ResearchPad - biochemical-simulations https://www.researchpad.co Default RSS Feed en-us © 2020 Newgen KnowledgeWorks <![CDATA[How global DNA unwinding causes non-uniform stress distribution and melting of DNA]]> https://www.researchpad.co/article/elastic_article_14712 DNA unwinding is an important process that controls binding of proteins, gene expression and melting of double-stranded DNA. In a series of all-atom MD simulations on two DNA molecules containing a transcription start TATA-box sequence we demonstrate that application of a global restraint on the DNA twisting dramatically changes the coupling between helical parameters and the distribution of deformation energy along the sequence. Whereas only short range nearest-neighbor coupling is observed in the relaxed case, long-range coupling is induced in the globally restrained case. With increased overall unwinding the elastic deformation energy is strongly non-uniformly distributed resulting ultimately in a local melting transition of only the TATA box segment during the simulations. The deformation energy tends to be stored more in cytidine/guanine rich regions associated with a change in conformational substate distribution. Upon TATA box melting the deformation energy is largely absorbed by the melting bubble with the rest of the sequences relaxing back to near B-form. The simulations allow us to characterize the structural changes and the propagation of the elastic energy but also to calculate the associated free energy change upon DNA unwinding up to DNA melting. Finally, we design an Ising model for predicting the local melting transition based on empirical parameters. The direct comparison with the atomistic MD simulations indicates a remarkably good agreement for the predicted necessary torsional stress to induce a melting transition, for the position and length of the melted region and for the calculated associated free energy change between both approaches.

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<![CDATA[Crystal structure of <i>Thermus thermophilus</i> methylenetetrahydrofolate dehydrogenase and determinants of thermostability]]> https://www.researchpad.co/article/elastic_article_13865 The elucidation of mechanisms behind the thermostability of proteins is extremely important both from the theoretical and applied perspective. Here we report the crystal structure of methylenetetrahydrofolate dehydrogenase (MTHFD) from Thermus thermophilus HB8, a thermophilic model organism. Molecular dynamics trajectory analysis of this protein at different temperatures (303 K, 333 K and 363 K) was compared with homologous proteins from the less temperature resistant organism Thermoplasma acidophilum and the mesophilic organism Acinetobacter baumannii using several data reduction techniques like principal component analysis (PCA), residue interaction network (RIN) analysis and rotamer analysis. These methods enabled the determination of important residues for the thermostability of this enzyme. The description of rotamer distributions by Gini coefficients and Kullback–Leibler (KL) divergence both revealed significant correlations with temperature. The emerging view seems to indicate that a static salt bridge/charged residue network plays a fundamental role in the temperature resistance of Thermus thermophilus MTHFD by enhancing both electrostatic interactions and entropic energy dispersion. Furthermore, this analysis uncovered a relationship between residue mutations and evolutionary pressure acting on thermophilic organisms and thus could be of use for the design of future thermostable enzymes.

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<![CDATA[Time-lapse imaging of HeLa spheroids in soft agar culture provides virtual inner proliferative activity]]> https://www.researchpad.co/article/Nceafa1bd-f75c-4e08-9c15-587118f668b1

Cancer is a complex disease caused by multiple types of interactions. To simplify and normalize the assessment of drug effects, spheroid microenvironments have been utilized. Research models that involve agent measurement with the examination of clonogenic survival by monitoring culture process with image analysis have been developed for spheroid-based screening. Meanwhile, computer simulations using various models have enabled better predictions for phenomena in cancer. However, user-based parameters that are specific to a researcher’s own experimental conditions must be inputted. In order to bridge the gap between experimental and simulated conditions, we have developed an in silico analysis method with virtual three-dimensional embodiment computed using the researcher’s own samples. The present work focused on HeLa spheroid growth in soft agar culture, with spheroids being modeled in silico based on time-lapse images capturing spheroid growth. The spheroids in silico were optimized by adjusting the growth curves to those obtained from time-lapse images of spheroids and were then assigned virtual inner proliferative activity by using generations assigned to each cellular particle. The ratio and distribution of the virtual inner proliferative activities were confirmed to be similar to the proliferation zone ratio and histochemical profiles of HeLa spheroids, which were also consistent with those identified in an earlier study. We validated that time-lapse images of HeLa spheroids provided virtual inner proliferative activity for spheroids in vitro. The present work has achieved the first step toward an in silico analysis method using computational simulation based on a researcher’s own samples, helping to bridge the gap between experiment and simulation.

