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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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Macromolecular interaction mechanism of the bacteriocin EntDD14 with the receptor binding domain (RBD) for the inhibition of SARS-CoV-2 and the JN.1 variant: Biomedical study based on elastic networks, stochastic Markov models, and macromolecular volumetric analysis
(Elsevier, 2025)
Moncayo Molina, Luis
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Aguaiza Pichazaca, María Erlinda
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Yamasqui Padilla, José Isidro
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Pinos Calle, María Eufemia
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Yamasqui Pinos, Karla Maribel
Bacteriocins, a class of molecules produced by bacteria, exhibit potent antimicrobial properties, including antiviral activities. The urgent need for treatments against SARS-CoV-2 has proposed bacteriocins such as enterocin DD14 (EntDD14) as potential therapeutic agents. However, the mechanism of macromolecular interaction of EntDD14 for the inhibition of SARS-CoV-2 is not yet fully understood, and its efficacy against variants like JN.1 has not been completely established. To address these knowledge gaps, biocomputational analyses were employed using a diverse set of tools, including Markov state models and volumetric analyses. This analysis revealed a favorable interaction between EntDD14 and the receptor-binding domain (RBD) of SARS-CoV-2. Furthermore, it was found that EntDD14 induces changes in the flexibility of the RBD and alters the distribution and size of its internal cavities, particularly in the JN.1 variant. These findings align with experimental observations and support the inhibitory mechanism of EntDD14 against SARS-CoV-2. Additionally, they suggest that EntDD14 may possess a broader spectrum of action, encompassing the JN.1 variant. This study paves the way for future investigations and therapeutic applications, encouraging further exploration of the antiviral activity of bacteriocins like EntDD14 against variants of concern like JN.1. However, additional experimental demonstrations are warranted to substantiate these findings. ©The authors ©Elsevier
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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
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