Potent hepatitis C inhibitors bind directly to NS5A and reduce its affinity for RNA

Mining patents with large language models elucidates the chemical function landscape

The fundamental goal of small molecule discovery is to generate chemicals with target functionality. While this often proceeds through structure-based methods, we set out to investigate the practicality of methods that leverage the extensive corpus of chemical literature. We hypothesize that a sufficiently large text-derived chemical function dataset would mirror the actual landscape of chemical functionality. Such a landscape would implicitly capture complex physical and biological interactions given that chemical function arises from both a molecule's structure and its interacting partners. To evaluate this hypothesis, we built a Chemical Function (CheF) dataset of patent-derived functional labels. This dataset, comprising 631 K molecule-function pairs, was created using an LLM- and embedding-based method to obtain 1.5 K unique functional labels for approximately 100 K randomly selected molecules from their corresponding 188 K unique patents. We carry out a series of analyses demonstrating that the CheF dataset contains a semantically coherent textual representation of the functional landscape congruent with chemical structural relationships, thus approximating the actual chemical function landscape. We then demonstrate through several examples that this text-based functional landscape can be leveraged to identify drugs with target functionality using a model able to predict functional profiles from structure alone. We believe that functional label-guided molecular discovery may serve as an alternative approach to traditional structure-based methods in the pursuit of designing novel functional molecules.

Lipid sulfoxide polymers as potential inhalable drug delivery platforms with differential albumin binding affinity

Inhalable nanomedicines are increasingly being developed to optimise the pharmaceutical treatment of respiratory diseases. Large lipid-based nanosystems at the forefront of the inhalable nanomedicines development pipeline, though, have a number of limitations. The objective of this study was, therefore, to investigate the utility of novel small lipidated sulfoxide polymers based on poly(2-(methylsulfinyl)ethyl acrylate) (PMSEA) as inhalable drug delivery platforms with tuneable membrane permeability imparted by differential albumin binding kinetics. Linear PMSEA (5 kDa) was used as a hydrophilic polymer backbone with excellent anti-fouling and stealth properties compared to poly(ethylene glycol). Terminal lipids comprising single (1C2, 1C12) or double (2C12) chain diglycerides were installed to provide differing affinities for albumin and, by extension, albumin trafficking pathways in the lungs. Albumin binding kinetics, cytotoxicity, lung mucus penetration and cellular uptake and permeability through key cellular barriers in the lungs were examined in vitro. The polymers showed good mucus penetration and no cytotoxicity over 24 h at up to 1 mg ml-1. While 1C2-showed no interaction with albumin, 1C12-PMSEA and 2C12-PMSEA bound albumin with KD values of approximately 76 and 10 μM, respectively. Despite binding to albumin, 2C12-PMSEA showed reduced cell uptake and membrane permeability compared to the smaller polymers and the presence of albumin had little effect on cell uptake and membrane permeability. While PMSEA strongly shielded these lipids from albumin, the data suggest that there is scope to tune the lipid component of these systems to control membrane permeability and cellular interactions in the lungs to tailor drug disposition in the lungs.

Antiviral drugs prolong survival in murine recessive dystrophic epidermolysis bullosa

Recessive dystrophic epidermolysis bullosa (RDEB) is a rare inherited skin disease characterized by defects in type VII collagen leading to a range of fibrotic pathologies resulting from skin fragility, aberrant wound healing, and altered dermal fibroblast physiology. Using a novel in vitro model of fibrosis based on endogenously produced extracellular matrix, we screened an FDA-approved compound library and identified antivirals as a class of drug not previously associated with anti-fibrotic action. Preclinical validation of our lead hit, daclatasvir, in a mouse model of RDEB demonstrated significant improvement in fibrosis as well as overall quality of life with increased survival, weight gain and activity, and a decrease in pruritus-induced hair loss. Immunohistochemical assessment of daclatasvir-treated RDEB mouse skin showed a reduction in fibrotic markers, which was supported by in vitro data demonstrating TGFβ pathway targeting and a reduction of total collagen retained in the extracellular matrix. Our data support the clinical development of antivirals for the treatment of patients with RDEB and potentially other fibrotic diseases.

