Martínez Ríos, Félix Orlando

Main Affiliation

Facultad de Ingeniería - CampCM

Preferred name

Official Name

Martínez Ríos, Félix Orlando

ORCID

0000-0002-2346-5922

Researcher ID

N-7502-2018

Scopus Author ID

24339038500

Now showing 1 - 10 of 45

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A hybrid simulated annealing and threshold accepting for satisfiability problems using dynamically cooling schemes
(2007)
Martínez Ríos, Félix Orlando
;
Frausto-Solís, Juan
For Satisfiability (SAT) Problem there is not a deterministic algorithm able to solve it in a polynomial time. Simulated Annealing (SA) and similar algorithms like Threshold Accepting (TA) are able to find very good solutions of SAT instances only if their control parameters are correctly tuned. Classical TA usually uses the same Markov chain length for each temperature cycle but they spend a lot of time. In this paper a method based on the neighborhood structure to get the Markov chain length in a dynamical way for each temperature cycle is proposed. Three cooling schemes are also presented in the paper. The experimentation presented in the paper shows that the proposed method is more efficient than the classical one.
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New Particle Swarm Optimizer Algorithm with Chaotic Maps for Combinatorial Global Optimization Problems. An Application to the Deconvolution of Mössbauer Spectra
(Springer, 2024-01-01)
Martínez Ríos, Félix Orlando
;
Jiménez-López, Omar
;
González Morfín, Juan
In this chapter, we present a novel method for addressing global optimization problems inspired by evolutionary algorithms found in nature. We integrate the Comprehensive Learning Particle Swarm Optimization (CLPSO) algorithm with random value generation based on chaotic maps. The resulting algorithm is applied to the computationally complex task of deconvoluting Mossbauer spectra. We implement ten chaotic maps to generate random values and compare their performance with traditional random number generators. Through experiments, we demonstrate that the developed algorithm excels in exploring the search space and exhibits fast intensification in finding the global minimum. In addition, we perform a comprehensive review of existing solutions to the Mossbauer spectrum deconvolution problem, highlighting the scarce availability of developments in this area. We also present a user-friendly program designed with an intuitive interface to facilitate the deconvolution process by Spector Mossbauer. This program will be freely distributed without operational restrictions. Experimental validation is performed on Mossbauer spectra generated using the developed program and those obtained by experimental means, affirming the efficiency of the new algorithm conceived. ©Springer.
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A first-year design experience based on SAE Aero Design contest to support ABET learning outcomes and engineering vocation in freshmen student
(2017)
Martínez Ríos, Félix Orlando
The a-k outcomes established by Accreditation Board for Engineering and Technology (ABET) for Engineering students in their self-assessment framework, should be reflected in the different subjects that taught to the students of the first two years of the various engineering programs. On the other hand, in those first semesters, the vocation of the students about the different Engineering is not very well defined. This experiment shows a proposal that links the results of ABET with an international student competition such as Society of Automotive Engineers (SAE) Aero Design, to reinforce and guide the new students in their future choice of specialization in the School of Engineering. We also show the relationship between the challenges and problems in the SAE Aero Design competition for new students and ABET's a-k outcomes. We show the results obtained with nineteen students over three years. It is important to mention that none of the students involved in this experiment comes from Aeronautical Engineering (or similar to it).
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An efficient method to compare latencies in order to obtain the best route for SDN
(2017)
Elguea, Lorenzo M.
;
Martínez Ríos, Félix Orlando
Comparing two or more routes on Internet is difficult owing to the variability of the measurements resulting from the different routes or use conditions. With current tools such as SDN[1], it is important to determine with certainty which the best route between a user and an internet service. This will be achieved with fast measurements which do not affect the operation of the network. With trends such as IoT, the best routes can be identified based on latency and not just on the jumps between autonomous systems, fact that optimizes data traffic in a specific way whether it is IPv4 or IPv6. As time elapses, it becomes more important to have a perfect setting for the LAN, which means optimal DNS, LDAP Servers appropriate number, etc. Thats why we propose a precise method that contemplates every possible variation of data, thus making a comparison by means of the use of confidence limits.
Scopus© Citations 6 1 12
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A new swarm algorithm for global optimization of multimodal functions over multi-threading architecture hybridized with simulating annealing
(2018)
Martínez Ríos, Félix Orlando
;
Murillo-Suarez, Alfonso