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<![CDATA[Chemical profile of Lippia thymoides, evaluation of the acetylcholinesterase inhibitory activity of its essential oil, and molecular docking and molecular dynamics simulations]]> https://www.researchpad.co/article/5c8c194fd5eed0c484b4d3c7

The essential oils of the fresh and dry flowers, leaves, branches, and roots of Lippia thymoides were obtained by hydrodistillation and analyzed using gas chromatography (GC) and GC–mass spectrometry (MS). The acetylcholinesterase inhibitory activity of the essential oil of fresh leaves was investigated on silica gel plates. The interactions of the key compounds with acetylcholinesterase were simulated by molecular docking and molecular dynamics studies. In total, 75 compounds were identified, and oxygenated monoterpenes were the dominant components of all the plant parts, ranging from 19.48% to 84.99%. In the roots, the main compounds were saturated and unsaturated fatty acids, having contents varying from 39.5% to 32.17%, respectively. In the evaluation of the anticholinesterase activity, the essential oils (detection limit (DL) = 0.1 ng/spot) were found to be about ten times less active than that of physostigmine (DL = 0.01ng/spot), whereas thymol and thymol acetate presented DL values each of 0.01 ng/spot, equivalent to that of the positive control. Based on the docking and molecular dynamics studies, thymol and thymol acetate interact with the catalytic residues Ser203 and His447 of the active site of acetylcholinesterase. The binding free energies (ΔGbind) for these ligands were -18.49 and -26.88 kcal/mol, demonstrating that the ligands are able to interact with the protein and inhibit their catalytic activity.

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<![CDATA[The ability of locked nucleic acid oligonucleotides to pre-structure the double helix: A molecular simulation and binding study]]> https://www.researchpad.co/article/5c6c7570d5eed0c4843cfda2

Locked nucleic acid (LNA) oligonucleotides bind DNA target sequences forming Watson-Crick and Hoogsteen base pairs, and are therefore of interest for medical applications. To be biologically active, such an oligonucleotide has to efficiently bind the target sequence. Here we used molecular dynamics simulations and electrophoresis mobility shift assays to elucidate the relation between helical structure and affinity for LNA-containing oligonucleotides. In particular, we have studied how LNA substitutions in the polypyrimidine strand of a duplex (thus forming a hetero duplex, i.e. a duplex with a DNA polypurine strand and an LNA/DNA polypyrimidine strand) enhance triplex formation. Based on seven polypyrimidine single strand oligonucleotides, having LNAs in different positions and quantities, we show that alternating LNA with one or more non-modified DNA nucleotides pre-organizes the hetero duplex toward a triple-helical-like conformation. This in turn promotes triplex formation, while consecutive LNAs distort the duplex structure disfavoring triplex formation. The results support the hypothesis that a pre-organization in the hetero duplex structure enhances the binding of triplex forming oligonucleotides. Our findings may serve as a criterion in the design of new tools for efficient oligonucleotide hybridization.

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<![CDATA[Molecular dynamic (MD) studies on Gln233Arg (rs1137101) polymorphism of leptin receptor gene and associated variations in the anthropometric and metabolic profiles of Saudi women]]> https://www.researchpad.co/article/5c6f1542d5eed0c48467afac