Ser38-His93-Asn91 triad confers resistance of JFH1 HCV NS5A-Y93H variant to NS5A inhibitors

HCV NS5A is a dimeric phosphoprotein involved in HCV replication. NS5A inhibitors are among direct-acting antivirals (DAA) for HCV therapy. The Y93H mutant of NS5A is resistant to NS5A inhibitors, but the precise mechanism remains unclear. In this report, we proposed a Ser38-His93-Asn91 triad to dissect the mechanism. Using pymol 1.3 software, the homology structure of JFH1 NS5A was determined based on the dimer structure of genotype 1b extracted from the database Protein DataBank (www.ebi.ac.uk/pdbsum) with codes 1ZH1 and 3FQM/3FQQ. FLAG-NS5A-WT failed to form dimer in the absence of nonstructural proteins from subgenomic replicon (NS3-5A); however, FLAG-NS5A-Y93H was able to form dimer without the aid of NS3-5A. The Ser38-His93-Asn91 triad in the dimer of the Y93H variant predicts a structural crash of the cleft receiving the NS5A inhibitor daclatasvir. The dimerization assay revealed that the existence of JFH1-NS5A-1ZH1 and -3FQM homology dimers depended on each other for existence and that both NS5A-WT 1ZH1 and 3FQM dimers cooperated to facilitate RNA replication. However, NS5A-Y93H 1ZH1 alone could form dimer and conduct RNA replication in the absence of the 3FQM structure. In conclusion, this study provides novel insight into the functional significance of the Ser38-His93-Asn91 triad in resistance of the Y93H variant to NS5A inhibitors.

Evaluating physiochemical properties of FDA-approved orally administered drugs

INTRODUCTION

Analyses of orally administered FDA-approved drugs from 1990 to 1993 enabled the identification of a set of physiochemical properties known as Lipinski's Rule of Five (Ro5). The original Ro5 and extended versions still remain the reference criteria for drug development programs. Since many bioactive compounds do not conform to the Ro5, we validated the relevance of and adherence to these rulesets in a contemporary cohort of FDA-approved drugs.

AREAS COVERED

The authors noted that a significant proportion of FDA-approved orally administered parent compounds from 2011 to 2022 deviate from the original Ro5 criteria (~38%) or the Ro5 with extensions (~53%). They then evaluated if a contemporary Ro5 criteria (cRo5) could be devised to better predict oral bioavailability. Furthermore, they discuss many case studies showcasing the need for and benefit of increasing the size of certain compounds and cover several evolving strategies for improving oral bioavailability.

EXPERT OPINION

Despite many revisions to the Ro5, the authors find that no single proposed physiochemical rule has universal concordance with absolute oral bioavailability. Innovations in drug delivery and formulation have dramatically expanded the range of physicochemical properties and the chemical diversity for oral administration.

AI-Driven Enhancements in Drug Screening and Optimization

The greatest challenge in drug discovery remains the high rate of attrition across the different phases of the process, which cost the industry billions of dollars every year. While all phases remain crucial to ensure pharmaceutical-level safety, quality, and efficacy of the end product, streamlining these efforts toward compounds with success potential is pivotal for a more efficient and cost-effective process. The use of artificial intelligence (AI) within the pharmaceutical industry aims at just this, and has applications in preclinical screening for biological activity, optimization of pharmacokinetic properties for improved drug formulation, early toxicity prediction which reduces attrition, and pre-emptively screening for genetic changes in the biological target to improve therapeutic longevity. Here, we present a series of in silico tools that address these applications in small molecule development and describe how they can be embedded within the current pharmaceutical development pipeline.

Mining Patents with Large Language Models Elucidates the Chemical Function Landscape

The fundamental goal of small molecule discovery is to generate chemicals with target functionality. While this often proceeds through structure-based methods, we set out to investigate the practicality of orthogonal methods that leverage the extensive corpus of chemical literature. We hypothesize that a sufficiently large text-derived chemical function dataset would mirror the actual landscape of chemical functionality. Such a landscape would implicitly capture complex physical and biological interactions given that chemical function arises from both a molecule's structure and its interacting partners. To evaluate this hypothesis, we built a Chemical Function (CheF) dataset of patent-derived functional labels. This dataset, comprising 631K molecule-function pairs, was created using an LLM- and embedding-based method to obtain functional labels for approximately 100K molecules from their corresponding 188K unique patents. We carry out a series of analyses demonstrating that the CheF dataset contains a semantically coherent textual representation of the functional landscape congruent with chemical structural relationships, thus approximating the actual chemical function landscape. We then demonstrate that this text-based functional landscape can be leveraged to identify drugs with target functionality using a model able to predict functional profiles from structure alone. We believe that functional label-guided molecular discovery may serve as an orthogonal approach to traditional structure-based methods in the pursuit of designing novel functional molecules.

