Pharmacokinetics Profiler (PhaKinPro): Model Development, Validation, and Implementation as a Web Tool for Triaging Compounds with Undesired Pharmacokinetics Profiles

Computational models that predict pharmacokinetic properties are critical to deprioritize drug candidates that emerge as hits in high-throughput screening campaigns. We collected, curated, and integrated a database of compounds tested in 12 major end points comprising over 10,000 unique molecules. We then employed these data to build and validate binary quantitative structure-activity relationship (QSAR) models. All trained models achieved a correct classification rate above 0.60 and a positive predictive value above 0.50. To illustrate their utility in drug discovery, we used these models to predict the pharmacokinetic properties for drugs in the NCATS Inxight Drugs database. In addition, we employed the developed models to predict the pharmacokinetic properties of all compounds in the DrugBank. All models described in this paper have been integrated and made publicly available via the PhaKinPro Web-portal that can be accessed at https://phakinpro.mml.unc.edu/.

BigBind: Learning from Nonstructural Data for Structure-Based Virtual Screening

Deep learning methods that predict protein-ligand binding have recently been used for structure-based virtual screening. Many such models have been trained using protein-ligand complexes with known crystal structures and activities from the PDBBind data set. However, because PDBbind only includes 20K complexes, models typically fail to generalize to new targets, and model performance is on par with models trained with only ligand information. Conversely, the ChEMBL database contains a wealth of chemical activity information but includes no information about binding poses. We introduce BigBind, a data set that maps ChEMBL activity data to proteins from the CrossDocked data set. BigBind comprises 583 K ligand activities and includes 3D structures of the protein binding pockets. Additionally, we augmented the data by adding an equal number of putative inactives for each target. Using this data, we developed Banana (basic neural network for binding affinity), a neural network-based model to classify active from inactive compounds, defined by a 10 μM cutoff. Our model achieved an AUC of 0.72 on BigBind's test set, while a ligand-only model achieved an AUC of 0.59. Furthermore, Banana achieved competitive performance on the LIT-PCBA benchmark (median EF1% 1.81) while running 16,000 times faster than molecular docking with Gnina. We suggest that Banana, as well as other models trained on this data set, will significantly improve the outcomes of prospective virtual screening tasks.

Discovery of a cell-active chikungunya virus nsP2 protease inhibitor using a covalent fragment-based screening approach

Chikungunya virus (CHIKV) is a mosquito-borne alphavirus that has been responsible for numerous large-scale outbreaks in the last twenty years. Currently, there are no FDA-approved therapeutics for any alphavirus infection. CHIKV non-structural protein 2 (nsP2), which contains a cysteine protease domain, is essential for viral replication, making it an attractive target for a drug discovery campaign. Here, we optimized a CHIKV nsP2 protease (nsP2pro) biochemical assay for the screening of a 6,120-compound cysteine-directed covalent fragment library. Using a 50% inhibition threshold, we identified 153 hits (2.5% hit rate). In dose-response follow up, RA-0002034, a covalent fragment that contains a vinyl sulfone warhead, inhibited CHIKV nsP2pro with an IC 50 of 58 ± 17 nM, and further analysis with time-dependent inhibition studies yielded a k inact /K I of 6.4 × 10 3 M -1 s -1 . LC-MS/MS analysis determined that RA-0002034 covalently modified the catalytic cysteine in a site-specific manner. Additionally, RA-0002034 showed no significant off-target reactivity against a panel of cysteine proteases. In addition to the potent biochemical inhibition of CHIKV nsP2pro activity and exceptional selectivity, RA-0002034 was tested in cellular models of alphavirus infection and effectively inhibited viral replication of both CHIKV and related alphaviruses. This study highlights the discovery and characterization of the chemical probe RA-0002034 as a promising hit compound from covalent fragment-based screening for future development toward a CHIKV or pan-alphavirus therapeutic.

Significance Statement

Chikungunya virus is one of the most prominent and widespread alphaviruses and has caused explosive outbreaks of arthritic disease. Currently, there are no FDA-approved drugs to treat disease caused by chikungunya virus or any other alphavirus-caused infection. Here, we report the discovery of a covalent small molecule inhibitor of chikungunya virus nsP2 protease activity and viral replication of four diverse alphaviruses. This finding highlights the utility of covalent fragment screening for inhibitor discovery and represents a starting point towards the development of alphavirus therapeutics targeting nsP2 protease.

