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This study aims to assess the nanotribology research output at global level using scientometric tools. The SCOPUS database was used to retrieve records related to the nanotribology research for the period 1996–2010. Publications were counted on a fractional basis. The level of collaboration and its citation impact were examined. The performance of the most productive countries, institutes and most preferred journals is assessed. Various visualization tools such as the Sci2 tool and Ucinet were employed. The USA ranked top in terms of number of publications, citations per paper and h-index, while Switzerland published a higher percentage of international collaborative papers. The most productive institution was Tsinghua University followed by Ohio State University and Lanzhou Institute of Chemical Physics, CAS. The most preferred journals were Tribology Letters, Wear and Journal of Japanese Society of Tribologists. The result of author keywords analysis reveals that Molecular Dynamics, MEMS, Hard Disk and Diamond like Carbon are major research topics. [ABSTRACT FROM AUTHOR]

Periplasmic binding proteins (PBPs) are bacterial proteins commonly used as scaffolds for substrate-detecting biosensors. In these biosensors, effector proteins (for example fluorescent proteins) are inserted into a PBP such that the effector protein's output changes upon PBP-substate binding. The insertion site is often determined by comparison of PBP apo/holo crystal structures, but random insertion libraries have shown that this can miss the best sites. Here, we present a PBP biosensor design method based on residue contact analysis from molecular dynamics. This computational method identifies the best previously known insertion sites in the maltose binding PBP, and suggests further previously unknown sites. We experimentally characterise fluorescent protein insertions at these new sites, finding they too give functional biosensors. Furthermore, our method is sufficiently flexible to both suggest insertion sites compatible with a variety of effector proteins, and be applied to binding proteins beyond PBPs. Author summary: "Biosensors" are microscopic tools that can detect specific molecules of interest and are made of biological building blocks, such as proteins. Upon coming into contact with their target molecule, such as a marker of a specific disease, biosensors change shape and their properties are altered. For example, upon contact with a disease marker, a biosensor could glow brightly to work as a diagnostic, or perhaps it could produce a chemical signal that can be detected by the immune system. Understanding how biosensors change shape in response to their target is key to developing more biosensors with complex responses. In this paper, we use computer simulations of a biosensor component to understand what parameters are important for biosensor design. We use these parameters to generate new biosensors that respond to their target molecule by producing light, but put forward a case that the lesson learned are generalisable enough to inform more complex sensor outputs as well. [ABSTRACT FROM AUTHOR]

Sampling rare events in proteins is crucial for comprehending complex phenomena like cryptic pocket opening, where transient structural changes expose new binding sites. Understanding these rare events also sheds light on protein-ligand binding and allosteric communications, where distant site interactions influence protein function. Traditional unbiased molecular dynamics simulations often fail to sample such rare events, as the free energy barrier between metastable states is large relative to the thermal energy. This renders these events inaccessible on the timescales typically simulated by unbiased molecular dynamics, limiting our understanding of these critical processes. In this paper, we proposed a novel unsupervised learning approach termed as slow feature analysis (SFA) which aims to extract slowly varying features from high-dimensional temporal data. SFA trained on small unbiased molecular dynamics simulations launched from AlphaFold generated conformational ensembles manages to capture rare events governing cryptic pocket opening, protein-ligand binding, and allosteric communications in a kinase. Metadynamics simulations using SFA as collective variables manage to sample 'deep' cryptic pocket opening within a few hundreds of nanoseconds which was beyond the reach of microsecond long unbiased molecular dynamics simulations. SFA augmented metadynamics also managed to capture conformational plasticity of protein upon ligand binding/unbinding and provided novel insights into allosteric communication in receptor-interacting protein kinase 2 (RIPK2) which dictates protein-protein interaction. Taken together, our results show how SFA acts as a dimensionality reduction tool which bridges the gap between AlphaFold, molecular dynamics simulation and metadynamics in context of capturing rare events in biomolecules, extending the scope of structure-based drug discovery in the era of AlphaFold. [ABSTRACT FROM AUTHOR]

Human Immunodeficiency Virus type 1 protease (HIV-1 PR) is one of the most challenging targets of antiretroviral therapy used in the treatment of AIDS-infected people. The performance of protease inhibitors (PIs) is limited by the development of protease mutations that can promote resistance to the treatment. The current study was carried out using statistics and bioinformatics tools. A series of thirty-three compounds with known enzymatic inhibitory activities against HIV-1 protease was used in this paper to build a mathematical model relating the structure to the biological activity. These compounds were designed by software; their descriptors were computed using various tools, such as Gaussian, Chem3D, ChemSketch and MarvinSketch. Computational methods generated the best model based on its statistical parameters. The model's applicability domain (AD) was elaborated. Furthermore, one compound has been proposed as efficient against HIV-1 protease with comparable biological activity to the existing ones; this drug candidate was evaluated using ADMET properties and Lipinski's rule. Molecular Docking performed on Wild Type, and Mutant Type HIV-1 proteases allowed the investigation of the interaction types displayed between the proteases and the ligands, Darunavir (DRV) and the new drug (ND). Molecular dynamics simulation was also used in order to investigate the complexes' stability allowing a comparative study on the performance of both ligands (DRV & ND). Our study suggested that the new molecule showed comparable results to that of darunavir and maybe used for further experimental studies. Our study may also be used as pipeline to search and design new potential inhibitors of HIV-1 proteases. [ABSTRACT FROM AUTHOR]

The interaction between SARS-CoV-2 non-structural protein Nsp9 and the nanobody 2NSP90 was investigated by NMR spectroscopy using the paramagnetic perturbation methodology PENELOP (Paramagnetic Equilibrium vs Nonequilibrium magnetization Enhancement or LOss Perturbation). The Nsp9 monomer is an essential component of the replication and transcription complex (RTC) that reproduces the viral gRNA for subsequent propagation. Therefore preventing Nsp9 recruitment in RTC would represent an efficient antiviral strategy that could be applied to different coronaviruses, given the Nsp9 relative invariance. The NMR results were consistent with a previous characterization suggesting a 4:4 Nsp9-to-nanobody stoichiometry with the occurrence of two epitope pairs on each of the Nsp9 units that establish the inter-dimer contacts of Nsp9 tetramer. The oligomerization state of Nsp9 was also analyzed by molecular dynamics simulations and both dimers and tetramers resulted plausible. A different distribution of the mapped epitopes on the tetramer surface with respect to the former 4:4 complex could also be possible, as well as different stoichiometries of the Nsp9-nanobody assemblies such as the 2:2 stoichiometry suggested by the recent crystal structure of the Nsp9 complex with 2NSP23 (PDB ID: 8dqu), a nanobody exhibiting essentially the same affinity as 2NSP90. The experimental NMR evidence, however, ruled out the occurrence in liquid state of the relevant Nsp9 conformational change observed in the same crystal structure. [ABSTRACT FROM AUTHOR]

In this work, the electro-coalescence process of three nanodroplets under a constant DC electric field is investigated via molecular dynamics simulations (MD), aiming to explore the electric manipulation of multiple droplets coalescence on the molecular level. The symmetrical and asymmetrical dynamic evolutions of electrocoalescence process can be observed. Our MD simulations show that there are two types of critical electric fields to induce the special dynamics. The chain configuration can be formed, when one of the critical electric field is exceeded, referred to as Ecc. On the other hand, there is another critical electric field to change the coalescence pattern from complete coalescence to partial coalescence, the so-called Ecn. Finally, we find that the use of the pulsed DC electric field can overcome the drawbacks of the constant DC electric field in the crude oil industry, and the mechanisms behind the suppressed effect of the water chain or non-coalescence are further revealed. [ABSTRACT FROM AUTHOR]

Chagas' disease is a neglected tropical disease caused by the kinetoplastid protozoan Trypanosoma cruzi. The only therapies are the nitroheterocyclic chemicals nifurtimox and benznidazole that cause various adverse effects. The need to create safe and effective medications to improve medical care remains critical. The lack of verified T. cruzi therapeutic targets hinders medication research for Chagas' disease. In this respect, cytochrome bc1 has been identified as a promising therapeutic target candidate for antibacterial medicines of medical and agricultural interest. Cytochrome bc1 belongs to the mitochondrial electron transport chain and transfers electrons from ubiquinol to cytochrome c1 by the action of two catalytic sites named Qi and Qo. The two binding sites are highly selective, and specific inhibitors exist for each site. Recent studies identified the Qi site of the cytochrome bc1 as a promising drug target against T. cruzi. However, a lack of knowledge of the drug mechanism of action unfortunately hinders the development of new therapies. In this context, knowing the cause of binding site selectivity and the mechanism of action of inhibitors and substrates is crucial for drug discovery and optimization processes. In this paper, we provide a detailed computational investigation of the Qi site of T. cruzi cytochrome b to shed light on the molecular mechanism of action of known inhibitors and substrates. Our study emphasizes the action of inhibitors at the Qi site on a highly unstructured portion of cytochrome b that could be related to the biological function of the electron transport chain complex. Author summary: Chagas' disease is caused by the parasite Trypanosoma cruzi, which is prevalent in low-income African, Asian, and American countries and spread through the rest of the world through migrations infecting about 8 million people and causing 10 000 deaths per year. Currently, the only drugs approved for treating Chagas' disease have various side effects. Identifying proteins of the parasite that can limit its activity can help the development of new and more effective drugs. In this context, the cytochrome bc1 of Trypanosoma cruzi has been identified as a promising drug target. However, it is unclear how certain drugs affect cytochrome bc1 biological activity. Molecular dynamics simulations have been used to analyze the impact of specific small molecules on protein conformational changes that may be related to cytochrome bc1's biological function. This manuscript presents a computational approach that could identify small-molecule lead compounds and distinguish between true and false cytochrome b inhibitors. [ABSTRACT FROM AUTHOR]

