The molecular modeling toolkit: A new approach to molecular simulations

Analysis of Velocity Autocorrelation Functions from Molecular Dynamics Simulations of a Small Peptide by the Generalized Langevin Equation with a Power-Law Kernel

Internal motions play an essential role in the biological functions of proteins and have been the subject of numerous theoretical and spectroscopic studies. Such complex environments are associated with anomalous diffusion where, in contrast to the classical Brownian motion, the relevant correlation functions have power law decays with time. In this work, we investigate the presence of long memory stochastic processes through the analysis of atomic velocity autocorrelation functions. Analytical expressions of the velocity autocorrelation function spectrum obtained through a Mori-Zwanzig projection approach were shown to be compatible with molecular dynamics simulations of a small helical peptide (8-polyalanine).

Network Pharmacology Integrated Molecular Docking and Dynamics to Elucidate Saffron Compounds Targeting Human COX-2 Protein

Background and Objectives: Cyclooxygenase-2 (COX-2) is mostly linked to inflammation and has been validated as a molecular target for treating inflammatory diseases. The present study aimed to identify novel compounds that could inhibit COX-2, which is associated with various diseases including inflammation, and in such a scenario, plant-derived biomolecules have been considered as attractive candidates. Materials and Methods: In the present study, physiochemical properties and toxicity of natural compounds/drugs were determined by SWISSADME and ProTox-II. In the present study, the molecular docking binding features of saffron derivatives (crocetin, picrocrocin, quercetin, safranal, crocin, rutin, and dimethylcrocetin) against human COX-2 protein were assessed. Moreover, protein-protein interactions, topographic properties, gene enrichment analysis and molecular dynamics simulation were also determined. Results: The present study revealed that picrocrocin showed the highest binding affinity of -8.1 kcal/mol when docked against the COX-2 protein. PROCHECK analysis revealed that 90.3% of the protein residues were found in the most favored region. Compartmentalized Protein-Protein Interaction identified 90 interactions with an average interaction score of 0.62, and the highest localization score of 0.99 found in secretory pathways. The Computed Atlas of Surface Topography of Proteins was used to identify binding pockets and important residues that could serve as drug targets. Use of WEBnmα revealed protein dynamics by using normal mode analysis. Ligand and Receptor Dynamics used the Molecular Generalized Born Surface Area approach to determine the binding free energy of the protein. Gene enrichment analysis revealed that ovarian steroidogenesis, was the most significant enrichment pathway. Molecular dynamic simulations were executed for the best docked (COX-2-picrocrocin) complex, and the results displayed conformational alterations with more pronounced surface residue fluctuations in COX-2 with loss of the intra-protein hydrogen bonding network. The direct interaction of picrocrocin with various crucial amino-acid residues like GLN203, TYR385, HIS386 and 388, ASN382, and TRP387 causes modifications in these residues, which ultimately attenuates the activity of COX-2 protein. Conclusions: The present study revealed that picrocrocin was the most effective biomolecule and could be repurposed via computational approaches. However, various in vivo and in vitro observations are still needed.

Identification of additional mechanistically important residues in the multidrug transporter styMdtM of Salmonella Typhi

Multidrug efflux is a well-established mechanism of drug resistance in bacterial pathogens like Salmonella Typhi. styMdtM (locus name; STY4874) is a multidrug efflux transporter of the major facilitator superfamily expressed in S. Typhi. Functional assays identified several residues important for its transport activity. Here, we used an AlphaFold model to identify additional residues for analysis by mutagenesis. Mutation of peripheral residue Cys185 had no effect on the structure or function of the transporter. However, substitution of channel-lining residues Tyr29 and Tyr231 completely abolished transport function. Finally, mutation of Gln294, which faces peripheral helices of the transporter, resulted in the loss of transport of some substrates. Crystallization studies yielded diffraction data for the wild-type protein at 4.5 Å resolution and allowed the unit cell parameters to be established as a = b = 64.3 Å, c = 245.4 Å, α = β = γ = 90°, in space group P4. Our studies represent a further stepping stone towards a mechanistic understanding of the clinically important multidrug transporter styMdtM.Communicated by Ramaswamy H. Sarma.

Tryptophan-PNA gc Conjugates Self-Assemble to Form Fibers

Peptide nucleic acids and their conjugates to peptides can self-assemble and generate complex architectures. In this work, we explored the self-assembly of PNA dimers conjugated to the dipeptide WW. Our studies suggest that the indole ring of tryptophan promotes aggregation of the conjugates. The onset of fluorescence is observed upon self-assembly. The structure of self-assembled WWgc is concentration-dependent, being spherical at low concentrations and fibrous at high concentrations. As suggested by molecular modeling studies, fibers are stabilized by stacking interactions between tryptophans and Watson-Crick hydrogen bonds between nucleobases.

Identification of novel p-cresol inhibitors that reduce Clostridioides difficile's ability to compete with species of the gut microbiome

Treatment of Clostridioides difficile infection (CDI) is expensive and complex, with a high proportion of patients suffering infection relapse (20-35%), and some having multiple relapses. A healthy, unperturbed gut microbiome provides colonisation resistance against CDI through competition for nutrients and space. However, antibiotic consumption can disturb the gut microbiota (dysbiosis) resulting in the loss of colonisation resistance allowing C. difficile to colonise and establish infection. A unique feature of C. difficile is the production of high concentrations of the antimicrobial compound para-cresol, which provides the bacterium with a competitive advantage over other bacteria found in the gut. p-cresol is produced by the conversion of para-Hydroxyphenylacetic acid (p-HPA) by the HpdBCA enzyme complex. In this study, we have identified several promising inhibitors of HpdBCA decarboxylase, which reduce p-cresol production and render C. difficile less able to compete with a gut dwelling Escherichia coli strain. We demonstrate that the lead compound, 4-Hydroxyphenylacetonitrile, reduced p-cresol production by 99.0 ± 0.4%, whereas 4-Hydroxyphenylacetamide, a previously identified inhibitor of HpdBCA decarboxylase, only reduced p-cresol production by 54.9 ± 13.5%. To interpret efficacy of these first-generation inhibitors, we undertook molecular docking studies that predict the binding mode for these compounds. Notably, the predicted binding energy correlated well with the experimentally determined level of inhibition, providing a molecular basis for the differences in efficacy between the compounds. This study has identified promising p-cresol production inhibitors whose development could lead to beneficial therapeutics that help to restore colonisation resistance and therefore reduce the likelihood of CDI relapse.

