QuBiLS-MIDAS: A parallel free-software for molecular descriptors computation based on multilinear algebraic maps

2014 ◽  
Vol 35 (18) ◽  
pp. 1395-1409 ◽  
Author(s):  
César R. García-Jacas ◽  
Yovani Marrero-Ponce ◽  
Liesner Acevedo-Martínez ◽  
Stephen J. Barigye ◽  
José R. Valdés-Martiní ◽  
...  
Keyword(s):  
Molecular Descriptors ◽  
Free Software ◽  
Algebraic Maps

Multi-Server Approach for High-Throughput Molecular Descriptors Calculation based on Multi-Linear Algebraic Maps

2014 ◽  
Vol 34 (1) ◽  
pp. 60-69 ◽  
Author(s):  
César R. García-Jacas ◽  
Longendri Aguilera-Mendoza ◽  
Reisel González-Pérez ◽  
Yovani Marrero-Ponce ◽  
Liesner Acevedo-Martínez ◽  
...  
Keyword(s):  
High Throughput ◽  
Molecular Descriptors ◽  
Algebraic Maps ◽  
Multi Server

QSAR modeling for predicting carcinogenic potency of nitroso-compounds using 0D-2D molecular descriptors

2007 ◽  
Author(s):  
Maykel González ◽  
Aliuska Helguera ◽  
M. Natália Cordeiro ◽  
Miguel Cabrera Pérez ◽  
Reinaldo Ruiz ◽  
...  
Keyword(s):  
Molecular Descriptors ◽  
Nitroso Compounds ◽  
Qsar Modeling ◽  
Carcinogenic Potency

Implementation of an Inventory Control System for a Computer Center Using QR Codes on Android Mobile Devices

2017 ◽  
Vol 7 (11) ◽  
pp. 50
Author(s):  
Gustavo Poot Tah ◽  
Erika Llanes Castro ◽  
José Luis López Martínez ◽  
Victor Chi Pech
Keyword(s):  
Control System ◽  
Inventory Control ◽  
Mobile Devices ◽  
Mobile Application ◽  
Free Software ◽  
Qr Codes ◽  
Design And Development ◽  
Computer Center

This paper presents the design and development of a mobile application that uses QR codes for the inventory control of a computer center. This application was developed to support the administration of the computer center of the Multidisciplinary Unit Tizimin, with the aim to reduce costs and time of searching for articles when making an inventory, by leveraging the capabilities of smartphones and tablets. The implementation of the system was carried out using free software.

Intrinsic Stacking Interactions of Natural and Artificial Nucleobases

2019 ◽  
Author(s):  
Drew P. Harding ◽  
Laura J. Kingsley ◽  
Glen Spraggon ◽  
Steven Wheeler
Keyword(s):  
Gas Phase ◽  
Electrostatic Interactions ◽  
Density Functional ◽  
Molecular Descriptors ◽  
Stacking Interactions ◽  
Interaction Energies ◽  
Functional Theory ◽  
Binding Partner ◽  
Heavy Atoms ◽  
Wide Range

The intrinsic (gas-phase) stacking energies of natural and artificial nucleobases were explored using density functional theory (DFT) and correlated ab initio methods. Ranking the stacking strength of natural nucleobase dimers revealed a preference in binding partner similar to that seen from experiments, namely G > C > A > T > U. Decomposition of these interaction energies using symmetry-adapted perturbation theory (SAPT) showed that these dispersion dominated interactions are modulated by electrostatics. Artificial nucleobases showed a similar stacking preference for natural nucleobases and were also modulated by electrostatic interactions. A robust predictive multivariate model was developed that quantitively predicts the maximum stacking interaction between natural and a wide range of artificial nucleobases using molecular descriptors based on computed electrostatic potentials (ESPs) and the number of heavy atoms. This model should find utility in designing artificial nucleobase analogs that exhibit stacking interactions comparable to those of natural nucleobases. Further analysis of the descriptors in this model unveil the origin of superior stacking abilities of certain nucleobases, including cytosine and guanine.

