Discrete molecular dynamics studies of the folding of a protein-like model

Oligomer Formation by Physiologically Relevant C-Terminal Isoforms of Amyloid β-Protein

Alzheimer's disease (AD) is a neurological disorder associated with amyloid β-protein (Aβ) assembly into toxic oligomers. In addition to the two predominant alloforms, Aβ1-40 and Aβ1-42, other C-terminally truncated Aβ peptides, including Aβ1-38 and Aβ1-43, are produced in the brain. Here, we use discrete molecular dynamics (DMD) and a four-bead protein model with amino acid-specific hydropathic interactions, DMD4B-HYDRA, to examine oligomer formation of Aβ1-38, Aβ1-40, Aβ1-42, and Aβ1-43. Self-assembly of 32 unstructured monomer peptides into oligomers is examined using 32 replica DMD trajectories for each of the four peptides. In a quasi-steady state, Aβ1-38 and Aβ1-40 adopt similar unimodal oligomer size distributions with a maximum at trimers, whereas Aβ1-42 and Aβ1-43 oligomer size distributions are multimodal with the dominant maximum at trimers or tetramers, and additional maxima at hexamers and unidecamers (for Aβ1-42) or octamers and pentadecamers (for Aβ1-43). The free energy landscapes reveal isoform- and oligomer-order specific structural and morphological features of oligomer ensembles. Our results show that oligomers of each of the four isoforms have unique features, with Aβ1-42 alone resulting in oligomers with disordered and solvent-exposed N-termini. Our findings help unravel the structure-function paradigm governing oligomers formed by various Aβ isoforms.

A Piecewise Design Approach to Engineering a Miniature ACE2 Mimic to Bind SARS-CoV-2

As the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) continues its global spread, the exploration of novel therapeutic and diagnostic strategies is still needed. The virus enters host cells by binding the angiotensin-converting enzyme 2 (ACE2) receptor through the spike protein. Here, we develop an engineered, small, stable, and catalytically inactive version of ACE2, termed miniature ACE2 (mACE2), designed to bind the spike protein with high affinity. Employing a magnetic nanoparticle-based assay, we harnessed the strong binding affinity of mACE2 to develop a sensitive and specific platform for the detection or neutralization of SARS-CoV-2. Our findings highlight the potential of engineered mACE2 as a valuable tool in the fight against SARS-CoV-2. The success of developing such a small reagent based on a piecewise molecular design serves as a proof-of-concept approach for the rapid deployment of such agents to diagnose and fight other viral diseases.

APOE regulates the transport of GM1

Apolipoprotein E (APOE) is responsible for lipid transport, including cholesterol transport and clearance. While the ε4 allele of APOE (APOE4) is associated with a significant genetic risk factor for late-onset Alzheimer's disease (AD), no mechanistic understanding of its contribution to AD etiology has been established yet. In addition to cholesterol, monosialotetrahexosylganglioside (GM1) is a crucial lipid component in cell membranes and has been implicated in promoting the aggregation of amyloid beta protein (Aβ), a key protein associated with AD. Here, we ask whether there are direct interactions between APOE and GM1 that further impact AD pathology. We find that both APOE3 and APOE4 exhibit superior binding affinity to GM1 compared to cholesterol and have an enhanced cellular uptake to GM1 lipid structures than cholesterol lipid structures. APOE regulates the transport process of GM1 depending on the cell type, which is influenced by the expression of APOE receptors in different cell lines and alters GM1 contents in cell membranes. We also find that the presence of GM1 alters the secondary structure of APOE3 and APOE4 and enhances the binding affinity between APOE and its receptor low-density lipoprotein receptor (LDLR), consequently promoting the cellular uptake of lipid structures in the presence of APOE. To understand the enhanced cellular uptake observed in lipid structures containing 20% GM1, we determined the distribution of GM1 on the membrane and found that GM1 clustering in lipid rafts, thereby supporting the physiological interaction between APOE and GM1. Overall, we find that APOE plays a regulatory role in GM1 transport, and the presence of GM1 on the lipid structures influences this transport process. Our studies introduce a plausible direct link between APOE and AD etiology, wherein APOE regulates GM1, which, in turn, promotes Aβ oligomerization and aggregation.

Computer aided therapeutic tripeptide design, in alleviating the pathogenic proclivities of nocuous α-synuclein fibrils

Parkinson's disorder (PD) exacerbates neuronal degeneration of motor nerves, thereby effectuating uncoordinated movements and tremors. Aberrant alpha-synuclein (α-syn) is culpable of triggering PD, wherein cytotoxic amyloid aggregates of α-syn get deposited in motor neurons to instigate neuro-degeneration. Amyloid aggregates, typically rich in beta sheets are cardinal targets to mitigate their neurotoxic effects. In this analysis, owing to their interaction specificity, we formulated an efficacious tripeptide out of the aggregation-prone region of α-syn protein. With the help of a proficient computational pipeline, systematic peptide shortening and an adept molecular simulation platform, we formulated a tripeptide, VAV from α-syn structure based hexapeptide KISVRV. Indeed, the VAV tripeptide was able to effectively mitigate the α-syn amyloid fibrils' dynamic rate of beta-sheet formation. Additional trajectory analyses of the VAV- α-syn complex indicated that, upon its dynamic interaction, VAV efficiently altered the distinct pathogenic structural dynamics of α-syn, further advocating its potential in alleviating aberrant α-syn's amyloidogenic proclivities. Consistent findings from various computational analyses have led us to surmise that VAV could potentially re-alter the pathogenic conformational orientation of α-syn, essential to mitigate its cytotoxicity. Hence, VAV tripeptide could be an efficacious therapeutic candidate to efficiently ameliorate aberrant α-syn amyloid mediated neurotoxicity, eventually attenuating the nocuous effects of PD.Communicated by Ramaswamy H. Sarma.

Allosteric regulation of kinase activity in living cells

The dysregulation of protein kinases is associated with multiple diseases due to the kinases' involvement in a variety of cell signaling pathways. Manipulating protein kinase function, by controlling the active site, is a promising therapeutic and investigative strategy to mitigate and study diseases. Kinase active sites share structural similarities, making it difficult to specifically target one kinase, and allosteric control allows specific regulation and study of kinase function without directly targeting the active site. Allosteric sites are distal to the active site but coupled via a dynamic network of inter-atomic interactions between residues in the protein. Establishing an allosteric control over a kinase requires understanding the allosteric wiring of the protein. Computational techniques offer effective and inexpensive mapping of the allosteric sites on a protein. Here, we discuss the methods to map and regulate allosteric communications in proteins, and strategies to establish control over kinase functions in live cells and organisms. Protein molecules, or 'sensors,' are engineered to function as tools to control allosteric activity of the protein as these sensors have high spatiotemporal resolution and help in understanding cell phenotypes after immediate activation or inactivation of a kinase. Traditional methods used to study protein functions, such as knockout, knockdown, or mutation, cannot offer a sufficiently high spatiotemporal resolution. We discuss the modern repertoire of tools to regulate protein kinases as we enter a new era in deciphering cellular signaling and developing novel approaches to treat diseases associated with signal dysregulation.

