensemble is significantly challenging because of the huge conformational space of flexible molecules. Therefore, software which can accurately and efficiently locate the local minimum on the potential energy surface (PES) is highly relevant. While most packages explore the low-energy chemical space of drug-like molecules, such as Balloon, RDKit, OMEGA, and Forg2, conformer sampling in transition metal chemistry is less well investigated. For example, CREST develops a meta-dynamics driven search algorithm at a semiempirical quantum mechanics GFNn-xTB level to explore the conformational ensembles for almost any chemical species in either the gas-phase or explicit solvation. In terms of the sampling of TMCs, bond breaking may occur due to the excess bias potential exerted to drive the sampling and bond constraints need to be applied to remedy this issue. Simultaneously, Molassembler 54 proposes a graph-based method to construct the 3D structures of (in)organic molecules. Each molecule model is embedded as an undirected graph where atoms are represented as nodes and chemical bonds are encoded as edges. The spatial orientations of bonded atoms are traced in an index of permutation, including atom-centered stereopermutators which capture the orientation differences of neighbors around a central atom and bond-centered stereopermutators which capture bond rotation differences. Both types of representations are used for spatial modeling to generate a distance bounds matrix, which is finally converted to spatial atom coordinates via distance geometry (DG) to generate the conformer ensemble. However, the limited accessibility to stereopermutators may lead to failures to conformer generation and since no strict algorithm is introduced to control the generation of conformer at local minima, generated structures are not recommended for downstream tasks without further geometry optimization.