The main classes of theoretical molecular descriptors are: 1) 0D-descriptors (i.e. constitutional descriptors, count descriptors), 2) 1D-descriptors (i.e. list of structural fragments, fingerprints),3) 2D-descriptors (i.e. graph invariants),4) 3D-descriptors (such as, for example, 3D-MoRSE descriptors, WHIM descriptors, GETAWAY descriptors ...

Chemical descriptors are used to calculate and to develop methods for chemical property calculations (QSPR - quantitative structure-property relationship) or chemical activity (QSAR - quantitative structure-activity relationship) calculations.

Jul 26, 2022 · 2D Molecular Descriptors. You were introduced to chemical graph theory in section 2.1 of this Libretext. Mathematical notations provide a method for describing chemical structures, and allow for computational processing of molecules in a …

Jul 28, 2023 · Here, we describe a suite of open-source Python-based post-processing routines, called PyL3dMD, for calculating 3D descriptors from MD simulations. PyL3dMD is compatible with the popular simulation package LAMMPS and enables users to compute more than 2000 3D molecular descriptors from atomic trajectories generated by MD simulations.

May 23, 2020 · To note, I have seen in several cheminformatics projects that 2D descriptors generally perform as well as 3D descriptors in QSAR modeling, and also, 2D descriptors are very fast to compute. 4-Dimensional (4D) 4D descriptors are usually derived from reference grids and molecular dynamic simulations.

Extracting features from molecules is a common task in machine learning. There are 5 different types of features: 0D, 1D, 2D, 3D, or 4D. 0D features are descriptors that describe the individual parts of the molecule together as a whole, such as the number of atoms, bond counts or the molecular weight.

Aug 13, 2024 · One-dimensional (1D) descriptors include simple properties like molecular weight, logP (lipophilicity), and hydrogen bond donors/acceptors. Two-dimensional (2D) descriptors consider structural connectivity, such as topological indices and molecular fingerprints, which help quantify chemical similarity.

In this chapter, the main classes of theoretical molecular descriptors including 0D, 1D, 2D, 3D, and 4D descriptors are described. The most significant progress over the last few years in chemometrics, cheminformatics, and bioinformatics has led to new strategies for finding new molecular descriptors.

In this chapter, the main classes of theoretical molecular descriptors including 0D, 1D, 2D, 3D, and 4D-descriptors are described. The most significant progress over the last few years in chemometrics, cheminformatics, and bioinformatics has led to new strategies for finding new molecular descriptors.

Mordred is a comprehensive, open-source chemical descriptor calculation tool designed for use in cheminformatics, drug discovery, and materials science. It can compute a vast array of descriptors based on molecular structure, ranging from simple atomic counts to more complex 3D geometry calculations.