Identifying Innate Resistance Hotspots for SARS-CoV-2 Antivirals Using In Silico Protein Techniques

The development and approval of antivirals against SARS-CoV-2 has further equipped clinicians with treatment strategies against the COVID-19 pandemic, reducing deaths post-infection. Extensive clinical use of antivirals, however, can impart additional selective pressure, leading to the emergence of antiviral resistance. While we have previously characterized possible effects of circulating SARS-CoV-2 missense mutations on proteome function and stability, their direct effects on the novel antivirals remains unexplored. To address this, we have computationally calculated the consequences of mutations in the antiviral targets: RNA-dependent RNA polymerase and main protease, on target stability and interactions with their antiviral, nucleic acids, and other proteins. By analyzing circulating variants prior to antiviral approval, this work highlighted the inherent resistance potential of different genome regions. Namely, within the main protease binding site, missense mutations imparted a lower fitness cost, while the opposite was noted for the RNA-dependent RNA polymerase binding site. This suggests that resistance to nirmatrelvir/ritonavir combination treatment is more likely to occur and proliferate than that to molnupiravir. These insights are crucial both clinically in drug stewardship, and preclinically in the identification of less mutable targets for novel therapeutic design.

Sub-stoichiometric Modulation of Viral Targets-Potent Antiviral Agents That Exploit Target Vulnerability

The modulation of oligomeric viral targets at sub-stoichiometric ratios of drug to target has been advocated for its efficacy and potency, but there are only a limited number of documented examples. In this Viewpoint, we summarize the invention of the HIV-1 maturation inhibitor fipravirimat and discuss the emerging details around the mode of action of this class of drug that reflects inhibition of a protein composed of 1,300-1,600 monomers that interact in a cooperative fashion. Similarly, the HCV NS5A inhibitor daclatasvir has been shown to act in a highly sub-stoichiometric fashion, inhibiting viral replication at concentrations that are ∼23,500 lower than that of the protein target.

Mechanisms of Action of the Host-Targeting Agent Cyclosporin A and Direct-Acting Antiviral Agents against Hepatitis C Virus

Several direct-acting antivirals (DAAs) are available, providing interferon-free strategies for a hepatitis C cure. In contrast to DAAs, host-targeting agents (HTAs) interfere with host cellular factors that are essential in the viral replication cycle; as host genes, they are less likely to rapidly mutate under drug pressure, thus potentially exhibiting a high barrier to resistance, in addition to distinct mechanisms of action. We compared the effects of cyclosporin A (CsA), a HTA that targets cyclophilin A (CypA), to DAAs, including inhibitors of nonstructural protein 5A (NS5A), NS3/4A, and NS5B, in Huh7.5.1 cells. Our data show that CsA suppressed HCV infection as rapidly as the fastest-acting DAAs. CsA and inhibitors of NS5A and NS3/4A, but not of NS5B, suppressed the production and release of infectious HCV particles. Intriguingly, while CsA rapidly suppressed infectious extracellular virus levels, it had no significant effect on the intracellular infectious virus, suggesting that, unlike the DAAs tested here, it may block a post-assembly step in the viral replication cycle. Hence, our findings shed light on the biological processes involved in HCV replication and the role of CypA.

Studies of the symmetric binding mode of daclatasvir and analogs using a new homology model of HCV NS5A GT-4a

CONTEXT

Egypt has a high prevalence of the hepatitis C virus (HCV) genotype 4a (GT-4a). Unfortunately, the high resistance it exhibited still was not given the deserved attention in the scientific community. There is currently no consensus on the NS5A binding site because the crystal structure of HCV NS5A has not been resolved. The prediction of the binding modes of direct-acting antivirals (DAA) with the NS5A is a point of controversy due to the fact that several research groups presented different interaction models to elucidate the NS5A binding site. Consequently, a 3D model of HCV NS5A GT-4a was constructed and evaluated using molecular dynamics (MD) simulations. The generated model implies an intriguing new orientation of the AH relative to domain I. Additionally, the probable binding modes of marketed NS5A inhibitors were explored. MD simulations validated the stability of the predicted protein-ligand complexes. The suggested model predicts that daclatasvir and similar drugs bind symmetrically to HCV NS5A GT-4a. This will allow for the development of new NS5A-directed drugs, which may result in reduced resistance and/or a wider range of effectiveness against HCV.