The Gln233Arg (A>G; rs1137101) polymorphism of the leptin receptor gene (LEPR) has been investigated extensively and is reported to be associated with different metabolic states. In this investigation, we aimed to study the frequency of Gln233Arg genotypes and alleles in a group of Saudi women stratified by their body mass index (BMI), to correlate the LEPR genotypes with variations in anthropometric, lipid and hormonal parameters and to investigate conformational and structural variations in the mutant LEPR using molecular dynamic (MD) investigations. The study group included 122 Saudi women (normal weight = 60; obese = 62) attending the clinics for a routine checkup. Anthropometric data: height, weight, waist and hip circumference were recorded and fasting serum sample was used to estimate glucose, lipids, ghrelin, leptin and insulin. BMI, W/H ratio, and HOMA-IR values were calculated. Whole blood sample was used to extract DNA; exon 6 of the LEPR gene was amplified by PCR and sequencing was conducted on an ABI 3100 Avant Genetic Analyser. Molecular Dynamic Simulation studies were carried out using different softwares. The results showed the presence of all three genotypes of Gln233Arg in Saudi women, but the frequencies were significantly different when compared to reports from some populations. No differences were seen in the genotype and allele frequencies between the normal weight and obese women. Stratification by the genotypes showed significantly higher BMI, waist and hip circumference, leptin, insulin, fasting glucose and HOMA-IR and lower ghrelin levels in obese women carrying the GG genotype. Even in the normal weight group, individuals with GG genotype had higher BMI, waist and hip circumference and significantly lower ghrelin levels. The MD studies showed a significant effect of the Gln/Arg substitution on the conformation, flexibility, root-mean-square fluctuation (RMSF), radius of gyration (Rg) values, solvent-accessible surface area (SASA) and number of inter- and intra-molecular H-bonds. The results suggest that the structural changes brought about by the mutation, influence the signaling pathways by some unknown mechanism, which may be contributing to the abnormalities seen in the individuals carrying the G allele of rs1137101.

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<![CDATA[Metal based donepezil analogues designed to inhibit human acetylcholinesterase for Alzheimer’s disease]]> https://www.researchpad.co/article/5c76fe06d5eed0c484e5b2cd

Among neurodegenerative disorders, Alzheimer’s disease (AD) is one of the most common disorders showing slow progressive cognitive decline. Targeting acetylcholinesterase (AChE) is one of the major strategies for AD therapeutics, as cholinergic pathways in the cerebral cortex and basal forebrain are compromised. Herein, we report the design of some copper and other metal based donepezil derivatives, employing density functional theory (DFT). All designed compounds are optimized at the B3LYP/SDD level of theory. Dipole moments, electronic energie, enthalpies, Gibbs free energies, and HOMO-LUMO gaps of these modified compounds are also investigated in the subsequent analysis. The molecules were then subjected to molecular docking analysis with AChE to study the molecular interactions broadly. Ensemble based docking and molecular dynamics (MD) simulations of the best candidates were also performed. Docking and MD simulation reveal that modified drugs are more potent than unmodified donepezil, where Trp86, Tyr337, Phe330 residues play some important roles in drug-receptor interactions. According to ensemble based docking, D9 shows greater binding affinity compared to the parent in most conformations obtained from protein data bank and MD simulation. In addition, it is observed that the π- π stacking with the residues of Trp86, Tyr337, Tyr341, Tyr124 and Trp286 may be required for strong ligand binding. Moreover, ADME/T analysis suggests that modified derivatives are less toxic and have improved pharmacokinetic properties than those of the parent drug. These results further confirm the ability of metal-directed drugs to bind simultaneously to the active sites of AChE and support them as potential candidates for the future treatment of Alzheimer’s disease.

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<![CDATA[Modeling cell line-specific recruitment of signaling proteins to the insulin-like growth factor 1 receptor]]> https://www.researchpad.co/article/5c4a308ed5eed0c4844c04f9