We present OpenAWSEM and Open3SPN2, new cross-compatible implementations of coarse-grained models for protein (AWSEM) and DNA (3SPN2) molecular dynamics simulations within the OpenMM framework. These new implementations retain the chemical accuracy and intrinsic efficiency of the original models while adding GPU acceleration and the ease of forcefield modification provided by OpenMM's Custom Forces software framework. By utilizing GPUs, we achieve around a 30-fold speedup in protein and protein-DNA simulations over the existing LAMMPS-based implementations running on a single CPU core. We showcase the benefits of OpenMM's Custom Forces framework by devising and implementing two new potentials that allow us to address important aspects of protein folding and structure prediction and by testing the ability of the combined OpenAWSEM and Open3SPN2 to model protein-DNA binding. The first potential is used to describe the changes in effective interactions that occur as a protein becomes partially buried in a membrane. We also introduced an interaction to describe proteins with multiple disulfide bonds. Using simple pairwise disulfide bonding terms results in unphysical clustering of cysteine residues, posing a problem when simulating the folding of proteins with many cysteines. We now can computationally reproduce Anfinsen's early Nobel prize winning experiments by using OpenMM's Custom Forces framework to introduce a multi-body disulfide bonding term that prevents unphysical clustering. Our protein-DNA simulations show that the binding landscape is funneled towards structures that are quite similar to those found using experiments. In summary, this paper provides a simulation tool for the molecular biophysics community that is both easy to use and sufficiently efficient to simulate large proteins and large protein-DNA systems that are central to many cellular processes. These codes should facilitate the interplay between molecular simulations and cellular studies, which have been hampered by the large mismatch between the time and length scales accessible to molecular simulations and those relevant to cell biology. Author summary: The cell's most important pieces of machinery are large complexes of proteins often along with nucleic acids. From the ribosome, to CRISPR-Cas9, to transcription factors and DNA-wrangling proteins like the SMC-Kleisins, these complexes allow organisms to replicate and enable cells to respond to environmental cues. Computer simulation is a key technology that can be used to connect physical theories with biological reality. Unfortunately, the time and length scales accessible to molecular simulation have not kept pace with our ambition to study the cell's molecular factories. Many simulation codes also unfortunately remain effectively locked away from the user community who need to modify them as more of the underlying physics is learned. In this paper, we present OpenAWSEM and Open3SPN2, two new easy-to-use and easy to modify implementations of efficient and accurate coarse-grained protein and DNA simulation forcefields that can now be run hundreds of times faster than before, thereby making studies of large biomolecular machines more facile. [ABSTRACT FROM AUTHOR]

The spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus poses serious threats to the global public health and leads to worldwide crisis. No effective drug or vaccine is readily available. The viral RNA-dependent RNA polymerase (RdRp) is a promising therapeutic target. A hybrid drug screening procedure was proposed and applied to identify potential drug candidates targeting RdRp from 1906 approved drugs. Among the four selected market available drug candidates, Pralatrexate and Azithromycin were confirmed to effectively inhibit SARS-CoV-2 replication in vitro with EC50 values of 0.008μM and 9.453 μM, respectively. For the first time, our study discovered that Pralatrexate is able to potently inhibit SARS-CoV-2 replication with a stronger inhibitory activity than Remdesivir within the same experimental conditions. The paper demonstrates the feasibility of fast and accurate anti-viral drug screening for inhibitors of SARS-CoV-2 and provides potential therapeutic agents against COVID-19. Author summary: Currently, a novel coronavirus called SARS-COV-2 is spreading across many parts of the world. Unfortunately, there is still a lack of effective drugs against the virus. Additionally, it usually takes much longer time to develop a new drug using traditional methods. Thus, it is now better to rely on some alternative methods to develop drugs that can treat such a disease effectively. In this paper, we have proposed a deep learning and molecular dynamics simulation based hybrid drug screening procedure for identifying potential drug candidates targeting RdRp from 1906 market available drugs. Our screening have successfully identified a FDA-approved drug called Pralatrexate that strongly inhibits the replication of 2019-nCoV in vitro with EC50 values of 0.008μM. This work demonstrated the feasibility of accurate virtual drug screening for inhibitors of SARS-CoV-2 and provides potential therapeutic agents against COVID-19. [ABSTRACT FROM AUTHOR]

Chemical synapses exhibit a diverse array of internal mechanisms that affect the dynamics of transmission efficacy. Many of these processes, such as release of neurotransmitter and vesicle recycling, depend strongly on activity-dependent influx and accumulation of Ca2+. To model how each of these processes may affect the processing of information in neural circuits, and how their dysfunction may lead to disease states, requires a computationally efficient modelling framework, capable of generating accurate phenomenology without incurring a heavy computational cost per synapse. Constructing a phenomenologically realistic model requires the precise characterization of the timing and probability of neurotransmitter release. Difficulties arise in that functional forms of instantaneous release rate can be difficult to extract from noisy data without running many thousands of trials, and in biophysical synapses, facilitation of per-vesicle release probability is confounded by depletion. To overcome this, we obtained traces of free Ca2+ concentration in response to various action potential stimulus trains from a molecular MCell model of a hippocampal Schaffer collateral axon. Ca2+ sensors were placed at varying distance from a voltage-dependent calcium channel (VDCC) cluster, and Ca2+ was buffered by calbindin. Then, using the calcium traces to drive deterministic state vector models of synaptotagmin 1 and 7 (Syt-1/7), which respectively mediate synchronous and asynchronous release in excitatory hippocampal synapses, we obtained high-resolution profiles of instantaneous release rate, to which we applied functional fits. Synchronous vesicle release occurred predominantly within half a micron of the source of spike-evoked Ca2+ influx, while asynchronous release occurred more consistently at all distances. Both fast and slow mechanisms exhibited multi-exponential release rate curves, whose magnitudes decayed exponentially with distance from the Ca2+ source. Profile parameters facilitate on different time scales according to a single, general facilitation function. These functional descriptions lay the groundwork for efficient mesoscale modelling of vesicular release dynamics. Author summary: Most information transmission between neurons in the brain occurs via release of neurotransmitter from synaptic vesicles. In response to a presynaptic spike, calcium influx at the active zone of a synapse can trigger the release of neurotransmitter with a certain probability. These stochastic release events may occur immediately after a spike or with some delay. As calcium accumulates from one spike to the next, the probability of release may increase (facilitate) for subsequent spikes. This process, known as short-term plasticity, transforms the spiking code to a release code, underlying much of the brain's information processing. In this paper, we use an accurate, detailed model of presynaptic molecular physiology to characterize these processes at high precision in response to various spike trains. We then apply model reduction to the results to obtain a phenomenological model of release timing, probability, and facilitation, which can perform as accurately as the molecular model but with far less computational cost. This mesoscale model of spike-evoked release and facilitation helps to bridge the gap between microscale molecular dynamics and macroscale information processing in neural circuits. It can thus benefit large scale modelling of neural circuits, biologically inspired machine learning models, and the design of neuromorphic chips. [ABSTRACT FROM AUTHOR]

Identifying structural differences among proteins can be a non-trivial task. When contrasting ensembles of protein structures obtained from molecular dynamics simulations, biologically-relevant features can be easily overshadowed by spurious fluctuations. Here, we present SINATRA Pro, a computational pipeline designed to robustly identify topological differences between two sets of protein structures. Algorithmically, SINATRA Pro works by first taking in the 3D atomic coordinates for each protein snapshot and summarizing them according to their underlying topology. Statistically significant topological features are then projected back onto a user-selected representative protein structure, thus facilitating the visual identification of biophysical signatures of different protein ensembles. We assess the ability of SINATRA Pro to detect minute conformational changes in five independent protein systems of varying complexities. In all test cases, SINATRA Pro identifies known structural features that have been validated by previous experimental and computational studies, as well as novel features that are also likely to be biologically-relevant according to the literature. These results highlight SINATRA Pro as a promising method for facilitating the non-trivial task of pattern recognition in trajectories resulting from molecular dynamics simulations, with substantially increased resolution. Author summary: Structural features of proteins often serve as signatures of their biological function and molecular binding activity. Elucidating these structural features is essential for a full understanding of underlying biophysical mechanisms. While there are existing methods aimed at identifying structural differences between protein variants, such methods do not have the capability to jointly infer both geometric and dynamic changes, simultaneously. In this paper, we propose SINATRA Pro, a computational framework for extracting key structural features between two sets of proteins. SINATRA Pro robustly outperforms standard techniques in pinpointing the physical locations of both static and dynamic signatures across various types of protein ensembles, and it does so with improved resolution. [ABSTRACT FROM AUTHOR]

