AMADAR: a python-based package for large scale prediction of Diels-Alder transition state geometries and IRC path analysis.

ABSTRACT: Predicting transition state geometries is one of the most challenging tasks in computational chemistry, which often requires expert-based knowledge and permanent human intervention. This short communication reports technical details and preliminary results of a python-based tool (AMADAR) designed to generate any Diels-Alder (DA) transition state geometry (TS) and analyze determined IRC paths in a (quasi-)automated fashion, given the product SMILES. Two modules of the package are devoted to performing, from IRC paths, reaction force analyses (RFA) and atomic (fragment) decompositions of the reaction force F and reaction force constant [Formula: see text]. The performance of the protocol has been assessed using a dataset of 2000 DA cycloadducts retrieved from the ZINC database. The sequentia

SUBMITTER: Isamura BK 

PROVIDER: S-EPMC9202188 | biostudies-literature | 2022 Jun

REPOSITORIES: biostudies-literature