METHODS

The 3D model of HCV NS5A GT-4a was constructed using the comparative modeling approach of the web-based application Robetta. Its stability was tested with 200-ns MD simulations using the Desmond package of Schrodinger. The OPLS2005 force field was assigned for minimization, and the RMSD, RMSF, and rGyr were tracked throughout the MD simulations. Fpocket was used to identify druggable protein pockets (cavities) over the simulation trajectories. The binding modes of marketed NS5A inhibitors were then generated and refined with the aid of docking predictions made by FRED and AutoDock Vina. The stability of these drugs in complex with GT-4a was investigated by using energetic and structural analyses over MD simulations. The Prime MM-GBSA (molecular mechanics/generalized Born surface area) method was used as a validation tool after the docking stage and for the averaged clusters after the MD simulation stage. We utilized PyMOL and VMD to visualize the data.

Using Graph-Based Signatures to Guide Rational Antibody Engineering

Antibodies are essential experimental and diagnostic tools and as biotherapeutics have significantly advanced our ability to treat a range of diseases. With recent innovations in computational tools to guide protein engineering, we can now rationally design better antibodies with improved efficacy, stability, and pharmacokinetics. Here, we describe the use of the mCSM web-based in silico suite, which uses graph-based signatures to rapidly identify the structural and functional consequences of mutations, to guide rational antibody engineering to improve stability, affinity, and specificity.

Microscale Thermophoresis as a Tool to Study Protein Interactions and Their Implication in Human Diseases

The review highlights how protein–protein interactions (PPIs) have determining roles in most life processes and how interactions between protein partners are involved in various human diseases. The study of PPIs and binding interactions as well as their understanding, quantification and pharmacological regulation are crucial for therapeutic purposes. Diverse computational and analytical methods, combined with high-throughput screening (HTS), have been extensively used to characterize multiple types of PPIs, but these procedures are generally laborious, long and expensive. Rapid, robust and efficient alternative methods are proposed, including the use of Microscale Thermophoresis (MST), which has emerged as the technology of choice in drug discovery programs in recent years. This review summarizes selected case studies pertaining to the use of MST to detect therapeutically pertinent proteins and highlights the biological importance of binding interactions, implicated in various human diseases. The benefits and limitations of MST to study PPIs and to identify regulators are discussed.

Systematic evaluation of computational tools to predict the effects of mutations on protein stability in the absence of experimental structures

Changes in protein sequence can have dramatic effects on how proteins fold, their stability and dynamics. Over the last 20 years, pioneering methods have been developed to try to estimate the effects of missense mutations on protein stability, leveraging growing availability of protein 3D structures. These, however, have been developed and validated using experimentally derived structures and biophysical measurements. A large proportion of protein structures remain to be experimentally elucidated and, while many studies have based their conclusions on predictions made using homology models, there has been no systematic evaluation of the reliability of these tools in the absence of experimental structural data. We have, therefore, systematically investigated the performance and robustness of ten widely used structural methods when presented with homology models built using templates at a range of sequence identity levels (from 15% to 95%) and contrasted performance with sequence-based tools, as a baseline. We found there is indeed performance deterioration on homology models built using templates with sequence identity below 40%, where sequence-based tools might become preferable. This was most marked for mutations in solvent exposed residues and stabilizing mutations. As structure prediction tools improve, the reliability of these predictors is expected to follow, however we strongly suggest that these factors should be taken into consideration when interpreting results from structure-based predictors of mutation effects on protein stability.

Repurposing of FDA-approved drugs as potential inhibitors of the SARS-CoV-2 main protease: Molecular insights into improved therapeutic discovery