Unveiling Medin Folding and Dimerization Dynamics and Conformations via Atomistic Discrete Molecular Dynamics Simulations

Medin is a principal component of localized amyloid found in the vasculature of individuals over 50 years old. Its amyloid aggregation has been linked to endothelial dysfunction and vascular inflammation, contributing to the pathogenesis of various vascular diseases. Despite its significance, the structures of the medin monomer, oligomer, and fibril remain elusive, and the dynamic processes of medin aggregation are not fully understood. In this study, we comprehensively investigated the medin folding and dimerization dynamics and conformations using atomistic discrete molecular dynamics simulations. Our simulation results suggested that the folding initiation of the medin involved the formation of β-sheets around medin30-41 and medin42-50, with subsequent capping of other segments to their β-sheet edges. Medin monomers typically consisted of three or four β-strands, along with a dynamic N-terminal helix. Two isolated medin peptides readily aggregated into a β-sheet-rich dimer, displaying a strong aggregation propensity. Dimerization of medin not only enhanced the β-sheet conformations but also led to the formation of β-barrel oligomers. The aggregation tendencies of medin1-18 and medin19-29 were relatively weak. However, the segments of medin30-41 and medin42-50 played a crucial role as they primarily formed a β-sheet core and facilitated medin1-18 and medin19-29 to form intra- and interpeptide β-sheets. The findings highlight the critical role of the medin30-41 and medin42-50 regions in stabilizing the monomer structure and driving the medin amyloid aggregation. These regions could potentially serve as promising targets for designing antiamyloid inhibitors against amyloid aggregation of medin. Additionally, our study provides a full picture of the monomer conformations and dimerization dynamics for medin, which will help better understand the pathology of medin aggregation.

Allosteric regulation of kinase activity in living cells

The dysregulation of protein kinases is associated with multiple diseases due to the kinases' involvement in a variety of cell signaling pathways. Manipulating protein kinase function, by controlling the active site, is a promising therapeutic and investigative strategy to mitigate and study diseases. Kinase active sites share structural similarities making it difficult to specifically target one kinase, allosteric control allows specific regulation and study of kinase function without directly targeting the active site. Allosteric sites are distal to the active site but coupled via a dynamic network of inter-atomic interactions between residues in the protein. Establishing an allosteric control over a kinase requires understanding the allosteric wiring of the protein. Computational techniques offer effective and inexpensive mapping of the allosteric sites on a protein. Here, we discuss methods to map and regulate allosteric communications in proteins, and strategies to establish control over kinase functions in live cells and organisms. Protein molecules, or "sensors" are engineered to function as tools to control allosteric activity of the protein as these sensors have high spatiotemporal resolution and help in understanding cell phenotypes after immediate activation or inactivation of a kinase. Traditional methods used to study protein functions, such as knockout, knockdown, or mutation, cannot offer a sufficiently high spatiotemporal resolution. We discuss the modern repertoire of tools to regulate protein kinases as we enter a new era in deciphering cellular signaling and developing novel approaches to treat diseases associated with signal dysregulation.

Microcalorimetry reveals multi-state thermal denaturation of G. stearothermophilus tryptophanyl-tRNA synthetase

Mechanistic studies of Geobacillus stearothermophilus tryptophanyl-tRNA synthetase (TrpRS) afford an unusually detailed description-the escapement mechanism-for the distinct steps coupling catalysis to domain motion, efficiently converting the free energy of ATP hydrolysis into biologically useful alternative forms of information and work. Further elucidation of the escapement mechanism requires understanding thermodynamic linkages between domain configuration and conformational stability. To that end, we compare experimental thermal melting of fully liganded and apo TrpRS with a computational simulation of the melting of its fully liganded form. The simulation also provides important structural cameos at successively higher temperatures, enabling more confident interpretation. Experimental and simulated melting both proceed through a succession of three transitions at successively higher temperature. The low-temperature transition occurs at approximately the growth temperature of the organism and so may be functionally relevant but remains too subtle to characterize structurally. Structural metrics from the simulation imply that the two higher-temperature transitions entail forming a molten globular state followed by unfolding of secondary structures. Ligands that stabilize the enzyme in a pre-transition (PreTS) state compress the temperature range over which these transitions occur and sharpen the transitions to the molten globule and fully denatured states, while broadening the low-temperature transition. The experimental enthalpy changes provide a key parameter necessary to convert changes in melting temperature of combinatorial mutants into mutationally induced conformational free energy changes. The TrpRS urzyme, an excerpted model representing an early ancestral form, containing virtually the entire catalytic apparatus, remains largely intact at the highest simulated temperatures.

Defensin-based therapeutic peptide design in attenuating V30M TTR-induced Familial Amyloid Polyneuropathy

In the present study, we aimed to formulate an effective therapeutic candidate against V30M mutant transthyretin (TTR) protein to hinder its pathogenic misfolding. Nicotiana alata Defensin 1 (NaD1) Antimicrobial Peptide (AMP) was availed due to its tendency to aggregate, which may compete for aggregation-prone regions of pathogenic TTR protein. Based on NaD1's potential to bind to V30M TTR, we proposed NaD1-derived tetra peptides: CKTE and SKIL to be initial therapeutic candidates. Based on their association with mutant TTR protein, CKTE tetra peptide showed considerable interaction and curative potential as compared to SKIL tetra peptide. Further analyses from discrete molecular dynamics simulation corroborate CKTE tetra peptide's effectiveness as a 'beta-sheet breaker' against V30M TTR. Various post-simulation trajectory analyses suggested that CKTE tetra peptide alters the structural dynamics of pathogenic V30M TTR protein, thereby potentially attenuating its beta-sheets and impeding its aggregation. Normal mode analysis simulation corroborated that V30M TTR conformation is altered upon its interaction with CKTE peptide. Moreover, simulated thermal denaturation findings suggested that CKTE-V30M TTR complex is more susceptible to simulated denaturation, relative to pathogenic V30M TTR; further substantiating CKTE peptide's potential to alter V30M TTR's pathogenic conformation. Moreover, the residual frustration analysis augmented CKTE tetra peptide's proclivity in reorienting the conformation of V30M TTR. Therefore, we predicted that the tetra peptide, CKTE could be a promising therapeutic candidate in mitigating the amyloidogenic detrimental effects of V30M TTR-mediated familial amyloid polyneuropathy (FAP).

Supplementary Information

The online version contains supplementary material available at 10.1007/s13205-023-03646-4.

A noncommutative combinatorial protein logic circuit controls cell orientation in nanoenvironments

Single-protein-based devices that integrate signal sensing with logical operations to generate functional outputs offer exceptional promise for monitoring and modulating biological systems. Engineering such intelligent nanoscale computing agents is challenging, as it requires the integration of sensor domains into a functional protein via intricate allosteric networks. We incorporate a rapamycin-sensitive sensor (uniRapR) and a blue light-responsive LOV2 domain into human Src kinase, creating a protein device that functions as a noncommutative combinatorial logic circuit. In our design, rapamycin activates Src kinase, causing protein localization to focal adhesions, whereas blue light exerts the reverse effect that inactivates Src translocation. Focal adhesion maturation induced by Src activation reduces cell migration dynamics and shifts cell orientation to align along collagen nanolane fibers. Using this protein device, we reversibly control cell orientation by applying the appropriate input signals, a framework that may be useful in tissue engineering and regenerative medicine.