An Improved Metric and Benchmark for Assessing the Performance of Virtual Screening Models

Structure-based virtual screening (SBVS) is a key workflow in computational drug discovery. SBVS models are assessed by measuring the enrichment of known active molecules over decoys in retrospective screens. However, the standard formula for enrichment cannot estimate model performance on very large libraries. Additionally, current screening benchmarks cannot easily be used with machine learning (ML) models due to data leakage. We propose an improved formula for calculating VS enrichment and introduce the BayesBind benchmarking set composed of protein targets that are structurally dissimilar to those in the BigBind training set. We assess current models on this benchmark and find that none perform appreciably better than a KNN baseline. We publicly release the BayesBind benchmark at https://github.com/molecularmodelinglab/bigbind.

Utilizing Low-Dimensional Molecular Embeddings for Rapid Chemical Similarity Search

Nearest neighbor-based similarity searching is a common task in chemistry, with notable use cases in drug discovery. Yet, some of the most commonly used approaches for this task still leverage a brute-force approach. In practice this can be computationally costly and overly time-consuming, due in part to the sheer size of modern chemical databases. Previous computational advancements for this task have generally relied on improvements to hardware or dataset-specific tricks that lack generalizability. Approaches that leverage lower-complexity searching algorithms remain relatively underexplored. However, many of these algorithms are approximate solutions and/or struggle with typical high-dimensional chemical embeddings. Here we evaluate whether a combination of low-dimensional chemical embeddings and a k-d tree data structure can achieve fast nearest neighbor queries while maintaining performance on standard chemical similarity search benchmarks. We examine different dimensionality reductions of standard chemical embeddings as well as a learned, structurally-aware embedding-SmallSA-for this task. With this framework, searches on over one billion chemicals execute in less than a second on a single CPU core, five orders of magnitude faster than the brute-force approach. We also demonstrate that SmallSA achieves competitive performance on chemical similarity benchmarks.

Synthesis of 5-Benzylamino and 5-Alkylamino-Substituted Pyrimido[4,5-c]quinoline Derivatives as CSNK2A Inhibitors with Antiviral Activity

A series of 5-benzylamine-substituted pyrimido[4,5-c]quinoline derivatives of the CSNK2A chemical probe SGC-CK2-2 were synthesized with the goal of improving kinase inhibitor cellular potency and antiviral phenotypic activity while maintaining aqueous solubility. Among the range of analogs, those bearing electron-withdrawing (4c and 4g) or donating (4f) substituents on the benzyl ring as well as introduction of non-aromatic groups such as the cyclohexylmethyl (4t) were shown to maintain CSNK2A activity. The CSNK2A activity was also retained with N-methylation of SGC-CK2-2, but α-methyl substitution of the benzyl substituent led to a 10-fold reduction in potency. CSNK2A inhibition potency was restored with indene-based compound 4af, with activity residing in the S-enantiomer (4ag). Analogs with the highest CSNK2A potency showed good activity for inhibition of Mouse Hepatitis Virus (MHV) replication. Conformational analysis indicated that analogs with the best CSNK2A inhibition (4t, 4ac, and 4af) exhibited smaller differences between their ground state conformation and their predicted binding pose. Analogs with reduced activity (4ad, 4ae, and 4ai) required more substantial conformational changes from their ground state within the CSNK2A protein pocket.

HIt Discovery using docking ENriched by GEnerative Modeling (HIDDEN GEM): A novel computational workflow for accelerated virtual screening of ultra-large chemical libraries

Recent rapid expansion of make-on-demand, purchasable, chemical libraries comprising dozens of billions or even trillions of molecules has challenged the efficient application of traditional structure-based virtual screening methods that rely on molecular docking. We present a novel computational methodology termed HIDDEN GEM (HIt Discovery using Docking ENriched by GEnerative Modeling) that greatly accelerates virtual screening. This workflow uniquely integrates machine learning, generative chemistry, massive chemical similarity searching and molecular docking of small, selected libraries in the beginning and the end of the workflow. For each target, HIDDEN GEM nominates a small number of top-scoring virtual hits prioritized from ultra-large chemical libraries. We have benchmarked HIDDEN GEM by conducting virtual screening campaigns for 16 diverse protein targets using Enamine REAL Space library comprising 37 billion molecules. We show that HIDDEN GEM yields the highest enrichment factors as compared to state of the art accelerated virtual screening methods, while requiring the least computational resources. HIDDEN GEM can be executed with any docking software and employed by users with limited computational resources.

