Publicaciones de Jans Alzate-Morales
2024
Bedoya, Mauricio; Adasme-Carreño, Francisco; Peña-Martínez, Paula Andrea; Muñoz-Gutiérrez, Camila; Peña-Tejo, Luciano; Montesinos, José C. E. Márquez; Hernández-Rodríguez, Erix W.; González, Wendy; Martínez, Leandro; Alzate-Morales, Jans
Moltiverse: Molecular Conformer Generation Using Enhanced Sampling Methods Miscelánea
2024.
@misc{bedoya_moltiverse_2024,
title = {Moltiverse: Molecular Conformer Generation Using Enhanced Sampling Methods},
author = {Mauricio Bedoya and Francisco Adasme-Carreño and Paula Andrea Peña-Martínez and Camila Muñoz-Gutiérrez and Luciano Peña-Tejo and José C. E. Márquez Montesinos and Erix W. Hernández-Rodríguez and Wendy González and Leandro Martínez and Jans Alzate-Morales},
url = {https://chemrxiv.org/engage/chemrxiv/article-details/67621d996dde43c908780be8},
doi = {10.26434/chemrxiv-2024-qs0pc-v2},
year = {2024},
date = {2024-12-01},
urldate = {2025-01-03},
publisher = {Chemistry},
abstract = {Accurately predicting the diverse bound-state conformations of small molecules is crucial for successful drug discovery and design, particularly when detailed protein-ligand interactions are unknown. Established tools exist, but efficiently exploring the vast conformational space remains challenging. This work introduces Moltiverse, a novel protocol using enhanced sampling molecular dynamics (MD) simulations for conformer generation. The extended adaptive biasing force (eABF) algorithm combined with metadynamics, guided by a single collective variable (radius of gyration, RDGYR), efficiently samples the conformational landscape of a small molecule. Moltiverse demonstrates comparable accuracy and, in some cases, superior quality when benchmarked against established software like RDKit, CONFORGE, ConfGenX, Torsional diffusion, and Conformator. We present an exhaustive ranking based on eight quantitative metrics and statistical analysis for robust conformer generation algorithms comparison and provide recommendations for their improvement based on our findings. We introduce the Cofactorv1 dataset, a complementary resource for conformer generator evaluation. Unlike traditional datasets with thousands of single-conformer molecules, the Cofactorv1 dataset features only seven small molecule cofactors but with hundreds to thousands of experimental conformers per molecule (sourced from the PDB). This diversity, encompassing 15-29 rotatable bonds, poses a significant challenge for conformer generation benchmarks. Cofactorv1 is a complementary dataset that serves as a valuable resource for developing and evaluating conformer generation methods like Moltiverse, pushing the boundaries of accuracy and diversity in this relevant field.},
keywords = {},
pubstate = {published},
tppubtype = {misc}
}
Accurately predicting the diverse bound-state conformations of small molecules is crucial for successful drug discovery and design, particularly when detailed protein-ligand interactions are unknown. Established tools exist, but efficiently exploring the vast conformational space remains challenging. This work introduces Moltiverse, a novel protocol using enhanced sampling molecular dynamics (MD) simulations for conformer generation. The extended adaptive biasing force (eABF) algorithm combined with metadynamics, guided by a single collective variable (radius of gyration, RDGYR), efficiently samples the conformational landscape of a small molecule. Moltiverse demonstrates comparable accuracy and, in some cases, superior quality when benchmarked against established software like RDKit, CONFORGE, ConfGenX, Torsional diffusion, and Conformator. We present an exhaustive ranking based on eight quantitative metrics and statistical analysis for robust conformer generation algorithms comparison and provide recommendations for their improvement based on our findings. We introduce the Cofactorv1 dataset, a complementary resource for conformer generator evaluation. Unlike traditional datasets with thousands of single-conformer molecules, the Cofactorv1 dataset features only seven small molecule cofactors but with hundreds to thousands of experimental conformers per molecule (sourced from the PDB). This diversity, encompassing 15-29 rotatable bonds, poses a significant challenge for conformer generation benchmarks. Cofactorv1 is a complementary dataset that serves as a valuable resource for developing and evaluating conformer generation methods like Moltiverse, pushing the boundaries of accuracy and diversity in this relevant field.
