RRD 1.1.1

A package to compute the Reactivity-Related bond/atom-wise Descriptors (RRD).

Installation

# 安装依赖
pip install RRD

Usage

from RRD import RRDCalculator
RRDC = RRDCalculator(scale=True)
smiles = 'CCCC'

## one smiles
dfa, dfb = RRDC.transform(smiles)

## many smiles: compute in parallel
smiles_list = [smiles for i in range(20)]
res = RRDC.batch_transform(smiles_list, n_jobs=-1)

TODO list

• Buried Volume: trained model-based
• Frontier orbital energy

List of descriptors in our RRD package

Refernces

• [1]. Guan, Yanfei, et al. "Regio-selectivity prediction with a machine-learned reaction representation and on-the-fly quantum mechanical descriptors." Chemical science 12.6 (2021): 2198-2208.
• [2]. J.Gasteiger, M. Marseli, Iterative Equalization of Oribital Electronegatiity A Rapid Access to Atomic Charges, Tetrahedron Vol 36 p3219 1980
• [3]. Wildman, Scott A., and Gordon M. Crippen. "Prediction of physicochemical parameters by atomic contributions." Journal of chemical information and computer sciences 39.5 (1999): 868-873.
• [4]. Miller and Savchik, JACS 101(24) 7206-7213, 1979.
• [5]. Cao, Chenzhong, and Li Liu. "Topological steric effect index and its application." Journal of chemical information and computer sciences 44.2 (2004): 678-687.
• [6]. St John, Peter C., et al. "Prediction of organic homolytic bond dissociation enthalpies at near chemical accuracy with sub-second computational cost." Nature communications 11.1 (2020): 1-12.
• [7]. A. Poater, F. Ragone, R. Mariz, R. Dorta and L. Cavallo, Chem. Eur. J. 2010, 16, 14348–14353.