Coordinate-Dependent Drift-Diffusion Reveals the Kinetic Intermediate Traps of Top7-Based Proteins.

The computer-designed Top7 served as a scaffold to produce immunoreactive proteins by grafting of the 2F5 HIV-1 antibody epitope (Top7-2F5) followed by biotinylation (Top7-2F5-biotin). The resulting nonimmunoglobulin affinity proteins were effective in inducing and detecting the HIV-1 antibody. However, the grafted Top7-2F5 design led to protein aggregation, as opposed to the soluble biotinylated Top7-2F5-biotin. The structure-based model predicted that the thermodynamic cooperativity of Top7 increases after grafting and biotin-labeling, reducing their intermediate state populations. In this work, the folding kinetic traps that might contribute to the aggregation propensity are investigated by the diffusion theory. Since the engineered proteins have similar sequence and structural homology, they served as protein models to study the kinetic intermediate traps that were uncovered by characterizing the position-dependent drift-velocity (v(Q)) and the diffusion (D(Q)) coefficients. These coordinate-dependent coefficients were taken into account to obtain the folding and transition path times over the free energy transition states containing the intermediate kinetic traps. This analysis may be useful to predict the aggregated kinetic traps of scaffold-epitope proteins that might compose novel diagnostic and therapeutic platforms.

Biotinylation Eliminates the Intermediate State of Top7 Designed with an HIV-1 Epitope.

Broadly neutralizing antibodies against HIV-1 are rare with the 2F5 antibody being one of the most protective. Insertion of an antibody epitope into a stable and small protein scaffold overcomes many of the obstacles found to produce antibodies. However, the design leads to grafting of epitopes that may cause protein aggregation. Here, I investigated the 2F5 epitope grafted into the Top7 as the scaffold in which the resulting immunoreactive protein precipitates along the storage time, as opposed to its completely soluble biotinylated version. Molecular dynamics showed that biotinylation eliminates the intermediate state of the scaffold-epitope Top7-2F5 by switching a noncooperative to a cooperative folding. The aggregation propensity of the Top7-designed proteins is examined in light of thermodynamic cooperativity and kinetic traps along the decreasing depth of the intermediate ensemble in the free energy landscape. This protocol may predict stable and soluble scaffold-epitopes with the purpose of composing novel therapeutic and diagnostic platforms.

Preparation, cytotoxic activity and DNA interaction studies of new platinum(II) complexes with 1,10-phenanthroline and 5-alkyl-1,3,4-oxadiazol-2(3H)-thione derivatives.

This work describes the synthesis, characterization and in vitro anticancer activity of two platinum(II) complexes of the type [Pt(L1)2(1,10-phen)] 1 and [Pt(L2)2(1,10-phen)] 2, where L1 = 5-heptyl-1,3,4-oxadiazole-2-(3H)-thione, L2 = 5-nonyl-1,3,4-oxadiazole-2-(3H)-thione and 1,10-phen = 1,10-phenanthroline. As to the structure of these complexes, the X-ray structural analysis of 1 indicates that the geometry around the platinum(II) ion is distorted square-planar, where two 5-alkyl-1,3,4-oxadiazol-2-thione derivatives coordinate a platinum(II) ion through the sulfur atom. A chelating bidentate phenanthroline molecule completes the coordination sphere. We tested these complexes in two breast cancer cell lines, namely, MCF-7 (a hormone responsive cancer cell) and MDA-MB-231 (triple negative breast cancer cell). In both cells, the most lipophilic platinum compound, complex 2, was more active than cisplatin, one of the most widely used anticancer drugs nowadays. DNA binding studies indicated that such complexes are able to bind to ct-DNA with Kb values of 104 M-1. According to data from dichroism circular and fluorescence spectroscopy, these complexes appear to bind to the DNA in a non-intercalative, probably via minor groove. Molecular docking followed by semiempirical simulations indicated that these complexes showed favorable interactions with the minor groove of the double helix of ct-DNA in an A-T rich region. Thereafter, flow cytometry analysis showed that complex 2 induced apoptosis and necrosis in MCF-7 cells.

Biotin-painted proteins have thermodynamic stability switched by kinetic folding routes.