Molecular architecture and dynamics of SARS-CoV-2 envelope by integrative modeling

Despite tremendous efforts, the exact structure of SARS-CoV-2 and related betacoronaviruses remains elusive. SARS-CoV-2 envelope is a key structural component of the virion that encapsulates viral RNA. It is composed of three structural proteins, spike, membrane (M), and envelope, which interact with each other and with the lipids acquired from the host membranes. Here, we developed and applied an integrative multi-scale computational approach to model the envelope structure of SARS-CoV-2 with near atomistic detail, focusing on studying the dynamic nature and molecular interactions of its most abundant, but largely understudied, M protein. The molecular dynamics simulations allowed us to test the envelope stability under different configurations and revealed that the M dimers agglomerated into large, filament-like, macromolecular assemblies with distinct molecular patterns. These results are in good agreement with current experimental data, demonstrating a generic and versatile approach to model the structure of a virus de novo.

Wordom update 2: A user-friendly program for the analysis of molecular structures and conformational ensembles

We present the second update of Wordom, a user-friendly and efficient program for manipulation and analysis of conformational ensembles from molecular simulations. The actual update expands some of the existing modules and adds 21 new modules to the update 1 published in 2011. The new adds can be divided into three sets that: 1) analyze atomic fluctuations and structural communication; 2) explore ion-channel conformational dynamics and ionic translocation; and 3) compute geometrical indices of structural deformation. Set 1 serves to compute correlations of motions, find geometrically stable domains, identify a dynamically invariant core, find changes in domain-domain separation and mutual orientation, perform wavelet analysis of large-scale simulations, process the output of principal component analysis of atomic fluctuations, perform functional mode analysis, infer regions of mechanical rigidity, analyze overall fluctuations, and perform the perturbation response scanning. Set 2 includes modules specific for ion channels, which serve to monitor the pore radius as well as water or ion fluxes, and measure functional collective motions like receptor twisting or tilting angles. Finally, set 3 includes tools to monitor structural deformations by computing angles, perimeter, area, volume, β-sheet curvature, radial distribution function, and center of mass. The ring perception module is also included, helpful to monitor supramolecular self-assemblies. This update places Wordom among the most suitable, complete, user-friendly, and efficient software for the analysis of biomolecular simulations. The source code of Wordom and the relative documentation are available under the GNU general public license at http://wordom.sf.net.

Suramin, penciclovir, and anidulafungin exhibit potential in the treatment of COVID-19 via binding to nsp12 of SARS-CoV-2

COVID-19, for which no confirmed therapeutic agents are available, has claimed over 48,14,000 lives globally. A feasible and quicker method to resolve this problem may be 'drug repositioning'. We investigated selected FDA and WHO-EML approved drugs based on their previously promising potential as antivirals, antibacterials or antifungals. These drugs were docked onto the nsp12 protein, which reigns the RNA-dependent RNA polymerase activity of SARS-CoV-2, a key therapeutic target for coronaviruses. Docked complexes were reevaluated using MM-GBSA analysis and the top three inhibitor-protein complexes were subjected to 100 ns long molecular dynamics simulation followed by another round of MM-GBSA analysis. The RMSF plots, binding energies and the mode of physicochemical interaction of the active site of the protein with the drugs were evaluated. Suramin, Penciclovir, and Anidulafungin were found to bind to nsp12 with similar binding energies as that of Remdesivir, which has been used as a therapy for COVID-19. In addition, recent experimental evidences indicate that these drugs exhibit antiviral efficacy against SARS-CoV-2. Such evidence, along with the significant and varied physical interactions of these drugs with the key viral enzyme outlined in this investigation, indicates that they might have a prospective therapeutic potential in the treatment of COVID-19 as monotherapy or combination therapy with Remdesivir.

Explicit versus implicit consideration of binding partners in protein-protein complex to elucidate intrinsic dynamics

The binding of many proteins to their protein partners is tightly regulated via control of their relative intrinsic dynamics during the binding process, a phenomenon which can in turn be modulated. Therefore, investigating the intrinsic dynamics of proteins is necessary to understand function in a comprehensive way. By intrinsic dynamics herein, we principally refer to the vibrational signature of a protein molecule popularly obtained from normal modes or essential modes. For normal modes, one often considers that the molecule under investigation is a collection of springs in a solvent-free or implicit-solvent medium. In the context of a protein-binding partner, the analysis of vibration of the target protein is often complicated due to molecular interaction within the complex. Generally, it is assumed that the isolated bound conformation of the target protein captures the implicit effect of the binding partner on the intrinsic dynamics, therefore suggesting that any influence of the partner molecule is also already integrated. Such an assumption allows large-scale studies of the conservation of protein flexibility. However, in cases where a partner protein directly influences the vibration of the target via critical contacts at the protein-protein interface, the above assumption falls short of providing a detailed view. In this review article, we discuss the implications of considering the dynamics of a protein in a protein-protein complex, as modelled implicitly and explicitly with methods dependent on elastic network models. We further propose how such an explicit consideration can be applied to understand critical protein-protein contacts that can be targeted in future studies.

Methodology-Centered Review of Molecular Modeling, Simulation, and Prediction of SARS-CoV-2

Despite tremendous efforts in the past two years, our understanding of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), virus-host interactions, immune response, virulence, transmission, and evolution is still very limited. This limitation calls for further in-depth investigation. Computational studies have become an indispensable component in combating coronavirus disease 2019 (COVID-19) due to their low cost, their efficiency, and the fact that they are free from safety and ethical constraints. Additionally, the mechanism that governs the global evolution and transmission of SARS-CoV-2 cannot be revealed from individual experiments and was discovered by integrating genotyping of massive viral sequences, biophysical modeling of protein-protein interactions, deep mutational data, deep learning, and advanced mathematics. There exists a tsunami of literature on the molecular modeling, simulations, and predictions of SARS-CoV-2 and related developments of drugs, vaccines, antibodies, and diagnostics. To provide readers with a quick update about this literature, we present a comprehensive and systematic methodology-centered review. Aspects such as molecular biophysics, bioinformatics, cheminformatics, machine learning, and mathematics are discussed. This review will be beneficial to researchers who are looking for ways to contribute to SARS-CoV-2 studies and those who are interested in the status of the field.

Chiral Fibers Formation Upon Assembly of Tetraphenylalanine Peptide Conjugated to a PNA Dimer

Self‐assembly of biomolecules such as peptides, nucleic acids or their analogues affords supramolecular objects, exhibiting structures and physical properties dependent on the amino‐acid or nucleobase composition. Conjugation of the peptide diphenylalanine (FF) to peptide nucleic acids triggers formation of self‐assembled structures, mainly stabilized by interactions between FF. In this work we report formation of homogeneous chiral fibers upon self‐assembly of the hybrid composed of the tetraphenylalanine peptide (4F) conjugated to the PNA dimer adenine‐thymine (at). In this case nucleobases seem to play a key role in determining the morphology and chirality of the fibers. When the PNA “at” is replaced by guanine‐cytosine dimer “gc”, disordered structures are observed. Spectroscopic characterization of the self‐assembled hybrids, along with AFM and SEM studies is reported. Finally, a structural model consistent with the experimental evidence has also been obtained, showing how the building blocks of 4Fat arrange to give helical fibers.