Receptor tyrosine kinases (RTKs) typically contain multiple autophosphorylation sites in their cytoplasmic domains. Once activated, these autophosphorylation sites can recruit downstream signaling proteins containing Src homology 2 (SH2) and phosphotyrosine-binding (PTB) domains, which recognize phosphotyrosine-containing short linear motifs (SLiMs). These domains and SLiMs have polyspecific or promiscuous binding activities. Thus, multiple signaling proteins may compete for binding to a common SLiM and vice versa. To investigate the effects of competition on RTK signaling, we used a rule-based modeling approach to develop and analyze models for ligand-induced recruitment of SH2/PTB domain-containing proteins to autophosphorylation sites in the insulin-like growth factor 1 (IGF1) receptor (IGF1R). Models were parameterized using published datasets reporting protein copy numbers and site-specific binding affinities. Simulations were facilitated by a novel application of model restructuration, to reduce redundancy in rule-derived equations. We compare predictions obtained via numerical simulation of the model to those obtained through simple prediction methods, such as through an analytical approximation, or ranking by copy number and/or KD value, and find that the simple methods are unable to recapitulate the predictions of numerical simulations. We created 45 cell line-specific models that demonstrate how early events in IGF1R signaling depend on the protein abundance profile of a cell. Simulations, facilitated by model restructuration, identified pairs of IGF1R binding partners that are recruited in anti-correlated and correlated fashions, despite no inclusion of cooperativity in our models. This work shows that the outcome of competition depends on the physicochemical parameters that characterize pairwise interactions, as well as network properties, including network connectivity and the relative abundances of competitors.

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<![CDATA[Kinetic and thermodynamic insights into sodium ion translocation through the μ-opioid receptor from molecular dynamics and machine learning analysis]]> https://www.researchpad.co/article/5c536a92d5eed0c484a47639

The differential modulation of agonist and antagonist binding to opioid receptors (ORs) by sodium (Na+) has been known for decades. To shed light on the molecular determinants, thermodynamics, and kinetics of Na+ translocation through the μ-OR (MOR), we used a multi-ensemble Markov model framework combining equilibrium and non-equilibrium atomistic molecular dynamics simulations of Na+ binding to MOR active or inactive crystal structures embedded in an explicit lipid bilayer. We identify an energetically favorable, continuous ion pathway through the MOR active conformation only, and provide, for the first time: i) estimates of the energy differences and required timescales of Na+ translocation in inactive and active MORs, ii) estimates of Na+-induced changes to agonist binding validated by radioligand measurements, and iii) testable hypotheses of molecular determinants and correlated motions involved in this translocation, which are likely to play a key role in MOR signaling.

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<![CDATA[Characterisation of a type II functionally-deficient variant of alpha-1-antitrypsin discovered in the general population]]> https://www.researchpad.co/article/5c424390d5eed0c4845e05dc

Lung disease in alpha-1-antitrypsin deficiency (AATD) results from dysregulated proteolytic activity, mainly by neutrophil elastase (HNE), in the lung parenchyma. This is the result of a substantial reduction of circulating alpha-1-antitrypsin (AAT) and the presence in the plasma of inactive polymers of AAT. Moreover, some AAT mutants have reduced intrinsic activity toward HNE, as demonstrated for the common Z mutant, as well as for other rarer variants. Here we report the identification and characterisation of the novel AAT reactive centre loop variant Gly349Arg (p.G373R) present in the ExAC database. This AAT variant is secreted at normal levels in cellular models of AATD but shows a severe reduction in anti-HNE activity. Biochemical and molecular dynamics studies suggest it exhibits unfavourable RCL presentation to cognate proteases and compromised insertion of the RCL into β-sheet A. Identification of a fully dysfunctional AAT mutant that does not show a secretory defect underlines the importance of accurate genotyping of patients with pulmonary AATD manifestations regardless of the presence of normal levels of AAT in the circulation. This subtype of disease is reminiscent of dysfunctional phenotypes in anti-thrombin and C1-inibitor deficiencies so, accordingly, we classify this variant as the first pure functionally-deficient (type II) AATD mutant.

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<![CDATA[Allele-specific RNA imaging shows that allelic imbalances can arise in tissues through transcriptional bursting]]> https://www.researchpad.co/article/5c3fa5f1d5eed0c484caa55b

Extensive cell-to-cell variation exists even among putatively identical cells, and there is great interest in understanding how the properties of transcription relate to this heterogeneity. Differential expression from the two gene copies in diploid cells could potentially contribute, yet our ability to measure from which gene copy individual RNAs originated remains limited, particularly in the context of tissues. Here, we demonstrate quantitative, single molecule allele-specific RNA FISH adapted for use on tissue sections, allowing us to determine the chromosome of origin of individual RNA molecules in formaldehyde-fixed tissues. We used this method to visualize the allele-specific expression of Xist and multiple autosomal genes in mouse kidney. By combining these data with mathematical modeling, we evaluated models for allele-specific heterogeneity, in particular demonstrating that apparent expression from only one of the alleles in single cells can arise as a consequence of low-level mRNA abundance and transcriptional bursting.