Biotin-labeled proteins are widely used as tools to study protein-protein interactions and proximity in living cells. Proteomic methods broadly employ proximity-labeling technologies based on protein biotinylation in order to investigate the transient encounters of biomolecules in subcellular compartments. Biotinylation is a post-translation modification in which the biotin molecule is attached to lysine or tyrosine residues. So far, biotin-based technologies proved to be effective instruments as affinity and proximity tags. However, the influence of biotinylation on aspects such as folding, binding, mobility, thermodynamic stability, and kinetics needs to be investigated. Here, we selected two proteins [biotin carboxyl carrier protein (BCCP) and FKBP3] to test the influence of biotinylation on thermodynamic and kinetic properties. Apo (without biotin) and holo (biotinylated) protein structures were used separately to generate all-atom structure-based model simulations in a wide range of temperatures. Holo BCCP contains one biotinylation site, and FKBP3 was modeled with up to 23 biotinylated lysines. The two proteins had their estimated thermodynamic stability changed by altering their energy landscape. In all cases, after comparison between the apo and holo simulations, differences were observed on the free-energy profiles and folding routes. Energetic barriers were altered with the density of states clearly showing changes in the transition state. This study suggests that analysis of large-scale datasets of biotinylation-based proximity experiments might consider possible alterations in thermostability and folding mechanisms imposed by the attached biotins.

One year of COVID-19 pandemic: Epidemiological characteristics of COVID-19 in the city of Uberaba, Minas Gerais, Brazil / Um ano da pandemia de COVID-19: características epidemiológicas da COVID-19 na cidade de Uberaba, Minas Gerais, Brasil

Introduction: The new coronavirus pandemic (COVID-19) is unprecedented in recorded human history. It spread from Wuhan, China, in early December, 2019, crossing the entire planet and reaching Brazilian shores in the following February. It was declared a pandemic on March 11, 2020, with the first case  recorded in the city of Uberaba, state of Minas Gerais, Brazil, on March 18, 2020. Since then, we have been collecting data and assessing the evolution of this fatal disease. Objective: In this work, we report the epidemiological characteristics of one year of the COVID-19 in Uberaba, and discuss its implications to the general public. Method: This is an observational, descriptive, documentary and retrospective study to describe the epidemiological profile of COVID-19 cases in the city of Uberaba from March 18, 2020 to March 17, 2021. Results: The study shows that the young-working age population are those who most spread the virus; however, the elderly are those who suffer and die the most, with slight differences regarding sex. This is in line with the reported national and international epidemiological profiles that show a shifting tendency of younger generations to be increasingly active on the evolution of the pandemic. We observed two major peaks on the two epidemiological time-series, confirmed cases and deaths, with an average age of 41 years old for the confirmed cases and 68 for the confirmed deaths. It was also reported that the lethality rate was 2.45%, and 80.00% of the confirmed deaths suffered from some previous health condition. Conclusions: In this sense, a permanent epidemiological surveillance has to take place in order to guide public health counter-measurements. The epidemiological characteristics of COVID-19 in Uberaba and related analyses are reported in the online observatory at https://coviduberaba.github.io.

Introdução: A pandemia do novo coronavírus (COVID-19) é inédita na história humana registrada. Espalhou-se de Wuhan, na China, no início de dezembro de 2019, cruzando todo o planeta e chegando à costa brasileira no mês de fevereiro seguinte. Foi declarada pandemia em 11 de março de 2020, com o primeiro caso registrado na cidade de Uberaba, estado de Minas Gerais, Brasil, em 18 de março de 2020. Desde então, estamos coletando dados e avaliando a evolução dessa fatalidade doença. Objetivo: Neste trabalho, relatamos as características epidemiológicas de um ano da COVID-19 em Uberaba e discutimos suas implicações para o público em geral. Método: Trata-se de um estudo observacional, descritivo, documental e retrospectivo para descrever o perfil epidemiológico dos casos de COVID-19 na cidade de Uberaba no período de 18 de março de 2020 até 17 de março de 2021. Resultados: O estudo mostra que a população jovem em idade ativa é a que mais espalha o vírus, no entanto, os idosos são os que mais sofrem e morrem, com pequenas diferenças em relação ao sexo. Isso está de acordo com os perfis epidemiológicos nacionais e internacionais relatados que mostram uma tendência de mudança das gerações mais jovens a serem cada vez mais ativas na evolução da pandemia. Observamos dois grandes picos nas duas séries temporais epidemiológicas, casos confirmados e óbitos, com média de idade de 41 anos para os casos confirmados e 68 para os óbitos confirmados. Também foi relatado que a taxa de letalidade foi de 2,45%, e 80,00% das mortes confirmadas sofriam de alguma condição de saúde anterior. Conclusões: Nesse sentido, uma vigilância epidemiológica permanente deve ocorrer para orientar as contramedidas de saúde pública. As características epidemiológicas da COVID-19 em Uberaba e análises relacionadas são relatadas no observatório online em https://coviduberaba.github.io.