Bravo-Moraga, Felipe; Bedoya, Mauricio; Vergara-Jaque, Ariela; Alzate-Morales, Jans
En: J. Chem. Inf. Model., vol. 64, no 12, pp. 4759–4772, 2024, ISSN: 1549-960X.
@article{Bravo-Moraga2024,
title = {Understanding the Differences of Danusertib’s Residence Time in Aurora Kinases A/B: Dissociation Paths and Key Residues Identified using Conventional and Enhanced Molecular Dynamics Simulations},
author = {Felipe Bravo-Moraga and Mauricio Bedoya and Ariela Vergara-Jaque and Jans Alzate-Morales},
doi = {10.1021/acs.jcim.4c00387},
issn = {1549-960X},
year = {2024},
date = {2024-06-24},
journal = {J. Chem. Inf. Model.},
volume = {64},
number = {12},
pages = {4759--4772},
publisher = {American Chemical Society (ACS)},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Olguín-Orellana, Gabriel J.; Abad, Juan A. De La Rosa; Camarada, María B.; Mejía-Rosales, Sergio J.; Alzate-Morales, Jans; Mariscal, Marcelo M.
On the mechanical response of graphene-capped copper nanoparticles Artículo de revista
En: Physical Chemistry Chemical Physics, vol. 26, no 3, pp. 2260–2268, 2024, ISSN: 1463-9076, 1463-9084.
@article{olguin-orellana_mechanical_2024,
title = {On the mechanical response of graphene-capped copper nanoparticles},
author = {Gabriel J. Olguín-Orellana and Juan A. De La Rosa Abad and María B. Camarada and Sergio J. Mejía-Rosales and Jans Alzate-Morales and Marcelo M. Mariscal},
url = {https://xlink.rsc.org/?DOI=D3CP05273G},
doi = {10.1039/D3CP05273G},
issn = {1463-9076, 1463-9084},
year = {2024},
date = {2024-01-01},
urldate = {2025-01-02},
journal = {Physical Chemistry Chemical Physics},
volume = {26},
number = {3},
pages = {2260–2268},
abstract = {In this study, we investigated the mechanical behavior of pristine copper (Cu) nanoparticles (NPs) and Cu@graphene (Cu@G) hybrid NPs using molecular dynamics simulations.
, In this study, we investigated the mechanical behavior of pristine copper (Cu) nanoparticles (NPs) and Cu@graphene (Cu@G) hybrid NPs using molecular dynamics simulations. The longitudinal engineering strain was calculated as a measure of compression until reaching 25% of the initial size of the NPs. The stress–strain curves revealed the elastic-to-plastic transition in the Cu NPs at a longitudinal strain of 3.57% with a yield strength of 6.15 GPa. On the other hand, the Cu@G NPs exhibited a maximum average load point at a longitudinal strain of 6.81% with a yield strength of 8.26 GPa. The hybrid Cu@G NPs showed increased strength and resistance to plastic deformation compared to the pure Cu NPs, while the calculation of the elastic modulus indicated a higher load resistance provided by the graphene coverage for the Cu@G NPs. Furthermore, the analysis of atomic configurations, dislocations, and stress distribution demonstrated that the graphene flakes play a crucial role in preventing dislocation events and faceting in the Cu@G NPs by acting as a shock absorber, distributing the applied force on themselves, and producing a more homogeneous stress distribution on the Cu NPs; additionally, they prevent the movement of Cu atoms, reducing the occurrence of dislocations and surface faceting, thanks to their supportive effect. Overall, our findings highlight the potential of hybrid nanomaterials, such as Cu@G, for enhancing the mechanical properties of metallic NPs, which could have significant implications for the development of advanced nanomaterials with improved performance in a variety of applications.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
In this study, we investigated the mechanical behavior of pristine copper (Cu) nanoparticles (NPs) and Cu@graphene (Cu@G) hybrid NPs using molecular dynamics simulations.