An engineered N-acyltransferase-LOV2 domain fusion protein enables light-inducible allosteric control of enzymatic activity

Transferases are ubiquitous across all known life. While much work has been done to understand and describe these essential enzymes, there have been minimal efforts to exert tight and reversible control over their activity for various biotechnological applications. Here, we apply a rational, computation-guided methodology to design and test a transferase-class enzyme allosterically regulated by light-oxygen-voltage 2 sensing domain. We utilize computational techniques to determine the intrinsic allosteric networks within N-acyltransferase (Orf11/∗Dbv8) and identify potential allosteric sites on the protein's surface. We insert light-oxygen-voltage 2 sensing domain at the predicted allosteric site, exerting reversible control over enzymatic activity. We demonstrate blue-light regulation of N-acyltransferase (Orf11/∗Dbv8) function. Our study for the first time demonstrates optogenetic regulation of a transferase-class enzyme as a proof-of-concept for controllable transferase design. This successful design opens the door for many future applications in metabolic engineering and cellular programming.

Urolithin A analog inhibits castration-resistant prostate cancer by targeting the androgen receptor and its variant, androgen receptor-variant 7

We investigated the efficacy of a small molecule ASR-600, an analog of Urolithin A (Uro A), on blocking androgen receptor (AR) and its splice variant AR-variant 7 (AR-V7) signaling in castration-resistant prostate cancer (CRPC). ASR-600 effectively suppressed the growth of AR+ CRPC cells by inhibiting AR and AR-V7 expressions; no effect was seen in AR- CRPC and normal prostate epithelial cells. Biomolecular interaction assays revealed ASR-600 binds to the N-terminal domain of AR, which was further confirmed by immunoblot and subcellular localization studies. Molecular studies suggested that ASR-600 promotes the ubiquitination of AR and AR-V7 resulting in the inhibition of AR signaling. Microsomal and plasma stability studies suggest that ASR-600 is stable, and its oral administration inhibits tumor growth in CRPC xenografted castrated and non-castrated mice. In conclusion, our data suggest that ASR-600 enhances AR ubiquitination in both AR+ and AR-V7 CRPC cells and inhibits their growth in vitro and in vivo models.

Combining Experimental Restraints and RNA 3D Structure Prediction in RNA Nanotechnology

Precise RNA tertiary structure prediction can aid in the design of RNA nanoparticles. However, most existing RNA tertiary structure prediction methods are limited to small RNAs with relatively simple secondary structures. Large RNA molecules usually have complex secondary structures, including multibranched loops and pseudoknots, allowing for highly flexible RNA geometries and multiple stable states. Various experiments and bioinformatics analyses can often provide information about the distance between atoms (or residues) in RNA, which can be used to guide the prediction of RNA tertiary structure. In this chapter, we will introduce a platform, iFoldNMR, that can incorporate non-exchangeable imino protons resonance data from NMR as restraints for RNA 3D structure prediction. We also introduce an algorithm, DVASS, which optimizes distance restraints for better RNA 3D structure prediction.

Adaptation-proof SARS-CoV-2 vaccine design

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) surface spike glycoprotein - a major antibody target - is critical for virus entry via engagement of human angiotensin-converting enzyme 2 (ACE2) receptor. Despite successes with existing vaccines and therapies that primarily target the receptor binding domain (RBD) of the spike protein, the susceptibility of RBD to mutations provides escape routes for the SARS-CoV-2 from neutralizing antibodies. On the other hand, structural conservation in the spike protein can be targeted to reduce escape mutations and achieve broad protection. Here, we designed candidate stable immunogens that mimic surface features of selected conserved regions of spike protein through 'epitope grafting,' in which we present the target epitope topology on diverse heterologous scaffolds that can structurally accommodate the spike epitopes. Structural characterization of the epitope-scaffolds showed stark agreement with our computational models and target epitopes. The sera from mice immunized with engineered designs display epitope-scaffolds and spike binding activity. We also demonstrated the utility of the designed epitope-scaffolds in diagnostic applications. Taken all together, our study provides important methodology for targeting the conserved, non-RBD structural motifs of spike protein for SARS-CoV-2 epitope vaccine design and demonstrates the potential utility of 'epitope grafting' in rational vaccine design.

Activation of Disulfide Redox Switch in REDD1 Promotes Oxidative Stress Under Hyperglycemic Conditions

The stress response protein regulated in development and DNA damage response 1 (REDD1) has been implicated in visual deficits in patients with diabetes. The aim here was to investigate the mechanism responsible for the increase in retinal REDD1 protein content that is observed with diabetes. We found that REDD1 protein expression was increased in the retina of streptozotocin-induced diabetic mice in the absence of a change in REDD1 mRNA abundance or ribosome association. Oral antioxidant supplementation reduced retinal oxidative stress and suppressed REDD1 protein expression in the retina of diabetic mice. In human retinal Müller cell cultures, hyperglycemic conditions increased oxidative stress, enhanced REDD1 expression, and inhibited REDD1 degradation independently of the proteasome. Hyperglycemic conditions promoted a redox-sensitive cross-strand disulfide bond in REDD1 at C150/C157 that was required for reduced REDD1 degradation. Discrete molecular dynamics simulations of REDD1 structure revealed allosteric regulation of a degron upon formation of the disulfide bond that disrupted lysosomal proteolysis of REDD1. REDD1 acetylation at K129 was required for REDD1 recognition by the cytosolic chaperone HSC70 and degradation by chaperone-mediated autophagy. Disruption of REDD1 allostery upon C150/C157 disulfide bond formation prevented the suppressive effect of hyperglycemic conditions on REDD1 degradation and reduced oxidative stress in cells exposed to hyperglycemic conditions. The results reveal redox regulation of REDD1 and demonstrate the role of a REDD1 disulfide switch in development of oxidative stress.

Adaptation-proof SARS-CoV-2 vaccine design

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) surface spike glycoprotein - a major antibody target - is critical for virus entry via engagement of human angiotensin-converting enzyme 2 (ACE2) receptor. Despite successes with existing vaccines and therapies that primarily target the receptor binding domain (RBD) of the spike protein, the susceptibility of RBD to mutations provides escape routes for the SARS-CoV-2 from neutralizing antibodies. On the other hand, structural conservation in the spike protein can be targeted to reduce escape mutations and achieve broad protection. Here, we designed candidate stable immunogens that mimic surface features of selected conserved regions of spike protein through 'epitope grafting,' in which we present the target epitope topology on diverse heterologous scaffolds that can structurally accommodate the spike epitopes. Structural characterization of the epitope-scaffolds showed stark agreement with our computational models and target epitopes. The sera from mice immunized with engineered designs display epitope-scaffolds and spike binding activity. We also demonstrated the utility of the designed epitope-scaffolds in diagnostic applications. Taken all together, our study provides important methodology for targeting the conserved, non-RBD structural motifs of spike protein for SARS-CoV-2 epitope vaccine design and demonstrates the potential utility of 'epitope grafting' in rational vaccine design.