With numerous infections and fatalities, COVID-19 has wreaked havoc around the globe. The main protease (Mpro), which cleaves the polyprotein to form non-structural proteins, thereby helping in the replication of SARS-CoV-2, appears as an attractive target for antiviral therapeutics. As FDA-approved drugs have shown effectiveness in targeting Mpro in previous SARS-CoV(s), molecular docking and virtual screening of existing antiviral, antimalarial, and protease inhibitor drugs were carried out against SARS-CoV-2 Mpro. Among 53 shortlisted drugs with binding energies lower than that of the crystal-bound inhibitor α-ketoamide 13 b (−6.7 kcal/mol), velpatasvir, glecaprevir, grazoprevir, baloxavir marboxil, danoprevir, nelfinavir, and indinavir (−9.1 to −7.5 kcal/mol) were the most significant on the list (hereafter referred to as the 53-list). Molecular dynamics (MD) simulations confirmed the stability of their Mpro complexes, with the MMPBSA binding free energy (ΔG_bind) ranging between −124 kJ/mol (glecaprevir) and −28.2 kJ/mol (velpatasvir). Despite having the lowest initial binding energy, velpatasvir exhibited the highest ΔG_bind value for escaping the catalytic site during the MD simulations, indicating its reduced efficacy, as observed experimentally. Available inhibition assay data adequately substantiated the computational forecast. Glecaprevir and nelfinavir (ΔG_bind = −95.4 kJ/mol) appear to be the most effective antiviral drugs against Mpro. Furthermore, the remaining FDA drugs on the 53-list can be worth considering, since some have already demonstrated antiviral activity against SARS-CoV-2. Hence, theoretical pK_i (K_i = inhibitor constant) values for all 53 drugs were provided. Notably, ΔG_bind directly correlates with the average distance of the drugs from the His41–Cys145 catalytic dyad of Mpro, providing a roadmap for rapid screening and improving the inhibitor design against SARS-CoV-2 Mpro.

mmCSM-NA: accurately predicting effects of single and multiple mutations on protein-nucleic acid binding affinity

While protein-nucleic acid interactions are pivotal for many crucial biological processes, limited experimental data has made the development of computational approaches to characterise these interactions a challenge. Consequently, most approaches to understand the effects of missense mutations on protein-nucleic acid affinity have focused on single-point mutations and have presented a limited performance on independent data sets. To overcome this, we have curated the largest dataset of experimentally measured effects of mutations on nucleic acid binding affinity to date, encompassing 856 single-point mutations and 141 multiple-point mutations across 155 experimentally solved complexes. This was used in combination with an optimized version of our graph-based signatures to develop mmCSM-NA (http://biosig.unimelb.edu.au/mmcsm_na), the first scalable method capable of quantitatively and accurately predicting the effects of multiple-point mutations on nucleic acid binding affinities. mmCSM-NA obtained a Pearson's correlation of up to 0.67 (RMSE of 1.06 Kcal/mol) on single-point mutations under cross-validation, and up to 0.65 on independent non-redundant datasets of multiple-point mutations (RMSE of 1.12 kcal/mol), outperforming similar tools. mmCSM-NA is freely available as an easy-to-use web-server and API. We believe it will be an invaluable tool to shed light on the role of mutations affecting protein-nucleic acid interactions in diseases.

A Novel Small Molecule Inhibits Hepatitis C Virus Propagation in Cell Culture

Hepatitis C virus (HCV) can cause acute and chronic infection that is associated with considerable liver-related morbidity and mortality. In recent years, there has been a shift in the treatment paradigm with the discovery and approval of agents that target specific proteins vital for viral replication. We employed a cell culture-adapted strain of HCV and human hepatoma-derived cells lines to test the effects of our novel small-molecule compound (AO13) on HCV. Virus inhibition was tested by analyzing RNA replication, protein expression, and virus production in virus-infected cells treated with AO13. Treatment with AO13 inhibited virus spread in cell culture and showed a 100-fold reduction in the levels of infectious virus production. AO13 significantly reduced the level of viral RNA contained within cell culture fluids and reduced the cellular levels of HCV core protein, suggesting that the compound might act on a late step in the viral life cycle. Finally, we observed that AO13 did not affect the release of infectious virus from infected cells. Docking studies and molecular dynamics analyses suggested that AO13 might target the NS5B RNA polymerase, however, real-time RT-PCR analyses of cellular levels of HCV RNA showed only an ∼2-fold reduction in viral RNA levels in the presence of AO13. Taken together, this study revealed that AO13 showed consistent, but low-level antiviral effect against HCV, although the mechanism of action remains unclear.