, In this study, we investigated the mechanical behavior of pristine copper (Cu) nanoparticles (NPs) and Cu@graphene (Cu@G) hybrid NPs using molecular dynamics simulations. The longitudinal engineering strain was calculated as a measure of compression until reaching 25% of the initial size of the NPs. The stress–strain curves revealed the elastic-to-plastic transition in the Cu NPs at a longitudinal strain of 3.57% with a yield strength of 6.15 GPa. On the other hand, the Cu@G NPs exhibited a maximum average load point at a longitudinal strain of 6.81% with a yield strength of 8.26 GPa. The hybrid Cu@G NPs showed increased strength and resistance to plastic deformation compared to the pure Cu NPs, while the calculation of the elastic modulus indicated a higher load resistance provided by the graphene coverage for the Cu@G NPs. Furthermore, the analysis of atomic configurations, dislocations, and stress distribution demonstrated that the graphene flakes play a crucial role in preventing dislocation events and faceting in the Cu@G NPs by acting as a shock absorber, distributing the applied force on themselves, and producing a more homogeneous stress distribution on the Cu NPs; additionally, they prevent the movement of Cu atoms, reducing the occurrence of dislocations and surface faceting, thanks to their supportive effect. Overall, our findings highlight the potential of hybrid nanomaterials, such as Cu@G, for enhancing the mechanical properties of metallic NPs, which could have significant implications for the development of advanced nanomaterials with improved performance in a variety of applications.
, In this study, we investigated the mechanical behavior of pristine copper (Cu) nanoparticles (NPs) and Cu@graphene (Cu@G) hybrid NPs using molecular dynamics simulations. The longitudinal engineering strain was calculated as a measure of compression until reaching 25% of the initial size of the NPs. The stress–strain curves revealed the elastic-to-plastic transition in the Cu NPs at a longitudinal strain of 3.57% with a yield strength of 6.15 GPa. On the other hand, the Cu@G NPs exhibited a maximum average load point at a longitudinal strain of 6.81% with a yield strength of 8.26 GPa. The hybrid Cu@G NPs showed increased strength and resistance to plastic deformation compared to the pure Cu NPs, while the calculation of the elastic modulus indicated a higher load resistance provided by the graphene coverage for the Cu@G NPs. Furthermore, the analysis of atomic configurations, dislocations, and stress distribution demonstrated that the graphene flakes play a crucial role in preventing dislocation events and faceting in the Cu@G NPs by acting as a shock absorber, distributing the applied force on themselves, and producing a more homogeneous stress distribution on the Cu NPs; additionally, they prevent the movement of Cu atoms, reducing the occurrence of dislocations and surface faceting, thanks to their supportive effect. Overall, our findings highlight the potential of hybrid nanomaterials, such as Cu@G, for enhancing the mechanical properties of metallic NPs, which could have significant implications for the development of advanced nanomaterials with improved performance in a variety of applications.
2023
Olguín-Orellana, Gabriel J.; Soldano, Germán J.; Alzate-Morales, Jans; Camarada, María B.; Mariscal, Marcelo M.
Can graphene improve the thermal conductivity of copper nanofluids? Artículo de revista
En: Physical Chemistry Chemical Physics, vol. 25, no 7, pp. 5489–5500, 2023, ISSN: 1463-9076, 1463-9084.
@article{olguin-orellana_can_2023,
title = {Can graphene improve the thermal conductivity of copper nanofluids?},
author = {Gabriel J. Olguín-Orellana and Germán J. Soldano and Jans Alzate-Morales and María B. Camarada and Marcelo M. Mariscal},
url = {https://xlink.rsc.org/?DOI=D3CP00064H},
doi = {10.1039/D3CP00064H},
issn = {1463-9076, 1463-9084},
year = {2023},
date = {2023-01-01},
urldate = {2025-01-02},
journal = {Physical Chemistry Chemical Physics},
volume = {25},
number = {7},
pages = {5489–5500},
abstract = {We report here that nanofluids of copper capped by graphene have an improved thermal conductivity compared to the Cu nanofluids, being up to close 30 times higher for the graphene-trilayered NPs.