With the growth of the economy, the number of automobiles on the road is fast growing, resulting in substantial environmental pollution from exhaust gas emissions. In the automobile factory, some improvements have been achieved by constructing devices to degrade automobile exhaust. However, although most of the vehicle exhaust emissions have met the national standards, the exhaust gas is superimposed at the same time period due to the increasing traffic volume, making the exhaust emissions seriously reduce the air quality. Therefore, the scholars in the road field began to study new road materials to degrade vehicle exhaust, which has gradually become one of the effective ways to reduce automobile exhaust. Photocatalyst materials have been widely concerned because of their ability to oxidize harmful gases by solar photocatalysis. Yet, the effect has been not satisfactory because of the small light response range of photocatalyst material, which restricts the catalytic effect. In this study, this paper attempts to use Fe3+ to modify the TiO2, which is one of the main photocatalytic materials, to expand the range of light reaction band and to improve the degradation effect of automobile exhaust. The degradation effects of ordinary TiO2 and modified TiO2 on automobile exhaust were compared by test system in the laboratory. The results show that the modified TiO2 can effectively improve the performance of vehicle exhaust degradation. Moreover, the molecular dynamics method was used to establish the channel model of TiO2, and the dynamic process of automobile exhaust diffusion and absorption was simulated. The diffusion law and adsorption process of different types of automobile exhaust gas such as NO, CO, and CO2 in the TiO2 channel were analyzed from the molecular scale through the radial concentration distribution and adsorption energy. [ABSTRACT FROM AUTHOR]

Recent high-throughput techniques have generated a flood of biological data in all aspects. The transformation and visualization of multi-dimensional and numerical gene or protein expression data in a single heatmap can provide a concise but comprehensive presentation of molecular dynamics under different conditions. In this work, we developed an easy-to-use tool named HemI (Heat map Illustrator), which can visualize either gene or protein expression data in heatmaps. Additionally, the heatmaps can be recolored, rescaled or rotated in a customized manner. In addition, HemI provides multiple clustering strategies for analyzing the data. Publication-quality figures can be exported directly. We propose that HemI can be a useful toolkit for conveniently visualizing and manipulating heatmaps. The stand-alone packages of HemI were implemented in Java and can be accessed at . [ABSTRACT FROM AUTHOR]

Flip-flop of lipids of the lipid bilayer (LBL) constituting the plasma membrane (PM) plays a crucial role in a myriad of events ranging from cellular signaling and regulation of cell shapes to cell homeostasis, membrane asymmetry, phagocytosis, and cell apoptosis. While extensive research has been conducted to probe the lipid flip flop of planar lipid bilayers (LBLs), less is known regarding lipid flip-flop for highly curved, nanoscopic LBL systems despite the vast importance of membrane curvature in defining the morphology of cells and organelles and in maintaining a variety of cellular functions, enabling trafficking, and recruiting and localizing shape-responsive proteins. In this paper, we conduct molecular dynamics (MD) simulations to study the energetics, structure, and configuration of a lipid molecule undergoing flip-flop and desorption in a highly curved LBL, represented as a nanoparticle-supported lipid bilayer (NPSLBL) system. We compare our findings against those of a planar substrate supported lipid bilayer (PSSLBL). Our MD simulation results reveal that despite the vast differences in the curvature and other curvature-dictated properties (e.g., lipid packing fraction, difference in the number of lipids between inner and outer leaflets, etc.) between the NPSLBL and the PSSLBL, the energetics of lipid flip-flop and lipid desorption as well as the configuration of the lipid molecule undergoing lipid flip-flop are very similar for the NPSLBL and the PSSLBL. In other words, our results establish that the curvature of the LBL plays an insignificant role in lipid flip-flop and desorption. [ABSTRACT FROM AUTHOR]

The tryptophan hydroxylase 2 (TPH2) enzyme catalyzes the first step of serotonin biosynthesis. Serotonin is known for its role in several homeostatic systems related to sleep, mood, and food intake. As the reaction catalyzed by TPH2 is the rate-limiting step of serotonin biosynthesis, mutations in TPH2 have been associated with several psychiatric disorders (PD). This work undertakes an in silico analysis of the effects of genetic mutations in the human TPH2 protein. Ten algorithms were used to predict the functional and stability effects of the TPH2 mutations. ConSurf was used to estimate the evolutionary conservation of TPH2 amino acids. GROMACS was used to perform molecular dynamics (MD) simulations of TPH2 WT and P260S, R303W, and R441H, which had already been associated with the development of PD. Forty-six TPH2 variants were compiled from the literature. Among the analyzed variants, those occurring at the catalytic domain were shown to be more damaging to protein structure and function. The ConSurf analysis indicated that the mutations affecting the catalytic domain were also more conserved throughout evolution. The variants S364K and S383F were predicted to be deleterious by all the functional algorithms used and occurred at conserved positions, suggesting that they might be deleterious. The MD analyses indicate that the mutations P206S, R303W, and R441H affect TPH2 flexibility and essential mobility at the catalytic and oligomerization domains. The variants P206S, R303W, and R441H also exhibited alterations in dimer binding affinity and stability throughout the simulations. Thus, these mutations may impair TPH2 functional interactions and, consequently, its function, leading to the development of PD. Furthermore, we developed a database, SNPMOL (http://www.snpmol.org/), containing the results presented in this paper. Understanding the effects of TPH2 mutations on protein structure and function may lead to improvements in existing treatments for PD and facilitate the design of further experiments. [ABSTRACT FROM AUTHOR]

Aberrant aggregation of α-Synuclein is the pathological hallmark of a set of neurodegenerative diseases termed synucleinopathies. Recent advances in cryo-electron microscopy have led to the structural determination of the first synucleinopathy-derived α-Synuclein fibrils, which contain a non-proteinaceous, "mystery density" at the core of the protofilaments, hypothesized to be highly negatively charged. Guided by previous studies that demonstrated that polyphosphate (polyP), a universally conserved polyanion, significantly accelerates α-Synuclein fibril formation, we conducted blind docking and molecular dynamics simulation experiments to model the polyP binding site in α-Synuclein fibrils. Here, we demonstrate that our models uniformly place polyP into the lysine-rich pocket, which coordinates the mystery density in patient-derived fibrils. Subsequent in vitro studies and experiments in cells revealed that substitution of the 2 critical lysine residues K43 and K45 with alanine residues leads to a loss of all previously reported effects of polyP binding on α-Synuclein, including stimulation of fibril formation, change in filament conformation and stability as well as alleviation of cytotoxicity. In summary, our study demonstrates that polyP fits the unknown electron density present in in vivo α-Synuclein fibrils and suggests that polyP exerts its functions by neutralizing charge repulsion between neighboring lysine residues. Previous cryo-EM structures of synucleinopathy patient-derived α-synuclein fibrils revealed a 'mystery density' at the core of the protofilaments. This study identifies polyphosphate as this density, which binds a lysine-rich pocket and contributes to fiber stabilization. [ABSTRACT FROM AUTHOR]

Cerebroside sulfotransferase (CST) is considered a target protein in developing substrate reduction therapy for metachromatic leukodystrophy. This study employed a multistep virtual screening approach for getting a specific and potent inhibitor against CST from 35 phytoconstituents of Bacopa monnieri (L.) Pennell and 31 phytoconstituents of Mucuna pruriens (L.) DC. from the IMPPAT 2.0 database. Using a binding score cutoff of -8.0 kcal/mol with ADME and toxicity screening, four phytoconstituents IMPHY009537 (Stigmastenol), IMPHY004141 (alpha-Amyrenyl acetate), IMPHY014836 (beta-Sitosterol), and IMPHY001534 (jujubogenin) were considered for in-depth analysis. In the binding pocket of CST, the major amino acid residues that decide the orientation and interaction of compounds are Lys85, His84, His141, Phe170, Tyr176, and Phe177. The molecular dynamics simulation with a 100ns time span further validated the stability and rigidity of the docked complexes of the four hits by exploring the structural deviation and compactness, hydrogen bond interaction, solvent accessible surface area, principal component analysis, and free energy landscape analysis. Stigmastenol from Bacopa monnieri with no potential cross targets was found to be the most potent and selective CST inhibitor followed by alpha-Amyrenyl acetate from Mucuna pruriens as the second-best performing inhibitor against CST. Our computational drug screening approach may contribute to the development of oral drugs against metachromatic leukodystrophy. [ABSTRACT FROM AUTHOR]

