Expression and functional characterization of chimeric recombinant bovine follicle-stimulating hormone produced in Leishmania tarentolae.

Assisted reproductive techniques are routinely used in livestock species to increase and enhance productivity. Ovarian hyperstimulation is a process that currently relies on administering pituitary-derived follicle-stimulating hormone (FSH) or equine chorionic gonadotropin in combination with other hormones to promote the maturation of multiple follicles and thereby achieve superovulation. The use of partially purified preparations of FSH extracted from natural sources is associated with suboptimal and variable results. Recombinant FSH (rFSH) has been produced in a variety of heterologous organisms. However, attaining a bioactive rFSH of high quality and at low cost for use in livestock remains challenging. Here we report the production and characterization of a single chain bovine rFSH consisting of the ß- and α-subunit fused by a polypeptide linker (scbFSH) using Leishmania tarentolae as heterologous expression system. This unicellular eukaryote is non-pathogenic to mammals, can be grown in bioreactors using simple and inexpensive semisynthetic media at 26°C and does not require CO2 or bovine serum supplementation. Stable cell lines expressing scbFSH in an inducible fashion were generated and characterized for their productivity. Different culture conditions and purification procedures were evaluated, and the recombinant product was biochemically and biologically characterized, including bioassays in an animal model. The results demonstrate that L. tarentolae is a suitable host for producing a homogeneous, glycosylated and biologically active form of scbFSH with a reasonable yield.

Molecular Dynamics Simulation of Permeation Through Connexin Channels.

Molecular dynamics (MD) simulations are a collection of computational tools that can be used to trace intermolecular interactions at the sub-nanometer level. They offer possibilities that are often unavailable to experimental methods, making MD an ideal complementary technique for the understanding a plethora of biological processes. Thanks to significant efforts by many groups of developers around the world, setting up and running MD simulations has become progressively simpler. However, simulating ionic permeation through membrane channels still presents significant caveats.MD simulations of connexin (Cx) hemichannels (HCs) are particularly problematic because HCs create wide pores in the plasma membrane, and the lateral sizes of the extracellular and intracellular regions are quite different. In this chapter, we provide a detailed instruction to perform MD simulations aimed at computationally modeling the permeation of inorganic ions and larger molecules through Cx HCs.

SIRAH Late Harvest: Coarse-Grained Models for Protein Glycosylation.

Glycans constitute one of the most complex families of biological molecules. Despite their crucial role in a plethora of biological processes, they remain largely uncharacterized because of their high complexity. Their intrinsic flexibility and the vast variability associated with the many combination possibilities have hampered their experimental determination. Although theoretical methods have proven to be a valid alternative to the study of glycans, the large size associated with polysaccharides, proteoglycans, and glycolipids poses significant challenges to a fully atomistic description of biologically relevant glycoconjugates. On the other hand, the exquisite dependence on hydrogen bonds to determine glycans' structure makes the development of simplified or coarse-grained (CG) representations extremely challenging. This is particularly the case when glycan representations are expected to be compatible with CG force fields that include several molecular types. We introduce a CG representation able to simulate a wide variety of polysaccharides and common glycosylation motifs in proteins, which is fully compatible with the CG SIRAH force field. Examples of application to N-glycosylated proteins, including antibody recognition and calcium-mediated glycan-protein interactions, highlight the versatility of the enlarged set of CG molecules provided by SIRAH.

A FRET-based cGMP biosensor in Drosophila.

CUTie2 is a FRET-based cGMP biosensor tested so far only in cells. To expand its use to multicellular organisms we generated two transgenic Drosophila melanogaster strains that express the biosensor in a tissue-dependent manner. CUTie2 expression and subcellular localization was verified by confocal microscopy. The performance of CUTie2 was analyzed on dissected larval brains by hyperspectral microscopy and flow cytometry. Both approaches confirmed its responsivity, and the latter showed a rapid and reversible change in the fluorescence of the FRET acceptor upon cGMP treatment. This validated reporter system may prove valuable for studying cGMP signaling at organismal level.