Accurate ligand-protein docking in CASP15 using the ClusPro LigTBM server

In the ligand prediction category of CASP15, the challenge was to predict the positions and conformations of small molecules binding to proteins that were provided as amino acid sequences or as models generated by the AlphaFold2 program. For most targets, we used our template-based ligand docking program ClusPro ligTBM, also implemented as a public server available at https://ligtbm.cluspro.org/. Since many targets had multiple chains and a number of ligands, several templates, and some manual interventions were required. In a few cases, no templates were found, and we had to use direct docking using the Glide program. Nevertheless, ligTBM was shown to be a very useful tool, and by any ranking criteria, our group was ranked among the top five best-performing teams. In fact, all the best groups used template-based docking methods. Thus, it appears that the AlphaFold2-generated models, despite the high accuracy of the predicted backbone, have local differences from the x-ray structure that make the use of direct docking methods more challenging. The results of CASP15 confirm that this limitation can be frequently overcome by homology-based docking.

Mixed, nonclassical behavior in a classic allosteric protein

Allostery is a major driver of biological processes requiring coordination. Thus, it is one of the most fundamental and remarkable phenomena in nature, and there is motivation to understand and manipulate it to a multitude of ends. Today, it is often described in terms of two phenomenological models proposed more than a half-century ago involving only T(tense) or R(relaxed) conformations. Here, methyl-based NMR provides extensive detail on a dynamic T to R switch in the classical dimeric allosteric protein, yeast chorismate mutase (CM), that occurs in the absence of substrate, but only with the activator bound. Switching of individual subunits is uncoupled based on direct observation of mixed TR states in the dimer. This unique finding excludes both classic models and solves the paradox of a coexisting hyperbolic binding curve and highly skewed substrate-free T-R equilibrium. Surprisingly, structures of the activator-bound and effector-free forms of CM appear the same by NMR, providing another example of the need to account for dynamic ensembles. The apo enzyme, which has a sigmoidal activity profile, is shown to switch, not to R, but to a related high-energy state. Thus, the conformational repertoire of CM does not just change as a matter of degree depending on the allosteric input, be it effector and/or substrate. Rather, the allosteric model appears to completely change in different contexts, which is only consistent with modern ensemble-based frameworks.

PLANTAIN: Diffusion-inspired Pose Score Minimization for Fast and Accurate Molecular Docking

Molecular docking aims to predict the 3D pose of a small molecule in a protein binding site. Traditional docking methods predict ligand poses by minimizing a physics-inspired scoring function. Recently, a diffusion model has been proposed that iteratively refines a ligand pose. We combine these two approaches by training a pose scoring function in a diffusion-inspired manner. In our method, PLANTAIN, a neural network is used to develop a very fast pose scoring function. We parameterize a simple scoring function on the fly and use L-BFGS minimization to optimize an initially random ligand pose. Using rigorous benchmarking practices, we demonstrate that our method achieves state-of-the-art performance while running ten times faster than the next-best method. We release PLANTAIN publicly and hope that it improves the utility of virtual screening workflows.

Tyrosinase-Catalyzed Peptide Macrocyclization for mRNA Display

mRNA display of macrocyclic peptides has proven itself to be a powerful technique to discover high-affinity ligands for a protein target. However, only a limited number of cyclization chemistries are known to be compatible with mRNA display. Tyrosinase is a copper-dependent oxidase that oxidizes tyrosine phenol to an electrophilic o-quinone, which is readily attacked by cysteine thiol. Here we show that peptides containing tyrosine and cysteine are rapidly cyclized upon tyrosinase treatment. Characterization of the cyclization reveals it to be widely applicable to multiple macrocycle sizes and scaffolds. We combine tyrosinase-mediated cyclization with mRNA display to discover new macrocyclic ligands targeting melanoma-associated antigen A4 (MAGE-A4). These macrocycles potently inhibit the MAGE-A4 binding axis with nanomolar IC₅₀ values. Importantly, macrocyclic ligands show clear advantage over noncyclized analogues with ∼40-fold or greater decrease in IC₅₀ values.