Human and animal health is threatened by Hendra virus (HeV), which has few treatments. This in-silico vaccine design study focuses on HeV G (glycoprotein), F (fusion protein), and M (matrix protein). These proteins were computationally assessed for B and T-cell epitopes after considering HeV strain conservation, immunogenicity, and antigenicity. To improve vaccination immunogenicity, these epitopes were selectively ligated into a multiepitope construct. To improve vaccination longevity and immunological response, adjuvants and linkers were ligated. G, F, and M epitopes were used to create an mRNA HeV vaccine. Cytotoxic, helper, and linear B-lymphocytes' epitopes are targeted by this vaccine. The population coverage analysis demonstrates that multi-epitope vaccination covers 91.81 percent of CTL and 98.55 percent of HTL epitopes worldwide. GRAVY evaluated the vaccine's well-characterized physicochemical properties -0.503, indicating solubility and functional stability. Structure analysis showed well-stabilized 2° and 3° structures in the vaccine, with alpha helix, beta sheet, and coil structures (Ramachandran score of 88.5% and Z score of -3.44). There was a strong affinity as shown by docking tests with TLR-4 (central score of -1139.4 KJ/mol) and TLR-2 (center score of -1277.9 KJ/mol). The coupled V-apo, V-TLR2, and V-TLR4 complexes were tested for binding using molecular dynamics simulation where extremely stable complexes were found. The predicted mRNA structures provided significant stability. Codon optimization for Escherichia. coli synthesis allowed the vaccine to attain a GC content of 46.83% and a CAI score of 1.0, which supports its significant expression. Immunological simulations indicated vaccine-induced innate and adaptive immune reactions. Finally, this potential HeV vaccine needs more studies to prove its efficacy and safety. [ABSTRACT FROM AUTHOR]

The G protein-coupled receptor 40 (GPR40) is known to exert a significant influence on neurogenesis and neurodevelopment within the central nervous system of both humans and rodents. Research findings indicate that the activation of GPR40 by an agonist has been observed to promote the proliferation and viability of hypothalamus cells in the human body. The objective of the present study is to discover new agonist compounds for the GPR40 protein through the utilization of machine learning and pharmacophore-based screening techniques, in conjunction with other computational methodologies such as docking, molecular dynamics simulations, free energy calculations, and investigations of the free energy landscape. In the course of our investigation, we successfully identified five unreported agonist compounds that exhibit robust docking score, displayed stability in ligand RMSD and consistent hydrogen bonding with the receptor in the MD trajectories. Free energy calculations were observed to be higher than control molecule. The measured binding affinities of compounds namely 1, 3, 4, 6 and 10 were -13.9, -13.5, -13.4, -12.9, and -12.1 Kcal/mol, respectively. The identified molecular agonist that has been found can be assessed in terms of its therapeutic efficacy in the treatment of neurological diseases. [ABSTRACT FROM AUTHOR]

The dysregulation of the rat sarcoma (RAS) signaling pathway, particularly the MAPK/ERK cascade, is a hallmark of many cancers, leading to uncontrolled cellular proliferation and resistance to apoptosis-inducing treatments. Dysregulation of the MAPK/ERK pathway is common in various cancers including pancreatic, lung, and colon cancers, making it a critical target for therapeutic intervention. Natural compounds, especially phytochemicals, offer a promising avenue for developing new anticancer therapies due to their potential to interfere with these signaling pathways. This study investigates the potential of anticancer phytochemicals to inhibit the MAPK/ERK pathway through molecular docking and simulation techniques. A total of 26 phytochemicals were screened from an initial set of 340 phytochemicals which were retrieved from Dr. Duke's database using in silico methods for their binding affinity and stability. Molecular docking was performed to identify key interactions with ERK2, followed by molecular dynamics (MD) simulations to evaluate the stability of these interactions. The study identified several phytochemicals, including luteolin, hispidulin, and isorhamnetin with a binding score of -10.1±0 Kcal/mol, -9.86±0.15 Kcal/mol, -9.76±0.025 Kcal/mol, respectively as promising inhibitors of the ERK2 protein. These compounds demonstrated significant binding affinities and stable interactions with ERK2 in MD simulation studies up to 200ns, particularly at the active site. The radius of gyration analysis confirmed the stability of these phytochemical-protein complexes' compactness, indicating their potential to inhibit ERK activity. The stability and binding affinity of these compounds suggest that they can effectively inhibit ERK2 activity, potentially leading to more effective and less toxic cancer treatments. The findings underscore the therapeutic promise of these phytochemicals, which could serve as a basis for developing new cancer therapies. [ABSTRACT FROM AUTHOR]

Tuberculosis(TB) of the Central nervous system (CNS) is a rare and highly destructive disease. The emergence of drug resistance has increased treatment difficulty, leaving the Bacillus Calmette-Guérin (BCG) vaccine as the only licensed preventative immunization available. This study focused on identifying the epitopes of PknD (Rv0931c) and Rv0986 from Mycobacterium tuberculosis(Mtb) strain H37Rv using an in silico method. The goal was to develop a therapeutic mRNA vaccine for preventing CNS TB. The vaccine was designed to be non-allergenic, non-toxic, and highly antigenic. Codon optimization was performed to ensure effective translation in the human host. Additionally, the secondary and tertiary structures of the vaccine were predicted, and molecular docking with TLR-4 was carried out. A molecular dynamics simulation confirmed the stability of the complex. The results indicate that the vaccine structure shows effectiveness. Overall, the constructed vaccine exhibits ideal physicochemical properties, immune response, and stability, laying a theoretical foundation for future laboratory experiments. [ABSTRACT FROM AUTHOR]

Background: The increasing prevalence of diabetes and the side effects associated with current medications necessitate the development of novel candidate drugs targeting alpha-glucosidase as a potential treatment option. Methods: This study employed computer-aided drug design techniques to identify potential alpha-glucosidase inhibitors from the PubChem database. Molecular docking was used to evaluate 81,197 compounds, narrowing the set for further analysis and providing insights into ligand-target interactions. An ADMET study assessed the pharmacokinetic properties of these compounds, including absorption, distribution, metabolism, excretion, and toxicity. Molecular dynamics simulations validated the docking results. Results: 9 compounds were identified as potential candidate drugs based on their ability to form stable complexes with alpha-glucosidase and their favorable pharmacokinetic profiles, three of these compounds were subjected to the molecular dynamics, which showed stability throughout the entire 100 ns simulation. Conclusion: These findings suggest promising new alpha-glucosidase inhibitors for diabetes treatment. Further validation through in vitro and in vivo studies is recommended to confirm their efficacy and safety. [ABSTRACT FROM AUTHOR]

Profilin 1 (PFN1) protein plays key roles in neuronal growth and differentiation, membrane trafficking, and regulation of the actin cytoskeleton. Four natural variants of PFN1 were described as related to ALS, the most common adult-onset motor neuron disorder. However, the pathological mechanism of PFN1 in ALS is not yet completely understood. The goal of this work is to thoroughly analyze the effects of the ALS-related mutations on PFN1 structure and function using computational simulations. Here, PhD-SNP, PMUT, PolyPhen-2, SIFT, SNAP, SNPS&GO, SAAP, nsSNPAnalyzer, SNPeffect4.0 and I-Mutant2.0 were used to predict the functional and stability effects of PFN1 mutations. ConSurf was used for the evolutionary conservation analysis, and GROMACS was used to perform the MD simulations. The mutations C71G, M114T, and G118V, but not E117G, were predicted as deleterious by most of the functional prediction algorithms that were used. The stability prediction indicated that the ALS-related mutations could destabilize PFN1. The ConSurf analysis indicated that the mutation C71G, M114T, E117G, and G118V occur in highly conserved positions. The MD results indicated that the studied mutations could affect the PFN1 flexibility at the actin and PLP-binding domains, and consequently, their intermolecular interactions. It may be therefore related to the functional impairment of PFN1 upon C71G, M114T, E117G and G118V mutations, and their involvement in ALS development. We also developed a database, SNPMOL (), containing the results presented on this paper for biologists and clinicians to exploit PFN1 and its natural variants. [ABSTRACT FROM AUTHOR]

Bacteria contain several nucleoid-associated proteins that organize their genomic DNA into the nucleoid by bending, wrapping or bridging DNA. The Histone-like Nucleoid Structuring protein H-NS found in many Gram-negative bacteria is a DNA bridging protein and can structure DNA by binding to two separate DNA duplexes or to adjacent sites on the same duplex, depending on external conditions. Several nucleotide sequences have been identified to which H-NS binds with high affinity, indicating H-NS prefers AT-rich DNA. To date, highly detailed structural information of the H-NS DNA complex remains elusive. Molecular simulation can complement experiments by modelling structures and their time evolution in atomistic detail. In this paper we report an exploration of the different binding modes of H-NS to a high affinity nucleotide sequence and an estimate of the associated rate constant. By means of molecular dynamics simulations, we identified three types of binding for H-NS to AT-rich DNA. To further sample the transitions between these binding modes, we performed Replica Exchange Transition Interface Sampling, providing predictions of the mechanism and rate constant of H-NS binding to DNA. H-NS interacts with the DNA through a conserved QGR motif, aided by a conserved arginine at position 93. The QGR motif interacts first with phosphate groups, followed by the formation of hydrogen bonds between acceptors in the DNA minor groove and the sidechains of either Q112 or R114. After R114 inserts into the minor groove, the rest of the QGR motif follows. Full insertion of the QGR motif in the minor groove is stable over several tens of nanoseconds, and involves hydrogen bonds between the bases and both backbone and sidechains of the QGR motif. The rate constant for the process of H-NS binding to AT-rich DNA resulting in full insertion of the QGR motif is in the order of 106 M−1s−1, which is rate limiting compared to the non-specific association of H-NS to the DNA backbone at a rate of 108 M−1s−1. [ABSTRACT FROM AUTHOR]