Shedding Light on the Inhibitory Mechanisms of SARS-CoV-1/CoV-2 Spike Proteins by ACE2-Designed Peptides.

Angiotensin-converting enzyme 2 (ACE2) is the host cellular receptor that locks onto the surface spike protein of the 2002 SARS coronavirus (SARS-CoV-1) and of the novel, highly transmissible and deadly 2019 SARS-CoV-2, responsible for the COVID-19 pandemic. One strategy to avoid the virus infection is to design peptides by extracting the human ACE2 peptidase domain α1-helix, which would bind to the coronavirus surface protein, preventing the virus entry into the host cells. The natural α1-helix peptide has a stronger affinity to SARS-CoV-2 than to SARS-CoV-1. Another peptide was designed by joining α1 with the second portion of ACE2 that is far in the peptidase sequence yet grafted in the spike protein interface with ACE2. Previous studies have shown that, among several α1-based peptides, the hybrid peptidic scaffold is the one with the highest/strongest affinity for SARS-CoV-1, which is comparable to the full-length ACE2 affinity. In this work, binding and folding dynamics of the natural and designed ACE2-based peptides were simulated by the well-known coarse-grained structure-based model, with the computed thermodynamic quantities correlating with the experimental binding affinity data. Furthermore, theoretical kinetic analysis of native contact formation revealed the distinction between these processes in the presence of the different binding partners SARS-CoV-1 and SARS-CoV-2 spike domains. Additionally, our results indicate the existence of a two-state folding mechanism for the designed peptide en route to bind to the spike proteins, in contrast to a downhill mechanism for the natural α1-helix peptides. The presented low-cost simulation protocol demonstrated its efficiency in evaluating binding affinities and identifying the mechanisms involved in the neutralization of spike-ACE2 interaction by designed peptides. Finally, the protocol can be used as a computer-based screening of more potent designed peptides by experimentalists searching for new therapeutics against COVID-19.

The dynamics of subunit rotation in a eukaryotic ribosome.

Protein synthesis by the ribosome is coordinated by an intricate series of large-scale conformational rearrangements. Structural studies can provide information about long-lived states, however biological kinetics are controlled by the intervening free-energy barriers. While there has been progress describing the energy landscapes of bacterial ribosomes, very little is known about the energetics of large-scale rearrangements in eukaryotic systems. To address this topic, we constructed an all-atom model with simplified energetics and performed simulations of subunit rotation in the yeast ribosome. In these simulations, the small subunit (SSU; ~1MDa) undergoes spontaneous and reversible rotations (~8°). By enabling the simulation of this rearrangement under equilibrium conditions, these calculations provide initial insights into the molecular factors that control dynamics in eukaryotic ribosomes. Through this, we are able to identify specific inter-subunit interactions that have a pronounced influence on the rate-limiting free-energy barrier. We also show that, as a result of changes in molecular flexibility, the thermodynamic balance between the rotated and unrotated states is temperature-dependent. This effect may be interpreted in terms of differential molecular flexibility within the rotated and unrotated states. Together, these calculations provide a foundation, upon which the field may begin to dissect the energetics of these complex molecular machines.

The Role of Electrostatics and Folding Kinetics on the Thermostability of Homologous Cold Shock Proteins.

Understanding which aspects contribute to the thermostability of proteins is a challenge that has persisted for decades, and it is of great relevance for protein engineering. Several types of interactions can influence the thermostability of a protein. Among them, the electrostatic interactions have been a target of particular attention. Aiming to explore how this type of interaction can affect protein thermostability, this paper investigated four homologous cold shock proteins from psychrophilic, mesophilic, thermophilic, and hyperthermophilic organisms using a set of theoretical methodologies. It is well-known that electrostatics as well as hydrophobicity are key-elements for the stabilization of these proteins. Therefore, both interactions were initially analyzed in the native structure of each protein. Electrostatic interactions present in the native structures were calculated with the Tanford-Kirkwood model with solvent accessibility, and the amount of hydrophobic surface area buried upon folding was estimated by measuring both folded and extended structures. On the basis of Energy Landscape Theory, the local frustration and the simplified alpha-carbon structure-based model were modeled with a Debye-Hückel potential to take into account the electrostatics and the effects of an implicit solvent. Thermodynamic data for the structure-based model simulations were collected and analyzed using the Weighted Histogram Analysis and Stochastic Diffusion methods. Kinetic quantities including folding times, transition path times, folding routes, and Φ values were also obtained. As a result, we found that the methods are able to qualitatively infer that electrostatic interactions play an important role on the stabilization of the most stable thermophilic cold shock proteins, showing agreement with the experimental data.