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<![CDATA[On identifying collective displacements in apo-proteins that reveal eventual binding pathways]]> https://www.researchpad.co/article/5c478c43d5eed0c484bd1278

Binding of small molecules to proteins often involves large conformational changes in the latter, which open up pathways to the binding site. Observing and pinpointing these rare events in large scale, all-atom, computations of specific protein-ligand complexes, is expensive and to a great extent serendipitous. Further, relevant collective variables which characterise specific binding or un-binding scenarios are still difficult to identify despite the large body of work on the subject. Here, we show that possible primary and secondary binding pathways can be discovered from short simulations of the apo-protein without waiting for an actual binding event to occur. We use a projection formalism, introduced earlier to study deformation in solids, to analyse local atomic displacements into two mutually orthogonal subspaces—those which are “affine” i.e. expressible as a homogeneous deformation of the native structure, and those which are not. The susceptibility to non-affine displacements among the various residues in the apo- protein is then shown to correlate with typical binding pathways and sites crucial for allosteric modifications. We validate our observation with all-atom computations of three proteins, T4-Lysozyme, Src kinase and Cytochrome P450.

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<![CDATA[Protein—protein binding supersites]]> https://www.researchpad.co/article/5c3d00e9d5eed0c4840369fc

The lack of a deep understanding of how proteins interact remains an important roadblock in advancing efforts to identify binding partners and uncover the corresponding regulatory mechanisms of the functions they mediate. Understanding protein-protein interactions is also essential for designing specific chemical modifications to develop new reagents and therapeutics. We explored the hypothesis of whether protein interaction sites serve as generic biding sites for non-cognate protein ligands, just as it has been observed for small-molecule-binding sites in the past. Using extensive computational docking experiments on a test set of 241 protein complexes, we found that indeed there is a strong preference for non-cognate ligands to bind to the cognate binding site of a receptor. This observation appears to be robust to variations in docking programs, types of non-cognate protein probes, sizes of binding patches, relative sizes of binding patches and full-length proteins, and the exploration of obligate and non-obligate complexes. The accuracy of the docking scoring function appears to play a role in defining the correct site. The frequency of interaction of unrelated probes recognizing the binding interface was utilized in a simple prediction algorithm that showed accuracy competitive with other state of the art methods.

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<![CDATA[Energy landscape for the insertion of amphiphilic nanoparticles into lipid membranes: A computational study]]> https://www.researchpad.co/article/5c3fa610d5eed0c484cabadc

Amphiphilic, monolayer-protected gold nanoparticles (NPs) have been shown to enter cells via a non-endocytic, non-disruptive pathway that could be valuable for biomedical applications. The same NPs were also found to insert into a series of model cell membranes as a precursor to cellular uptake, but the insertion mechanism remains unclear. Previous simulations have demonstrated that an amphiphilic NP can insert into a single leaflet of a planar lipid bilayer, but in this configuration all charged end groups are localized to one side of the bilayer and it is unknown if further insertion is thermodynamically favorable. Here, we use atomistic molecular dynamics simulations to show that an amphiphilic NP can reach the bilayer midplane non-disruptively if charged ligands iteratively “flip” across the bilayer. Ligand flipping is a favorable process that relaxes bilayer curvature, decreases the nonpolar solvent-accessible surface area of the NP monolayer, and increases attractive ligand-lipid electrostatic interactions. Analysis of end group hydration further indicates that iterative ligand flipping can occur on experimentally relevant timescales. Supported by these results, we present a complete energy landscape for the non-disruptive insertion of amphiphilic NPs into lipid bilayers. These findings will help guide the design of NPs to enhance bilayer insertion and non-endocytic cellular uptake, and also provide physical insight into a possible pathway for the translocation of charged biomacromolecules.

