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Dive into the research topics where Alberto J.M. Martin is active.

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Featured researches published by Alberto J.M. Martin.


Journal of Biomolecular Structure & Dynamics | 2016

Multi-drug resistance profile of PR20 HIV-1 protease is attributed to distorted conformational and drug binding landscape: molecular dynamics insights

Sarentha Chetty; Soumendranath Bhakat; Alberto J.M. Martin; Mahmoud E. S. Soliman

The PR20 HIV-1 protease, a variant with 20 mutations, exhibits high levels of multi-drug resistance; however, to date, there has been no report detailing the impact of these 20 mutations on the conformational and drug binding landscape at a molecular level. In this report, we demonstrate the first account of a comprehensive study designed to elaborate on the impact of these mutations on the dynamic features as well as drug binding and resistance profile, using extensive molecular dynamics analyses. Comparative MD simulations for the wild-type and PR20 HIV proteases, starting from bound and unbound conformations in each case, were performed. Results showed that the apo conformation of the PR20 variant of the HIV protease displayed a tendency to remain in the open conformation for a longer period of time when compared to the wild type. This led to a phenomena in which the inhibitor seated at the active site of PR20 tends to diffuse away from the binding site leading to a significant change in inhibitor–protein association. Calculating the per-residue fluctuation (RMSF) and radius of gyration, further validated these findings. MM/GBSA showed that the occurrence of 20 mutations led to a drop in the calculated binding free energies (ΔGbind) by ~25.17 kcal/mol and ~5 kcal/mol for p2-NC, a natural peptide substrate, and darunavir, respectively, when compared to wild type. Furthermore, the residue interaction network showed a diminished inter-residue hydrogen bond network and changes in inter-residue connections as a result of these mutations. The increased conformational flexibility in PR20 as a result of loss of intra- and inter-molecular hydrogen bond interactions and other prominent binding forces led to a loss of protease grip on ligand. It is interesting to note that the difference in conformational flexibility between PR20 and WT conformations was much higher in the case of substrate-bound conformation as compared to DRV. Thus, developing analogues of DRV by retaining its key pharmacophore features will be the way forward in the search for novel protease inhibitors against multi-drug resistant strains.


Frontiers in Physiology | 2017

On Biophysical Properties and Sensitivity to Gap Junction Blockers of Connexin 39 Hemichannels Expressed in HeLa Cells

Aníbal A. Vargas; Bruno A. Cisterna; Fujiko Saavedra-Leiva; Luis A. Cea; Alex H. Vielma; Sebastian E. Gutierrez-Maldonado; Alberto J.M. Martin; Claudia Pareja-Barrueto; Yerko Escalona; Oliver Schmachtenberg; Carlos F. Lagos; Tomas Perez-Acle; Juan C. Sáez

Although connexins (Cxs) are broadly expressed by cells of mammalian organisms, Cx39 has a very restricted pattern of expression and the biophysical properties of Cx39-based channels [hemichannels (HCs) and gap junction channels (GJCs)] remain largely unknown. Here, we used HeLa cells transfected with Cx39 (HeLa-Cx39 cells) in which intercellular electrical coupling was not detected, indicating the absence of GJCs. However, functional HCs were found on the surface of cells exposed to conditions known to increase the open probability of other Cx HCs (e.g., extracellular divalent cationic-free solution (DCFS), extracellular alkaline pH, mechanical stimulus and depolarization to positive membrane potentials). Cx39 HCs were blocked by some traditional Cx HC blockers, but not by others or a pannexin1 channel blocker. HeLa-Cx39 cells showed similar resting membrane potentials (RMPs) to those of parental cells, and exposure to DCFS reduced RMPs in Cx39 transfectants, but not in parental cells. Under these conditions, unitary events of ~75 pS were frequent in HeLa-Cx39 cells and absent in parental cells. Real-time cellular uptake experiments of dyes with different physicochemical features, as well as the application of a machine-learning approach revealed that Cx39 HCs are preferentially permeable to molecules characterized by six categories of descriptors, namely: (1) electronegativity, (2) ionization potential, (3) polarizability, (4) size and geometry, (5) topological flexibility and (6) valence. However, Cx39 HCs opened by mechanical stimulation or alkaline pH were impermeable to Ca2+. Molecular modeling of Cx39-based channels suggest that a constriction present at the intracellular portion of the para helix region co-localizes with an electronegative patch, imposing an energetic and steric barrier, which in the case of GJCs may hinder channel function. Results reported here demonstrate that Cx39 form HCs and add to our understanding of the functional roles of Cx39 HCs under physiological and pathological conditions in cells that express them.


