An efficient algorithm for searching low-energy conformers of cyclic and acyclic molecules

构象异构 化学 摄动(天文学) 分子 脂环化合物 计算化学 立体化学 物理 量子力学 有机化学
作者
Midori Goto,Eiji Ōsawa
出处
期刊:Journal of the Chemical Society 卷期号: (2): 187-198 被引量:384
标识
DOI:10.1039/p29930000187
摘要

A set of strategies for exhaustively finding low-energy conformers of cyclic, acyclic or alicyclic molecules is presented. Starting from any conformation, local perturbation is systematically applied to all the flexible portions of the molecule in question to produce candidates of new conformation. The perturbations consist of flapping and/or flipping for endocyclic bonds and stepwise rotation for acyclic bonds. The conformations they produced are believed to lie close to the initial geometry in the conformational space. The global energy minimum (GEM) structure of the starting domain of conformational space can be quickly reached by always choosing the most stable of the conformers produced in the last perturbation cycle as the next initial structure. Once GEM of the domain is reached, the local perturbations direct the search gradually to higher and higher energy regions while exhaustively finding all the low-energy conformers therein. The variable search-limit strategy allows one to use unstable conformers as the initial structure for perturbation to ensure the exhaustiveness of the search in the low-energy region. By further increasing the search-limit, new domains of conformational space may be found. A program CONFLEX3 containing several additional strategies for improved performance has been tested for n-alkanes up to decane and cycloalkanes up to cyclododecane.

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
兮曦123完成签到,获得积分10
2秒前
科研通AI6.3应助111采纳,获得10
2秒前
顾矜应助zqz421采纳,获得10
2秒前
3秒前
科研通AI6.1应助lily采纳,获得10
5秒前
5秒前
6秒前
Ou完成签到,获得积分10
6秒前
luminious完成签到,获得积分10
7秒前
NexusExplorer应助waoller1采纳,获得10
8秒前
JamesPei应助waoller1采纳,获得10
8秒前
Ava应助waoller1采纳,获得10
8秒前
脑洞疼应助waoller1采纳,获得10
8秒前
桐桐应助waoller1采纳,获得10
8秒前
天天快乐应助waoller1采纳,获得10
8秒前
8秒前
Lucas应助waoller1采纳,获得10
8秒前
希望天下0贩的0应助waoller1采纳,获得10
8秒前
丘比特应助waoller1采纳,获得10
8秒前
9秒前
jiajia发布了新的文献求助10
10秒前
打打应助文静的猕猴桃采纳,获得10
10秒前
11秒前
科研小白完成签到 ,获得积分10
11秒前
111发布了新的文献求助10
12秒前
充电宝应助清脆的凉面采纳,获得10
13秒前
Shi发布了新的文献求助10
13秒前
mabenchem完成签到,获得积分20
14秒前
慕山完成签到 ,获得积分10
14秒前
14秒前
15秒前
想人陪的飞薇完成签到 ,获得积分10
15秒前
拼搏的白云完成签到,获得积分10
16秒前
Rui_Rui应助听云采纳,获得20
17秒前
20秒前
20秒前
amy完成签到 ,获得积分10
21秒前
21秒前
22秒前
小番茄发布了新的文献求助10
23秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
PowerCascade: A Synthetic Dataset for Cascading Failure Analysis in Power Systems 2000
Various Faces of Animal Metaphor in English and Polish 800
Signals, Systems, and Signal Processing 610
Photodetectors: From Ultraviolet to Infrared 500
On the Dragon Seas, a sailor's adventures in the far east 500
Yangtze Reminiscences. Some Notes And Recollections Of Service With The China Navigation Company Ltd., 1925-1939 500
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 物理 内科学 复合材料 催化作用 物理化学 光电子学 电极 细胞生物学 基因 无机化学
热门帖子
关注 科研通微信公众号,转发送积分 6349124
求助须知:如何正确求助?哪些是违规求助? 8164200
关于积分的说明 17177195
捐赠科研通 5405552
什么是DOI,文献DOI怎么找? 2862070
邀请新用户注册赠送积分活动 1839826
关于科研通互助平台的介绍 1689134