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<![CDATA[Trajectory-based training enables protein simulations with accurate folding and Boltzmann ensembles in cpu-hours]]> https://www.researchpad.co/article/5c2e7fdbd5eed0c48451bc2f

An ongoing challenge in protein chemistry is to identify the underlying interaction energies that capture protein dynamics. The traditional trade-off in biomolecular simulation between accuracy and computational efficiency is predicated on the assumption that detailed force fields are typically well-parameterized, obtaining a significant fraction of possible accuracy. We re-examine this trade-off in the more realistic regime in which parameterization is a greater source of error than the level of detail in the force field. To address parameterization of coarse-grained force fields, we use the contrastive divergence technique from machine learning to train from simulations of 450 proteins. In our procedure, the computational efficiency of the model enables high accuracy through the precise tuning of the Boltzmann ensemble. This method is applied to our recently developed Upside model, where the free energy for side chains is rapidly calculated at every time-step, allowing for a smooth energy landscape without steric rattling of the side chains. After this contrastive divergence training, the model is able to de novo fold proteins up to 100 residues on a single core in days. This improved Upside model provides a starting point both for investigation of folding dynamics and as an inexpensive Bayesian prior for protein physics that can be integrated with additional experimental or bioinformatic data.

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<![CDATA[Molecular basis for the increased affinity of an RNA recognition motif with re-engineered specificity: A molecular dynamics and enhanced sampling simulations study]]> https://www.researchpad.co/article/5c12cf9cd5eed0c484914a5f

The RNA recognition motif (RRM) is the most common RNA binding domain across eukaryotic proteins. It is therefore of great value to engineer its specificity to target RNAs of arbitrary sequence. This was recently achieved for the RRM in Rbfox protein, where four mutations R118D, E147R, N151S, and E152T were designed to target the precursor to the oncogenic miRNA 21. Here, we used a variety of molecular dynamics-based approaches to predict specific interactions at the binding interface. Overall, we have run approximately 50 microseconds of enhanced sampling and plain molecular dynamics simulations on the engineered complex as well as on the wild-type Rbfox·pre-miRNA 20b from which the mutated systems were designed. Comparison with the available NMR data on the wild type molecules (protein, RNA, and their complex) served to establish the accuracy of the calculations.

Free energy calculations suggest that further improvements in affinity and selectivity are achieved by the S151T replacement.

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<![CDATA[Rosetta FunFolDes – A general framework for the computational design of functional proteins]]> https://www.researchpad.co/article/5bfc6223d5eed0c484ec6c7f

The robust computational design of functional proteins has the potential to deeply impact translational research and broaden our understanding of the determinants of protein function and stability. The low success rates of computational design protocols and the extensive in vitro optimization often required, highlight the challenge of designing proteins that perform essential biochemical functions, such as binding or catalysis. One of the most simplistic approaches for the design of function is to adopt functional motifs in naturally occurring proteins and transplant them to computationally designed proteins. The structural complexity of the functional motif largely determines how readily one can find host protein structures that are “designable”, meaning that are likely to present the functional motif in the desired conformation. One promising route to enhance the “designability” of protein structures is to allow backbone flexibility. Here, we present a computational approach that couples conformational folding with sequence design to embed functional motifs into heterologous proteins—Rosetta Functional Folding and Design (FunFolDes). We performed extensive computational benchmarks, where we observed that the enforcement of functional requirements resulted in designs distant from the global energetic minimum of the protein. An observation consistent with several experimental studies that have revealed function-stability tradeoffs. To test the design capabilities of FunFolDes we transplanted two viral epitopes into distant structural templates including one de novo “functionless” fold, which represent two typical challenges where the designability problem arises. The designed proteins were experimentally characterized showing high binding affinities to monoclonal antibodies, making them valuable candidates for vaccine design endeavors. Overall, we present an accessible strategy to repurpose old protein folds for new functions. This may lead to important improvements on the computational design of proteins, with structurally complex functional sites, that can perform elaborate biochemical functions related to binding and catalysis.