A database of calculated solution parameters for the AlphaFold predicted protein structures

Recent spectacular advances by AI programs in 3D structure predictions from protein sequences have revolutionized the field in terms of accuracy and speed. The resulting “folding frenzy” has already produced predicted protein structure databases for the entire human and other organisms’ proteomes. However, rapidly ascertaining a predicted structure’s reliability based on measured properties in solution should be considered. Shape-sensitive hydrodynamic parameters such as the diffusion and sedimentation coefficients (\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${D_{t(20,w)}^{0}}$$\end{document}Dt(20,w)0, \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${s_{{\left( {{20},w} \right)}}^{{0}} }$$\end{document}s20,w0) and the intrinsic viscosity ([η]) can provide a rapid assessment of the overall structure likeliness, and SAXS would yield the structure-related pair-wise distance distribution function p(r) vs. r. Using the extensively validated UltraScan SOlution MOdeler (US-SOMO) suite, a database was implemented calculating from AlphaFold structures the corresponding \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${D_{t(20,w)}^{0}}$$\end{document}Dt(20,w)0, \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${s_{{\left( {{20},w} \right)}}^{{0}} }$$\end{document}s20,w0, [η], p(r) vs. r, and other parameters. Circular dichroism spectra were computed using the SESCA program. Some of AlphaFold’s drawbacks were mitigated, such as generating whenever possible a protein’s mature form. Others, like the AlphaFold direct applicability to single-chain structures only, the absence of prosthetic groups, or flexibility issues, are discussed. Overall, this implementation of the US-SOMO-AF database should already aid in rapidly evaluating the consistency in solution of a relevant portion of AlphaFold predicted protein structures.

Probing allosteric regulations with coevolution-driven molecular simulations

Protein-mediated allosteric regulations are essential in biology, but their quantitative characterization continues to posit formidable challenges for both experiments and computations. Here, we combine coevolutionary information, multiscale molecular simulations, and free-energy methods to interrogate and quantify the allosteric regulation of functional changes in protein complexes. We apply this approach to investigate the regulation of adenylyl cyclase (AC) by stimulatory and inhibitory G proteins—a prototypical allosteric system that has long escaped from in-depth molecular characterization. We reveal a surprisingly simple ON/OFF regulation of AC functional dynamics through multiple pathways of information transfer. The binding of G proteins reshapes the free-energy landscape of AC following the classical population-shift paradigm. The model agrees with structural and biochemical data and reveals previously unknown experimentally consistent intermediates. Our approach showcases a general strategy to explore uncharted functional space in complex biomolecular regulations.

Structure of prion β-oligomers as determined by short-distance crosslinking constraint-guided discrete molecular dynamics simulations

The conversion of the native monomeric cellular prion protein (PrP^C ) into an aggregated pathological β-oligomeric form (PrP^β ) and an infectious form (PrP^Sc ) is the central element in the development of prion diseases. The structure of the aggregates and the molecular mechanisms of the conformational changes involved in the conversion are still unknown. We applied mass spectrometry combined with chemical crosslinking, hydrogen/deuterium exchange, limited proteolysis, and surface modification for the differential characterization of the native and the urea+acid-converted prion β-oligomer structures to obtain insights into the mechanisms of conversion and aggregation. For the determination of the structure of the monomer and the dimer unit of the β-oligomer, we applied a recently-developed approach for de novo protein structure determination which is based on the incorporation of zero-length and short-distance crosslinking data as intra- and inter-protein constraints in discrete molecular dynamics simulations (CL-DMD). Based on all of the structural-proteomics experimental data and the computationally predicted structures of the monomer units, we propose the potential mode of assembly of the β-oligomer. The proposed β-oligomer assembly provides a clue on the β-sheet nucleation site, and how template-based conversion of the native prion molecule occurs, growth of the prion aggregates, and maturation into fibrils may occur.

Identification and characterization of novel candidate compounds targeting 6- and 7-transmembrane μ-opioid receptor isoforms

BACKGROUND AND PURPOSE

The μ-opioid receptor (μ receptor) is the primary target for opioid analgesics. The 7-transmembrane (TM) and 6TM μ receptor isoforms mediate inhibitory and excitatory cellular effects. Here, we developed compounds selective for 6TM- or 7TM-μ receptors to further our understanding of the pharmacodynamic properties of μ receptors.

EXPERIMENTAL APPROACH

We performed virtual screening of the ZINC Drug Now library of compounds using in silico 7TM- and 6TM-μ receptor structural models and identified potential compounds that are selective for 6TM- and/or 7TM-μ receptors. Subsequently, we characterized the most promising candidate compounds in functional in vitro studies using Be2C neuroblastoma transfected cells, behavioural in vivo pain assays using various knockout mice and in ex vivo electrophysiology studies.

KEY RESULTS

Our virtual screen identified 30 potential candidate compounds. Subsequent functional in vitro cellular assays shortlisted four compounds (#5, 10, 11 and 25) that demonstrated 6TM- or 7TM-μ receptor-dependent NO release. In in vivo pain assays these compounds also produced dose-dependent hyperalgesic responses. Studies using mice that lack specific opioid receptors further established the μ receptor-dependent nature of identified novel ligands. Ex vivo electrophysiological studies on spontaneous excitatory postsynaptic currents in isolated spinal cord slices also validated the hyperalgesic properties of the most potent 6TM- (#10) and 7TM-μ receptor (#5) ligands.

CONCLUSION AND IMPLICATIONS

Our novel compounds represent a new class of ligands for μ receptors and will serve as valuable research tools to facilitate the development of opioids with significant analgesic efficacy and fewer side-effects.

Amyloid Oligomers: A Joint Experimental/Computational Perspective on Alzheimer's Disease, Parkinson's Disease, Type II Diabetes, and Amyotrophic Lateral Sclerosis

Protein misfolding and aggregation is observed in many amyloidogenic diseases affecting either the central nervous system or a variety of peripheral tissues. Structural and dynamic characterization of all species along the pathways from monomers to fibrils is challenging by experimental and computational means because they involve intrinsically disordered proteins in most diseases. Yet understanding how amyloid species become toxic is the challenge in developing a treatment for these diseases. Here we review what computer, in vitro, in vivo, and pharmacological experiments tell us about the accumulation and deposition of the oligomers of the (Aβ, tau), α-synuclein, IAPP, and superoxide dismutase 1 proteins, which have been the mainstream concept underlying Alzheimer's disease (AD), Parkinson's disease (PD), type II diabetes (T2D), and amyotrophic lateral sclerosis (ALS) research, respectively, for many years.

Discontinuous Molecular Dynamics Simulations of Biomolecule Interfacial Behavior: Study of Ovispirin-1 Adsorption on a Graphene Surface

Fundamental understanding of biomolecular interfacial behavior, such as protein adsorption at the microscopic scale, is critical to broad applications in biomaterials, nanomedicine, and nanoparticle-based biosensing techniques. The goal of achieving both computational efficiency and accuracy presents a major challenge for simulation studies at both atomistic and molecular scales. In this work, we developed a unique, accurate, high-throughput simulation method which, by integrating discontinuous molecular dynamics (DMD) simulations with the Go-like protein-surface interaction model, not only solves the dynamics efficiently, but also describes precisely the protein intramolecular and intermolecular interactions at the atomistic scale and the protein-surface interactions at the coarse-grained scale. Using our simulation method and in-house developed software, we performed a systematic study of α-helical ovispirin-1 peptide adsorption on a graphene surface, and our study focused on the effect of surface hydrophobic interactions and π-π stacking on protein adsorption. Our DMD simulations were consistent with full-atom molecular dynamics simulations and showed that a single ovispirin-1 peptide lay down on the flat graphene surface with randomized secondary structure due to strong protein-surface interactions. Peptide aggregates were formed with an internal hydrophobic core driven by strong interactions of hydrophobic residues in the bulk environment. However, upon adsorption, the hydrophobic graphene surface can break the hydrophobic core by denaturing individual peptide structures, leading to disassembling the aggregate structure and further randomizing the ovispirin-1 peptide's secondary structures.