PLOS ONE | 2016

Graphlet based metrics for the comparison of gene regulatory networks

Alberto J.M. Martin; Calixto Dominguez; Sebastián Contreras-Riquelme; David S. Holmes; Tomas Perez-Acle

Understanding the control of gene expression remains one of the main challenges in the post-genomic era. Accordingly, a plethora of methods exists to identify variations in gene expression levels. These variations underlay almost all relevant biological phenomena, including disease and adaptation to environmental conditions. However, computational tools to identify how regulation changes are scarce. Regulation of gene expression is usually depicted in the form of a gene regulatory network (GRN). Structural changes in a GRN over time and conditions represent variations in the regulation of gene expression. Like other biological networks, GRNs are composed of basic building blocks called graphlets. As a consequence, two new metrics based on graphlets are proposed in this work: REConstruction Rate (REC) and REC Graphlet Degree (RGD). REC determines the rate of graphlet similarity between different states of a network and RGD identifies the subset of nodes with the highest topological variation. In other words, RGD discerns how th GRN was rewired. REC and RGD were used to compare the local structure of nodes in condition-specific GRNs obtained from gene expression data of Escherichia coli, forming biofilms and cultured in suspension. According to our results, most of the network local structure remains unaltered in the two compared conditions. Nevertheless, changes reported by RGD necessarily imply that a different cohort of regulators (i.e. transcription factors (TFs)) appear on the scene, shedding light on how the regulation of gene expression occurs when E. coli transits from suspension to biofilm. Consequently, we propose that both metrics REC and RGD should be adopted as a quantitative approach to conduct differential analyses of GRNs. A tool that implements both metrics is available as an on-line web server (http://dlab.cl/loto).


Biochemical and Biophysical Research Communications | 2017

Stochastic simulation of multiscale complex systems with PISKaS: A rule-based approach

Tomas Perez-Acle; Ignacio Fuenzalida; Alberto J.M. Martin; Rodrigo Santibáñez; Rodrigo Avaria; Alejandro Bernardin; Alvaro M. Bustos; Daniel Garrido; Jonathan Dushoff; James H. Liu

Computational simulation is a widely employed methodology to study the dynamic behavior of complex systems. Although common approaches are based either on ordinary differential equations or stochastic differential equations, these techniques make several assumptions which, when it comes to biological processes, could often lead to unrealistic models. Among others, model approaches based on differential equations entangle kinetics and causality, failing when complexity increases, separating knowledge from models, and assuming that the average behavior of the population encompasses any individual deviation. To overcome these limitations, simulations based on the Stochastic Simulation Algorithm (SSA) appear as a suitable approach to model complex biological systems. In this work, we review three different models executed in PISKaS: a rule-based framework to produce multiscale stochastic simulations of complex systems. These models span multiple time and spatial scales ranging from gene regulation up to Game Theory. In the first example, we describe a model of the core regulatory network of gene expression in Escherichia coli highlighting the continuous model improvement capacities of PISKaS. The second example describes a hypothetical outbreak of the Ebola virus occurring in a compartmentalized environment resembling cities and highways. Finally, in the last example, we illustrate a stochastic model for the prisoners dilemma; a common approach from social sciences describing complex interactions involving trust within human populations. As whole, these models demonstrate the capabilities of PISKaS providing fertile scenarios where to explore the dynamics of complex systems.