Inhibition of Arenaviridae nucleoprotein exonuclease by bisphosphonate

Arenaviruses are emerging enveloped negative-sense RNA viruses that cause neurological and hemorrhagic diseases in humans. Currently, no FDA-approved vaccine or therapeutic agent is available except for ribavirin, which must be administered early during infection for optimum efficacy. A hallmark of arenavirus infection is rapid and efficient immune suppression mediated by the exonuclease domain encoded by the nucleoprotein. This exonuclease is therefore an attractive target for the design of novel antiviral drugs since exonuclease inhibitors might not only have a direct effect on the enzyme but could also boost viral clearance through stimulation of the innate immune system of the host cell. Here, in silico screening and an enzymatic assay were used to identify a novel, specific but weak inhibitor of the arenavirus exonuclease, with IC50 values of 65.9 and 68.6 µM for Mopeia virus and Lymphocytic choriomeningitis virus, respectively. This finding was further characterized using crystallographic and docking approaches. This study serves as a proof of concept and may have assigned a new therapeutic purpose for the bisphosphonate family, therefore paving the way for the development of inhibitors against Arenaviridae.

From Data to Knowledge: Systematic Review of Tools for Automatic Analysis of Molecular Dynamics Output

An increasing number of crystal structures available on one side, and the boost of computational power available for computer-aided drug design tasks on the other, have caused that the structure-based drug design tools are intensively used in the drug development pipelines. Docking and molecular dynamics simulations, key representatives of the structure-based approaches, provide detailed information about the potential interaction of a ligand with a target receptor. However, at the same time, they require a three-dimensional structure of a protein and a relatively high amount of computational resources. Nowadays, as both docking and molecular dynamics are much more extensively used, the amount of data output from these procedures is also growing. Therefore, there are also more and more approaches that facilitate the analysis and interpretation of the results of structure-based tools. In this review, we will comprehensively summarize approaches for handling molecular dynamics simulations output. It will cover both statistical and machine-learning-based tools, as well as various forms of depiction of molecular dynamics output.

Crystal structures of bacterial small multidrug resistance transporter EmrE in complex with structurally diverse substrates

Proteins from the bacterial small multidrug resistance (SMR) family are proton-coupled exporters of diverse antiseptics and antimicrobials, including polyaromatic cations and quaternary ammonium compounds. The transport mechanism of the Escherichia coli transporter, EmrE, has been studied extensively, but a lack of high-resolution structural information has impeded a structural description of its molecular mechanism. Here, we apply a novel approach, multipurpose crystallization chaperones, to solve several structures of EmrE, including a 2.9 Å structure at low pH without substrate. We report five additional structures in complex with structurally diverse transported substrates, including quaternary phosphonium, quaternary ammonium, and planar polyaromatic compounds. These structures show that binding site tryptophan and glutamate residues adopt different rotamers to conform to disparate structures without requiring major rearrangements of the backbone structure. Structural and functional comparison to Gdx-Clo, an SMR protein that transports a much narrower spectrum of substrates, suggests that in EmrE, a relatively sparse hydrogen bond network among binding site residues permits increased sidechain flexibility.

Ground state chemical potential of parahydrogen clusters of size N = 21-40

We report the ground state chemical potential of parahydrogen clusters between N = 21-40 calculated using the Langevin equation Path Integral Ground State method. There has been much debate in the past whether the chemical potential size evolution in this region is jagged (indicating magic number cluster sizes) or if it is smooth (indicating some quantum melting below 1 K). We compare to previous diffusion Monte Carlo and Path Integral Ground State (PIGS) results, including very recent Variational Path Integral Molecular Dynamics (VPIMD) calculations [S. Miura, J. Chem. Phys. 148, 102333 (2018)]. We find that the ground state chemical potential is not a smooth curve and that magic number clusters are present, consistent with VPIMD and PIGS Monte Carlo results.

Path integral simulations of confined parahydrogen molecules within clathrate hydrates: Merging low temperature dynamics with the zero-temperature limit

Clathrate hydrates, or cages comprised solely of water molecules, have long been investigated as a clean storage facility for hydrogen molecules. A breakthrough occurred when hydrogen molecules were experimentally placed within a structure-II clathrate hydrate, which sparked much interest to determine their feasibility for energy storage [Mao et al., Science 297, 2247-2249 (2002)]. We use Path Integral Molecular Dynamics (PIMD) and Langevin equation Path Integral Ground State (LePIGS) for finite temperature and zero-temperature studies, respectively, to determine parahydrogen occupancy properties in the small dodecahedral (5¹²) and large hexakaidecahedral (5¹²6⁴) sized cages that comprise the structure-II unit cell. We look at energetic and structural properties of small clusters of hydrogen, treated as point-like particles, confined within each of the different sized clathrates, and treated as rigid, to determine energetic and structural properties in the zero-temperature limit. Our predicted hydrogen occupancy within these two cage sizes is consistent with previous literature values. We then calculate the energies as a function of temperature and merge the low temperature results calculated using finite temperature PIMD with the zero-temperature results using LePIGS, demonstrating that the two methods are compatible.

Calcite Scale Inhibition Using Environmental-Friendly Amino Acid Inhibitors: DFT Investigation

Scale prevention is a long-term challenge. It is essential for ensuring the optimum utilization of oil and gas wells and minimizing economic losses due to disruptions in the hydrocarbon flow. Among the commonly precipitated scales is calcite, especially in oilfield production facilities. Previous studies on scale inhibitors have focused on investigating the performance of several phosphonates and carboxylates. However, the increased environmental awareness has pushed toward investigating environmental-friendly inhibitors. Research studies demonstrated the potential of using amino acids as standalone inhibitors or as inhibitor-modifying reagents. In this study, 10 amino acids for calcite inhibitors have been investigated using molecular simulations. Eco-toxicity, quantum chemical calculations, binding energy, geometrical, and charge analyses were all evaluated to gain a holistic view of the behavior and interaction of these inhibitors with the calcite {1 0 4} surface. According to the DFT simulation, alanine, aspartic acid, phenylalanine, and tyrosine amino acids have the best inhibitor features. The results revealed that the binding energies were -2.16, -1.75, -2.24, and -2.66 eV for alanine, aspartic acid, phenylalanine, and tyrosine, respectively. Therefore, this study predicted an inhibition efficiency of the order tyrosine > phenylalanine > alanine > aspartic acid. The predicted inhibition efficiency order reveals agreement with the reported experimental results. Finally, the geometrical and charge analyses illustrated that the adsorption onto calcite is physisorption in the acquired adsorption energy range.