Conserved coronavirus proteins as targets of broad-spectrum antivirals

Coronaviruses are a class of single-stranded, positive-sense RNA viruses that have caused three major outbreaks over the past two decades: Middle East respiratory syndrome–related coronavirus (MERS-CoV), severe acute respiratory syndrome coronavirus (SARS-CoV), and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). All outbreaks have been associated with significant morbidity and mortality. In this study, we have identified and explored conserved binding sites in the key coronavirus proteins for the development of broad-spectrum direct acting anti-coronaviral compounds and validated the significance of this conservation for drug discovery with existing experimental data. We have identified four coronaviral proteins with highly conserved binding site sequence and 3D structure similarity: PL^pro, M^pro, nsp10-nsp16 complex(methyltransferase), and nsp15 endoribonuclease. We have compiled all available experimental data for known antiviral medications inhibiting these targets and identified compounds active against multiple coronaviruses. The identified compounds representing potential broad-spectrum antivirals include: GC376, which is active against six viral M^pro (out of six tested, as described in research literature); mycophenolic acid, which is active against four viral PL^pro (out of four); and emetine, which is active against four viral RdRp (out of four). The approach described in this study for coronaviruses, which combines the assessment of sequence and structure conservation across a viral family with the analysis of accessible chemical structure – antiviral activity data, can be explored for the development of broad-spectrum drugs for multiple viral families.

Mapping co-regulatory interactions among ligand-binding sites in ryanodine receptor 1

Ryanodine receptor 1 (RyR1) is an intracellular calcium ion (Ca²⁺ ) release channel required for skeletal muscle contraction. Although cryo-electron microscopy identified binding sites of three coactivators Ca²⁺ , ATP, and caffeine (CFF), the mechanism of co-regulation and synergy of these activators is unknown. Here, we report allosteric connections among the three ligand-binding sites and pore region in (i) Ca²⁺ bound-closed, (ii) ATP/CFF bound-closed, (iii) Ca²⁺ /ATP/CFF bound-closed, and (iv) Ca²⁺ /ATP/CFF bound-open RyR1 states. We identified two dominant networks of interactions that mediate communication between the Ca²⁺ -binding site and pore region in Ca²⁺ bound-closed state, which partially overlapped with the pore communications in ATP/CFF bound-closed RyR1 state. In Ca²⁺ /ATP/CFF bound-closed and -open RyR1 states, co-regulatory interactions were analogous to communications in the Ca²⁺ bound-closed and ATP/CFF bound-closed states. Both ATP- and CFF-binding sites mediate communication between the Ca²⁺ -binding site and the pore region in Ca²⁺ /ATP/CFF bound-open RyR1 structure. We conclude that Ca²⁺ , ATP, and CFF propagate their effects to the pore region through a network of overlapping interactions that mediate allosteric control and molecular synergy in channel regulation.

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.

Learning from history: do not flatten the curve of antiviral research!

Here, we explore the dynamics of the response of the scientific community to several epidemics, including Coronavirus Disease 2019 (COVID-19), as assessed by the numbers of clinical trials, publications, and level of research funding over time. All six prior epidemics studied [bird flu, severe acute respiratory syndrome (SARS), swine flu, Middle East Respiratory Syndrome (MERS), Ebola, and Zika] were characterized by an initial spike of research response that flattened shortly thereafter. Unfortunately, no antiviral medications have been discovered to date as treatments for any of these diseases. By contrast, the HIV/AIDS pandemic has garnered consistent research investment since it began and resulted in drugs being developed within 7 years of its start date, with many more to follow. We argue that, to develop effective treatments for COVID-19 and be prepared for future epidemics, long-term, consistent investment in antiviral research is needed.

Ligand-induced disorder-to-order transitions characterized by structural proteomics and molecular dynamics simulations

For disordered proteins, ligand binding can be a critical event that changes their structural dynamics. The ability to characterize such changes would facilitate the development of drugs designed to stabilize disordered proteins, whose mis-folding is important for a number of pathologies, including neurodegenerative diseases such as Parkinson's and Alzheimer's diseases. In this study, we used hydrogen/deuterium exchange, differential crosslinking, differential surface modification, and molecular dynamics (MD) simulations to characterize the structural changes in disordered proteins that result from ligand binding. We show here that both an ATP-independent protein chaperone, Spy L32P, and the FK506 binding domain of a prolyl isomerase, FKBP-25 F145A/I223P, are disordered, yet exhibit structures that are distinct from chemically denatured unfolded states in solution, and that they undergo transitions to a more structured state upon ligand binding. These systems may serve as models for the characterization of ligand-induced disorder-to-order transitions in proteins using structural proteomics approaches. SIGNIFICANCE: In this study, we used hydrogen/deuterium exchange, differential crosslinking, differential surface modification, and molecular-dynamics simulations to characterize the structural changes in disordered proteins that result from ligand binding. The protein-ligand systems studied here (the ATP-independent protein chaperone, Spy L32P, and the FK506 binding domain of a prolyl isomerase, FKBP-25 F145A/I223P) may serve as models for understanding ligand-induced disorder-to-order transitions in proteins. Additionally, the structural proteomic techniques demonstrated here are shown to be effective tools for the characterization of disorder-to-order transitions and can be used to facilitate study of other systems in which this class of structural transition can be used for modulating major pathological features of disease, such as the abnormal protein aggregation that occurs with Parkinson's disease and Alzheimer's disease.