AmberTools.

AmberTools is a free and open-source collection of programs used to set up, run, and analyze molecular simulations. The newer features contained within AmberTools23 are briefly described in this Application note.

Pragmatic Coarse-Graining of Proteins: Models and Applications.

The molecular details involved in the folding, dynamics, organization, and interaction of proteins with other molecules are often difficult to assess by experimental techniques. Consequently, computational models play an ever-increasing role in the field. However, biological processes involving large-scale protein assemblies or long time scale dynamics are still computationally expensive to study in atomistic detail. For these applications, employing coarse-grained (CG) modeling approaches has become a key strategy. In this Review, we provide an overview of what we call pragmatic CG protein models, which are strategies combining, at least in part, a physics-based implementation and a top-down experimental approach to their parametrization. In particular, we focus on CG models in which most protein residues are represented by at least two beads, allowing these models to retain some degree of chemical specificity. A description of the main modern pragmatic protein CG models is provided, including a review of the most recent applications and an outlook on future perspectives in the field.

The Mechanism of Antimicrobial Small-Cationic Peptides from Coarse-Grained Simulations.

Antimicrobial cationic peptides (AMPs) are excellent candidates for use as therapeutic antimicrobial agents. Among them, short peptides possessing sequences of 9-11 amino acids have some advantages over long-sequence peptides. However, one of the main limitations of short peptides is that their mechanism of action at the molecular level is not well-known. In this article, we report a model based on multiscale molecular dynamics simulations of short peptides interacting with vesicles containing palmitoyl-oleoyl-phosphatidylglycerol (POPG)/palmitoyl-oleoyl-phosphatidylethanolamine (POPE). Simulations using this approach have allowed us to understand the different behaviors of peptides with antimicrobial activity with respect to those that do not produce this effect. We found remarkable agreement with a series of experimental results directly supporting our model. Moreover, these results allow us to understand the mechanism of action at the molecular level of these short peptides. Our simulations suggest that mechanical inhomogeneities appear in the membrane, promoting membrane rupture when a threshold concentration of peptides adsorbed on the membrane is achieved. These results explain the high structural demand for these peptides to maintain a delicate balance between the affinity for the bilayer surface, a low peptide-peptide repulsion (in order to reach the threshold concentration), and an acceptable tendency to penetrate into the bilayer. This mechanism is different from those proposed for peptides with long amino acid sequences. Such information is very useful from the medicinal chemistry point of view for the design of new small antimicrobial peptides.

Customizably designed multibodies neutralize SARS-CoV-2 in a variant-insensitive manner.

The COVID-19 pandemic evolves constantly, requiring adaptable solutions to combat emerging SARS-CoV-2 variants. To address this, we created a pentameric scaffold based on a mammalian protein, which can be customized with up to 10 protein binding modules. This molecular scaffold spans roughly 20 nm and can simultaneously neutralize SARS-CoV-2 Spike proteins from one or multiple viral particles. Using only two different modules targeting the Spike's RBD domain, this construct outcompetes human antibodies from vaccinated individuals' serum and blocks in vitro cell attachment and pseudotyped virus entry. Additionally, the multibodies inhibit viral replication at low picomolar concentrations, regardless of the variant. This customizable multibody can be easily produced in procaryote systems, providing a new avenue for therapeutic development and detection devices, and contributing to preparedness against rapidly evolving pathogens.

Early stages in Aß1-42 spontaneous aggregation: An unbiased dataset from coarse-grained molecular dynamics simulations.