This paper presents a new algorithm, PCLPSO, based on particle swarm optimization, which uses comprehensive learning particle swarm optimizer. Our algorithm executes C parallel CLPSO algorithms. We adopted as a criterion of completion a maximum value of evaluations of the objective function. During the execution of the CLPSO algorithms, when a certain evaluation value of the functions is reached, the best k are selected, and different initialization criteria are applied to continue the execution of the CLPSO algorithms: restarting the worst ones for the best solution or restores the worst ones to a random solution. For this restart, we use the Boltzmann criterion in a similar way as Simulating Annealing (SA) does. In this work, the experimental results obtained for the search of the minimum of 16 multimodal test functions such as Rosenbrock, Griewank, Rastrigin, Brannin, Schwefel, and others. Our algorithm proved to be more efficient than the traditional CLPSO in its experimental results, and the nonparametric Wilcoxon test confirmed this.
1Scopus© Citations 10 13
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Biological Implications of the Intrinsic Deformability of Human Acetylcholinesterase Induced by Diverse Compounds: A Computational Study
(MDPI, 2024)
Alvarado, Ysaías J.
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González-Paz, Lenin
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Paz , José L.
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Loroño-González, Marcos A.
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Santiago Contreras, Julio
The enzyme acetylcholinesterase (AChE) plays a crucial role in the termination of nerve impulses by hydrolyzing the neurotransmitter acetylcholine (ACh). The inhibition of AChE has emerged as a promising therapeutic approach for the management of neurological disorders such as Lewy body dementia and Alzheimer’s disease. The potential of various compounds as AChE inhibitors was investigated. In this study, we evaluated the impact of natural compounds of interest on the intrinsic deformability of human AChE using computational biophysical analysis. Our approach incorporates classical dynamics, elastic networks (ENM and NMA), statistical potentials (CUPSAT and SWOTein), energy frustration (Frustratometer), and volumetric cavity analyses (MOLE and PockDrug). The results revealed that cyanidin induced significant changes in the flexibility and rigidity of AChE, especially in the distribution and volume of internal cavities, compared to model inhibitors such as TZ2PA6, and through a distinct biophysical-molecular mechanism from the other inhibitors considered. These findings suggest that cyanidin could offer potential mechanistic pathways for future research and applications in the development of new treatments for neurodegenerative diseases. ©The authors ©MDPI
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Biophysical Analysis of Potential Inhibitors of SARS-CoV-2 Cell Recognition and Their Effect on Viral Dynamics in Different Cell Types: A Computational Prediction from In Vitro Experimental Data
(American Chemical Society, 2024)
González-Paz, Lenin
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Lossada, Carla
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Hurtado-León, María Laura
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Vera-Villalobos, Joan
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L. Paz, José
Recent reports have suggested that the susceptibility of cells to SARS-CoV-2 infection can be influenced by various proteins that potentially act as receptors for the virus. To investigate this further, we conducted simulations of viral dynamics using different cellular systems (Vero E6, HeLa, HEK293, and CaLu3) in the presence and absence of drugs (anthelmintic, ARBs, anticoagulant, serine protease inhibitor, antimalarials, and NSAID) that have been shown to impact cellular recognition by the spike protein based on experimental data. Our simulations revealed that the susceptibility of the simulated cell systems to SARS-CoV-2 infection was similar across all tested systems. Notably, CaLu3 cells exhibited the highest susceptibility to SARS-CoV-2 infection, potentially due to the presence of receptors other than ACE2, which may account for a significant portion of the observed susceptibility. Throughout the study, all tested compounds showed thermodynamically favorable and stable binding to the spike protein. Among the tested compounds, the anticoagulant nafamostat demonstrated the most favorable characteristics in terms of thermodynamics, kinetics, theoretical antiviral activity, and potential safety (toxicity) in relation to SARS-CoV-2 spike protein-mediated infections in the tested cell lines. This study provides mathematical and bioinformatic models that can aid in the identification of optimal cell lines for compound evaluation and detection, particularly in studies focused on repurposed drugs and their mechanisms of action. It is important to note that these observations should be experimentally validated, and this research is expected to inspire future quantitative experiments. ©American Chemical Society
Scopus© Citations 2 25
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Innovative Alignment-Based Method for Antiviral Peptide Prediction
(2024)
Daniela de Llano García
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Marrero Ponce, Yovani
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Guillermin Agüero-Chapin
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Francesc J. Ferri
;
Agostinho Antunes