IMPORTANCE The discovery of curative antiviral drugs for a chronic disease such as HCV infection has encouraged drug discovery in the context of other viruses for which no curative drugs currently exist. Since we currently face a novel virus that has caused a pandemic, the need for new antiviral agents is more apparent than ever. We describe here a novel compound that shows a modest antiviral effect against HCV that could serve as a lead compound for future drug development against other important viruses such as SARS-CoV-2.

mmCSM-PPI: predicting the effects of multiple point mutations on protein-protein interactions

Protein-protein interactions play a crucial role in all cellular functions and biological processes and mutations leading to their disruption are enriched in many diseases. While a number of computational methods to assess the effects of variants on protein-protein binding affinity have been proposed, they are in general limited to the analysis of single point mutations and have been shown to perform poorly on independent test sets. Here, we present mmCSM-PPI, a scalable and effective machine learning model for accurately assessing changes in protein-protein binding affinity caused by single and multiple missense mutations. We expanded our well-established graph-based signatures in order to capture physicochemical and geometrical properties of multiple wild-type residue environments and integrated them with substitution scores and dynamics terms from normal mode analysis. mmCSM-PPI was able to achieve a Pearson's correlation of up to 0.75 (RMSE = 1.64 kcal/mol) under 10-fold cross-validation and 0.70 (RMSE = 2.06 kcal/mol) on a non-redundant blind test, outperforming existing methods. Our method is freely available as a user-friendly and easy-to-use web server and API at http://biosig.unimelb.edu.au/mmcsm_ppi.

Distinguishing between PTEN clinical phenotypes through mutation analysis

Phosphate and tensin homolog on chromosome ten (PTEN) germline mutations are associated with an overarching condition known as PTEN hamartoma tumor syndrome. Clinical phenotypes associated with this syndrome range from macrocephaly and autism spectrum disorder to Cowden syndrome, which manifests as multiple noncancerous tumor-like growths (hamartomas), and an increased predisposition to certain cancers. It is unclear, however, the basis by which mutations might lead to these very diverse phenotypic outcomes. Here we show that, by considering the molecular consequences of mutations in PTEN on protein structure and function, we can accurately distinguish PTEN mutations exhibiting different phenotypes. Changes in phosphatase activity, protein stability, and intramolecular interactions appeared to be major drivers of clinical phenotype, with cancer-associated variants leading to the most drastic changes, while ASD and non-pathogenic variants associated with more mild and neutral changes, respectively. Importantly, we show via saturation mutagenesis that more than half of variants of unknown significance could be associated with disease phenotypes, while over half of Cowden syndrome mutations likely lead to cancer. These insights can assist in exploring potentially important clinical outcomes delineated by PTEN variation.

Hepatitis C Viral Replication Complex

The life cycle of the hepatitis C virus (HCV) can be divided into several stages, including viral entry, protein translation, RNA replication, viral assembly, and release. HCV genomic RNA replication occurs in the replication organelles (RO) and is tightly linked to ER membrane alterations containing replication complexes (proteins NS3 to NS5B). The amplification of HCV genomic RNA could be regulated by the RO biogenesis, the viral RNA structure (i.e., cis-acting replication elements), and both viral and cellular proteins. Studies on HCV replication have led to the development of direct-acting antivirals (DAAs) targeting the replication complex. This review article summarizes the viral and cellular factors involved in regulating HCV genomic RNA replication and the DAAs that inhibit HCV replication.

ThermoMutDB: a thermodynamic database for missense mutations

Proteins are intricate, dynamic structures, and small changes in their amino acid sequences can lead to large effects on their folding, stability and dynamics. To facilitate the further development and evaluation of methods to predict these changes, we have developed ThermoMutDB, a manually curated database containing >14,669 experimental data of thermodynamic parameters for wild type and mutant proteins. This represents an increase of 83% in unique mutations over previous databases and includes thermodynamic information on 204 new proteins. During manual curation we have also corrected annotation errors in previously curated entries. Associated with each entry, we have included information on the unfolding Gibbs free energy and melting temperature change, and have associated entries with available experimental structural information. ThermoMutDB supports users to contribute to new data points and programmatic access to the database via a RESTful API. ThermoMutDB is freely available at: http://biosig.unimelb.edu.au/thermomutdb.

Combining structure and genomics to understand antimicrobial resistance

Antimicrobials against bacterial, viral and parasitic pathogens have transformed human and animal health. Nevertheless, their widespread use (and misuse) has led to the emergence of antimicrobial resistance (AMR) which poses a potentially catastrophic threat to public health and animal husbandry. There are several routes, both intrinsic and acquired, by which AMR can develop. One major route is through non-synonymous single nucleotide polymorphisms (nsSNPs) in coding regions. Large scale genomic studies using high-throughput sequencing data have provided powerful new ways to rapidly detect and respond to such genetic mutations linked to AMR. However, these studies are limited in their mechanistic insight. Computational tools can rapidly and inexpensively evaluate the effect of mutations on protein function and evolution. Subsequent insights can then inform experimental studies, and direct existing or new computational methods. Here we review a range of sequence and structure-based computational tools, focussing on tools successfully used to investigate mutational effect on drug targets in clinically important pathogens, particularly Mycobacterium tuberculosis. Combining genomic results with the biophysical effects of mutations can help reveal the molecular basis and consequences of resistance development. Furthermore, we summarise how the application of such a mechanistic understanding of drug resistance can be applied to limit the impact of AMR.