Drift-diffusion (DrDiff) framework determines kinetics and thermodynamics of two-state folding trajectory and tunes diffusion models.

The stochastic drift-diffusion (DrDiff) theory is an approach used to characterize the dynamical properties of simulation data. With new features in transition times analyses, the framework characterized the thermodynamic free-energy profile [F(Q)], the folding time (τf), and transition path time (τTP) by determining the coordinate-dependent drift-velocity [v(Q)] and diffusion [D(Q)] coefficients from trajectory time traces. In order to explore the DrDiff approach and to tune it with two other methods (Bayesian analysis and fep1D algorithm), a numerical integration of the Langevin equation with known D(Q) and F(Q) was performed and the inputted coefficients were recovered with success by the diffusion models. DrDiff was also applied to investigate the prion protein (PrP) kinetics and thermodynamics by analyzing folding/unfolding simulations. The protein structure-based model, the well-known Go¯-model, was employed in a coarse-grained Cα level to generate long constant-temperature time series. PrP was chosen due to recent experimental single-molecule studies in D and τTP that stressed the importance and the difficulty of probing these quantities and the rare transition state events related to prion misfolding and aggregation. The PrP thermodynamic double-well F(Q) profile, the "X" shape of τf(T), and the linear shape of τTP(T) were predicted with v(Q) and D(Q) obtained by the DrDiff algorithm. With the advance of single-molecule techniques, the DrDiff framework might be a useful ally for determining kinetic and thermodynamic properties by analyzing time observables of biomolecular systems. The code is freely available at https://github.com/ronaldolab/DrDiff.

Stochastic diffusion framework determines the free-energy landscape and rate from single-molecule trajectory.

A theoretical stochastic diffusion framework is developed that characterizes the position-dependent diffusion coefficient [D(Q)] and drift velocity [ v (Q)] by analysing single-molecule time traces [Q(t)]. The free-energy landscape [F(Q)] that governs the dynamics is reconstructed with the calculated D and v . There are many computational tools that perform this task in which some are computationaly demanding, difficult to run, and, most of the time, not directly available to the community. This is a first attempt to implement the simplified stochastic diffusion framework that is fast, easy to run in a Python environment, and available to be extended as needed. It does not require adjustable parameters, inference methods, or sampling bias such as Monte Carlo Bayesian estimators or umbrella samplings. The stochastic framework was applied in the protein-like lattice model with Monte Carlo simulations, which accurately predicted the folding rates with the coordinate-dependent D and F plugged into Kramers' theory. The results were compared with two other independently developed methodologies (the Bayesian analysis and fep1D algorithm) presenting a good match, which confirms its validity. This theoretical framework might be useful in determining the free-energy and rates by providing time series only from biological or condensed-phase systems. The code is freely available at https://github.com/ronaldolab/stochastic_diffusion.

Isolation, leishmanicidal evaluation and molecular docking simulations of piperidine alkaloids from Senna spectabilis.

Leishmaniasis is one of the most important neglected tropical diseases (NTDs) that are especially common among low-income populations in developing regions of Africa, Asia, and the Americas. Many natural products, particularly alkaloids, have been reported to have inhibitory activity against arginase, the key enzyme in the pathology caused by Leishmania sp. In this way, piperidine alkaloids (-)-cassine (1), (-)-spectaline (2), (-)-3-O-acetylcassine (3), and (-)-3-O-acetylspectaline (4) were isolated from Senna spectabilis flowers. These compounds (1/2 and 3/4) initially present as homologous mixtures were separated by high performance liquid chromatography and evaluated against the promastigote phase of Leishmania amazonensis. In addition, molecular docking simulations were implemented in order to probe the binding modes of the ligands 1-4 to the amino acids in the active site of L. amazonensis arginase. Alkaloid 2 (IC50 15.81 µg mL-1) was the most effective against L. amazonensis. Compounds 2 and 4, with larger side chain, were more effective against the parasite than compounds 1 and 3. The cell viability test on Vero cells revealed that compound 2 (CC50 66.67 µg mL-1) was the most toxic. The acetyl group in the 3-O position of the parent structures reduced the leishmanicidal activity and the toxicity of the alkaloids. Further, molecular docking suggested that Asn143 is essential for arginase to interact with (-)-spectaline-derived compounds, which agreed with the IC50 measurements. Our findings revealed that S. spectabilis is an important source of piperidine alkaloids with leishmanicidal activity. Moreover, the natural compound 3 has been isolated for the first time. Experimental investigation combined with theoretical study advances knowledge about the enzyme binding site mode of interaction and contributes to the design of new bioactive drugs against Leishmania infection.