The Glycoside Hydrolase Family 13 (GH13) is both evolutionarily diverse and relevant to many industrial applications. Its members hydrolyze starch into smaller carbohydrates and members of the family have been bioengineered to improve catalytic function under industrial environments. We introduce a framework to analyze the response to selection of GH13 protein structures given some phylogenetic and simulated dynamic information. We find that the TIM-barrel (a conserved protein fold consisting of eight α-helices and eight parallel β-strands that alternate along the peptide backbone, common to all amylases) is not selectable since it is under purifying selection. We also show a method to rank important residues with higher inferred response to selection. These residues can be altered to effect change in properties. In this work, we define fitness as inferred thermodynamic stability. We show that under the developed framework, residues 112Y, 122K, 124D, 125W, and 126P are good candidates to increase the stability of the truncated α-amylase protein from Geobacillus thermoleovorans (PDB code: 4E2O; α-1,4-glucan-4-glucanohydrolase; EC 3.2.1.1). Overall, this paper demonstrates the feasibility of a framework for the analysis of protein structures for any other fitness landscape. [ABSTRACT FROM AUTHOR]

Transcription regulation in cestodes has been little studied. Here, we characterize the Taenia solium TATA-binding protein (TBP) gene. We found binding sites for transcription factors such as NF1, YY1, and AP-1 in the proximal promoter. We also identified two TATA-like elements in the promoter; however, neither could bind TBP. Additionally, we mapped the transcription start site (A+1) within an initiator and identified a putative downstream promoter element (DPE) located at +27 bp relative to the transcription start site. These two elements are important and functional for gene expression. Moreover, we identified the genes encoding T. solium TBP-Associated Factor 6 (TsTAF6) and 9 (TsTAF9). A Western blot assay revealed that both factors are expressed in the parasite; electrophoretic mobility shift assays and super-shift assays revealed interactions between the DPE probe and TsTAF6-TsTAF9. Finally, we used molecular dynamics simulations to formulate an interaction model among TsTAF6, TsTAF9, and the DPE probe; we stabilized the model with interactions between the histone fold domain pair in TAFs and several pairs of nucleotides in the DPE probe. We discuss novel and interesting features of the TsTAF6-TsTAF9 complex for interaction with DPE on T. solium promoters. [ABSTRACT FROM AUTHOR]

Obesity has become a global issue that affects the emergence of various chronic diseases such as diabetes mellitus, dysplasia, heart disorders, and cancer. In this study, an integration method was developed between the metabolite profile of the active compound of Murraya paniculata and the exploration of the targeting mechanism of adipose tissue using network pharmacology, molecular docking, molecular dynamics simulation, and in vitro tests. Network pharmacology results obtained with the skyline query technique using a block-nested loop (BNL) showed that histone acetyltransferase p300 (EP300), peroxisome proliferator-activated receptor gamma (PPARG), and peroxisome proliferator-activated receptor gamma coactivator 1-alpha (PPARGC1A) are potential targets for treating obesity. Enrichment analysis of these three proteins revealed their association with obesity, thermogenesis, energy metabolism, adipocytokines, fat cell differentiation, and glucose homeostasis. Metabolite profiling of M. paniculata leaves revealed sixteen active compounds, ten of which were selected for molecular docking based on drug-likeness and ADME results. Molecular docking results between PPARG and EP300 with the ten active compounds showed a binding affinity value of ≤ -5.0 kcal/mol in all dockings, indicating strong binding. The stability of the protein-ligand complex resulting from docking was examined using molecular dynamics simulations, and we observed the best average root mean square deviation (RMSD) of 0.99 Å for PPARG with trans-3-indoleacrylic acid, which was lower than with the native ligand BRL (2.02 Å). Furthermore, the RMSD was 2.70 Å for EP300 and the native ligand 99E, and the lowest RMSD with the ligand (1R,9S)-5-[(E)-2-(4-Chlorophenyl)vinyl]-11-(5-pyrimidinylcarbonyl)-7,11-diazatricyclo[7.3.1.02,7]trideca-2,4-dien-6-one was 3.33 Å. The in vitro tests to validate the potential of M. paniculata in treating obesity showed that there was a significant decrease in PPARG and EP300 gene expressions in 3T3-L1 mature adipocytes treated with M. paniculata ethanolic extract starting at concentrations 62.5 μg/ml and 15.625 μg/ml, respectively. These results indicate that M. paniculata can potentially treat obesity by disrupting adipocyte maturation and influencing intracellular lipid metabolism. [ABSTRACT FROM AUTHOR]

TOR (target of rapamycin), a ubiquitous protein kinase central to cellular homeostasis maintenance, fundamentally regulates ribosome biogenesis in part by its target La-related protein 1 (LARP1). Among other target transcripts, LARP1 specifically binds TOP (terminal oligopyrimidine) mRNAs encoding all 80 ribosomal proteins in a TOR-dependent manner through its C-terminal region containing the DM15 module. Though the functional implications of the LARP1 interaction with target mRNAs is controversial, it is clear that the TOP-LARP1-TOR axis is critical to cellular health in humans. Its existence and role in evolutionarily divergent animals remain less understood. We focused our work on expanding our knowledge of the first arm of the axis: the connection between LARP1-DM15 and the 5' TOP motif. We show that the overall DM15 architecture observed in humans is conserved in fruit fly and zebrafish. Both adopt familiar curved arrangements of HEAT-like repeats that bind 5' TOP mRNAs on the same conserved surface, although molecular dynamics simulations suggest that the N-terminal fold of the fruit fly DM15 is predicted to be unstable and unfold. We demonstrate that each ortholog interacts with TOP sequences with varying affinities. Importantly, we determine that the ability of the DM15 region to bind some TOP sequences but not others might amount to the context of the RNA structure, rather than the ability of the module to recognize some sequences but not others. We propose that TOP mRNAs may retain similar secondary structures to regulate LARP1 DM15 recognition. [ABSTRACT FROM AUTHOR]

Microcephaly, Guillain-Barré syndrome, and potential sexual transmission stand as prominent complications associated with Zika virus (ZIKV) infection. The absence of FDA-approved drugs or vaccines presents a substantial obstacle in combatting the virus. Furthermore, the inclusion of pregnancy in the pharmacological screening process complicates and extends the endeavor to ensure molecular safety and minimal toxicity. Given its pivotal role in viral assembly and maturation, the NS2B-NS3 viral protease emerges as a promising therapeutic target against ZIKV. In this context, a dipeptide inhibitor was specifically chosen as a control against 200 compounds for docking analysis. Subsequent molecular dynamics simulations extending over 200 ns were conducted to ascertain the stability of the docked complex and confirm the binding of the inhibitor at the protein's active site. The simulation outcomes exhibited conformity to acceptable thresholds, encompassing parameters such as root mean square deviation (RMSD), root mean square fluctuation (RMSF), ligand-protein interaction analysis, ligand characterization, and surface area analysis. Notably, analysis of ligand angles bolstered the identification of prospective ligands capable of inhibiting viral protein activity and impeding virus dissemination. In this study, the integration of molecular docking and dynamics simulations has pinpointed the dipeptide inhibitor as a potential candidate ligand against ZIKV protease, thereby offering promise for therapeutic intervention against the virus. [ABSTRACT FROM AUTHOR]

The retromer is a cellular structure that recruits and recycles proteins inside the cell. In mammalian and yeast, the retromer components have been widely studied, but very little in parasites. In yeast, it is formed by a SNX-BAR membrane remodeling heterodimer and the cargo selecting complex (CSC), composed by three proteins. One of them, the Vps26 protein, possesses a flexible and intrinsically disordered region (IDR), that facilitates interactions with other proteins and contributes to the retromer binding to the endosomal membrane. In Entamoeba histolytica, the protozoan parasite responsible for human amoebiasis, the retromer actively participates during the high mobility and phagocytosis of trophozoites, but the molecular details in these events, are almost unknown. Here, we studied the EhVps26 role in phagocytosis. Bioinformatic analyses of EhVps26 revealed a typical arrestin folding structure of the protein, and a long and charged IDR, as described in other systems. EhVps26 molecular dynamics simulations (MDS) allowed us to predict binding pockets for EhVps35, EhSNX3, and a PX domain-containing protein; these pockets were disorganized in a EhVps26 truncated version lacking the IDR. The AlphaFold2 software predicted the interaction of EhVps26 with EhVps35, EhVps29 and EhSNX3, in a model similar to the reported mammalian crystals. By confocal and transmission electron microscopy, EhVps26 was found in the trophozoites plasma membrane, cytosol, endosomes, and Golgi-like apparatus. During phagocytosis, it followed the erythrocytes pathway, probably participating in cargoes selection and recycling. Ehvps26 gene knocking down evidenced that the EhVps26 protein is necessary for efficient phagocytosis. [ABSTRACT FROM AUTHOR]