The small soluble aggregates of Aß1-42 are broadly documented as potential targets for the development of new compounds with the capacity to inhibit the early stages of Alzheimer´s disease. Nevertheless, Aß1-42 peptides show an intrinsically disordered character with a high propensity for aggregation, which complicates the identification of conserved structural patterns. Because of this, experimental techniques find substantial difficulties in the characterization of such soluble oligomers. Theoretical techniques, such as molecular dynamics (MD) simulations, provide a possible workaround for this problem. However, the computational cost associated with comprehensively sampling the vast conformational space accessible to these peptides might become prohibitive. In this sense, coarse-grained (CG) simulations can effectively overcome that hurdle at a fraction of the computational cost. In this dataset, we furnish an extensive collection of Aß1-42 peptides in dimeric conformation generated with the SIRAH force field for CG MD simulation. It comprises 25 independent trajectories in .xtc (gromacs) format of Aß1-42 couples of peptides that evolve towards dimeric states along eleven µs-long unbiased simulations. Thanks to the backmapping capabilities of our force field, pseudo atomistic coordinates can be straightforwardly recovered from MD trajectories reported here and analyzed with popular molecular editing programs. This set of simulations performed at room conditions and physiological salt concentrations may furnish a complete collection of inter-peptide interfaces that can be used in high-throughput docking or as new starting states for peptide oligomerization seeding of Aß1-42 dimerization.

In silico induced effect of N-ε-lysine acetylation on microtubule stability and subsequent interaction of microtubule-associated proteins.

Plant systems have been considered valuable models for addressing fundamental questions of microtubule (MT) organization due to their considerable practical utility. Protein acetylation is a very common protein modification, and therate of acetylation can be modulated in cells in different biological states, and these changes can be detected at a molecular level. Here, we focused on K40, K112, and K394 residues as putative acetylation sites, which were shown to exist in both plants and mammals. Such residual effect of acetylation causes critical but unclear effect on MT stability. In turn, it was shown that acetylation indirectly affects the probability of interaction with different MAPs (Microtubule-associated proteins). In a multiscale study using an all-atom force field to reproduce several lattice-forming elements found on the surface the microtubule, we assembled a fragment of a plant microtubule composed of nine tubulins and used it as a model object along with the existing human complex. Triplets of tubulins assembled in a lattice cell were then simulated for both human and plant protein complexes, using a coarse-grained force field. We then analyzed the trajectories and identified some critical deformations of the MAP interaction surface. The initial coordinates were used to investigate the structural scenario in which autophagy-related protein 8 (ATG8) was able to interact with the MT fragment.

The SIRAH force field: A suite for simulations of complex biological systems at the coarse-grained and multiscale levels.

The different combinations of molecular dynamics simulations with coarse-grained representations have acquired considerable popularity among the scientific community. Especially in biocomputing, the significant speedup granted by simplified molecular models opened the possibility of increasing the diversity and complexity of macromolecular systems, providing realistic insights on large assemblies for more extended time windows. However, a holistic view of biological ensembles' structural and dynamic features requires a self-consistent force field, namely, a set of equations and parameters that describe the intra and intermolecular interactions among moieties of diverse chemical nature (i.e., nucleic and amino acids, lipids, solvent, ions, etc.). Nevertheless, examples of such force fields are scarce in the literature at the fully atomistic and coarse-grained levels. Moreover, the number of force fields capable of handling simultaneously different scales is restricted to a handful. Among those, the SIRAH force field, developed in our group, furnishes a set of topologies and tools that facilitate the setting up and running of molecular dynamics simulations at the coarse-grained and multiscale levels. SIRAH uses the same classical pairwise Hamiltonian function implemented in the most popular molecular dynamics software. In particular, it runs natively in AMBER and Gromacs engines, and porting it to other simulation packages is straightforward. This review describes the underlying philosophy behind the development of SIRAH over the years and across families of biological molecules, discussing current limitations and future implementations.

Substrate Recognition Properties from an Intermediate Structural State of the UreA Transporter.