, Copper (Cu) nanofluids (NFs) have attracted attention due to their high thermal conductivity, which has conferred a wide variety of applications. However, their high reactivity favors oxidation, corrosion and aggregation, leading them to lose their properties of interest. Copper capped by graphene (Cu@G) core@shell nanoparticles (NPs) have also attracted interest from the medical and industrial sectors because graphene can shield the Cu NPs from undesired phenomena. Additionally, they share some properties that expand the range of applications of Cu NFs. In this work, new Morse potentials are reported to reproduce the behavior of Cu@G NPs through molecular dynamics. Coordination-dependent Morse parameters were fitted for C, H, and Cu based on density functional theory calculations. Then, these parameters were implemented to evaluate the thermal conductivity of Cu@G NFs employing the Green–Kubo formalism, with NPs from 1.5 to 6.1 nm at 100 to 800 K, varying the size, the number of layers and the orientation of the graphene flakes. It was found that Cu@G NFs are stable and have an improved thermal conductivity compared to the Cu NFs, being 3.7 to 18.2 times higher at 300 K with only one graphene layer and above 26.2 times higher for the graphene-trilayered NPs. These values can be higher for temperatures below 300 K. Oppositely, the size, homogeneity and orientations of the graphene flakes did not affect the thermal conductivity of the Cu@G NFs.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
We report here that nanofluids of copper capped by graphene have an improved thermal conductivity compared to the Cu nanofluids, being up to close 30 times higher for the graphene-trilayered NPs.
, Copper (Cu) nanofluids (NFs) have attracted attention due to their high thermal conductivity, which has conferred a wide variety of applications. However, their high reactivity favors oxidation, corrosion and aggregation, leading them to lose their properties of interest. Copper capped by graphene (Cu@G) core@shell nanoparticles (NPs) have also attracted interest from the medical and industrial sectors because graphene can shield the Cu NPs from undesired phenomena. Additionally, they share some properties that expand the range of applications of Cu NFs. In this work, new Morse potentials are reported to reproduce the behavior of Cu@G NPs through molecular dynamics. Coordination-dependent Morse parameters were fitted for C, H, and Cu based on density functional theory calculations. Then, these parameters were implemented to evaluate the thermal conductivity of Cu@G NFs employing the Green–Kubo formalism, with NPs from 1.5 to 6.1 nm at 100 to 800 K, varying the size, the number of layers and the orientation of the graphene flakes. It was found that Cu@G NFs are stable and have an improved thermal conductivity compared to the Cu NFs, being 3.7 to 18.2 times higher at 300 K with only one graphene layer and above 26.2 times higher for the graphene-trilayered NPs. These values can be higher for temperatures below 300 K. Oppositely, the size, homogeneity and orientations of the graphene flakes did not affect the thermal conductivity of the Cu@G NFs.
, Copper (Cu) nanofluids (NFs) have attracted attention due to their high thermal conductivity, which has conferred a wide variety of applications. However, their high reactivity favors oxidation, corrosion and aggregation, leading them to lose their properties of interest. Copper capped by graphene (Cu@G) core@shell nanoparticles (NPs) have also attracted interest from the medical and industrial sectors because graphene can shield the Cu NPs from undesired phenomena. Additionally, they share some properties that expand the range of applications of Cu NFs. In this work, new Morse potentials are reported to reproduce the behavior of Cu@G NPs through molecular dynamics. Coordination-dependent Morse parameters were fitted for C, H, and Cu based on density functional theory calculations. Then, these parameters were implemented to evaluate the thermal conductivity of Cu@G NFs employing the Green–Kubo formalism, with NPs from 1.5 to 6.1 nm at 100 to 800 K, varying the size, the number of layers and the orientation of the graphene flakes. It was found that Cu@G NFs are stable and have an improved thermal conductivity compared to the Cu NFs, being 3.7 to 18.2 times higher at 300 K with only one graphene layer and above 26.2 times higher for the graphene-trilayered NPs. These values can be higher for temperatures below 300 K. Oppositely, the size, homogeneity and orientations of the graphene flakes did not affect the thermal conductivity of the Cu@G NFs.