HYPK coordinates degradation of polyneddylated proteins by autophagy

Selective degradation of protein aggregates by macroautophagy/autophagy is an essential homeostatic process of safeguarding cells from the effects of proteotoxicity. Among the ubiquitin-like proteins, NEDD8 conjugation to misfolded proteins is prominent in stress-induced protein aggregates, albeit the function of neddylation in autophagy is unclear. Here, we report that polyneddylation functions as a post-translational modification for autophagic degradation of proteotoxic-stress induced protein aggregates. We also show that HYPK functions as an autophagy receptor in the polyneddylation-dependent aggrephagy. The scaffolding function of HYPK is facilitated by its C-terminal ubiquitin-associated domain and N-terminal tyrosine-type LC3-interacting region which bind to NEDD8 and LC3 respectively. Both NEDD8 and HYPK are positive modulators of basal and proteotoxicity-induced autophagy, leading to protection of cells from protein aggregates, such as aggregates of mutant HTT exon 1. Thus, we propose an indispensable and additive role of neddylation and HYPK in clearance of protein aggregates by autophagy, resulting in cytoprotective effect during proteotoxic stress.Abbreviations: ATG5, autophagy related 5; ATG12, autophagy related 12; ATG14, autophagy related 14; BECN1, beclin 1; CBL, casitas B-lineage lymphoma; CBLB, Cbl proto-oncogene B; GABARAP, GABA type A receptor-associated protein; GABARAPL1, GABA type A receptor associated protein like 1; GABARAPL2, GABA type A receptor associated protein like 2; GFP, green fluorescent protein; HTT, huntingtin; HTT97Q exon 1, huntingtin 97-glutamine exon 1; HUWE1, HECT, UBA and WWE domain containing E3 ubiquitin protein ligase 1; HYPK, huntingtin interacting protein K; IgG, immunoglobulin G; IMR-32, Institute for Medical Research-32; KD, knockdown; K_d, dissociation constant; LAMP1, lysosomal associated membrane protein 1; LIR, LC3 interacting region; MAP1LC3/LC3, microtubule associated protein 1 light chain 3; MAP1LC3A/LC3A, microtubule associated protein 1 light chain 3 alpha; MAP1LC3B/LC3B, microtubule associated protein 1 light chain 3 beta; MARK1, microtubule affinity regulating kinase 1; MARK2, microtubule affinity regulating kinase 2; MARK3, microtubule affinity regulating kinase 3; MARK4, microtubule affinity regulating kinase 4; MCF7, Michigan Cancer Foundation-7; MTOR, mechanistic target of rapamycin kinase; NAE1, NEDD8 activating enzyme E1 subunit 1; NBR1, NBR1 autophagy cargo receptor; NEDD8, NEDD8 ubiquitin like modifier; Ni-NTA, nickel-nitrilotriacetic acid; NUB1, negative regulator of ubiquitin like proteins 1; PIK3C3, phosphatidylinositol 3-kinase catalytic subunit type 3; PolyQ, poly-glutamine; PSMD8, proteasome 26S subunit, non-ATPase 8; RAD23A, RAD23 homolog A, nucleotide excision repair protein; RAD23B, RAD23 homolog B, nucleotide excision repair protein; RFP, red fluorescent protein; RPS27A, ribosomal protein S27a; RSC1A1, regulator of solute carriers 1; SNCA, synuclein alpha; SIK1, salt inducible kinase 1; siRNA, small interfering ribonucleic acid; SOD1, superoxide dismutase 1; SPR, surface plasmon resonance; SQSTM1, sequestosome 1; SUMO1, small ubiquitin like modifier 1; TAX1BP1, Tax1 binding protein 1; TDRD3, tudor domain containing 3; TNRC6C, trinucleotide repeat containing adaptor 6C; TOLLIP, toll interacting protein; TUBA, tubulin alpha; TUBB, tubulin beta class I; UBA, ubiquitin-associated; UBA1, ubiquitin like modifier activating enzyme 1; UBA5, ubiquitin like modifier activating enzyme 5; UBAC1, UBA domain containing 1; UBAC2, UBA domain containing 2; UBAP1, ubiquitin associated protein 1; UBAP2, ubiquitin associated protein 2; UBASH3B, ubiquitin associated and SH3 domain containing B; UBD/FAT10, ubiquitin D; UBE2K, ubiquitin conjugating enzyme E2 K; UBLs, ubiquitin-like proteins; UBL7, ubiquitin like 7; UBQLN1, ubiquilin 1; UBQLN2, ubiquilin 2; UBQLN3, ubiquilin 3; UBQLN4, ubiquilin 4; UBXN1, UBX domain protein 1; ULK1, unc-51 like autophagy activating kinase 1; URM1, ubiquitin related modifier 1; USP5, ubiquitin specific peptidase 5; USP13, ubiquitin specific peptidase 13; VPS13D, vacuolar protein sorting 13 homolog D.

Biobox: a toolbox for biomolecular modelling

MOTIVATION

The implementation of biomolecular modelling methods and analyses can be cumbersome, often carried out with in-house software reimplementing common tasks, and requiring the integration of diverse software libraries.

RESULTS

We present Biobox, a Python-based toolbox facilitating the implementation of biomolecular modelling methods.

AVAILABILITY AND IMPLEMENTATION

Biobox is freely available on https://github.com/degiacom/biobox, along with its API and interactive Jupyter notebook tutorials.

Modeling Perturbations in Protein Filaments at the Micro and Meso Scale Using NAMD and PTools/Heligeom

Protein filaments are dynamic entities that respond to external stimuli by slightly or substantially modifying the internal binding geometries between successive protomers. This results in overall changes in the filament architecture, which are difficult to model due to the helical character of the system. Here, we describe how distortions in RecA nucleofilaments and their consequences on the filament-DNA and bound DNA-DNA interactions at different stages of the homologous recombination process can be modeled using the PTools/Heligeom software and subsequent molecular dynamics simulation with NAMD. Modeling methods dealing with helical macromolecular objects typically rely on symmetric assemblies and take advantage of known symmetry descriptors. Other methods dealing with single objects, such as MMTK or VMD, do not integrate the specificities of regular assemblies. By basing the model building on binding geometries at the protomer-protomer level, PTools/Heligeom frees the building process from a priori knowledge of the system topology and enables irregular architectures and symmetry disruption to be accounted for. Graphical abstract: Model of ATP hydrolysis-induced distortions in the recombinant nucleoprotein, obtained by combining RecA-DNA and two RecA-RecA binding geometries.

Recent advances in user-friendly computational tools to engineer protein function

Progress in technology and algorithms throughout the past decade has transformed the field of protein design and engineering. Computational approaches have become well-engrained in the processes of tailoring proteins for various biotechnological applications. Many tools and methods are developed and upgraded each year to satisfy the increasing demands and challenges of protein engineering. To help protein engineers and bioinformaticians navigate this emerging wave of dedicated software, we have critically evaluated recent additions to the toolbox regarding their application for semi-rational and rational protein engineering. These newly developed tools identify and prioritize hotspots and analyze the effects of mutations for a variety of properties, comprising ligand binding, protein-protein and protein-nucleic acid interactions, and electrostatic potential. We also discuss notable progress to target elusive protein dynamics and associated properties like ligand-transport processes and allosteric communication. Finally, we discuss several challenges these tools face and provide our perspectives on the further development of readily applicable methods to guide protein engineering efforts.

libxtc: an efficient library for reading XTC-compressed MD trajectory data

Objective

The purpose of this work is to optimize the processing of molecular dynamics (MD) trajectory data obtained for large biomolecular systems. Two popular software tools were chosen as the reference: the tng and the xdrfile libraries. Current implementation of tng algorithms and library is either fast or storage efficient and xdrfile is storage efficient but slow. Our aim was to combine speed and storage efficiency through the xdrfile’s code modification.