PeerJ | 2017

LoTo: a graphlet based method for the comparison of local topology between gene regulatory networks

Alberto J.M. Martin; Sebastián Contreras-Riquelme; Calixto Dominguez; Tomas Perez-Acle

One of the main challenges of the post-genomic era is the understanding of how gene expression is controlled. Changes in gene expression lay behind diverse biological phenomena such as development, disease and the adaptation to different environmental conditions. Despite the availability of well-established methods to identify these changes, tools to discern how gene regulation is orchestrated are still required. The regulation of gene expression is usually depicted as a Gene Regulatory Network (GRN) where changes in the network structure (i.e., network topology) represent adjustments of gene regulation. Like other networks, GRNs are composed of basic building blocks; small induced subgraphs called graphlets. Here we present LoTo, a novel method that using Graphlet Based Metrics (GBMs) identifies topological variations between different states of a GRN. Under our approach, different states of a GRN are analyzed to determine the types of graphlet formed by all triplets of nodes in the network. Subsequently, graphlets occurring in a state of the network are compared to those formed by the same three nodes in another version of the network. Once the comparisons are performed, LoTo applies metrics from binary classification problems calculated on the existence and absence of graphlets to assess the topological similarity between both network states. Experiments performed on randomized networks demonstrate that GBMs are more sensitive to topological variation than the same metrics calculated on single edges. Additional comparisons with other common metrics demonstrate that our GBMs are capable to identify nodes whose local topology changes between different states of the network. Notably, due to the explicit use of graphlets, LoTo captures topological variations that are disregarded by other approaches. LoTo is freely available as an online web server at http://dlab.cl/loto.


MOL2NET 2016, International Conference on Multidisciplinary Sciences, 2nd edition | 2016

Development of a method for inferring regulatory networks of genes time and specific location: application and comparative studies in D. melanogaster .

Leandro Murgas Saavedra; Calixto Dominguez; Alberto J.M. Martin

The regulation of gene expression is one of the determining factors in the development and maintenance of life in all organisms. This regulation is carried out mainly through the action of Transcription Factors (TFs), although other elements are also involved. Notably, any new knowledge on the regulation of the expression is key to unravel the functioning of the various organisms at the molecular level. This knowledge also has direct application in the understanding of the processes that trigger different diseases, allowing the development of new therapeutic strategies. Gene regulation is usually represented in the form of Gene Regulatory Networks (GRNs). These networks are a simplified representation of how genes are controlled allowing the characterization and study of the different interdependencies of the various factors that are involved in the regulation of the expression of genes. Given the abundance of experimental data on the various factors involved in the regulation of gene expression and the little specific knowledge of this regulation in different tissues and cell types forming organisms in certain stages of development, the creation of new computational methods to integrate all this information into site and time specific networks is a key element for future studies. In this work, time and condition specific GRNs will be conducted to study the development of the embryo of Drosophila melanogaster. D. melanogaster, is a model organism widely studied, given its short generation time and easy culture. In this way, different networks of each stage of development will be created by integrating experimental data from various databases. Finally, GRNs obtained will be characterized and studied employing graphlets based techniques to identify specific elements whose relationship with the rest of the network vary over time during the development of the fly embryo.


Molecular BioSystems | 2014

An integrated molecular dynamics, principal component analysis and residue interaction network approach reveals the impact of M184V mutation on HIV reverse transcriptase resistance to lamivudine

Soumendranath Bhakat; Alberto J.M. Martin; Mahmoud E. S. Soliman


F1000Research | 2017

PISKaS: a HPC tool for stochastic agent/rule-based modeling of spatially explicit biological systems

Ignacio Fuenzalida; Alvaro M. Bustos; David Inostroza; Alejandro Bernardin; Alberto J.M. Martin; Tomas Perez-Acle


F1000Research | 2015

Modeling multiscale complex biological systems using PISKa

Ignacio Fuenzalida; Alberto J.M. Martin; Alejandro Bernardin; Tomas Perez-Acle


F1000Research | 2017

Stochastic modeling of gene regulatory networks in Escherichia coli

Rodrigo Santibáñez; Daniel Garrido; Tomas Perez-Acle; Alberto J.M. Martin

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Tomas Perez-Acle

Pontifical Catholic University of Chile

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Calixto Dominguez

Pontifical Catholic University of Chile

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Tomas Perez-Acle

Pontifical Catholic University of Chile

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Daniel Garrido

Pontifical Catholic University of Chile

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Rodrigo Santibáñez

Pontifical Catholic University of Chile

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