Use of multiple picosecond high-mass molecular dynamics simulations to predict crystallographic B-factors of folded globular proteins

Assessment of Four Theoretical Approaches to Predict Protein Flexibility in the Crystal Phase and Solution

In this paper, we evaluated the ability of four coarse-grained methods to predict protein flexible regions with potential biological importance, UNRES-flex, UNRES-DSSP-flex (based on the united residue model of polypeptide chains without and with secondary structure restraints, respectively), CABS-flex (based on the C-α, C-β, and side chain model), and nonlinear rigid block normal mode analysis (NOLB) with a set of 100 protein structures determined by NMR spectroscopy or X-ray crystallography, with all secondary structure types. End regions with high fluctuations were excluded from analysis. The Pearson and Spearman correlation coefficients were used to quantify the conformity between the calculated and experimental fluctuation profiles, the latter determined from NMR ensembles and X-ray B-factors, respectively. For X-ray structures (corresponding to proteins in a crowded environment), NOLB resulted in the best agreement between the predicted and experimental fluctuation profiles, while for NMR structures (corresponding to proteins in solution), the ranking of performance is CABS-flex > UNRES-DSSP-flex > UNRES-flex > NOLB; however, CABS-flex sometimes exaggerated the extent of small fluctuations, as opposed to UNRES-DSSP-flex.

In silico analysis and molecular docking studies of natural compounds of Withania somnifera against bovine NLRP9

CONTEXT

NLRP9 is a member of nucleotide-binding domain leucine-rich repeat-containing receptors and is found to be associated with many inflammatory diseases. In the current scenario, the identification of promising anti-inflammatory compounds from natural sources by repurposing approach is still relevant for the early prevention and effective management of the disease.

METHODS

In the present study, we docked bioactives of Ashwagandha (Withanoside IV, Withanoside V, Withanolide A, Withanolide B, and Sitoindoside IX) and two control drugs against bovine NLRP9 protein. ADME/T analysis was used to determine the physiochemical properties of compounds and standard drugs. Molecular modeling was used to evaluate the correctness and quality of protein structures. In silico docking analysis revealed Withanolide B had the highest binding affinity score of -10.5 kcal/mol, whereas, among control drugs, doxycycline hydrochloride was most effective (-10.3 kcal/mol). The results of this study revealed that bioactives of Withania somnifera could be promising inhibitors against bovine NLRP9. In the present study, molecular simulation was used to measure protein conformational changes over time. The Rg value was found to be 34.77A°. RMSD and B-factor were also estimated to provide insights into the flexibility and mobile regions of protein structure. A functional protein network interaction was constructed from information collected from non-curative sources as protein-protein interactions (PPI) that play an important role in determining the function of the target protein and the ability of the drug molecule. Thus, in the present situation, it is important to identify bioactives with the potential to combat inflammatory diseases and provide strength and immunity to the host. However, there is still a need to study in vitro and in vivo to further support these findings.

Insights into receptor structure and dynamics at the surface of living cells

Evaluating protein structures in living cells remains a challenge. Here, we investigate Interleukin-4 receptor alpha (IL-4Rα) into which the non-canonical amino acid bicyclo[6.1.0]nonyne-lysine (BCNK) is incorporated by genetic code expansion. Bioorthogonal click labeling is performed with tetrazine-conjugated dyes. To quantify the reaction yield in situ, we develop brightness-calibrated ratiometric imaging, a protocol where fluorescent signals in confocal multi-color images are ascribed to local concentrations. Screening receptor mutants bearing BCNK in the extracellular domain uncovered site-specific variations of both click efficiency and Interleukin-4 binding affinity, indicating subtle well-defined structural perturbations. Molecular dynamics and continuum electrostatics calculations suggest solvent polarization to determine site-specific variations of BCNK reactivity. Strikingly, signatures of differential click efficiency, measured for IL-4Rα in ligand-bound and free form, mirror sub-angstrom deformations of the protein backbone at corresponding locations. Thus, click efficiency by itself represents a remarkably informative readout linked to protein structure and dynamics in the native plasma membrane.