Through a combination of comparative modeling, site-directed and classical random mutagenesis approaches, we previously identified critical residues for binding, recognition, and translocation of urea, and its inhibition by 2-thiourea and acetamide in the Aspergillus nidulans urea transporter, UreA. To deepen the structural characterization of UreA, we employed the artificial intelligence (AI) based AlphaFold2 (AF2) program. In this analysis, the resulting AF2 models lacked inward- and outward-facing cavities, suggesting a structural intermediate state of UreA. Moreover, the orientation of the W82, W84, N279, and T282 side chains showed a large variability, which in the case of W82 and W84, may operate as a gating mechanism in the ligand pathway. To test this hypothesis non-conservative and conservative substitutions of these amino acids were introduced, and binding and transport assessed for urea and its toxic analogue 2-thiourea, as well as binding of the structural analogue acetamide. As a result, residues W82, W84, N279, and T282 were implicated in substrate identification, selection, and translocation. Using molecular docking with Autodock Vina with flexible side chains, we corroborated the AF2 theoretical intermediate model, showing a remarkable correlation between docking scores and experimental affinities determined in wild-type and UreA mutants. The combination of AI-based modeling with classical docking, validated by comprehensive mutational analysis at the binding region, would suggest an unforeseen option to determine structural level details on a challenging family of proteins.

Differential neutralizing antibody responses elicited by CoronaVac and BNT162b2 against SARS-CoV-2 Lambda in Chile.

SARS-CoV-2 variant Lambda was dominant in several South American countries, including Chile. To ascertain the efficacy of local vaccination efforts, we used pseudotyped viruses to characterize the neutralization capacity of antibodies elicited by CoronaVac (n = 53) and BNT162b2 (n = 56) in healthcare workers from Clínica Santa María and the Faculty of Medicine at Universidad de Chile, as well as in convalescent plasma from individuals infected during the first wave visiting the Hospital Clínico at Pontificia Universidad Católica (n = 30). We observed that BNT162b2 elicits higher neutralizing antibody titres than CoronaVac, with differences ranging from 7.4-fold for the ancestral spike (Wuhan-Hu-1) to 8.2-fold for the Lambda spike and 13-fold for the Delta spike. Compared with the ancestral virus, neutralization against D614G, Alpha, Gamma, Lambda and Delta variants was reduced by between 0.93- and 4.22-fold for CoronaVac, 1.04- and 2.38-fold for BNT162b2, and 1.26- and 2.67-fold for convalescent plasma. Comparative analyses among the spike structures of the different variants suggest that mutations in the spike protein from the Lambda variant, including the 246-252 deletion in an antigenic supersite at the N-terminal domain loop and L452Q/F490S within the receptor-binding domain, may account for immune escape. Interestingly, analyses using pseudotyped and whole viruses showed increased entry rates into HEK293T-ACE2 cells, but reduced replication rates in Vero-E6 cells for the Lambda variant when compared with the Alpha, Gamma and Delta variants. Our data show that inactivated virus and messenger RNA vaccines elicit different levels of neutralizing antibodies with different potency to neutralize SARS-CoV-2 variants, including the variant of interest Lambda.

How to Make the CUTiest Sensor in Three Simple Steps for Computational Pedestrians.

Genetically encoded FRET sensors for revealing local concentrations of second messengers in living cells have enormously contributed to our understanding of physiological and pathological processes. However, the development of sensors remains an intricate process. Using simulation techniques, we recently introduced a new architecture to measure intracellular concentrations of cAMP named CUTie, which works as a FRET tag for arbitrary targeting domains. Although our method showed quasi-quantitative predictive power in the design of cAMP and cGMP sensors, it remains intricate and requires specific computational skills. Here, we provide a simplified computer-aided protocol to design tailor-made CUTie sensors based on arbitrary cyclic nucleotide-binding domains. As a proof of concept, we applied this method to construct a new CUTie sensor with a significantly higher cAMP sensitivity (EC50 = 460 nM).This simple protocol, which integrates our previous experience, only requires free web servers and can be straightforwardly used to create cAMP sensors adapted to the physicochemical characteristics of known cyclic nucleotide-binding domains.