Identification of lysine methylation in the core GTPase domain by GoMADScan

RAS is the founding member of a superfamily of GTPases and regulates signaling pathways involved in cellular growth control. While recent studies have shown that the activation state of RAS can be controlled by lysine ubiquitylation and acetylation, the existence of lysine methylation of the RAS superfamily GTPases remains unexplored. In contrast to acetylation, methylation does not alter the side chain charge and it has been challenging to deduce its impact on protein structure by conventional amino acid substitutions. Herein, we investigate lysine methylation on RAS and RAS-related GTPases. We developed GoMADScan (Go language-based Modification Associated Database Scanner), a new user-friendly application that scans and extracts posttranslationally modified peptides from databases. The GoMADScan search on PhosphoSitePlus databases identified methylation of conserved lysine residues in the core GTPase domain of RAS superfamily GTPases, including residues corresponding to RAS Lys-5, Lys-16, and Lys-117. To follow up on these observations, we immunoprecipitated endogenous RAS from HEK293T cells, conducted mass spectrometric analysis and found that RAS residues, Lys-5 and Lys-147, undergo dimethylation and monomethylation, respectively. Since mutations of Lys-5 have been found in cancers and RASopathies, we set up molecular dynamics (MD) simulations to assess the putative impact of Lys-5 dimethylation on RAS structure. Results from our MD analyses predict that dimethylation of Lys-5 does not significantly alter RAS conformation, suggesting that Lys-5 methylation may alter existing protein interactions or create a docking site to foster new interactions. Taken together, our findings uncover the existence of lysine methylation as a novel posttranslational modification associated with RAS and the RAS superfamily GTPases, and putative impact of Lys-5 dimethylation on RAS structure.

Inter-Active Site Communication Mediated by the Dimer Interface β-Sheet in the Half-the-Sites Enzyme, Thymidylate Synthase

Thymidylate synthase (TS) is a dimeric enzyme conserved in all life forms that exhibits the allosteric feature of half-the-sites activity. Neither the reason for nor the mechanism of this phenomenon is understood. We used a combined nuclear magnetic resonance (NMR) and molecular dynamics approach to study a stable intermediate preceding hydride transfer, which is the rate-limiting and half-the-sites step. In NMR titrations with ligands leading to this intermediate, we measured chemical shifts of the apoenzyme (lig₀), the saturated holoenzyme (lig₂), and the typically elusive singly bound (lig₁) states. Approximately 40 amides showed quartet patterns providing direct NMR evidence of coupling between the active site and probes >30 Å away in the distal subunit. Quartet peak patterns have symmetrical character, indicating reciprocity in communicating the first and second binding events to the distal protomer. Quartets include key catalytic residues and map to the dimer interface β-sheet, which also represents the shortest path between the two active sites. Simulations corroborate the coupling observed in solution in that there is excellent overlap between quartet residues and main-chain atoms having intersubunit cross-correlated motions. Simulations identify five hot spot residues, three of which lie at the kink in the unique β-bulge abutting the active sites on either end of the sheet. Interstrand cross-correlated motions become more organized and pronounced as the enzyme progresses from lig₀ to lig₁ and ultimately lig₂. Coupling in the apparently symmetrical complex has implications for half-the-sites reactivity and potentially resolves the paradox of inequivalent TS active sites despite the vast majority of X-ray structures appearing to be symmetrical.

Uncovered Dynamic Coupling Resolves the Ambiguous Mechanism of Phenylalanine Hydroxylase Oxygen Binding

Phenylalanine hydroxylase (PAH) is an iron enzyme catalyzing the oxidation of l-Phe to l-Tyr during phenylalanine catabolism. Dysfunction of PAH leads to the debilitating condition phenylketonuria (PKU), which prompted research into the structure and function of PAH over the last 50 years. Despite intensive study, there is no consensus on the atomistic details of the mechanism of O₂ binding and splitting by wild-type (WT) PAH and how it varies with PKU-inducing mutations, Arg158Gln and Glu280Lys. We studied structures involved in a proposed mechanism for the WT and mutants using extensive mixed quantum-classical molecular dynamics simulations. Simulations reveal a previously unobserved dynamic coupling between the active site and the mutation sites, suggesting how they can affect the catalytic performance of PAH. Furthermore, the effect of the coupling on the PAH structure agrees with and expands our understanding of the experimentally observed differences in activity between the WT and mutants.

