Juvenal Yosa Reyes

Bacterial resistance is responsible for a wide variety of health problems, both in children and adults. The persistence of symptoms and infections are mainly treated with β-lactam antibiotics. The increasing resistance to those antibiotics by bacterial pathogens generated the emergence of extended-spectrum β-lactamases (ESBLs), an actual public health problem. This is due to rapid mutations of bacteria when exposed to antibiotics. In this case, β-lactamases are enzymes used by bacteria to hydrolyze the beta-lactam rings present in the antibiotics. Therefore, it was necessary to explore novel molecules as potential β-lactamases inhibitors to find antibacterial compounds against infection caused by ESBLs. A computational methodology based on molecular docking and molecular dynamic simulations was used to find new microalgae metabolites inhibitors of β-lactamase. Six 3D β-lactamase proteins were selected, and the molecular docking revealed that the metabolites belonging to the same structural families, such as phenylacridine (4-Ph), quercetin (Qn), and cryptophycin (Cryp), exhibit a better binding score and binding energy than commercial clinical medicine β-lactamase inhibitors, such as clavulanic acid, sulbactam, and tazobactam. These results indicate that 4-Ph, Qn, and Cryp molecules, homologous from microalgae metabolites, could be used, likely as novel β-lactamase inhibitors or as structural templates for new in-silico pharmaceutical designs, with the possibility of combatting β-lactam resistance

The coronavirus pandemic is a major public health crisis affecting global health systems with dire socioeconomic consequences, especially in vulnerable regions such as Latin America (LATAM). There is an urgent need for a vaccine to help control contagion, reduce mortality and alleviate social costs. In this study, we propose a rational multi-epitope candidate vaccine against SARS-CoV-2. Using bioinformatics, we constructed a library of potential vaccine peptides, based on the affinity of the most common major human histocompatibility complex (HLA) I and II molecules in the LATAM population to predict immunological complexes among antigenic, non-toxic and non-allergenic peptides extracted from the conserved regions of 92 proteomes. Although HLA-C, had the greatest antigenic peptide capacity from SARS-CoV-2, HLA-B and HLA-A, could be more relevant based on COVID-19 risk of infection in LATAM countries. We also used three-dimensional structures of SARS-CoV-2 proteins to identify potential regions for antibody production. The best HLA-I and II predictions (with increased coverage in common alleles and regions evoking B lymphocyte responses) were grouped into an optimized final multi-epitope construct containing the adjuvants Beta defensin-3, TpD, and PADRE, which are recognized for invoking a safe and specific immune response. Finally, we used Molecular Dynamics to identify the multi-epitope construct which may be a stable target for TLR-4/MD-2. This would prove to be safe and provide the physicochemical requirements for conducting experimental tests around the world.

Biofilms are communities of microorganisms that can colonize biotic and abiotic surfaces and thus play a significant role in the persistence of bacterial infection and resistance to antimicrobial. About 65% and 80% of microbial and chronic infections are associated with biofilm formation, respectively. The increase in infections by multi-resistant bacteria instigates the need for the discovery of novel natural-based drugs that act as inhibitory molecules. The inhibition of diguanylate cyclases (DGCs), the enzyme implicated in the synthesis of the second messenger, cyclic diguanylate (c-di-GMP), involved in the biofilm formation, represents a potential approach for preventing the biofilm development. It has been extensively studied using PleD protein as a model of DGC for in silico studies as virtual screening and as a model for in vitro studies in biofilms formation. This study aimed to search for natural products capable of inhibiting the Caulobacter crescentus enzyme PleD. For this purpose, 224,205 molecules from the natural products ZINC15 database, have been evaluated through molecular docking and molecular dynamic simulation. Our results suggest trans-Aconitic acid (TAA) as a possible starting point for hit-to-lead methodologies to obtain new inhibitors of the PleD protein and hence blocking the biofilm formation.