Modifications to the Framework Regions Eliminate Chimeric Antigen Receptor Tonic Signaling

Chimeric antigen receptor (CAR) tonic signaling, defined as spontaneous activation and release of proinflammatory cytokines by CAR-T cells, is considered a negative attribute because it leads to impaired antitumor effects. Here, we report that CAR tonic signaling is caused by the intrinsic instability of the mAb single-chain variable fragment (scFv) to promote self-aggregation and signaling via the CD3ζ chain incorporated into the CAR construct. This phenomenon was detected in a CAR encoding either CD28 or 4-1BB costimulatory endodomains. Instability of the scFv was caused by specific amino acids within the framework regions (FWR) that can be identified by computational modeling. Substitutions of the amino acids causing instability, or humanization of the FWRs, corrected tonic signaling of the CAR, without modifying antigen specificity, and enhanced the antitumor effects of CAR-T cells. Overall, we demonstrated that tonic signaling of CAR-T cells is determined by the molecular instability of the scFv and that computational analyses of the scFv can be implemented to correct the scFv instability in CAR-T cells with either CD28 or 4-1BB costimulation.

Direct Observation of β-Barrel Intermediates in the Self-Assembly of Toxic SOD128-38 and Absence in Nontoxic Glycine Mutants

Soluble low-molecular-weight oligomers formed during the early stage of amyloid aggregation are considered the major toxic species in amyloidosis. The structure-function relationship between oligomeric assemblies and the cytotoxicity in amyloid diseases are still elusive due to the heterogeneous and transient nature of these aggregation intermediates. To uncover the structural characteristics of toxic oligomeric intermediates, we compared the self-assembly dynamics and structures of SOD1_28-38, a cytotoxic fragment of the superoxide dismutase 1 (SOD1) associated with the amyotrophic lateral sclerosis, with its two nontoxic mutants G33V and G33W using molecular dynamics simulations. Single-point glycine substitutions in SOD1_28-38 have been reported to abolish the amyloid toxicity. Our simulation results showed that the toxic SOD1_28-38 and its nontoxic mutants followed different aggregation pathways featuring distinct aggregation intermediates. Specifically, wild-type SOD1_28-38 initially self-assembled into random-coil-rich oligomers, among which fibrillar aggregates composed of well-defined curved single-layer β-sheets were nucleated via coil-to-sheet conversions and the formation of β-barrels as intermediates. In contrast, the nontoxic G33V/G33W mutants readily assembled into small β-sheet-rich oligomers and then coagulated with each other into cross-β fibrils formed by two-layer β-sheets without forming β-barrels as the intermediates. The direct observation of β-barrel oligomers during the assembly of toxic SOD1_28-38 fragments but not the nontoxic glycine-substitution mutants strongly supports β-barrels as the toxic oligomers in amyloidosis, probably via interactions with the cell membrane and forming amyloid pores. With well-defined structures, the β-barrel might serve as a novel therapeutic target against amyloid-related diseases.

Pathogen-specific antimicrobials engineered de novo through membrane-protein biomimicry

Precision antimicrobials aim to kill pathogens without damaging commensal bacteria in the host, and thus to cure disease without antibiotic-associated dysbiosis. Here, we report the de novo design of a synthetic host defence peptide that targets a specific pathogen by mimicking key molecular features of the pathogen’s channel-forming membrane proteins. By exploiting physical and structural vulnerabilities within the pathogen’s cellular envelope, we designed a peptide sequence that undergoes instructed tryptophan-zippered assembly within the mycolic-acid rich outer membrane of Mycobacterium tuberculosis (Mtb) to specifically kill the pathogen without collateral toxicity towards lung commensal bacteria or host tissue. These ‘mycomembrane-templated’ assemblies elicit rapid mycobactericidal activity, and enhance the potency of antibiotics by improving their otherwise poor diffusion across the rigid Mtb envelope with respect to agents that exploit transmembrane protein channels for antimycobacterial activity. This biomimetic strategy may aid the design of other narrow-spectrum antimicrobial peptides.

Prefusion spike protein stabilization through computational mutagenesis

A novel severe acute respiratory syndrome (SARS)‐like coronavirus (SARS‐CoV‐2) has emerged as a human pathogen, causing global pandemic and resulting in over 400 000 deaths worldwide. The surface spike protein of SARS‐CoV‐2 mediates the process of coronavirus entry into human cells by binding angiotensin‐converting enzyme 2 (ACE2). Due to the critical role in viral‐host interaction and the exposure of spike protein, it has been a focus of most vaccines' developments. However, the structural and biochemical studies of the spike protein are challenging because it is thermodynamically metastable. Here, we develop a new pipeline that automatically identifies mutants that thermodynamically stabilize the spike protein. Our pipeline integrates bioinformatics analysis of conserved residues, motion dynamics from molecular dynamics simulations, and other structural analysis to identify residues that significantly contribute to the thermodynamic stability of the spike protein. We then utilize our previously developed protein design tool, Eris, to predict thermodynamically stabilizing mutations in proteins. We validate the ability of our pipeline to identify protein stabilization mutants through known prefusion spike protein mutants. We finally utilize the pipeline to identify new prefusion spike protein stabilization mutants.

RNA-Puzzles Round IV: 3D structure predictions of four ribozymes and two aptamers

RNA-Puzzles is a collective endeavor dedicated to the advancement and improvement of RNA 3D structure prediction. With agreement from crystallographers, the RNA structures are predicted by various groups before the publication of the crystal structures. We now report the prediction of 3D structures for six RNA sequences: four nucleolytic ribozymes and two riboswitches. Systematic protocols for comparing models and crystal structures are described and analyzed. In these six puzzles, we discuss (i) the comparison between the automated web servers and human experts; (ii) the prediction of coaxial stacking; (iii) the prediction of structural details and ligand binding; (iv) the development of novel prediction methods; and (v) the potential improvements to be made. We show that correct prediction of coaxial stacking and tertiary contacts is essential for the prediction of RNA architecture, while ligand binding modes can only be predicted with low resolution and simultaneous prediction of RNA structure with accurate ligand binding still remains out of reach. All the predicted models are available for the future development of force field parameters and the improvement of comparison and assessment tools.

Experimentally-driven protein structure modeling

Revolutions in natural and exact sciences started at the dawn of last century have led to the explosion of theoretical, experimental, and computational approaches to determine structures of molecules, complexes, as well as their rich conformational dynamics. Since different experimental methods produce information that is attributed to specific time and length scales, corresponding computational methods have to be tailored to these scales and experiments. These methods can be then combined and integrated in scales, hence producing a fuller picture of molecular structure and motion from the "puzzle pieces" offered by various experiments. Here, we describe a number of computational approaches to utilize experimental data to glance into structure of proteins and understand their dynamics. We will also discuss the limitations and the resolution of the constraints-based modeling approaches. SIGNIFICANCE: Experimentally-driven computational structure modeling and determination is a rapidly evolving alternative to traditional approaches for molecular structure determination. These new hybrid experimental-computational approaches are proving to be a powerful microscope to glance into the structural features of intrinsically or partially disordered proteins, dynamics of molecules and complexes. In this review, we describe various approaches in the field of experimentally-driven computational structure modeling.