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.

High-speed atomic force microscopy reveals structural dynamics of α-synuclein monomers and dimers

α-Synuclein (α-syn) is the major component of the intraneuronal inclusions called Lewy bodies, which are the pathological hallmark of Parkinson's disease. α-Syn is capable of self-assembly into many different species, such as soluble oligomers and fibrils. Even though attempts to resolve the structures of the protein have been made, detailed understanding about the structures and their relationship with the different aggregation steps is lacking, which is of interest to provide insights into the pathogenic mechanism of Parkinson's disease. Here we report the structural flexibility of α-syn monomers and dimers in an aqueous solution environment as probed by single-molecule time-lapse high-speed AFM. In addition, we present the molecular basis for the structural transitions using discrete molecular dynamics (DMD) simulations. α-Syn monomers assume a globular conformation, which is capable of forming tail-like protrusions over dozens of seconds. Importantly, a globular monomer can adopt fully extended conformations. Dimers, on the other hand, are less dynamic and show a dumbbell conformation that experiences morphological changes over time. DMD simulations revealed that the α-syn monomer consists of several tightly packed small helices. The tail-like protrusions are also helical with a small β-sheet, acting as a "hinge". Monomers within dimers have a large interfacial interaction area and are stabilized by interactions in the non-amyloid central (NAC) regions. Furthermore, the dimer NAC-region of each α-syn monomer forms a β-rich segment. Moreover, NAC-regions are located in the hydrophobic core of the dimer.

Mapping allosteric linkage to channel gating by extracellular domains in the human epithelial sodium channel

The epithelial sodium channel (ENaC) mediates sodium absorption in lung, kidney, and colon epithelia. Channels in the ENaC/degenerin family possess an extracellular region that senses physicochemical changes in the extracellular milieu and allosterically regulates the channel opening. Proteolytic cleavage activates the ENaC opening, by the removal of specific segments in the finger domains of the α- and γ ENaC-subunits. Cleavage causes perturbations in the extracellular region that propagate to the channel gate. However, it is not known how the channel structure mediates the propagation of activation signals through the extracellular sensing domains. Here, to identify the structure-function determinants that mediate allosteric ENaC activation, we performed MD simulations, thiol modification of residues substituted by cysteine, and voltage-clamp electrophysiology recordings. Our simulations of an ENaC heterotetramer, α₁βα₂γ, in the proteolytically cleaved and uncleaved states revealed structural pathways in the α-subunit that are responsible for ENaC proteolytic activation. To validate these findings, we performed site-directed mutagenesis to introduce cysteine substitutions in the extracellular domains of the α-, β-, and γ ENaC-subunits. Insertion of a cysteine at the α-subunit Glu⁵⁵⁷ site, predicted to stabilize a closed state of ENaC, inhibited ENaC basal activity and retarded the kinetics of proteolytic activation by 2-fold. Our results suggest that the lower palm domain of αENaC is essential for ENaC activation. In conclusion, our integrated computational and experimental approach suggests key structure-function determinants for ENaC proteolytic activation and points toward a mechanistic model for the allosteric communication in the extracellular domains of the ENaC/degenerin family channels.

Solving protein structures using short-distance cross-linking constraints as a guide for discrete molecular dynamics simulations

We present an integrated experimental and computational approach for de novo protein structure determination in which short-distance cross-linking data are incorporated into rapid discrete molecular dynamics (DMD) simulations as constraints, reducing the conformational space and achieving the correct protein folding on practical time scales. We tested our approach on myoglobin and FK506 binding protein-models for α helix-rich and β sheet-rich proteins, respectively-and found that the lowest-energy structures obtained were in agreement with the crystal structure, hydrogen-deuterium exchange, surface modification, and long-distance cross-linking validation data. Our approach is readily applicable to other proteins with unknown structures.

Image formation in CARS and SRS: effect of an inhomogeneous nonresonant background medium

We investigate the role of a spatially inhomogenous nonresonant background medium on several Raman-based imaging modalities. In particular, we consider a small resonant bead submerged in a spatially heterogeneous nonresonant χ(3) background. Using detailed 3D electrodynamic simulations, we compare coherent anti-Stokes Raman scattering (CARS), frequency-modulated CARS, amplitude-modulated stimulated Raman scattering (SRS), and frequency-modulated SRS. We find that only FM-SRS is background-free.