Alzheimer's Disease (AD) is the prevailing type of neurodegenerative illness, characterised by the accumulation of amyloid beta plaques. The symptoms associated with AD are memory loss, emotional variability, and a decline in cognitive functioning. To date, the pharmaceuticals currently accessible in the marketplace are limited to symptom management. According to several research, antidepressants have demonstrated potential efficacy in the management of AD. In this particular investigation, a total of 24 anti-depressant medications were selected as ligands, while the Microtubule Affinity Receptor Kinase 4 (MARK4) protein was chosen as the focal point of our study. The selection of MARK4 was based on its known involvement in the advancement of AD and other types of malignancies, rendering it a highly prospective target for therapeutic interventions. The initial step involved doing ADMET analysis, which was subsequently followed by molecular docking of 24 drugs. This was succeeded by molecular dynamics simulation and molecular mechanics generalised Born surface area (MMGBSA) calculations. Upon conducting molecular docking experiments, it has been determined that the binding affinities observed fall within the range of -5.5 kcal/mol to -9.0 kcal/mol. In this study, we selected six anti-depressant compounds (CID ID ‐ 4184, 2771, 4205, 5533, 4543, and 2160) based on their binding affinities, which were determined to be -9.0, -8.7, -8.4, -8.3, -8.2, and -8.2, respectively. Molecular dynamics simulations were conducted for all six drugs, with donepezil serving as the control drug. Various analyses were performed, including basic analysis and post-trajectory analysis such as free energy landscape (FEL), polarizable continuum model (PCM), and MMGBSA calculations. Based on the findings from molecular dynamics simulations and the MMGBSA analysis, it can be inferred that citalopram and mirtazapine exhibit considerable potential as anti-depressant agents. Consequently, these compounds warrant further investigation through in vitro and in vivo investigations in the context of treating AD. [ABSTRACT FROM AUTHOR]

The histone deacetylase 2 (HDAC2), an enzyme involved in gene regulation, is a potent drug target for the treatment of colon cancer. Phytocompounds having anticancer properties show the ability to interact with HDAC2 enzyme. Among the compounds, docking scores of caffeic acid (CA) and p-coumaric acid (pCA) with HDAC2 showed good binding efficacy of -5.46 kcal/mol and -5.16 kcal/mol, respectively, with small inhibition constants. The higher binding efficacy of CA compared to pCA can be credited to the presence of an extra oxygen atom in the CA molecule, which forms an additional hydrogen bond with Tyr297. The HDAC2 in complex with these molecules was found to be stable by analyzing RMSD, RMSF, Rg, and SASA values obtained through MD simulations. Furthermore, CA and pCA exhibited low MM/GBSA free energies of -16.32 ± 2.62 kcal/mol and -17.01 ± 2.87 kcal/mol, respectively. The HOMO and LUMO energy gaps, dipole moments, global reactivity descriptor values, and MEP surfaces showed the reactivity of the molecules. The favourable physicochemical and pharmacokinetic properties, along with absence of toxicity of the molecules determined using ADMET analysis, suggested both the acids to be regarded as effective drugs in the treatment of colon cancer. [ABSTRACT FROM AUTHOR]

Membrane binding is a crucial mechanism for many proteins, but understanding the specific interactions between proteins and membranes remains a challenging endeavor. Coagulation factor Va (FVa) is a large protein whose membrane interactions are complicated due to the presence of multiple anchoring domains that individually can bind to lipid membranes. Using molecular dynamics simulations, we investigate the membrane binding of FVa and identify the key mechanisms that govern its interaction with membranes. Our results reveal that FVa can either adopt an upright or a tilted molecular orientation upon membrane binding. We further find that the domain organization of FVa deviates (sometimes significantly) from its crystallographic reference structure, and that the molecular orientation of the protein matches with domain reorganization to align the C2 domain toward its favored membrane-normal orientation. We identify specific amino acid residues that exhibit contact preference with phosphatidylserine lipids over phosphatidylcholine lipids, and we observe that mostly electrostatic effects contribute to this preference. The observed lipid-binding process and characteristics, specific to FVa or common among other membrane proteins, in concert with domain reorganization and molecular tilt, elucidate the complex membrane binding dynamics of FVa and provide important insights into the molecular mechanisms of protein-membrane interactions. An updated version of the HMMM model, termed extHMMM, is successfully employed for efficiently observing membrane bindings of systems containing the whole FVa molecule. Author summary: Understanding the intricacies of protein-membrane interaction is essential for fleshing out the functional roles of membrane proteins. Substantial evidence indicates that the binding of some proteins, such as coagulation factor Va, proceeds in a multi-step manner requiring some form of rearrangements within the structure and dynamics of the protein, as well as in the protein's orientation relative to the membrane surface. In the case of factor Va, the intricate binding process can be attributed to the presence of multiple membrane-anchoring domains. In order to feasibly study the dynamics of these mechanisms, we employ an enhanced membrane-mimetic model, HMMM, capable of capturing such processes and rearrangements and making new discoveries possible using the molecular dynamics technique. The successful execution of these studies demanded several modifications to the original implementation of the HMMM. Our exploration not only improves our understanding of FVa's membrane binding dynamics but also contributes to the broader molecular mechanisms governing protein-membrane interactions. [ABSTRACT FROM AUTHOR]

Serine protease inhibitors (serpins) include thousands of structurally conserved proteins playing key roles in many organisms. Mutations affecting serpins may disturb their conformation, leading to inactive forms. Unfortunately, conformational consequences of serpin mutations are difficult to predict. In this study, we integrate experimental data of patients with mutations affecting one serpin with the predictions obtained by AlphaFold and molecular dynamics. Five SERPINC1 mutations causing antithrombin deficiency, the strongest congenital thrombophilia were selected from a cohort of 350 unrelated patients based on functional, biochemical, and crystallographic evidence supporting a folding defect. AlphaFold gave an accurate prediction for the wild-type structure. However, it also produced native structures for all variants, regardless of complexity or conformational consequences in vivo. Similarly, molecular dynamics of up to 1000 ns at temperatures causing conformational transitions did not show significant changes in the native structure of wild-type and variants. In conclusion, AlphaFold and molecular dynamics force predictions into the native conformation at conditions with experimental evidence supporting a conformational change to other structures. It is necessary to improve predictive strategies for serpins that consider the conformational sensitivity of these molecules. [ABSTRACT FROM AUTHOR]

Mitochondrial shape and network formation have been primarily associated with the well-established processes of fission and fusion. However, recent research has unveiled an intricate and multifaceted landscape of mitochondrial morphology that extends far beyond the conventional fission–fusion paradigm. These less-explored dimensions harbor numerous unresolved mysteries. This review navigates through diverse processes influencing mitochondrial shape and network formation, highlighting the intriguing complexities and gaps in our understanding of mitochondrial architecture. The exploration encompasses various scales, from biophysical principles governing membrane dynamics to molecular machineries shaping mitochondria, presenting a roadmap for future research in this evolving field. Mitochondria come in many shapes and sizes. This Unsolved Mystery navigates the diverse processes that influence mitochondrial shape and network formation, highlighting the intriguing complexities and gaps in our understanding of mitochondrial architecture. [ABSTRACT FROM AUTHOR]

Interactive Jupyter Notebooks in combination with Conda environments can be used to generate FAIR (Findable, Accessible, Interoperable and Reusable/Reproducible) biomolecular simulation workflows. The interactive programming code accompanied by documentation and the possibility to inspect intermediate results with versatile graphical charts and data visualization is very helpful, especially in iterative processes, where parameters might be adjusted to a particular system of interest. This work presents a collection of FAIR notebooks covering various areas of the biomolecular simulation field, such as molecular dynamics (MD), protein–ligand docking, molecular checking/modeling, molecular interactions, and free energy perturbations. Workflows can be launched with myBinder or easily installed in a local system. The collection of notebooks aims to provide a compilation of demonstration workflows, and it is continuously updated and expanded with examples using new methodologies and tools. [ABSTRACT FROM AUTHOR]