"Smart" Composite Microneedle Patch Stabilizes Glucagon and Prevents Nocturnal Hypoglycemia: Experimental Studies and Molecular Dynamics Simulation

Hypoglycemia is a major complication associated with insulin therapy in people with diabetes that could cause life-threatening conditions if untreated. Glucagon, a counter-acting hormone, is thus administered for rescue of severe hypoglycemia. However, due to the instability of glucagon, only limited medications are available for emergency use, which are unsuitable for patients with hypoglycemia unawareness or with the inability to self-administer, especially during sleep (namely, nocturnal hypoglycemia). To prevent unattended and extended hypoglycemia, we designed a "smart" composite microneedle (cMN) patch capable of stabilizing glucagon, sensing hypoglycemia, and delivering glucagon automatically on demand. In this design, native glucagon was encapsulated in glucose-responsive microgels containing a glucagon-stabilizing component rationally selected by molecular dynamics (MD) simulation. A cMN patch was then prepared by incorporating the glucagon microgels with poly(methyl vinyl ether-alt-maleic anhydride) (PMVE-MAH) and poly(ethylene glycol) (PEG) followed by thermal cross-linking. The rationally designed zwitterionic polymer-based microgels preserved the native structure of glucagon and prevented heat-induced fibrillation evidenced by RP-HPLC, circular dichroism, and transmission electron microscopy. MD simulations suggested that the polymeric microgels stabilized glucagon by inhibition of oligomer formation via peptide-polymer noncovalent interactions. The polymer formed multiple hydrogen bonds with the polar and charged amino acid residues of the glucagon molecule, shielding the peptide surface from aggregation. In vivo efficacy studies using streptozotocin-induced type 1 diabetic (T1D) rats demonstrated that the glucagon-loaded cMN patch could prevent hypoglycemia induced by insulin overdose during a 12 h period. The results suggest that this new glucagon "smart" patch may be a promising system for improving the quality of life of those suffering from nocturnal hypoglycemia and hypoglycemia unawareness.

Protein Fluctuations in Response to Random External Forces

Elastic network models (ENMs) have been widely used in the last decades to investigate protein motions and dynamics. There the intrinsic fluctuations based on the isolated structures are obtained from the normal modes of these elastic networks, and they generally show good agreement with the B-factors extracted from X-ray crystallographic experiments, which are commonly considered to be indicators of protein flexibility. In this paper, we propose a new approach to analyze protein fluctuations and flexibility, which has a more appropriate physical basis. It is based on the application of random forces to the protein ENM to simulate the effects of collisions of solvent on a protein structure. For this purpose, we consider both the Cα-atom coarse-grained anisotropic network model (ANM) and an elastic network augmented with points included for the crystallized waters. We apply random forces to these protein networks everywhere, as well as only on the protein surface alone. Despite the randomness of the directions of the applied perturbations, the computed average displacements of the protein network show a remarkably good agreement with the experimental B-factors. In particular, for our set of 919 protein structures, we find that the highest correlation with the B-factors is obtained when applying forces to the external surface of the water-augmented ANM (an overall gain of 3% in the Pearson’s coefficient for the entire dataset, with improvements up to 30% for individual proteins), rather than when evaluating the fluctuations obtained from the normal modes of a standard Cα-atom coarse-grained ANM. It follows that protein fluctuations should be considered not just as the intrinsic fluctuations of the internal dynamics, but also equally well as responses to external solvent forces, or as a combination of both.

Parameterizing elastic network models to capture the dynamics of proteins

Coarse-grained normal mode analyses of protein dynamics rely on the idea that the geometry of a protein structure contains enough information for computing its fluctuations around its equilibrium conformation. This geometry is captured in the form of an elastic network (EN), namely a network of edges between its residues. The normal modes of a protein are then identified with the normal modes of its EN. Different approaches have been proposed to construct ENs, focusing on the choice of the edges that they are comprised of, and on their parameterizations by the force constants associated with those edges. Here we propose new tools to guide choices on these two facets of EN. We study first different geometric models for ENs. We compare cutoff-based ENs, whose edges have lengths that are smaller than a cutoff distance, with Delaunay-based ENs and find that the latter provide better representations of the geometry of protein structures. We then derive an analytical method for the parameterization of the EN such that its dynamics leads to atomic fluctuations that agree with experimental B-factors. To limit overfitting, we attach a parameter referred to as flexibility constant to each atom instead of to each edge in the EN. The parameterization is expressed as a non-linear optimization problem whose parameters describe both rigid-body and internal motions. We show that this parameterization leads to improved ENs, whose dynamics mimic MD simulations better than ENs with uniform force constants, and reduces the number of normal modes needed to reproduce functional conformational changes.