Visualizing 3D Molecular Structures Using an Augmented Reality App

2019 ◽  
Author(s):  
Kristina Eriksen ◽  
Bjarne Nielsen ◽  
Michael Pittelkow
Keyword(s):  
Augmented Reality ◽  
Small Molecules ◽  
Computer Modelling ◽  
Simple Procedure ◽  
3D Structure ◽  
Molecular Structures ◽  
Free Software ◽  
Programming Skills ◽  
2D Space ◽  
Made In

<p>We present a simple procedure to make an augmented reality app to visualize any 3D chemical model. The molecular structure may be based on data from crystallographic data or from computer modelling. This guide is made in such a way, that no programming skills are needed and the procedure uses free software and is a way to visualize 3D structures that are normally difficult to comprehend in the 2D space of paper. The process can be applied to make 3D representation of any 2D object, and we envisage the app to be useful when visualizing simple stereochemical problems, when presenting a complex 3D structure on a poster presentation or even in audio-visual presentations. The method works for all molecules including small molecules, supramolecular structures, MOFs and biomacromolecules.</p>

Free Software Act

SCRIPT-ed ◽  
2004 ◽  
pp. 636-638 ◽  
Author(s):  
Maureen O'Sullivan
Keyword(s):  
Free Software

Quantitative Structure-Property Relationship (QSPR) Study of the Hydrophobicity of Phenols and 2-(Aryloxy-a-acetyl)-phenoxathiin Derivatives

2008 ◽  
Vol 59 (11) ◽  
Author(s):  
Adrian Beteringhe ◽  
Ana Cristina Radutiu ◽  
Titus Constantinescu ◽  
Luminita Patron ◽  
Alexandru T. Balaban
Keyword(s):  
Water Solubility ◽  
Molecular Descriptors ◽  
Log P ◽  
Structure Property ◽  
Substituted Phenols ◽  
Reverse Phase ◽  
Aromaticity Index ◽  
Structure Property Relationship ◽  
Layer Chromatography ◽  
Energy Of Formation

In a preceding study, the molecular hydrophobicity (RM0) was determined experimentally from reverse-phase thin-layer chromatography data for several substituted phenols and 2-(aryloxy-a-acetyl)-phenoxathiin derivatives, obtained from the corresponding phenoxides and 2-(a-bromoacetyl)-phenoxathiin. QSPR correlations for RM0 were explored using four calculated molecular descriptors: the water solubility parameter (log Sw), log P, the Gibbs energy of formation (DGf), and the aromaticity index (HOMA). Triparametric correlations do not improve substantially the biparametric correlation of RM0 in terms of log Sw and HOMA.

Generalized Molecular Descriptors Derived From Event-Based Discrete Derivative

2016 ◽  
Vol 22 (33) ◽  
pp. 5095-5113 ◽  
Author(s):  
Oscar Martínez-Santiago ◽  
Reisel Cabrera ◽  
Yovani Marrero-Ponce ◽  
Stephen Barigye ◽  
Huong Le-Thi-Thu ◽  
...  
Keyword(s):  
Molecular Descriptors ◽  
Discrete Derivative ◽  
Event Based

Molecular Topology and Other Promiscuity Determinants as Predictors of Therapeutic Class - A Theoretical Framework to Guide Drug Repositioning?

2018 ◽  
Vol 18 (13) ◽  
pp. 1110-1122 ◽  
Author(s):  
Juan F. Morales ◽  
Lucas N. Alberca ◽  
Sara Chuguransky ◽  
Mauricio E. Di Ianni ◽  
Alan Talevi ◽  
...  
Keyword(s):  
Molecular Descriptors ◽  
Drug Repositioning ◽  
Drug Repurposing ◽  
Topological Descriptors ◽  
Log P ◽  
Acidity Constant ◽  
Molecular Topology ◽  
Clustering Methods ◽  
Mean Values ◽  
Qsar Models

Much interest has been paid in the last decade on molecular predictors of promiscuity, including molecular weight, log P, molecular complexity, acidity constant and molecular topology, with correlations between promiscuity and those descriptors seemingly being context-dependent. It has been observed that certain therapeutic categories (e.g. mood disorders therapies) display a tendency to include multi-target agents (i.e. selective non-selectivity). Numerous QSAR models based on topological descriptors suggest that the topology of a given drug could be used to infer its therapeutic applications. Here, we have used descriptive statistics to explore the distribution of molecular topology descriptors and other promiscuity predictors across different therapeutic categories. Working with the publicly available ChEMBL database and 14 molecular descriptors, both hierarchical and non-hierchical clustering methods were applied to the descriptors mean values of the therapeutic categories after the refinement of the database (770 drugs grouped into 34 therapeutic categories). On the other hand, another publicly available database (repoDB) was used to retrieve cases of clinically-approved drug repositioning examples that could be classified into the therapeutic categories considered by the aforementioned clusters (111 cases), and the correspondence between the two studies was evaluated. Interestingly, a 3- cluster hierarchical clustering scheme based on only 14 molecular descriptors linked to promiscuity seem to explain up to 82.9% of approved cases of drug repurposing retrieved of repoDB. Therapeutic categories seem to display distinctive molecular patterns, which could be used as a basis for drug screening and drug design campaigns, and to unveil drug repurposing opportunities between particular therapeutic categories.

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