[Control of nanoparticles in food and biological objects. Report 2. Filtration, centrifugation, spectral methods and electrophoresis]

The large number of the analysis methods of engineered nanoparticles and nanoobjects as a part of disperse systems on the basis of principles of a membrane filtration (micro, ultra- and a nanofiltration) ultracentrifugation, spectral methods, including dynamic and static laser light scattering, Raman light scattering, low-angle X-ray scattering, x-ray techniques, laser decomposition spectroscopy, and other methods are developed. Mass spectrometry with inductively coupled plasma can be successfully used in studying of nanomaterials chemical composition in conditions when there is additional independent information on presence of analyzed substance in a nanoscale form. Methods of electrophoresis in a supportive environment and capillary electrophoresis are beginning to be successfully applied in the study of artificial nanomaterials. However, in terms of the identification of engineered nanoparticles and nanoobjects in complex, multicomponent, heterophase systems, that the objects of the environment and, in particular, food products are, all these methods currently can't compete transmission electron microscopy and atomic force microscopy, specified for purpose of certain particular applications, features of which been described in a previous eport in detail.

[Methods of nanoparticles control in food and biological objects. Report 1. Use of microscopic and chromatography investigation methods]

One of the promising applications of modern nanotechnology are food productions, which includes the improvement of food packaging, creation of new forms of nutrients that are characterized by improved assimilation and technological characteristics, quality control through the creation of compact and cheap test kits. All these applications of nanomaterials related to the risks of the possibility of receipt of potentially toxic nanoparticles in the diet. The task of regulation and hygienic standardization requires developing of the methods, their qualitative and quantitative analysis for such complex, multicomponent systems, which are the agricultural commodities and food products. The best hope in this plan are assigned to a group of approaches related to the microscopic visualization of artificial nanoparticles in the biological objects. While the typical size of nanoparticles (<100 nm) are below the theoretical maximum-resolution light optical methods, transmission electron microscopy often allows not only to identify nanoparticles on their size and shape, but also a qualitative and quantitative analysis their chemical composition with the use of additional analytical options. Another group of elaborate methods used in solving the problems of qualitative and quantitative analysis of nanoparticles are chromatographic methods, in particular, the exclusion, hydrodynamic, high-performance liquid chromatography, and the flow-field fractionation. Limitation of chromatographic approaches related with the need of complex sample preparation, as well as specific difficulties in nanoparticles detecting in chromatographic fractions. Transmission electron microscopy and high-performance liquid chromatography methods are officially recommended in Russia for the analysis of artificial nanoparticles in natural biological systems, including food products.

[Characterization of silver nanoparticles migration from package materials destined for contact with foods]

There was studied migration of artificial silver nanoparticles from polyethylene films destined for package of such foods as bread and poultry into model media reproducing physico-chemical properties and composition of said products. Modification of films was performed by 5- or 10-fold spraying of silver nanoparticles on the surface of package material. Model media were composed from water, alcohol and plant oil according to US FDA and Russian Federal Service for Surveillance of Consumer Rights Protection and Human Well-Being official recommendation. Nanoparticles were detected in model media by means of transmission electron and atomic force microscopy. Quantification of silver in nanoparticles migrating from films was performed by mass-spectrometry with inductively coupled plasma. The results obtained showed that silver migrated from films into test media in form of nanoparticles with mean diameter close to 10-20 nm. Migrated particles were partially aggregated to complexes with dimension about 50 nm with degree of aggregation depending on media composition. Quantification showed that amounts of silver nanoparticles migrating in foods did not exceed save level of this nanomaterial consumption even in aggravated conditions when almost all volume of product was consumed in form packaged in films modified with nanosilver.

Surface induced self-organization of comb-like macromolecules

We present a review of the theoretical and experimental evidence for the peculiar properties of comb copolymers, demonstrating the uniqueness of these materials among other polymer architectures. These special properties include an increase in stiffness upon increasing side-chain length, the spontaneous curvature of adsorbed combs, rod-globule transition, and specific intramolecular self-assembly. We also propose a theory of chemically heterogeneous surface nanopattern formation in ultrathin films of comblike macromolecules containing two different types (A and B) of incompatible side chains (so-called binary combs). Side chains of the binary combs are strongly adsorbed on a surface and segregated with respect to the backbone. The thickness of surface domains formed by the B side chains is controlled by the interaction with the substrate. We predict the stability of direct and inverse disc-, torus- and stripelike nanostructures. Phase diagrams of the film are constructed.

