Core/Sheath Organic Nanocable Constructed with a Master-Slave Molecular Pair for Optically Switched Memories

2011 ◽  
Vol 23 (43) ◽  
pp. 5059-5063 ◽  
Author(s):  
Gang Xu ◽  
Qing-Dan Yang ◽  
Feng-Yun Wang ◽  
Wen-Feng Zhang ◽  
Yong-Bing Tang ◽  
...  
Keyword(s):  
Molecular Pair

mmpdb: An Open Source Matched Molecular Pair Platform for Large Multi-Property Datasets

2018 ◽  
Author(s):  
Andrew Dalke ◽  
Jerome Hert ◽  
Christian Kramer
Keyword(s):  
Open Source ◽  
Large Datasets ◽  
Molecular Pair ◽  
New Algorithms

We present mmpdb, an open source Matched Molecular Pair (MMP) platform to create, compile, store, retrieve, and use MMP rules. mmpdb is suitable for the large datasets typically found in pharmaceutical and agrochemical companies and provides new algorithms for fragment canonicalization and stereochemistry handling. The platform is written in Python and based on the RDKit toolkit. mmpdb is freely available.

Bioactivity Prediction Based on Matched Molecular Pair and Matched Molecular Series Methods

2020 ◽  
Vol 26 (33) ◽  
pp. 4195-4205
Author(s):  
Xiaoyu Ding ◽  
Chen Cui ◽  
Dingyan Wang ◽  
Jihui Zhao ◽  
Mingyue Zheng ◽  
...  
Keyword(s):  
Prediction Model ◽  
Large Scale ◽  
Prediction Models ◽  
Predictive Accuracy ◽  
Lead Optimization ◽  
Consensus Method ◽  
Molecular Pair ◽  
Bioactivity Prediction ◽  
Compound Synthesis ◽  
Consensus Modeling

Background: Enhancing a compound’s biological activity is the central task for lead optimization in small molecules drug discovery. However, it is laborious to perform many iterative rounds of compound synthesis and bioactivity tests. To address the issue, it is highly demanding to develop high quality in silico bioactivity prediction approaches, to prioritize such more active compound derivatives and reduce the trial-and-error process. Methods: Two kinds of bioactivity prediction models based on a large-scale structure-activity relationship (SAR) database were constructed. The first one is based on the similarity of substituents and realized by matched molecular pair analysis, including SA, SA_BR, SR, and SR_BR. The second one is based on SAR transferability and realized by matched molecular series analysis, including Single MMS pair, Full MMS series, and Multi single MMS pairs. Moreover, we also defined the application domain of models by using the distance-based threshold. Results: Among seven individual models, Multi single MMS pairs bioactivity prediction model showed the best performance (R2 = 0.828, MAE = 0.406, RMSE = 0.591), and the baseline model (SA) produced the most lower prediction accuracy (R2 = 0.798, MAE = 0.446, RMSE = 0.637). The predictive accuracy could further be improved by consensus modeling (R2 = 0.842, MAE = 0.397 and RMSE = 0.563). Conclusion: An accurate prediction model for bioactivity was built with a consensus method, which was superior to all individual models. Our model should be a valuable tool for lead optimization.

scholarly journals Спектральные моменты характеристик бинарных взаимодействий между линейными молекулами

2021 ◽  
Vol 129 (3) ◽  
pp. 253
Author(s):  
А.В. Соколов ◽  
А.П. Коузов ◽  
Ж.В. Булдырева ◽  
Н.И. Егорова
Keyword(s):  
Interaction Potential ◽  
Spectral Moments ◽  
New Approach ◽  
Relaxation Matrix ◽  
Arbitrary Rank ◽  
Molecular Pair ◽  
Linear Molecules ◽  
Computer Codes ◽  
Spectral Distributions ◽  
The Way

A new approach to derive symmetrized expressions of leading classical moments of spectral distributions characterizing different anisotropic terms of the interaction potential for the case of two liear molecules is presented. The results allow to calculate diffuse shapes formed by transitions between continuous eigenstates of a molecular pair and open the way to account for the nonMarkov effects (due to finite collision durations) in the rotatonal relaxation matrix of an arbitrary rank. The approach is also applied to the spectral moments of vector and tensor characteristics determining the band intensities in the collision-induced spectra of linear molecules. Generally, the use of symmetrized expressions lead to considerably faster computer codes.

scholarly journals A structure–kinetic relationship study using matched molecular pair analysis

2020 ◽  
Vol 11 (11) ◽  
pp. 1285-1294
Author(s):  
Doris A. Schuetz ◽  
Lars Richter ◽  
Riccardo Martini ◽  
Gerhard F. Ecker
Keyword(s):  
Large Scale ◽  
Kinetic Relationship ◽  
Molecular Pair ◽  
Large Scale Study ◽  
Relationship Study ◽  
Pair Analysis

A large-scale study employing matched molecular pair (MMP) analysis to uncover the contribution of a compound's polarity to its association and dissociation rates.

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