Thermo- and pH-responsive fibrillization of squid suckerin A1H1 peptide

Stimuli-responsive smart materials have attracted considerable attention with numerous applications in nanotechnology, sensing, and biomedicine. Suckerin family proteins found in squid ring teeth represent such a class of peptide-based smart materials with their self-assemblies featuring excellent thermo-plasticity and pH-dependence. Similar to block copolymers, suckerin proteins are comprised of two repeating sequence motifs, where M1 motifs are abundant in alanine and histidine residues and M2 are rich in glycine. Experimental studies of suckerin assemblies suggested that M1 regions mainly formed nano-confined β-sheets within an amorphous matrix made of M2 modules stabilizing these β-rich nano-assemblies. The histidine-containing M1 modules are believed to govern the pH- and temperature-sensitive properties of suckerin assemblies. To better understand the stimuli-responsive properties of suckerin assemblies at the molecular level, we systematically studied the self-assembly dynamics of A1H1 peptides - a representative M1 sequence - at different temperatures and pH conditions with atomistic discrete molecular dynamic simulations. Our simulations with twenty A1H1 peptides demonstrated that below the transition temperature Tagg, they could readily self-assemble from isolated monomers into well-defined β-sheet nanostructures by both primary and secondary nucleation of β-sheets and subsequent aggregation growth via elongation and coagulation. Interestingly, the dissociation of pre-formed A1H1 β-sheet nanostructures featured a melting temperature Tm higher than Tagg, exhibiting the thermal hysteresis that is characteristic of first-order phase transitions with high energy barriers. In acidic environments where all histidine residues were protonated, the stability of the A1H1 β-sheet nano-assemblies was reduced and the β-rich assemblies easily dissociated into unstructured monomers at significantly lower temperatures than in the neutral solution. The computationally derived molecular mechanisms for pH- and temperature-dependent A1H1 self-assembly will help to understand the supramolecular assembly structures and functions of the large suckerin family and aid in the future design of peptide-based stimuli-responsive smart materials.

Observing the three-dimensional terephthalic acid supramolecular growth mechanism on a stearic acid buffer layer by molecular simulation methods

The terephthalic acid (TPA) supramolecular growth mechanisms on the stearic acid (STA) buffer layer, such as the phase separation and layer-by-layer (LBL) mechanisms, were considered by molecular simulations.

Distinct Binding Modes of Vinculin Isoforms Underlie Their Functional Differences

Vinculin and its splice isoform metavinculin play key roles in regulating cellular morphology, motility, and force transduction. Vinculin is distinct from metavinculin in its ability to bundle filamentous actin (F-actin). To elucidate the molecular basis for these differences, we employed computational and experimental approaches. Results from these analyses suggest that the C terminus of both vinculin and metavinculin form stable interactions with the F-actin surface. However, the metavinculin tail (MVt) domain contains a 68 amino acid insert, with helix 1 (H1) sequestered into a globular subdomain, which protrudes from the F-actin surface and prevents actin bundling by sterically occluding actin filaments. Consistent with our model, deletion and selective point mutations within the MVt H1 disrupt this protruding structure, and facilitate actin bundling similar to vinculin tail (Vt) domain.

Computationally Guided Design of Single-Chain Variable Fragment Improves Specificity of Chimeric Antigen Receptors

Chimeric antigen receptor (CAR)-T cell-based immunotherapy of malignant disease relies on the specificity and association constant of single-chain variable fragments (scFvs). The latter are synthesized from parent antibodies by fusing their light (V_L) and heavy (V_H)-chain variable domains into a single chain using a flexible linker peptide. The fusion of V_L and V_H domains can distort their relative orientation, thereby compromising specificity and association constant of scFv, and reducing the lytic efficacy of CAR-T cells. Here, we circumvent the complications of domains' fusion by designing scFv mutants that stabilize interaction between scFv and its target, thereby rescuing scFv efficacy. We employ an iterative approach, based on structural modeling and mutagenesis driven by computational protein design. To demonstrate the power of this approach, we use the scFv derived from an antibody specific to a human leukocyte antigen A2 (HLA-A2)-HER2-derived peptide complex. Whereas the parental antibody is highly specific to its target, the scFv showed reduced specificity. Using our approach, we design mutations into scFvs that restore specificity of the original antibody.

In silico study of colchicine resistance molecular mechanisms caused by tubulin structural polymorphism

Starting from 1972, colchicine is known as the most useful drug for prevention of familial Mediterranean fever attacks. However, some patients do not respond to colchicine treatment, even taken in high doses. Despite the fact, that different hypotheses have been proposed, the molecular mechanisms of colchicine resistance are not completely clear. It is generally known, that colchicine binds β-tubulin and inhibits microtubules polymerization. The β-tubulin gene has SNPs, which lead to amino acid substitutions, and some of them are located in colchicine binding site (CBS). We have assumed, that this SNPs can affect tubulin-colchicine interaction and might be the reason for colchicine resistance. With this in mind, we modeled 7 amino acid substitutions in CBS, performed molecular dynamics simulations of tubulin-colchicine complex and calculated binding energies for every amino acid substitution. Thus, our study shows, that two amino acid substitutions in the β-tubulin, namely A248T and M257V, reduce binding energy for approximately 2-fold. Based on this, we assume, that these amino acid substitutions could be the reason for colchicine resistance. Thus, our study gives a new insight into colchicine resistance mechanism and provides information for designing colchicine alternatives, that could be effective for colchicine resistant patients.

Rational design of linear tripeptides against the aggregation of human mutant SOD1 protein causing amyotrophic lateral sclerosis

Formation of protein aggregation is considered a hallmark feature of various neurological diseases. Amyotrophic lateral sclerosis is one such devastating neurodegenerative disorder characterized by mutation in Cu/Zn superoxide dismutase protein (SOD1). In our study, we contemplated the most aggregated and pathogenic mutant A4V in a viewpoint of finding a therapeutic regime by inhibiting the formation of the aggregates with the aid of tripeptides since new perspectives in the field of drug design in the current era are being focused on peptide-based drugs. Reports from the experimental study have stipulated that the SOD1 derived peptide, "LSGDHCIIGRTLVVHEKADD" was found to have the inhibitory activity against aggregated SOD1 protein. Moreover, it was determined that the hexapeptide, "LSGDHC" was the key factor in inhibiting the aggregates of SOD1. Accordingly, we utilized the computerized algorithms and programs on determining the binding efficiency and inhibitory activity of hexapeptide on mutant SOD1. Following that, we incorporated a cutting-edge methodology with the use of molecular docking, affinity predictions, alanine scanning, steered molecular dynamics (SMD) and discrete molecular dynamics (DMD) in designing the de novo tripeptides, which could act against the aggregated mutant SOD1 protein. Upon examining the results from the various conformational studies, we identified that CGH had an enhanced binding affinity and inhibitory activity against the aggregated mutant SOD1 protein than other tripeptides and hexapeptide. Thus, our study could be a lead for state-of-the-art design in peptide-based drugs for doctoring the cureless ALS disorder.