Image formation in CARS microscopy: effect of the Gouy phase shift

Image formation in Coherent Anti-Stokes Raman Scattering (CARS) microscopy of sub-wavelength objects is investigated via a combined experimental, numerical and theoretical study. We consider a resonant spherical object in the presence of a nonresonant background, using tightly focused laser pulses. When the object is translated along the laser propagation axis, we find the CARS signal to be asymmetric about the laser focal plane. When the object is located before the focus, there is a distinct shadow within the image, whereas the brightest signal is obtained when the object is behind the focus. This behaviour is caused by interference between resonant and nonresonant signals, and the Gouy phase shift is responsible for the observed asymmetry within the image.

Morphology of femtosecond laser modification of bulk dielectrics

Using 3D Finite-Difference-Time-Domain simulations, we study the morphology of the laser-created damage inside fused silica. Among the competing effects limiting the intensity in the dielectric, we find the most important is the pulse defocusing by the plasma lens, partially balanced by the Kerr effect. Less important are collisional energy dissipation and laser depletion by multi-photon absorption. We also found that the profile of generated plasma is asymmetrical in the transverse cross-section, with the plasma extended along the direction perpendicular to the laser polarization.

Ion response to relativistic electron bunches in the blowout regime of laser-plasma accelerators

The ion response to relativistic electron bunches in the so called bubble or blowout regime of a laser-plasma accelerator is discussed. In response to the strong fields of the accelerated electrons the ions form a central filament along the laser axis that can be compressed to densities 2 orders of magnitude higher than the initial particle density. A theory of the filament formation and a model of ion self-compression are proposed. It is also shown that in the case of a sharp rear plasma-vacuum interface the ions can be accelerated by a combination of three basic mechanisms. The long time ion evolution that results from the strong electrostatic fields of an electron bunch provides a unique diagnostic of laser-plasma accelerators.

18-Crown-6 and dibenzo-18-crown-6 assisted extraction of cesium from water into room temperature ionic liquids and its correlation with stability constants for cesium complexes

The pH-profiles of the extraction of Cs⁺ into four conventional (1-butyl-3- methylimidazolium hexafluorophosphate and bis[trifluoromethyl)sulphonyl]imides of 1- butyl-3-methylimidazolium, 1-hexyl-3-methylimidazolium, and 1-(2-ethylhexyl)-3-methylimidazolium) and two novel (trioctylmethylammonium salicylate and tetrahexyl-ammonium dihexylsulfosuccinate) room temperature ionic liquids have been determined both in the absence and in the presence of crown ether (18-crown-6 or dibenzo-18-crown-6). The pH-profiles of distribution ratio of crown ethers have been established in the same conditions. The relationship of cesium extraction efficiency both with the stability of its complexes with crown ethers and crown ethers’ distribution ratio has been clarified.

Two mechanisms of spontaneous curvature of strongly adsorbed (2D) double comblike copolymers

We propose a theory of spontaneous curvature of 2D comblike macromolecules with incompatible side chains of types A and B. It is expected that the side chains of both types are able to change their positions with respect to the backbone. We predict two mechanisms of curvature. In the case of strong incompatibility of the side chains, their complete segregation with respect to the backbone is responsible for the formation of the so-called "energetic" curvature that is a result of the difference in the length (or in the number) of the A and B chains. In the case of moderate incompatibility, partial mixing of the A and B side chains on the convex side of the molecule (a flip of shorter chains to the side of longer chains) can be entropically favorable. In this case, the stretching of the side chains decreases. The radius of the entropic curvature is determined by the length of the longer side chains.

[Experience of laparoscopic cholecystectomy in calculous cholecystitis]

Laparoscopic cholecystectomy (LCE) was performed in 330 patients aged from 14 to 77 years; it was completed successfully in 308 (93.3%) patients. Conversion to laparotomy and standard cholecystectomy was carried out in 22 patients (6.7%) due chiefly (86.4%) to inflammatory disorders of infrahepatic area. 188 (61%) LCE were performed for chronic calculous cholecystitis, 120--for acute calculous cholecystitis. In the latter group destructive forms of cholecystitis were revealed in 34.2% patients. Combined with LCE interventions were performed in 13 patients (4.2%). There were no lethal outcomes after LCE. Severe intra- and postoperative complications occurred in 26 (8.4%) patients; laparotomy for removing these complications was necessary in 3 patients (1%).