Inhibition of acetylcholinesterase (AChE) is a crucial target in the treatment of Alzheimer's disease (AD). Common anti-acetylcholinesterase drugs such as Galantamine, Rivastigmine, Donepezil, and Tacrine have significant inhibition potential. Due to side effects and safety concerns, we aimed to investigate a wide range of phytochemicals and structural analogues of these compounds. Compounds similar to the established drugs, and phytochemicals were investigated as potential inhibitors for AChE in treating AD. A total of 2,270 compound libraries were generated for further analysis. Initial virtual screening was performed using Pyrx software, resulting in 638 molecules showing higher binding affinities compared to positive controls Tacrine (-9.0 kcal/mol), Donepezil (-7.3 kcal/mol), Galantamine (-8.3 kcal/mol), and Rivastigmine (-6.4 kcal/mol). Subsequently, ADME properties were assessed, including blood-brain barrier permeability and Lipinski's rule of five violations, leading to 88 compounds passing the ADME analysis. Among the rivastigmine analogous, [3-(1-methylpiperidin-2-yl)phenyl] N,N-diethylcarbamate showed interaction with Tyr123, Tyr336, Tyr340, Phe337, Trp285 residues of AChE. Tacrine similar compounds, such as 4-amino-2-styrylquinoline, exhibited bindings with Tyr123, Phe337, Tyr336, Trp285, Trp85, Gly119, and Gly120 residues. A phytocompound (bisdemethoxycurcumin) showed interaction with Trp285, Tyr340, Trp85, Tyr71, and His446 residues of AChE with favourable binding. These findings underscore the potential of these compounds as novel inhibitors of AChE, offering insights into alternative therapeutic avenues for AD. A 100ns simulation analysis confirmed the stability of protein-ligand complex based on the RMSD, RMSF, ligand properties, PCA, DCCM and MMGBS parameters. The investigation suggested 3 ligands as a potent inhibitor of AChE which are [3-(1-methylpiperidin-2-yl)phenyl] N,N-diethylcarbamate, 4-Amino-2-styrylquinoline and bisdemethoxycurcumin. Furthermore, investigation, including in-vitro and in-vivo studies, is needed to validate the efficacy, safety profiles, and therapeutic potential of these compounds for AD treatment. [ABSTRACT FROM AUTHOR]

The Organic Cation Transporter Novel 1 (OCTN1), also known as SLC22A4, is widely expressed in various human tissues, and involved in numerous physiological and pathological processes remains. It facilitates the transport of organic cations, zwitterions, with selectivity for positively charged solutes. Ergothioneine, an antioxidant compound, and acetylcholine (Ach) are among its substrates. Given the lack of experimentally solved structures of this protein, this study aimed at generating a reliable 3D model of OCTN1 to shed light on its substrate-binding preferences and the role of sodium in substrate recognition and transport. A chimeric model was built by grafting the large extracellular loop 1 (EL1) from an AlphaFold-generated model onto a homology model. Molecular dynamics simulations revealed domain-specific mobility, with EL1 exhibiting the highest impact on overall stability. Molecular docking simulations identified cytarabine and verapamil as highest affinity ligands, consistent with their known inhibitory effects on OCTN1. Furthermore, MM/GBSA analysis allowed the categorization of substrates into weak, good, and strong binders, with molecular weight strongly correlating with binding affinity to the recognition site. Key recognition residues, including Tyr211, Glu381, and Arg469, were identified through interaction analysis. Ach demonstrated a low interaction energy, supporting the hypothesis of its one-directional transport towards to outside of the membrane. Regarding the role of sodium, our model suggested the involvement of Glu381 in sodium binding. Molecular dynamics simulations of systems at increasing levels of Na+ concentrations revealed increased sodium occupancy around Glu381, supporting experimental data associating Na+ concentration to molecule transport. In conclusion, this study provides valuable insights into the 3D structure of OCTN1, its substrate-binding preferences, and the role of sodium in the recognition. These findings contribute to the understanding of OCTN1 involvement in various physiological and pathological processes and may have implications for drug development and disease management. [ABSTRACT FROM AUTHOR]

This paper presents a novel method for the systematic implementation of low-power microelectronic circuits aimed at computing nonlinear cellular and molecular dynamics. The method proposed is based on the Nonlinear Bernoulli Cell Formalism (NBCF), an advanced mathematical framework stemming from the Bernoulli Cell Formalism (BCF) originally exploited for the modular synthesis and analysis of linear, time-invariant, high dynamic range, logarithmic filters. Our approach identifies and exploits the striking similarities existing between the NBCF and coupled nonlinear ordinary differential equations (ODEs) typically appearing in models of naturally encountered biochemical systems. The resulting continuous-time, continuous-value, low-power CytoMimetic electronic circuits succeed in simulating fast and with good accuracy cellular and molecular dynamics. The application of the method is illustrated by synthesising for the first time microelectronic CytoMimetic topologies which simulate successfully: 1) a nonlinear intracellular calcium oscillations model for several Hill coefficient values and 2) a gene-protein regulatory system model. The dynamic behaviours generated by the proposed CytoMimetic circuits are compared and found to be in very good agreement with their biological counterparts. The circuits exploit the exponential law codifying the low-power subthreshold operation regime and have been simulated with realistic parameters from a commercially available CMOS process. They occupy an area of a fraction of a square-millimetre, while consuming between 1 and 12 microwatts of power. Simulations of fabrication-related variability results are also presented. [ABSTRACT FROM AUTHOR]

In this paper, we report that the PX domain-containing protein SNX16, a member of the sorting nexin family, is associated with late endosome membranes. We find that SNX16 is selectively enriched on tubulo-cisternal elements of this membrane system, whose highly dynamic properties and formation depend on intact microtubules. By contrast, SNX16 was not found on vacuolar elements that typically contain LBPA, and thus presumably correspond to multivesicular endosomes. We conclude that SNX16, together with its partner phosphoinositide, define a highly dynamic subset of late endosomal membranes, supporting the notion that late endosomes are organized in distinct morphological and functional regions. Our data also indicate that SNX16 is involved in tubule formation and cholesterol transport as well as trafficking of the tetraspanin CD81, suggesting that the protein plays a role in the regulation of late endosome membrane dynamics. [ABSTRACT FROM AUTHOR]

Periplasmic Binding Proteins (PBPs) trap nutrients for their internalization into bacteria by ABC transporters. Ligand binding triggers PBP closure by bringing its two domains together like a Venus flytrap. The atomic determinants that control PBP opening and closure for nutrient capture and release are not known, although it is proposed that opening and ligand release occur while in contact with the ABC transporter for concurrent substrate translocation. In this paper we evaluated the effect of the isomerization of a conserved proline, located near the binding site, on the propensity of PBPs to open and close. ArgT/LAO from Salmonella typhimurium and HisJ from Escherichia coli were studied through molecular mechanics at two different temperatures: 300 and 323 K. Eight microseconds were simulated per protein to analyze protein opening and closure in the absence of the ABC transporter. We show that when the studied proline is in trans, closed empty LAO and HisJ can open. In contrast, with the proline in cis, opening transitions were much less frequent and characterized by smaller changes. The proline in trans also renders the open trap prone to close over a ligand. Our data suggest that the isomerization of this conserved proline modulates the PBP mechanism: the proline in trans allows the exploration of conformational space to produce trap opening and closure, while in cis it restricts PBP movement and could limit ligand release until in productive contact with the ABC transporter. This is the first time that a proline isomerization has been related to the control of a large conformational change like the PBP flytrap mechanism. [ABSTRACT FROM AUTHOR]

N-methyl--aspartate receptors (NMDARs) are members of the ionotropic glutamate receptor family that mediate excitatory synaptic transmission in the central nervous system. The channels of NMDARs are permeable to Ca2+ but blocked by Mg2+, distinctive properties that underlie essential brain processes such as induction of synaptic plasticity. However, due to limited structural information about the NMDAR transmembrane ion channel forming domain, the mechanism of divalent cation permeation and block is understood poorly. In this paper we developed an atomistic model of the transmembrane domain (TMD) of NMDARs composed of GluN1 and GluN2A subunits (GluN1/2A receptors). The model was generated using (a) a homology model based on the structure of the NaK channel and a partially resolved structure of an AMPA receptor (AMPAR), and (b) a partially resolved X-ray structure of GluN1/2B NMDARs. Refinement and extensive Molecular Dynamics (MD) simulations of the NMDAR TMD model were performed in explicit lipid bilayer membrane and water. Targeted MD with simulated annealing was introduced to promote structure refinement. Putative positions of the Mg2+ and Ca2+ ions in the ion channel divalent cation binding site are proposed. Differences in the structural and dynamic behavior of the channel protein in the presence of Mg2+ or Ca2+ are analyzed. NMDAR protein conformational flexibility was similar with no ion bound to the divalent cation binding site and with Ca2+ bound, whereas Mg2+ binding reduced protein fluctuations. While bound at the binding site both ions retained their preferred ligand coordination numbers: 6 for Mg2+, and 7–8 for Ca2+. Four asparagine side chain oxygens, a back-bone oxygen, and a water molecule participated in binding a Mg2+ ion. The Ca2+ ion first coordination shell ligands typically included four to five side-chain oxygen atoms of the binding site asparagine residues, two water molecules and zero to two backbone oxygens of the GluN2B subunits. These results demonstrate the importance of high-resolution channel structures for elucidation of mechanisms of NMDAR permeation and block. [ABSTRACT FROM AUTHOR]