In silico drug discovery for a complex immunotherapeutic target - human c-Rel protein

Target evaluation and rational drug design rely on identifying and characterising small-molecule binding sites on therapeutically relevant target proteins. Immunotherapeutics development is especially challenging because of complex disease etiology and heterogenous nature of targets. c-Rel protein, a promising target in many human inflammatory and cancer pathologies, was selected as a case study for an effective in silico screening platform development since this transcription factor currently has no successful therapeutic inhibitors or modulators. This study introduces a novel in silico screening approach to probe binding sites using structural validation sets, molecular modelling and describes a method of a computer-aided drug design when a crystal structure is not available for the target of interest. In addition, we showed that binding sites can be analysed with the machine learning as well as molecular simulation approaches to help assess and systematically analyse how drug candidates can exert their mode of action. Finally, this cutting-edge approach was subjected to a high through-put virtual screen of selected 34 M drug-like compounds filtered from a library of 659 M compounds by identifying the most promising structures and proposing potential action mechanisms for the future development of highly selective human c-Rel inhibitors and/or modulators.

Structural and Energetic Affinity of Annocatacin B with ND1 Subunit of the Human Mitochondrial Respiratory Complex I as a Potential Inhibitor: An In Silico Comparison Study with the Known Inhibitor Rotenone

ND1 subunit possesses the majority of the inhibitor binding domain of the human mitochondrial respiratory complex I. This is an attractive target for the search for new inhibitors that seek mitochondrial dysfunction. It is known, from in vitro experiments, that some metabolites from Annona muricata called acetogenins have important biological activities, such as anticancer, antiparasitic, and insecticide. Previous studies propose an inhibitory activity of bovine mitochondrial respiratory complex I by bis-tetrahydrofurans acetogenins such as annocatacin B, however, there are few studies on its inhibitory effect on human mitochondrial respiratory complex I. In this work, we evaluate the in silico molecular and energetic affinity of the annocatacin B molecule with the human ND1 subunit in order to elucidate its potential capacity to be a good inhibitor of this subunit. For this purpose, quantum mechanical optimizations, molecular dynamics simulations and the molecular mechanics/Poisson-Boltzmann surface area (MM/PBSA) analysis were performed. As a control to compare our outcomes, the molecule rotenone, which is a known mitochondrial respiratory complex I inhibitor, was chosen. Our results show that annocatacin B has a greater affinity for the ND1 structure, its size and folding were probably the main characteristics that contributed to stabilize the molecular complex. Furthermore, the MM/PBSA calculations showed a 35% stronger binding free energy compared to the rotenone complex. Detailed analysis of the binding free energy shows that the aliphatic chains of annocatacin B play a key role in molecular coupling by distributing favorable interactions throughout the major part of the ND1 structure. These results are consistent with experimental studies that mention that acetogenins may be good inhibitors of the mitochondrial respiratory complex I.

Remote Activation of a Latent Epitope in an Autoantigen Decoded With Simulated B-Factors

Mutants of a catalytically inactive variant of Proteinase 3 (PR3)—iPR3-Val¹⁰³ possessing a Ser195Ala mutation relative to wild-type PR3-Val¹⁰³—offer insights into how autoantigen PR3 interacts with antineutrophil cytoplasmic antibodies (ANCAs) in granulomatosis with polyangiitis (GPA) and whether such interactions can be interrupted. Here we report that iHm5-Val¹⁰³, a triple mutant of iPR3-Val¹⁰³, bound a monoclonal antibody (moANCA518) from a GPA patient on an epitope remote from the mutation sites, whereas the corresponding epitope of iPR3-Val¹⁰³ was latent to moANCA518. Simulated B-factor analysis revealed that the binding of moANCA518 to iHm5-Val¹⁰³ was due to increased main-chain flexibility of the latent epitope caused by remote mutations, suggesting rigidification of epitopes with therapeutics to alter pathogenic PR3·ANCA interactions as new GPA treatments.

Sequence-specific dynamic information in proteins

We examine the local and global properties of the average B-factor, 〈B〉, as a residue-specific indicator of protein dynamic characteristics. It has been shown that values of 〈B〉 for the 20 amino acids differ in a statistically significant manner, and that, while strongly determined by the static physical properties of amino acids, they also encode averaged information about the influence of global fold on single-residue dynamics. Therefore, complete sequences of amino acids also encode fold-related global dynamic information, in addition to the local information that arises from static physical properties. We show that the relative magnitudes of these two contributions can be determined using Fourier methods, which represent the global properties of the sequences. It has also been shown that the behavior of Fourier components of 〈B〉 differs, with very high statistical significance, between structural groups, and that this information is not available from a comparable analysis of static amino acid properties.