<jats:p>Antiviral peptides (AVPs) represent a promising strategy for addressing the global challenges of viral infections and their growing resistances to traditional drugs. Lab-based AVP discovery methods are resource-intensive, highlighting the need for efficient computational alternatives. In this study, we developed five non-trained but supervised multi-query similarity search models (MQSSMs) integrated into the StarPep toolbox. Rigorous testing and validation across diverse AVP datasets confirmed the models’ robustness and reliability. The top-performing model, M13+, demonstrated impressive results, with an accuracy of 0.969 and a Matthew’s correlation coefficient of 0.71. To assess their competitiveness, the top five models were benchmarked against 14 publicly available machine-learning and deep-learning AVP predictors. The MQSSMs outperformed these predictors, highlighting their efficiency in terms of resource demand and public accessibility. Another significant achievement of this study is the creation of the most comprehensive dataset of antiviral sequences to date. In general, these results suggest that MQSSMs are promissory tools to develop good alignment-based models that can be successfully applied in the screening of large datasets for new AVP discovery.</jats:p>
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Modeling the functional impact of CPEB3 and CPEB4 dysregulation in autism: A theoretical–computational framework
(Elsevier BV, 2026)
González-Paz, Lenin
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Vivas, Alejandro
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Cardozo-Urdaneta, Arlene
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Lossada, Carla
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Mendez, Anibal
Autism spectrum disorder (ASD) involves impaired synaptic plasticity tightly coupled to local mRNA translation. Cytoplasmic polyadenylation element-binding proteins 3 and 4 (CPEB3 and CPEB4) are post-transcriptional regulators of neuronal mRNA translation that may contribute to ASD-related molecular alterations. In this theoretical–computational study, we develop a weighted functional impact model that integrates transcriptomic expression with intrinsic molecular constraints of CPEB3 and CPEB4 to estimate regional and cell type–specific vulnerability in ASD. Coarse-grained molecular dynamics (MD) simulations were quantitatively analyzed to assess aggregation, diffusion, and cluster stability under cell type–specific cytoplasmic conditions, with statistical uncertainty explicitly evaluated. The anterior cingulate cortex and thalamus emerged as primary vulnerability sites. Despite higher CPEB4 expression—mainly in glial cells—our weighted functional impact model predicted greater theoretical susceptibility linked to CPEB3 dysfunction, particularly in inhibitory and excitatory neurons. MD simulations revealed that CPEB3 forms transient diffusion-permissive aggregates, whereas CPEB4 tends to assemble into more stable condensates. These complementary behaviors suggest differential but interdependent regulation of neuronal and glial functions. Importantly, the proposed framework provides experimentally testable predictions on how protein–protein interactions, microexon loss, and cytoplasmic crowding influence translational control in ASD. This integrative approach provides a quantitative and biologically grounded framework to investigate how post-transcriptional regulators contribute to ASD-relevant molecular vulnerability. ©The authors ©Sciencedirect ©Elsevier.
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In Silico Identification of Potential Clovibactin-like Antibiotics Binding to Unique Cell Wall Precursors in Diverse Gram-Positive Bacterial Strains
(MDPI, 2025-02-18)
Sierra-Hernandez, Olimpo
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Saurith-Coronell, Oscar
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Rodríguez-Macías, Juan
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Márquez, Edgar
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Ramón Mora, José
The rise in multidrug-resistant bacteria highlights the critical need for novel antibiotics. This study explores clovibactin-like compounds as potential therapeutic agents targeting lipid II, a crucial component in bacterial cell wall synthesis, using in silico techniques. A total of 2624 clovibactin analogs were sourced from the PubChem database and screened using ProTox 3.0 software based on their ADME-Tox properties, prioritizing candidates with favorable pharmacokinetic profiles and minimal toxicity. Molecular docking protocols were then employed to assess the binding interactions of the selected compounds with lipid II. Our analysis identified Compound 22 as a particularly promising candidate, exhibiting strong binding affinity, stable complex formation, and high selectivity for the target. Binding energy analysis, conducted via molecular dynamics simulations, revealed a highly negative value of −25.50 kcal/mol for Compound 22, surpassing that of clovibactin and underscoring its potential efficacy. In addition, Compound 22 was prioritized due to its exceptional binding affinity to lipid II and its favorable ADME-Tox properties, suggesting a lower likelihood of adverse effects. These characteristics position Compound 22 as a promising candidate for further pharmacological development. While our computational results are encouraging, experimental validation is essential to confirm the efficacy and safety of these compounds. This study not only advances our understanding of clovibactin analogs but also contributes to the ongoing efforts to combat antimicrobial resistance through innovative antibiotic development. ©The authors ©International Journal of Molecular Sciences ©MDPI.
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Martínez Ríos, Félix Orlando

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