In a reaction, determination of an optimal path with a high reaction rate (or a low free energy barrier) is important for the study of the reaction mechanism. This is a complicated problem that involves lots of degrees of freedom. For simple models, one can build an initial path in the collective variable space by the interpolation method first and then update the whole path constantly in the optimization. However, such interpolation method could be risky in the high dimensional space for large molecules. On the path, steric clashes between neighboring atoms could cause extremely high energy barriers and thus fail the optimization. Moreover, performing simulations for all the snapshots on the path is also time-consuming. In this paper, we build and optimize the path by a growing method on the free energy surface. The method grows a path from the reactant and extends its length in the collective variable space step by step. The growing direction is determined by both the free energy gradient at the end of the path and the direction vector pointing at the product. With fewer snapshots on the path, this strategy can let the path avoid the high energy states in the growing process and save the precious simulation time at each iteration step. Applications show that the presented method is efficient enough to produce optimal paths on either the two-dimensional or the twelve-dimensional free energy surfaces of different small molecules. [ABSTRACT FROM AUTHOR]

The propensity of cellular prion protein to aggregation is reputed essential for the initiation of the amyloid cascade that ultimately lead to the accumulation of neurotoxic aggregates. In this paper, we extended and applied an already reported computational workflow [Proteins 2015; 83: 1751–1765] to elucidate in details the aggregation propensity of PrP protein systems including wild type, wild type treated at different [Ca2+] and E200K mutant. The application of the computational procedure to two segments of PrPC, i.e. 125–228 and 120–231, allowed to emphasize how the inclusion of complete C-terminus and last portion (120–126) of the neurotoxic segment 106–126 may be crucial to unveil significant and unexpected interaction properties. Indeed, the anchoring of N-terminus on H2 domain detected in the wild type resulted to be disrupted upon either E200K mutation or Ca2+ binding, and to unbury hydrophobic spots on the PrPC surface. A peculiar dinuclear Ca2+ binding motif formed by the C-terminus and the S2-H2 loop was detected for [Ca2+] > 5 mM and showed similarities with binding motifs retraced in other protein systems, thus suggesting a possible functional meaning for its formation. Therefore, we potentiated the computational procedure by including a tool that clusterize the minima of molecular interaction fields of a proteinand delimit the regions of space with higher hydrophobic or higher hydrophilic character, hence, more likely involved in the self-assembly process. Plausible models for the self-assembly of either the E200K mutated or Ca2+-bound PrPC were sketched and discussed. The present investigation provides for structure-based information and new prompts that may represent a starting point for future experimental or computational works on the PrPC aggregation. [ABSTRACT FROM AUTHOR]

We use AlphaFold2 (AF2) to model the monomer and dimer structures of an intrinsically disordered protein (IDP), Nvjp-1, assisted by molecular dynamics (MD) simulations. We observe relatively rigid dimeric structures of Nvjp-1 when compared with the monomer structures. We suggest that protein conformations from multiple AF2 models and those from MD trajectories exhibit a coherent trend: the conformations of an IDP are deviated from each other and the conformations of a well-folded protein are consistent with each other. We use a residue-residue interaction network (RIN) derived from the contact map which show that the residue-residue interactions in Nvjp-1 are mainly transient; however, those in a well-folded protein are mainly persistent. Despite the variation in 3D shapes, we show that the AF2 models of both disordered and ordered proteins exhibit highly consistent profiles of the pLDDT (predicted local distance difference test) scores. These results indicate a potential protocol to justify the IDPs based on multiple AF2 models and MD simulations. [ABSTRACT FROM AUTHOR]

Mammals have 6 highly conserved actin isoforms with nonredundant biological functions. The molecular basis of isoform specificity, however, remains elusive due to a lack of tools. Here, we describe the development of IntAct, an internal tagging strategy to study actin isoforms in fixed and living cells. We identified a residue pair in β-actin that permits tag integration and used knock-in cell lines to demonstrate that IntAct β-actin expression and filament incorporation is indistinguishable from wild type. Furthermore, IntAct β-actin remains associated with common actin-binding proteins (ABPs) and can be targeted in living cells. We demonstrate the usability of IntAct for actin isoform investigations by showing that actin isoform-specific distribution is maintained in human cells. Lastly, we observed a variant-dependent incorporation of tagged actin variants into yeast actin patches, cables, and cytokinetic rings demonstrating cross species applicability. Together, our data indicate that IntAct is a versatile tool to study actin isoform localization, dynamics, and molecular interactions. Mammals have six highly-conserved actin isoforms with nonredundant functions, but their molecular properties remain unknown. These authors develop IntAct, a versatile tool to study actin isoform localization, dynamics and molecular interactions across species in both fixed an living cells. [ABSTRACT FROM AUTHOR]

Experimental and mathematical studies in immunology have revealed that the dynamics of the programmed T cell response to vigorous infection can be conveniently modelled using a sigmoidal or a discontinuous immune response function. This paper hypothesizes strong synergies between this existing work and the dynamical behaviour of engineering systems with a variable structure control (VSC) law. These findings motivate the interpretation of the immune system as a variable structure control system. It is shown that dynamical properties as well as conditions to analytically assess the transition from health to disease can be developed for the specific T cell response from the theory of variable structure control. In particular, it is shown that the robustness properties of the specific T cell response as observed in experiments can be explained analytically using a VSC perspective. Further, the predictive capacity of the VSC framework to determine the T cell help required to overcome chronic Lymphocytic Choriomeningitis Virus (LCMV) infection is demonstrated. The findings demonstrate that studying the immune system using variable structure control theory provides a new framework for evaluating immunological dynamics and experimental observations. A modelling and simulation tool results with predictive capacity to determine how to modify the immune response to achieve healthy outcomes which may have application in drug development and vaccine design. [ABSTRACT FROM AUTHOR]

Tethered bilayer lipid membranes (tBLMs) provide a stable platform for modeling the dynamics and order of biological membranes where the tethers mimic the cytoskeletal supports present in biological cell membranes. In this paper coarse-grained molecular dynamics (CGMD) is applied to study the effects of tethers on lipid membrane properties. Using results from the CGMD model and the overdamped Fokker-Planck equation, we show that the diffusion tensor and particle density of water in the tBLM is spatially dependent. Further, it is shown that the membrane thickness, lipid diffusion, defect density, free energy of lipid flip-flop, and membrane dielectric permittivity are all dependent on the tether density. The numerically computed results from the CGMD model are in agreement with the experimentally measured results from tBLMs containing different tether densities and lipids derived from Archaebacteria. Additionally, using experimental measurements from Escherichia coli bacteria and Saccharomyces Cerevisiae yeast tethered membranes, we illustrate how previous molecular dynamics results can be combined with the proposed model to estimate the dielectric permittivity and defect density of these membranes as a function of tether density. [ABSTRACT FROM AUTHOR]

Kinks are a structural feature of alpha-helices and many are known to have functional roles. Kinks have previously tended to be defined in a binary fashion. In this paper we have deliberately moved towards defining them on a continuum, which given the unimodal distribution of kink angles is a better description. From this perspective, we examine the conservation of kinks in proteins. We find that kink angles are not generally a conserved property of homologs, pointing either to their not being functionally critical or to their function being related to conformational flexibility. In the latter case, the different structures of homologs are providing snapshots of different conformations. Sequence identity between homologous helices is informative in terms of kink conservation, but almost equally so is the sequence identity of residues in spatial proximity to the kink. In the specific case of proline, which is known to be prevalent in kinked helices, loss of a proline from a kinked helix often also results in the loss of a kink or reduction in its kink angle. We carried out a study of the seven transmembrane helices in the GPCR family and found that changes in kinks could be related both to subfamilies of GPCRs and also, in a particular subfamily, to the binding of agonists or antagonists. These results suggest conformational change upon receptor activation within the GPCR family. We also found correlation between kink angles in different helices, and the possibility of concerted motion could be investigated further by applying our method to molecular dynamics simulations. These observations reinforce the belief that helix kinks are key, functional, flexible points in structures. [ABSTRACT FROM AUTHOR]

Insertions/deletions are common evolutionary tools employed to alter the structural and functional repertoire of protein domains. An insert situated proximal to the active site or ligand binding site frequently impacts protein function; however, the effect of distal indels on protein activity and/or stability are often not studied. In this paper, we have investigated a distal insert, which influences the function and stability of a unique DNA polymerase, called terminal deoxynucleotidyl transferase (TdT). TdT (EC:2.7.7.31) is a monomeric 58 kDa protein belonging to family X of eukaryotic DNA polymerases and known for its role in V(D)J recombination as well as in non-homologous end-joining (NHEJ) pathways. Two murine isoforms of TdT, with a length difference of twenty residues and having different biochemical properties, have been studied. All-atom molecular dynamics simulations at different temperatures and interaction network analyses were performed on the short and long-length isoforms. We observed conformational changes in the regions distal to the insert position (thumb subdomain) in the longer isoform, which indirectly affects the activity and stability of the enzyme through a mediating loop (Loop1). A structural rationale could be provided to explain the reduced polymerization rate as well as increased thermosensitivity of the longer isoform caused by peripherally located length variations within a DNA polymerase. These observations increase our understanding of the roles of length variants in introducing functional diversity in protein families in general. [ABSTRACT FROM AUTHOR]