Results

Here we present libxtc, a ready-to-use library for reading MD trajectory files in xtc format. The effectiveness of libxtc is demonstrated for several biomolecular systems of various sizes (~ 2 × 10⁴ to ~ 2 × 10⁵ atoms). In sequential mode, the performance of libxtc is up to 1.8 times higher and 1.4 times lower than xdrfile and tng, respectively. In parallel mode, libxtc is about 3 and 1.3 times faster than xdrfile and tng. At the same time, MD data stored in the xtc format require about 1.3 times less disk space than those treated with the tng algorithm in the fastest reading mode, which is a noticeable saving especially when the MD trajectory is long and the number of atoms is large—this applies to most biologically relevant systems.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13104-021-05536-5.

In vivo structural characterization of the SARS-CoV-2 RNA genome identifies host proteins vulnerable to repurposed drugs

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the cause of the ongoing coronavirus disease 2019 (COVID-19) pandemic. Understanding of the RNA virus and its interactions with host proteins could improve therapeutic interventions for COVID-19. By using icSHAPE, we determined the structural landscape of SARS-CoV-2 RNA in infected human cells and from refolded RNAs, as well as the regulatory untranslated regions of SARS-CoV-2 and six other coronaviruses. We validated several structural elements predicted in silico and discovered structural features that affect the translation and abundance of subgenomic viral RNAs in cells. The structural data informed a deep-learning tool to predict 42 host proteins that bind to SARS-CoV-2 RNA. Strikingly, antisense oligonucleotides targeting the structural elements and FDA-approved drugs inhibiting the SARS-CoV-2 RNA binding proteins dramatically reduced SARS-CoV-2 infection in cells derived from human liver and lung tumors. Our findings thus shed light on coronavirus and reveal multiple candidate therapeutics for COVID-19 treatment.

Structure and Dynamics of Ribonuclease A during Thermal Unfolding: The Failure of the Zimm Model

Disordered regions as found in intrinsically disordered proteins (IDP) or during protein folding define response time to stimuli and protein folding times. Neutron spin-echo spectroscopy is a powerful tool to directly access the collective motions of the unfolded chain to enlighten the physical origin of basic conformational relaxation. During the thermal unfolding of native ribonuclease A, we examine the structure and dynamics of the disordered state within a two-state transition model using polymer models, including internal friction, to describe the chain dynamics. The presence of four disulfide bonds alters the disordered configuration to a more compact configuration compared to a Gaussian chain that is defined by the additional links, as demonstrated by coarse-grained simulation. The dynamics of the disordered chain is described by Zimm dynamics with internal friction (ZIF) between neighboring amino acids. Relaxation times are dominated by mode-independent internal friction. Internal friction relaxation times show an Arrhenius-like behavior with an activation energy of 33 kJ/mol. The Zimm dynamics is dominated by internal friction and suggest that the characteristic motions correspond to overdamped elastic modes similar to the motions observed for folded proteins but within a pool of disordered configurations spanning the configurational space. For IDP, internal friction dominates while solvent friction and hydrodynamic interactions are smaller corrections.

Differential Stabilities of Mefloquine-Bound Human and Plasmodium falciparum Acyl-CoA-Binding Proteins

Toxic effects of pharmacological drugs restrict their robust application against human diseases. Although used as a drug in the combinatorial therapy to treat malaria, the use of mefloquine is not highly recommended because of its adverse effects in humans. Mefloquine inhibits the binding of acyl-CoAs to acyl-CoA-binding proteins of Plasmodium falciparum (PfACBPs) and human (hACBP). In this study, we have used molecular dynamics simulation and other computational approaches to investigate the differences of stabilities of mefloquine-PfACBP749 and mefloquine-hACBP complexes. The stability of mefloquine in the binding cavity of PfACBP749 is less than its stability in the binding pocket of hACBP. Although the essential tyrosine residues (tyrosine-30 and tyrosine-33 of PfACBP749 and tyrosine-29 and tyrosine-32 of hACBP) mediate the initial binding of mefloquine to the proteins by π-stacking interactions, additional temporally longer interactions between mefloquine and aspartate-22 and methionine-25 of hACBP result in stronger binding of mefloquine to hACBP. The higher fluctuation of mefloquine-binding residues of PfACBP749 contributes to the instability of mefloquine in the binding cavity of the protein. On the contrary, in the mefloquine-bound state, the stability of hACBP protein is less than the stability of PfACBP749. The helix-to-coil transition of the N-terminal hydrophobic region of hACBP has a destabilizing effect upon the protein's structure. This causes the induction of aggregation properties in the hACBP in the mefloquine-bound state. Taken together, we describe the mechanistic features that affect the differential dynamic stabilities of mefloquine-bound PfACBP749 and hACBP proteins.

AlloSigMA 2: paving the way to designing allosteric effectors and to exploring allosteric effects of mutations

The AlloSigMA 2 server provides an interactive platform for exploring the allosteric signaling caused by ligand binding and/or mutations, for analyzing the allosteric effects of mutations and for detecting potential cancer drivers and pathogenic nsSNPs. It can also be used for searching latent allosteric sites and for computationally designing allosteric effectors for these sites with required agonist/antagonist activity. The server is based on the implementation of the Structure-Based Statistical Mechanical Model of Allostery (SBSMMA), which allows one to evaluate the allosteric free energy as a result of the perturbation at per-residue resolution. The Allosteric Signaling Map (ASM) providing a comprehensive residue-by-residue allosteric control over the protein activity can be obtained for any structure of interest. The Allosteric Probing Map (APM), in turn, allows one to perform the fragment-based-like computational design experiment aimed at finding leads for potential allosteric effectors. The server can be instrumental in elucidating of allosteric mechanisms and actions of allosteric mutations, and in the efforts on design of new elements of allosteric control. The server is freely available at: http://allosigma.bii.a-star.edu.sg.