Effects of pH and aggregation in the human prion conversion into scrapie form: a study using molecular dynamics with excited normal modes.

There are two different prion conformations: (1) the cellular natural (PrPC) and (2) the scrapie (PrPSc), an infectious form that tends to aggregate under specific conditions. PrPC and PrPSc are widely different regarding secondary and tertiary structures. PrPSc contains more and longer ß-strands compared to PrPC. The lack of solved PrPSc structures precludes a proper understanding of the mechanisms related to the transition between cellular and scrapie forms, as well as the aggregation process. In order to investigate the conformational transition between PrPC and PrPSc, we applied MDeNM (molecular dynamics with excited normal modes), an enhanced sampling simulation technique that has been recently developed to probe large structural changes. These simulations yielded new structural rearrangements of the cellular prion that would have been difficult to obtain with standard MD simulations. We observed an increase in ß-sheet formation under low pH (≤ 4) and upon oligomerization, whose relevance was discussed on the basis of the energy landscape theory for protein folding. The characterization of intermediate structures corresponding to transition states allowed us to propose a conversion model from the cellular to the scrapie prion, which possibly ignites the fibril formation. This model can assist the design of new drugs to prevent neurological disorders related to the prion aggregation mechanism.

Structure and functional dynamics characterization of the ion channel of the human respiratory syncytial virus (hRSV) small hydrophobic protein (SH) transmembrane domain by combining molecular dynamics with excited normal modes.

The human respiratory syncytial virus (hRSV) is the major cause of lower respiratory tract infection in children and elderly people worldwide. Its genome encodes 11 proteins including SH protein, whose functions are not well known. Studies show that SH protein increases RSV virulence degree and permeability to small compounds, suggesting it is involved in the formation of ion channels. The knowledge of SH structure and function is fundamental for a better understanding of its infection mechanism. The aim of this study was to model, characterize, and analyze the structural behavior of SH protein in the phospholipids bilayer environment. Molecular modeling of SH pentameric structure was performed, followed by traditional molecular dynamics (MD) simulations of the protein immersed in the lipid bilayer. Molecular dynamics with excited normal modes (MDeNM) was applied in the resulting system in order to investigate long time scale pore dynamics. MD simulations support that SH protein is stable in its pentameric form. Simulations also showed the presence of water molecules within the bilayer by density distribution, thus confirming that SH protein is a viroporin. This water transport was also observed in MDeNM studies with histidine residues of five chains (His22 and His51), playing a key role in pore permeability. The combination of traditional MD and MDeNM was a very efficient protocol to investigate functional conformational changes of transmembrane proteins that act as molecular channels. This protocol can support future investigations of drug candidates by acting on SH protein to inhibit viral infection. Graphical Abstract The ion channel of the human respiratory syncytial virus (hRSV) small hydrophobic protein (SH) transmembrane domainᅟ.

VirB7 and VirB9 Interactions Are Required for the Assembly and Antibacterial Activity of a Type IV Secretion System.

The type IV secretion system (T4SS) from the phytopathogen Xanthomonas citri (Xac) is a bactericidal nanomachine. The T4SS core complex is a ring composed of multiple copies of VirB7-VirB9-VirB10 subunits. Xac-VirB7 contains a disordered N-terminal tail (VirB7NT) that recognizes VirB9, and a C-terminal domain (VirB7CT) involved in VirB7 self-association. Here, we show that VirB7NT forms a short ß strand upon binding to VirB9 and stabilizes it. A tight interaction between them is essential for T4SS assembly and antibacterial activity. Abolishing VirB7 self-association or deletion of the VirB7 C-terminal domain impairs this antibacterial activity without disturbing T4SS assembly. These findings reveal protein interactions within the core complex that are critical for the stability and activity of a T4SS.