SOD1 in amyotrophic lateral sclerosis development - in silico analysis and molecular dynamics of A4F and A4V variants

Amyotrophic lateral sclerosis (ALS) is a neurodegenerative disease that is characterized by the selective loss of motor neurons. Approximately 5% to 10% of patients with ALS have a family history of the disease, and approximately 20% of familial amyotrophic lateral sclerosis (fALS) cases are associated with mutations in Cu/Zn superoxide dismutase (SOD1). In this study, we evaluated the structural and functional effects of human A4F and A4V SOD1 protein mutations. We performed an in silico analysis using prediction algorithms of nonsynonymous single-nucleotide polymorphisms (nsSNPs) associated with the fALS development. Our structural conservation results show that the mutations analyzed (A4V and A4F) were in a highly conserved region. Molecular dynamics simulations using the Linux GROMACS package revealed how these mutations affect protein structure, protein stability, and aggregation. These results suggest that there might be an effect on the SOD1 function. Understanding the molecular basis of disease provides new insights useful for rational drug design and advancing our understanding of the ALS development.

How large B-factors can be in protein crystal structures

BACKGROUND

Protein crystal structures are potentially over-interpreted since they are routinely refined without any restraint on the upper limit of atomic B-factors. Consequently, some of their atoms, undetected in the electron density maps, are allowed to reach extremely large B-factors, even above 100 square Angstroms, and their final positions are purely speculative and not based on any experimental evidence.

RESULTS

A strategy to define B-factors upper limits is described here, based on the analysis of protein crystal structures deposited in the Protein Data Bank prior 2008, when the tendency to allow B-factor to arbitrary inflate was limited. This B-factor upper limit (B_max) is determined by extrapolating the relationship between crystal structure average B-factor and percentage of crystal volume occupied by solvent (pcVol) to pcVol =100%, when, ab absurdo, the crystal contains only liquid solvent, the structure of which is, by definition, undetectable in electron density maps.

CONCLUSIONS

It is thus possible to highlight structures with average B-factors larger than B_max, which should be considered with caution by the users of the information deposited in the Protein Data Bank, in order to avoid scientifically deleterious over-interpretations.

Overcoming antibiotic resistance: Is siderophore Trojan horse conjugation an answer to evolving resistance in microbial pathogens?

Comparative study of siderophore biosynthesis pathway in pathogens provides potential targets for antibiotics and host drug delivery as a part of computationally feasible microbial therapy. Iron acquisition using siderophore models is an essential and well established model in all microorganisms and microbial infections a known to cause great havoc to both plant and animal. Rapid development of antibiotic resistance in bacterial as well as fungal pathogens has drawn us at a verge where one has to get rid of the traditional way of obstructing pathogen using single or multiple antibiotic/chemical inhibitors or drugs. 'Trojan horse' strategy is an answer to this imperative call where antibiotic are by far sneaked into the pathogenic cell via the siderophore receptors at cell and outer membrane. This antibiotic once gets inside, generates a 'black hole' scenario within the opportunistic pathogens via iron scarcity. For pathogens whose siderophore are not compatible to smuggle drug due to their complex conformation and stiff valence bonds, there is another approach. By means of the siderophore biosynthesis pathways, potential targets for inhibition of these siderophores in pathogenic bacteria could be achieved and thus control pathogenic virulence. Method to design artificial exogenous siderophores for pathogens that would compete and succeed the battle of intake is also covered with this review. These manipulated siderophore would enter pathogenic cell like any other siderophore but will not disperse iron due to which iron inadequacy and hence pathogens control be accomplished. The aim of this review is to offer strategies to overcome the microbial infections/pathogens using siderophore.

How fast fast-folding proteins fold in silico

In reported microcanonical molecular dynamics simulations, fast-folding proteins CLN025 and Trp-cage autonomously folded to experimentally determined native conformations. However, the folding times of these proteins derived from the simulations were more than 4-10 times longer than their experimental values. This article reports autonomous folding of CLN025 and Trp-cage in isobaric-isothermal molecular dynamics simulations with agreements within factors of 0.69-1.75 between simulated and experimental folding times at different temperatures. These results show that CLN025 and Trp-cage can now autonomously fold in silico as fast as in experiments, and suggest that the accuracy of folding simulations for fast-folding proteins begins to overlap with the accuracy of folding experiments. This opens new prospects of developing computer algorithms that can predict both ensembles of conformations and their interconversion rates for a protein from its sequence for artificial intelligence on how and when a protein acts as a receiver, switch, and relay to facilitate various subcellular-to-tissue communications. Then the genetic information that encodes proteins can be better read in the context of intricate biological functions.