The Bio3D packages for structural bioinformatics

Bio3D is a family of R packages for the analysis of biomolecular sequence, structure, and dynamics. Major functionality includes biomolecular database searching and retrieval, sequence and structure conservation analysis, ensemble normal mode analysis, protein structure and correlation network analysis, principal component, and related multivariate analysis methods. Here, we review recent package developments, including a new underlying segregation into separate packages for distinct analysis, and introduce a new method for structure analysis named ensemble difference distance matrix analysis (eDDM). The eDDM approach calculates and compares atomic distance matrices across large sets of homologous atomic structures to help identify the residue wise determinants underlying specific functional processes. An eDDM workflow is detailed along with an example application to a large protein family. As a new member of the Bio3D family, the Bio3D-eddm package supports both experimental and theoretical simulation-generated structures, is integrated with other methods for dissecting sequence-structure-function relationships, and can be used in a highly automated and reproducible manner. Bio3D is distributed as an integrated set of platform independent open source R packages available from: http://thegrantlab.org/bio3d/.

Coagulation modifiers targeting SARS-CoV-2 main protease Mpro for COVID-19 treatment: an in silico approach

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection depends on viral polyprotein processing, catalysed by the main proteinase (Mpro). The solution of the SARS-CoV-2 Mpro structure allowed the investigation of potential inhibitors. This work aims to provide first evidences of the applicability of commercially approved drugs to treat coronavirus disease-19 (COVID-19). We screened 4,334 compounds to found potential inhibitors of SARS-CoV-2 replication using an in silico approach. Our results evidenced the potential use of coagulation modifiers in COVID-19 treatment due to the structural similarity of SARS-CoV-2 Mpro and human coagulation factors thrombin and Factor Xa. Further in vitro and in vivo analysis are needed to corroborate these results.

Targeted chemotherapy overcomes drug resistance in melanoma

In this study, Yue et al. describe a therapeutic strategy termed “targeted chemotherapy” that involves depleting PP2A or inhibiting it using a small molecule inhibitor, phendione, in drug-resistant melanoma. The authors show phendione induces DNA damage response without causing DNA breaks or inducing cellular dormancy, therefore blocking tumor growth of BRAF mutant and NRAS mutant melanomas.

The emergence of drug resistance is a major obstacle for the success of targeted therapy in melanoma. Additionally, conventional chemotherapy has not been effective as drug-resistant cells escape lethal DNA damage effects by inducing growth arrest commonly referred to as cellular dormancy. We present a therapeutic strategy termed “targeted chemotherapy” by depleting protein phosphatase 2A (PP2A) or its inhibition using a small molecule inhibitor (1,10-phenanthroline-5,6-dione [phendione]) in drug-resistant melanoma. Targeted chemotherapy induces the DNA damage response without causing DNA breaks or allowing cellular dormancy. Phendione treatment reduces tumor growth of BRAF^V600E-driven melanoma patient-derived xenografts (PDX) and diminishes growth of NRAS^Q61R-driven melanoma, a cancer with no effective therapy. Remarkably, phendione treatment inhibits the acquisition of resistance to BRAF inhibition in BRAF^V600E PDX highlighting its effectiveness in combating the advent of drug resistance.

Alchemical Grid Dock (AlGDock): Binding Free Energy Calculations between Flexible Ligands and Rigid Receptors

Alchemical Grid Dock (AlGDock) is open-source software designed to compute the binding potential of mean force-the binding free energy between a flexible ligand and a rigid receptor-for a small organic ligand and a biological macromolecule. Multiple BPMFs can be used to rigorously compute binding affinities between flexible partners. AlGDock uses replica exchange between thermodynamic states at different temperatures and receptor-ligand interaction strengths. Receptor-ligand interaction energies are represented by interpolating precomputed grids. Thermodynamic states are adaptively initialized and adjusted on-the-fly to maintain adequate replica exchange rates. In demonstrative calculations, when the bound ligand is treated as fully solvated, AlGDock estimates BPMFs with a precision within 4 kT in 65% and within 8 kT for 91% of systems. It correctly identifies the native binding pose in 83% of simulations. Performance is sometimes limited by subtle differences in the important configuration space of sampled and targeted thermodynamic states. © 2019 Wiley Periodicals, Inc.

Dynamics-function relationship in the catalytic domains of N-terminal acetyltransferases

N-terminal acetyltransferases (NATs) belong to the superfamily of acetyltransferases. They are enzymes catalysing the transfer of an acetyl group from acetyl coenzyme A to the N-terminus of polypeptide chains. N-terminal acetylation is one of the most common protein modifications. To date, not much is known on the molecular basis for the exclusive substrate specificity of NATs. All NATs share a common fold called GNAT. A characteristic of NATs is the β6β7 hairpin loop covering the active site and forming with the α1α2 loop a narrow tunnel surrounding the catalytic site in which cofactor and polypeptide meet and exchange an acetyl group. We investigated the dynamics-function relationships of all available structures of NATs covering the three domains of Life. Using an elastic network model and normal mode analysis, we found a common dynamics pattern conserved through the GNAT fold; a rigid V-shaped groove formed by the β4 and β5 strands and splitting the fold in two dynamical subdomains. Loops α1α2, β3β4 and β6β7 all show clear displacements in the low frequency normal modes. We characterized the mobility of the loops and show that even limited conformational changes of the loops along the low-frequency modes are able to significantly change the size and shape of the ligand binding sites. Based on the fact that these movements are present in most low-frequency modes, and common to all NATs, we suggest that the α1α2 and β6β7 loops may regulate ligand uptake and the release of the acetylated polypeptide.

Transition between protein-like and polymer-like dynamic behavior: Internal friction in unfolded apomyoglobin depends on denaturing conditions

Equilibrium dynamics of different folding intermediates and denatured states is strongly connected to the exploration of the conformational space on the nanosecond time scale and might have implications in understanding protein folding. For the first time, the same protein system apomyoglobin has been investigated using neutron spin-echo spectroscopy in different states: native-like, partially folded (molten globule) and completely unfolded, following two different unfolding paths: using acid or guanidinium chloride (GdmCl). While the internal dynamics of the native-like state can be understood using normal mode analysis based on high resolution structural information of myoglobin, for the unfolded and even for the molten globule states, models from polymer science are employed. The Zimm model accurately describes the slowly-relaxing, expanded GdmCl-denaturated state, ignoring the individuality of the different aminoacid side chain. The dynamics of the acid unfolded and molten globule state are similar in the framework of the Zimm model with internal friction, where the chains still interact and hinder each other: the first Zimm relaxation time is as large as the internal friction time. Transient formation of secondary structure elements in the acid unfolded and presence of α-helices in the molten globule state lead to internal friction to a similar extent.