β-Methylamino-L-alanine substitution of serine in SOD1 suggests a direct role in ALS etiology

Exposure to the environmental toxin β-methylamino-L-alanine (BMAA) is linked to amyotrophic lateral sclerosis (ALS), but its disease-promoting mechanism remains unknown. We propose that incorporation of BMAA into the ALS-linked protein Cu,Zn superoxide dismutase (SOD1) upon translation promotes protein misfolding and aggregation, which has been linked to ALS onset and progression. Using molecular simulation and predictive energetic computation, we demonstrate that substituting any serine with BMAA in SOD1 results in structural destabilization and aberrant dynamics, promoting neurotoxic SOD1 aggregation. We propose that translational incorporation of BMAA into SOD1 is directly responsible for its toxicity in neurodegeneration, and BMAA modification of SOD1 may serve as a biomarker of ALS.

Limits in accuracy and a strategy of RNA structure prediction using experimental information

RNA structural complexity and flexibility present a challenge for computational modeling efforts. Experimental information and bioinformatics data can be used as restraints to improve the accuracy of RNA tertiary structure prediction. Regarding utilization of restraints, the fundamental questions are: (i) What is the limit in prediction accuracy that one can achieve with arbitrary number of restraints? (ii) Is there a strategy for selection of the minimal number of restraints that would result in the best structural model? We address the first question by testing the limits in prediction accuracy using native contacts as restraints. To address the second question, we develop an algorithm based on the distance variation allowed by secondary structure (DVASS), which ranks restraints according to their importance to RNA tertiary structure prediction. We find that due to kinetic traps, the greatest improvement in the structure prediction accuracy is achieved when we utilize only 40-60% of the total number of native contacts as restraints. When the restraints are sorted by DVASS algorithm, using only the first 20% ranked restraints can greatly improve the prediction accuracy. Our findings suggest that only a limited number of strategically selected distance restraints can significantly assist in RNA structure modeling.

Amyloid Self-Assembly of hIAPP8-20 via the Accumulation of Helical Oligomers, α-Helix to β-Sheet Transition, and Formation of β-Barrel Intermediates

The self-assembly of human islet amyloid polypeptide (hIAPP) into β-sheet-rich nanofibrils is associated with the pathogeny of type 2 diabetes. Soluble hIAPP is intrinsically disordered with N-terminal residues 8-17 as α-helices. To understand the contribution of the N-terminal helix to the aggregation of full-length hIAPP, here the oligomerization dynamics of the hIAPP fragment 8-20 (hIAPP8-20) are investigated with combined computational and experimental approaches. hIAPP8-20 forms cross-β nanofibrils in silico from isolated helical monomers via the helical oligomers and α-helices to β-sheets transition, as confirmed by transmission electron microscopy, atomic force microscopy, circular dichroism spectroscopy, Fourier transform infrared spectroscopy, and reversed-phase high performance liquid chromatography. The computational results also suggest that the critical nucleus of aggregation corresponds to hexamers, consistent with a recent mass-spectroscopy study of hIAPP8-20 aggregation. hIAPP8-20 oligomers smaller than hexamers are helical and unstable, while the α-to-β transition starts from the hexamers. Converted β-sheet-rich oligomers first form β-barrel structures as intermediates before aggregating into cross-β nanofibrils. This study uncovers a complete picture of hIAPP8-20 peptide oligomerization, aggregation nucleation via conformational conversion, formation of β-barrel intermediates, and assembly of cross-β protofibrils, thereby shedding light on the aggregation of full-length hIAPP, a hallmark of pancreatic beta-cell degeneration.

Go-Kit: A Tool To Enable Energy Landscape Exploration of Proteins

Coarse-grained Go̅-like models, based on the principle of minimal frustration, provide valuable insight into fundamental questions in the field of protein folding and dynamics. In conjunction with commonly used molecular dynamics (MD) simulations, energy landscape exploration methods like discrete path sampling (DPS) with Go̅-like models can provide quantitative details of the thermodynamics and kinetics of proteins. Here we present Go-kit, a software that facilitates the setup of MD and DPS simulations of several flavors of Go̅-like models. Go-kit is designed for use with MD (GROMACS) and DPS (PATHSAMPLE) simulation engines that are open source. The Go-kit code is written in python2.7 and is also open source. A case study for the ribosomal protein S6 is discussed to illustrate the utility of the software, which is available at https://github.com/gokit1/gokit .

MERTK mediated novel site Akt phosphorylation alleviates SAV1 suppression

Akt plays indispensable roles in cell proliferation, survival and metabolism. Mechanisms underlying posttranslational modification-mediated Akt activation have been extensively studied yet the Akt interactome is less understood. Here, we report that SAV1, a Hippo signaling component, inhibits Akt, a function independent of its role in Hippo signaling. Binding to a proline-tyrosine motif in the Akt-PH domain, SAV1 suppresses Akt activation by blocking Akt’s movement to plasma membrane. We further identify cancer-associated SAV1 mutations with impaired ability to bind Akt, leading to Akt hyperactivation. We also determine that MERTK phosphorylates Akt1-Y26, releasing SAV1 binding and allowing Akt responsiveness to canonical PI-3K pathway activation. This work provides a mechanism underlying MERTK-mediated Akt activation and survival signaling in kidney cancer. Akt activation drives oncogenesis and therapeutic resistance; this mechanism of Akt regulation by MERTK/SAV1 provides yet another complexity in an extensively studied pathway, and may yield prognostic information and therapeutic targets.

Hyperactivation of Akt promotes tumorigenesis. Here, the authors show that SAV1, a member of Hippo signalling, interacts with Akt to suppress Akt activity and MERTK-mediated Akt phosphorylation relieves this suppression to facilitate Akt oncogenic activity in clear cell renal carcinomas.

Conformational ensemble of native α-synuclein in solution as determined by short-distance crosslinking constraint-guided discrete molecular dynamics simulations

Combining structural proteomics experimental data with computational methods is a powerful tool for protein structure prediction. Here, we apply a recently-developed approach for de novo protein structure determination based on the incorporation of short-distance crosslinking data as constraints in discrete molecular dynamics simulations (CL-DMD) for the determination of conformational ensemble of the intrinsically disordered protein α-synuclein in the solution. The predicted structures were in agreement with hydrogen-deuterium exchange, circular dichroism, surface modification, and long-distance crosslinking data. We found that α-synuclein is present in solution as an ensemble of rather compact globular conformations with distinct topology and inter-residue contacts, which is well-represented by movements of the large loops and formation of few transient secondary structure elements. Non-amyloid component and C-terminal regions were consistently found to contain β-structure elements and hairpins.