The coronavirus pandemic is a major public health crisis affecting global health systems with dire socioeconomic consequences, especially in vulnerable regions such as Latin America. There is an urgent need for a vaccine to help control contagion, reduce mortality and alleviate social costs. In this study, we propose a rational multi-epitope vaccine against SARS-CoV-2. Using bioinformatics, we constructed a library of potential vaccine peptides to predict immunological complexes among antigenic, non-toxic and non-allergenic peptides extracted from the conserved regions of 92 proteomes. We included the most common HLA-I and II molecules in the Latin American population. We also used three-dimensional structures of SARS-CoV-2 proteins to identify potential regions for antibody production. The best HLA-I and II predictions (with increased coverage in common alleles and regions evoking B lymphocyte responses) were grouped into an optimised final construct that meets the necessary safety and physicochemical requirements for conducting experimental tests.

Breast cancer is a group of multigenic diseases. It is the most common cancer diagnosed among women worldwide and is often treated with tamoxifen. Tamoxifen is catalysed by cytochrome P450 2D6 (CYP2D6), and inter-individual variations in the enzyme due to single nucleotide polymorphisms (SNPs) could alter enzyme activity. We evaluated SNPs in patients from Colombia in South America who were receiving tamoxifen treatment for breast cancer. Allelic diversity in the CYP2D6 gene was found in the studied population, with two patients displaying the poor-metaboliser phenotype. Molecular dynamics and trajectory analyses were performed for CYP2D6 from these two patients, comparing it with the common allelic form (CYP2D6*1). Although we found no significant structural change in the protein, its dynamics differ significantly from those of CYP2D6*1, the effect of such differential dynamics resulting in an inefficient enzyme with serious implications for tamoxifen-treated patients, increasing the risk of disease relapse and ineffective treatment.

Vibrationally induced photodissociation in sulfurochloridic acid (HSO₃Cl) is found to be a viable process to form SO₃and HCl from excitations of the OH-stretching overtone starting atν_OH= 4.

Vibrationally induced photodissociation of sulfuric acid into H₂O + SO₃ is investigated based on reactive molecular dynamics (MD) simulations. Multisurface adiabatic reactive MD simulations allow us to follow both, H-transfer and water elimination after excitation of the ν₉ OH-stretching mode. Analysis of several thousand trajectories finds that the H₂O and SO₃ fragments have distinct final state distributions with respect to translational, rotational, and vibrational degrees of freedom. Rotational distributions peak at quantum numbers j ≤ 5 for water and j ≈ 60 for SO₃. The final state distributions should be useful in identifying products in forthcoming experiments. Based on the MD trajectories, a kinetic scheme has been developed which is able to explain most of the trajectory data and suggests that IVR is very rapid. Typical lifetimes of the excited complex range from several 10 picoseconds to hundreds of nanoseconds, depending on the excitation level. Including temperature and pressure profiles characteristic for the stratosphere in the kinetic model shows that excitations higher than ν₉ = 4 can significantly contribute to the photolysis rate. This extends and specifies earlier work in that multi-level modeling is required to understand the significance of vibrationally induced decomposition pathways of sulfuric acid in the middle atmosphere.

Adiabatic reactive molecular dynamics (ARMD) simulation method is a surface-crossing algorithm for modeling chemical reactions in classical molecular dynamics simulations using empirical force fields. As the ARMD Hamiltonian is time dependent during crossing, it allows only approximate energy conservation. In the current work, the range of applicability of conventional ARMD is explored, and a new multisurface ARMD (MS-ARMD) method is presented, implemented in CHARMM and applied to the vibrationally induced photodissociation of sulfuric acid (H₂SO₄) in the gas phase. For this, an accurate global potential energy surface (PES) involving 12 H₂SO₄ and 4 H₂O + SO₃ force fields fitted to MP2/6-311G++(2d,2p) reference energies is employed. The MS-ARMD simulations conserve total energy and feature both intramolecular H-transfer reactions and water elimination. An analytical treatment of the dynamics in the crossing region finds that conventional ARMD can approximately conserve total energy for limiting cases. In one of them, the reduced mass of the system is large, which often occurs for simulations of solvated biomolecular systems. On the other hand, MS-ARMD is a general approach for modeling chemical reactions including gas-phase, homogeneous, heterogeneous, and enzymatic catalytic reactions while conserving total energy in atomistic simulations.