Mefloquine binding to human acyl-CoA binding protein leads to redox stress-mediated apoptotic death of human neuroblastoma cells

Malaria is an infectious disease that is caused by different species of Plasmodium. Several antimalarial drugs are used to counter the spread and infectivity of Plasmodium species. However, humans are also vulnerable to many of the antimalarial drugs, including the quinoline-based drugs. In particular, the antimalarial mefloquine has been reported to show adverse neuropsychiatric effects in humans. Though mefloquine is known to be neurotoxic, the molecular mechanisms associated with this phenomenon are still obscure. In this study, we show that mefloquine binds to and inactivates the human acyl-CoA binding protein (hACBP), potentially inducing redox stress in human neuroblastoma cells (IMR-32). Mefloquine occupies the acyl-CoA binding pocket of hACBP by interacting with several of the critical acyl-CoA binding amino acids. This leads to the competitive inhibition of acyl-CoA(s) binding to hACBP and to the accumulation of lipid droplets inside the IMR-32 cells. The accumulation of cytosolic lipid globules and oxidative stress finally correlates with the apoptotic death of cells. Taken together, our study deciphers a mechanistic detail of how mefloquine leads to the death of human cells by perturbing the activity of hACBP and lipid homeostasis.

T54R mutation destabilizes the dimer of superoxide dismutase 1T54R by inducing steric clashes at the dimer interface

Mutations cause abnormalities in protein structure, function and oligomerization. Different mutations in the superoxide dismutase 1 (SOD1) protein cause its misfolding, loss of dimerization and aggravate its aggregation in the amyotrophic lateral sclerosis disease. In this study, we report the mechanistic details of how a threonine-to-arginine mutation at the 54^th position (T54R) of SOD1 results in destabilization of the dimer interface of SOD1^T54R. Using computational and experimental methods, we show that the T54R mutation increases fluctuation of the mutation-harboring loop (R54-loop) of SOD1^T54R. Fluctuation of this loop causes steric clashes that involve arginine-54 (R54) and other residues of SOD1^T54R, resulting in loss of inter-subunit contacts at the dimer interface. Since the T54 residue-containing loop is necessary for the dimerization of wild-type SOD1, fluctuation of the R54-loop, steric clashes involving R54 and loss of inter-subunit contacts give rise to the loss of SOD1^T54R dimer stability. This correlates to energetically unfavorable tethering of the monomers of SOD1^T54R. The outcome is gradual splitting of SOD1^T54R dimers into monomers, thereby exposing the previously buried hydrophobic interface residues to the aqueous environment. This event finally leads to aggregation of SOD1^T54R. T54R mutation has no effect in altering the relative positions of copper and zinc ion binding residues of SOD1^T54R. The native SOD1 structure is stable, and there is no destabilizing effect at its dimer interface. Overall, our study reveals the intricate mechanism of T54R mutation-associated destabilization of the dimer of the SOD1^T54R protein.

T54R mutation destabilizes the dimer of SOD1^T54R.

Localised contacts lead to nanosecond hinge motions in dimeric bovine serum albumin

Domain motions in proteins are crucial for biological function. In the present manuscript, we present a neutron spin-echo spectroscopy (NSE) study of native bovine serum albumin (BSA) in solution. NSE allows to probe both global and internal dynamics of the BSA monomer and dimer equilibrium that is formed in solution. Using a model independent approach, we were able to identify an internal dynamic process in BSA that is visible in addition to global rigid-body diffusion of the BSA monomer and dimer mixture. The observed internal protein motion is characterised by a relaxation time of 43 ns. The overdamped Brownian oscillator was considered as an alternative analytical theory that was able to describe the internal process as first-order approximation. More detailed information on the physical nature of the internal protein motion was extracted from the q-dependent internal diffusion coefficients ΔDeff(q) that were detected by NSE in addition to global rigid-body translational and rotational diffusion. The ΔDeff(q) were interpreted using normal mode analysis based on the available crystal structures of the BSA monomer and dimer as structural test models. Normal mode analysis demonstrates that the observed internal dynamic process can be attributed to bending motion of the BSA dimer. The native BSA monomer does not show any internal dynamics on the time- and length-scales probed by NSE. An intermolecular disulphide bridge or a direct structural contact between the BSA monomers forms a localised link acting as a molecular hinge in the BSA dimer. The effect of that hinge on the observed motion of BSA in the used dimeric structural model is discussed in terms of normal modes in a molecular picture.

RapidRMSD: rapid determination of RMSDs corresponding to motions of flexible molecules

Motivation

The root mean square deviation (RMSD) is one of the most used similarity criteria in structural biology and bioinformatics. Standard computation of the RMSD has a linear complexity with respect to the number of atoms in a molecule, making RMSD calculations time-consuming for the large-scale modeling applications, such as assessment of molecular docking predictions or clustering of spatially proximate molecular conformations. Previously, we introduced the RigidRMSD algorithm to compute the RMSD corresponding to the rigid-body motion of a molecule. In this study, we go beyond the limits of the rigid-body approximation by taking into account conformational flexibility of the molecule. We model the flexibility with a reduced set of collective motions computed with e.g. normal modes or principal component analysis.

Results

The initialization of our algorithm is linear in the number of atoms and all the subsequent evaluations of RMSD values between flexible molecular conformations depend only on the number of collective motions that are selected to model the flexibility. Therefore, our algorithm is much faster compared to the standard RMSD computation for large-scale modeling applications. We demonstrate the efficiency of our method on several clustering examples, including clustering of flexible docking results and molecular dynamics (MD) trajectories. We also demonstrate how to use the presented formalism to generate pseudo-random constant-RMSD structural molecular ensembles and how to use these in cross-docking.

Availability and implementation

We provide the algorithm written in C++ as the open-source RapidRMSD library governed by the BSD-compatible license, which is available at http://team.inria.fr/nano-d/software/RapidRMSD/. The constant-RMSD structural ensemble application and clustering of MD trajectories is available at http://team.inria.fr/nano-d/software/nolb-normal-modes/.

Supplementary information

Supplementary data are available at Bioinformatics online.

Normal Mode Analysis as a Routine Part of a Structural Investigation

Normal mode analysis (NMA) is a technique that can be used to describe the flexible states accessible to a protein about an equilibrium position. These states have been shown repeatedly to have functional significance. NMA is probably the least computationally expensive method for studying the dynamics of macromolecules, and advances in computer technology and algorithms for calculating normal modes over the last 20 years have made it nearly trivial for all but the largest systems. Despite this, it is still uncommon for NMA to be used as a component of the analysis of a structural study. In this review, we will describe NMA, outline its advantages and limitations, explain what can and cannot be learned from it, and address some criticisms and concerns that have been voiced about it. We will then review the most commonly used techniques for reducing the computational cost of this method and identify the web services making use of these methods. We will illustrate several of their possible uses with recent examples from the literature. We conclude by recommending that NMA become one of the standard tools employed in any structural study.

Dynamics of proteins in solution

The dynamics of proteins in solution includes a variety of processes, such as backbone and side-chain fluctuations, interdomain motions, as well as global rotational and translational (i.e. center of mass) diffusion. Since protein dynamics is related to protein function and essential transport processes, a detailed mechanistic understanding and monitoring of protein dynamics in solution is highly desirable. The hierarchical character of protein dynamics requires experimental tools addressing a broad range of time- and length scales. We discuss how different techniques contribute to a comprehensive picture of protein dynamics, and focus in particular on results from neutron spectroscopy. We outline the underlying principles and review available instrumentation as well as related analysis frameworks.