As the population ages, neurodegenerative diseases such as Parkinson’s disease will become an increasing problem in many countries. Aggregation of the protein α-synuclein is the primary cause of Parkinson’s disease, but there is still a dearth of structural information pertaining to the native, non-aggregating form of this protein. A better understanding the structural state of the native protein may prove useful for the design of new therapeutics to combat this disease. In order to obtain more structural information on this protein, we have recently modelled the native α-synuclein protein. These models were generated using a novel approach which combines protein crosslinking and discrete molecular dynamics simulations. We have found that the α-synuclein protein can adopt several shapes, all with a similar topology, resembling a three fingered closed claw. A region of the protein important for aggregation was found to be protected from the surrounding biological environment in these conformations, and the stabilization of these structures may be a fruitful avenue for future drug research into mitigating the cause and effect of Parkinson’s disease.

Computational Investigation on Electrostatic Loop Mutants Instigating Destabilization and Aggregation on Human SOD1 Protein Causing Amyotrophic Lateral Sclerosis

Mutations in the gene encoding Cu/Zn Superoxide Dismutase 1 (SOD1) protein are contemplated to be a protruding reason for Amyotrophic lateral sclerosis (ALS), which leads towards protein aggregation, misfolding and destabilization. Thus, we investigated the systematic action of entire mutations reported on electrostatic loop of SOD1 protein through thermodynamical and discrete molecular dynamics (DMD) studies. Accordingly, we analyzed the outcomes distinctly for screening the mutant structures having both, deleterious and destabilizing effect. Progressively, the impacts of those mutations on SOD1 were studied using DMD program. Surprisingly, our results predicted that the mutants viz., L126S, N139H and G141A to be the most destabilizing, misfolded and disease-causing compared to other mutants. Besides, the outcomes from secondary structural propensities and free energy landscapes, together assertively suggested that L126S, N139H and G141A tend to increase the formation of aggregates in SOD1 relative to other mutants. Hence, this study could provide an insight into the sprouting neurodegenerative disorder distressing the humans.

Ligand binding to a remote site thermodynamically corrects the F508del mutation in the human cystic fibrosis transmembrane conductance regulator

Many disease-causing mutations impair protein stability. Here, we explore a thermodynamic strategy to correct the disease-causing F508del mutation in the human cystic fibrosis transmembrane conductance regulator (hCFTR). F508del destabilizes nucleotide-binding domain 1 (hNBD1) in hCFTR relative to an aggregation-prone intermediate. We developed a fluorescence self-quenching assay for compounds that prevent aggregation of hNBD1 by stabilizing its native conformation. Unexpectedly, we found that dTTP and nucleotide analogs with exocyclic methyl groups bind to hNBD1 more strongly than ATP and preserve electrophysiological function of full-length F508del-hCFTR channels at temperatures up to 37 °C. Furthermore, nucleotides that increase open-channel probability, which reflects stabilization of an interdomain interface to hNBD1, thermally protect full-length F508del-hCFTR even when they do not stabilize isolated hNBD1. Therefore, stabilization of hNBD1 itself or of one of its interdomain interfaces by a small molecule indirectly offsets the destabilizing effect of the F508del mutation on full-length hCFTR. These results indicate that high-affinity binding of a small molecule to a remote site can correct a disease-causing mutation. We propose that the strategies described here should be applicable to identifying small molecules to help manage other human diseases caused by mutations that destabilize native protein conformation.

Graphene quantum dots against human IAPP aggregation and toxicity in vivo

The development of biocompatible nanomaterials has become a new frontier in the detection, treatment and prevention of human amyloid diseases. Here we demonstrated the use of graphene quantum dots (GQDs) as a potent inhibitor against the in vivo aggregation and toxicity of human islet amyloid polypeptide (IAPP), a hallmark of type 2 diabetes. GQDs initiated contact with IAPP through electrostatic and hydrophobic interactions as well as hydrogen bonding, which subsequently drove the peptide fibrillization off-pathway to eliminate the toxic intermediates. Such interactions, probed in vitro by a thioflavin T kinetic assay, fluorescence quenching, circular dichroism spectroscopy, a cell viability assay and in silico by discrete molecular dynamics simulations, translated to a significant recovery of embryonic zebrafish from the damage elicited by IAPP in vivo, as indicated by improved hatching as well as alleviated reactive oxygen species production, abnormality and mortality of the organism. This study points to the potential of using zero-dimensional nanomaterials for in vivo mitigation of a range of amyloidosis.

Reversible and Tunable Photoswitching of Protein Function through Genetic Encoding of Azobenzene Amino Acids in Mammalian Cells

The genetic encoding of three different azobenzene phenylalanines with different photochemical properties was achieved in human cells by using an engineered pyrrolysyl tRNA/tRNA synthetase pair. In order to demonstrate reversible light control of protein function, azobenzenes were site-specifically introduced into firefly luciferase. Computational strategies were applied to guide the selection of potential photoswitchable sites that lead to a reversibly controlled luciferase enzyme. In addition, the new azobenzene analogues provide enhanced thermal stability, high photoconversion, and responsiveness to visible light. These small-molecule photoswitches can reversibly photocontrol protein function with excellent spatiotemporal resolution, and preferred sites for incorporation can be computationally determined, thus providing a new tool for investigating biological processes.

Comparative binding of kaempferol and kaempferide on inhibiting the aggregate formation of mutant (G85R) SOD1 protein in familial amyotrophic lateral sclerosis: A quantum chemical and molecular mechanics study

Mutation in Cu/Zn superoxide dismutase (SOD1) at position 85 from glycine to arginine was found to be a prominent cause of aggregation characterized by an increased content of β-sheets in familial amyotrophic lateral sclerosis (fALS). Various literatures reported that natural polyphenols could act as a β-sheet breaker and therefore, treated as a potential therapeutics against various aggregated proteins involved in neurodegenerative disorders. Through computational perspective, molecular docking, quantum chemical studies, and discrete molecular dynamics were implemented to study the binding and structural effect of natural polyphenols, kaempferol, and kaempferide on mutant SOD1. Kaempferol exhibited significant binding and greater residual energy contribution with mutant SOD1 than kaempferide. More interestingly, kaempferol was found to reduce the β-sheet content augmenting the mutant conformational stability and flexibility relative to that of kaempferide. Hence, the inhibition of mutant SOD1 aggregation by kaempferol was explored, thereby suggesting kaempferol could act as a drug candidate for the design of the natural therapeutics against fALS. © 2018 BioFactors, 44(5):431-442, 2018.

miRNA-711 Binds and Activates TRPA1 Extracellularly to Evoke Acute and Chronic Pruritus

Increasing evidence suggests that extracellular miRNAs may serve as biomarkers of diseases, but the physiological relevance of extracellular miRNA is unclear. We find that intradermal cheek injection of miR-711 induces TRPA1-depedent itch (scratching) without pain (wiping) in naive mice. Extracellular perfusion of miR-711 induces TRPA1 currents in both Trpa1-expressing heterologous cells and native sensory neurons through the core sequence GGGACCC. Computer simulations reveal that the core sequence binds several residues at the extracellular S5-S6 loop of TRPA1, which are critical for TRPA1 activation by miR-711 but not allyl isothiocyanate. Intradermal inoculation of human Myla cells induces lymphoma and chronic itch in immune-deficient mice, associated with increased serum levels of miR-711, secreted from cancer cells. Lymphoma-induced chronic itch is suppressed by miR-711 inhibitor and a blocking peptide that disrupts the miR-711/TRPA1 interaction. Our findings demonstrated an unconventional physiological role of extracellular naked miRNAs as itch mediators and ion channel modulators.