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<![CDATA[Towards a molecular basis of ubiquitin signaling: A dual-scale simulation study of ubiquitin dimers]]> https://www.researchpad.co/article/5bf86f60d5eed0c48405a957

Covalent modification of proteins by ubiquitin or ubiquitin chains is one of the most prevalent post-translational modifications in eukaryotes. Different types of ubiquitin chains are assumed to selectively signal respectively modified proteins for different fates. In support of this hypothesis, structural studies have shown that the eight possible ubiquitin dimers adopt different conformations. However, at least in some cases, these structures cannot sufficiently explain the molecular basis of the selective signaling mechanisms. This indicates that the available structures represent only a few distinct conformations within the entire conformational space adopted by a ubiquitin dimer. Here, molecular simulations on different levels of resolution can complement the structural information. We have combined exhaustive coarse grained and atomistic simulations of all eight possible ubiquitin dimers with a suitable dimensionality reduction technique and a new method to characterize protein-protein interfaces and the conformational landscape of protein conjugates. We found that ubiquitin dimers exhibit characteristic linkage type-dependent properties in solution, such as interface stability and the character of contacts between the subunits, which can be directly correlated with experimentally observed linkage-specific properties.

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<![CDATA[De novo protein structure prediction using ultra-fast molecular dynamics simulation]]> https://www.researchpad.co/article/5bfdb391d5eed0c4845ca84a

Modern genomics sequencing techniques have provided a massive amount of protein sequences, but experimental endeavor in determining protein structures is largely lagging far behind the vast and unexplored sequences. Apparently, computational biology is playing a more important role in protein structure prediction than ever. Here, we present a system of de novo predictor, termed NiDelta, building on a deep convolutional neural network and statistical potential enabling molecular dynamics simulation for modeling protein tertiary structure. Combining with evolutionary-based residue-contacts, the presented predictor can predict the tertiary structures of a number of target proteins with remarkable accuracy. The proposed approach is demonstrated by calculations on a set of eighteen large proteins from different fold classes. The results show that the ultra-fast molecular dynamics simulation could dramatically reduce the gap between the sequence and its structure at atom level, and it could also present high efficiency in protein structure determination if sparse experimental data is available.

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<![CDATA[Combining multi-scale modelling methods to decipher molecular motions of a branching sucrase from glycoside-hydrolase family 70]]> https://www.researchpad.co/article/5b6d94bd463d7e2f79286cc2

Among α-transglucosylases from Glycoside-Hydrolase family 70, the ΔN123-GB-CD2 enzyme derived from the bifunctional DSR-E from L. citreum NRRL B-1299 is particularly interesting as it was the first described engineered Branching Sucrase, not able to elongate glucan polymers from sucrose substrate. The previously reported overall structural organization of this multi-domain enzyme is an intricate U-shape fold conserved among GH70 enzymes which showed a certain conformational variability of the so-called domain V, assumed to play a role in the control of product structures, in available X-ray structures. Understanding the role of functional dynamics on enzyme reaction and substrate recognition is of utmost interest although it remains a challenge for biophysical methods. By combining long molecular dynamics simulation (1μs) and multiple analyses (NMA, PCA, Morelet Continuous Wavelet Transform and Cross Correlations Dynamics), we investigated here the dynamics of ΔN123-GB-CD2 alone and in interaction with sucrose substrate. Overall, our results provide the detailed picture at atomic level of the hierarchy of motions occurring along different timescales and how they are correlated, in agreement with experimental structural data. In particular, detailed analysis of the different structural domains revealed cooperative dynamic behaviors such as twisting, bending and wobbling through anti- and correlated motions, and also two structural hinge regions, of which one was unreported. Several highly flexible loops surrounding the catalytic pocket were also highlighted, suggesting a potential role in the acceptor promiscuity of ΔN123-GBD-CD2. Normal modes and essential dynamics underlined an interesting two-fold dynamic of the catalytic domain A, pivoting about an axis splitting the catalytic gorge in two parts. The comparison of the conformational free energy landscapes using principal component analysis of the enzyme in absence or in presence of sucrose, also revealed a more harmonic basin when sucrose is bound with a shift population of the bending mode, consistent with the substrate binding event.

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