Characterization of Lipid Binding Properties of Plasmodium falciparum Acyl-Coenzyme A Binding Proteins and Their Competitive Inhibition by Mefloquine

Malaria remains a worldwide concern in terms of morbidity and mortality. Limited understanding of the Plasmodium proteome makes it challenging to control malaria. Understanding of the expression and functions of different Plasmodium proteins will help in knowing this organism's virulence properties, besides facilitating the drug development process. In this study, we characterize the lipid binding and biophysical properties of the putative Plasmodium falciparum acyl-CoA binding proteins (PfACBPs), which may have intriguing functions in different stages of P. falciparum life cycle. While the PfACBPs can bind to long-chain fatty acyl-CoAs with high affinity, their affinity for short-chain fatty acyl-CoAs is weak. Base-stacking, electrostatic, and hydrophobic interactions between the aromatic rings, charged groups or residues, and hydrophobic chains or residues are responsible for acyl-CoA binding to PfACBPs. PfACBPs can also bind to phospholipids. PfACBPs cannot bind to the fatty acids and unphosphorylated fatty acid esters. PfACBPs are globular-helical proteins that contain a conserved acyl-CoA binding region. They exist in folded or unfolded conformations without attaining any intermediate state. In a systematic high-throughput in silico screening, mefloquine is identified as a potential ligand of PfACBPs. Binding affinities of mefloquine are much higher than those of fatty acyl-CoAs for all PfACBPs. Mefloquine binds to the acyl-CoA binding pocket of PfACBPs, thereby engaging many of the critical residues. Thus, mefloquine acts as a competitive inhibitor against fatty acyl-CoA binding to PfACBPs, leading to the prevention of P. falciparum growth and proliferation. Taken together, our study characterizes the functions of annotated PfACBPs and highlights the mechanistic details of their inactivation by mefloquine.

Stochastic modeling of macromolecules in solution. I. Relaxation processes

A framework for the stochastic description of relaxation processes in flexible macromolecules, including dissipative effects, is introduced from an atomistic point of view. Projection-operator techniques are employed to obtain multidimensional Fokker-Planck operators governing the relaxation of internal coordinates and global degrees of freedom and depending upon parameters fully recoverable from classic force fields (energetics) and continuum models (friction tensors). A hierarchy of approaches of different complexity is proposed in this unified context, aimed primarily at the interpretation of magnetic resonance relaxation experiments. In particular, a model based on a harmonic internal Hamiltonian is discussed as a test case.

Stochastic modeling of macromolecules in solution. II. Spectral densities

In Paper I [Polimeno et al., J. Chem. Phys. 150, 184107 (2019)], we proposed a general approach for interpreting relaxation properties of a macromolecule in solution, derived from an atomistic description. A simple scheme (the semiflexible Brownian, SFB, model) has been defined for the case of limited internal flexibility, but retaining full coupling with external degrees of freedom, inclusion of all of the momenta, and dissipation. Here we discuss the application of the SFB model to the practical evaluation of orientation spectral densities, based on two complementary computational treatments.

Toward Comprehensive Allosteric Control over Protein Activity

Universality of allosteric signaling in proteins, molecular machines, and receptors complemented by the great advantages of prospected allosteric drugs in the highly specific, non-competitive, and modulatory nature of their actions calls for deeper theoretical understanding of allosteric communication. We present a computational model that makes it possible to tackle the problem of modulating the energetics of protein allosteric communication. In the context of the energy landscape paradigm, allosteric signaling is always a result of perturbations, such as ligand binding, mutations, and intermolecular interactions. The calculation of local partition functions in the protein harmonic model with perturbations allows us to evaluate the energetics of allosteric communication at the single-residue level. In this framework, Allosteric Signaling Maps are proposed as a tool to exhaustively describe allosteric communication in the protein, to tune already existing signaling, and to design new elements of regulation for taking the protein activity under allosteric control.

The central region of CNOT1 and CNOT9 stimulates deadenylation by the Ccr4-Not nuclease module

Regulated degradation of cytoplasmic mRNA is important for the accurate execution of gene expression programmes in eukaryotic cells. A key step in this process is the shortening and removal of the mRNA poly(A) tail, which can be achieved by the recruitment of the multi-subunit Ccr4-Not nuclease complex via sequence-specific RNA-binding proteins or the microRNA machinery. The Ccr4-Not complex contains several modules that are attached to its large subunit CNOT1. Modules include the nuclease module, which associates with the MIF4G domain of CNOT1 and contains the catalytic subunits Caf1 and Ccr4, as well as the module containing the non-catalytic CNOT9 subunit, which binds to the DUF3819 domain of CNOT1. To understand the contributions of the individual modules to the activity of the complex, we have started to reconstitute sub-complexes of the human Ccr4-Not complex containing one or several functional modules. Here, we report the reconstitution of a pentameric complex including a BTG2-Caf1-Ccr4 nuclease module, CNOT9 and the central region of CNOT1 encompassing the MIF4G and DUF3819 domains. By comparing the biochemical activities of the pentameric complex and the nuclease module, we conclude that the CNOT1-CNOT9 components stimulate deadenylation by the nuclease module. In addition, we show that a pentameric complex containing the melanoma-associated CNOT9 P131L variant is able to support deadenylation similar to a complex containing the wild-type CNOT9 protein.

A model for hydrophobic protrusions on peripheral membrane proteins

With remarkable spatial and temporal specificities, peripheral membrane proteins bind to biological membranes. They do this without compromising solubility of the protein, and their binding sites are not easily distinguished. Prototypical peripheral membrane binding sites display a combination of patches of basic and hydrophobic amino acids that are also frequently present on other protein surfaces. The purpose of this contribution is to identify simple but essential components for membrane binding, through structural criteria that distinguish exposed hydrophobes at membrane binding sites from those that are frequently found on any protein surface. We formulate the concepts of protruding hydrophobes and co-insertability and have analysed more than 300 families of proteins that are classified as peripheral membrane binders. We find that this structural motif strongly discriminates the surfaces of membrane-binding and non-binding proteins. Our model constitutes a novel formulation of a structural pattern for membrane recognition and emphasizes the importance of subtle structural properties of hydrophobic membrane binding sites.

Peripheral membrane proteins bind cellular membranes transiently, and are otherwise soluble proteins. As the interaction between proteins and membranes happens at cellular interfaces they are naturally involved in important interfacial processes such as recognition, signaling and trafficking. Commonly their binding sites are also soluble, and their binding mechanisms poorly understood. This complicates the elaboration of conceptual and quantitative models for peripheral membrane binding and makes binding site prediction difficult. It is therefore of great interest to discover traits that are common between these binding sites and that distinguishes them from other protein surfaces. In this work we identify simple and general structural features that facilitate membrane recognition by soluble proteins. We show that these motifs are highly over-represented on peripheral membrane proteins.