In silico design and analysis of NS4B inhibitors against hepatitis C virus

The hepatitis C virus is a communicable disease that gradually harms the liver leading to cirrhosis and hepatocellular carcinoma. Important therapeutic interventions have been reached since the discovery of the disease. However, its resurgence urges the need for new approaches against this malady. The NS4B receptor is one of the important proteins for Hepatitis C Virus RNA replication that acts by mediating different viral properties. In this work, we opt to explore the relationships between the molecular structures of biologically tested NS4B inhibitors and their corresponding inhibitory activities to assist the design of novel and potent NS4B inhibitors. For that, a set of 115 indol-2-ylpyridine-3-sulfonamides (IPSA) compounds with inhibitory activity against NS4B is used. A hybrid genetic algorithm combined with multiple linear regressions (GA-MLR) was implemented to construct a predictive model. This model was further used and applied to a set of compounds that were generated based on a pharmacophore modeling study combined with virtual screening to identify structurally similar lead compounds. Multiple filtrations were implemented for selecting potent hits. The selected hits exhibited advantageous molecular features, allowing for favorable inhibitory activity against HCV. The results showed that 7 out of 1285 screened compounds, were selected as potent candidate hits where Zinc14822482 exhibits the best predicted potency and pharmacophore features. The predictive pharmacokinetic analysis further justified the compounds as potential hit molecules, prompting their recommendation for a confirmatory biological evaluation. We believe that our strategy could help in the design and screening of potential inhibitors in drug discovery.Communicated by Ramaswamy H. Sarma.

mCSM-AB2: guiding rational antibody design using graph-based signatures

MOTIVATION

A lack of accurate computational tools to guide rational mutagenesis has made affinity maturation a recurrent challenge in antibody (Ab) development. We previously showed that graph-based signatures can be used to predict the effects of mutations on Ab binding affinity.

RESULTS

Here we present an updated and refined version of this approach, mCSM-AB2, capable of accurately modelling the effects of mutations on Ab-antigen binding affinity, through the inclusion of evolutionary and energetic terms. Using a new and expanded database of over 1800 mutations with experimental binding measurements and structural information, mCSM-AB2 achieved a Pearson's correlation of 0.73 and 0.77 across training and blind tests, respectively, outperforming available methods currently used for rational Ab engineering.

AVAILABILITY AND IMPLEMENTATION

mCSM-AB2 is available as a user-friendly and freely accessible web server providing rapid analysis of both individual mutations or the entire binding interface to guide rational antibody affinity maturation at http://biosig.unimelb.edu.au/mcsm_ab2.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

DynaMut2: Assessing changes in stability and flexibility upon single and multiple point missense mutations

Predicting the effect of missense variations on protein stability and dynamics is important for understanding their role in diseases, and the link between protein structure and function. Approaches to estimate these changes have been proposed, but most only consider single‐point missense variants and a static state of the protein, with those that incorporate dynamics are computationally expensive. Here we present DynaMut2, a web server that combines Normal Mode Analysis (NMA) methods to capture protein motion and our graph‐based signatures to represent the wildtype environment to investigate the effects of single and multiple point mutations on protein stability and dynamics. DynaMut2 was able to accurately predict the effects of missense mutations on protein stability, achieving Pearson's correlation of up to 0.72 (RMSE: 1.02 kcal/mol) on a single point and 0.64 (RMSE: 1.80 kcal/mol) on multiple‐point missense mutations across 10‐fold cross‐validation and independent blind tests. For single‐point mutations, DynaMut2 achieved comparable performance with other methods when predicting variations in Gibbs Free Energy (ΔΔG) and in melting temperature (ΔT_m). We anticipate our tool to be a valuable suite for the study of protein flexibility analysis and the study of the role of variants in disease. DynaMut2 is freely available as a web server and API at http://biosig.unimelb.edu.au/dynamut2.

Identifying Genotype-Phenotype Correlations via Integrative Mutation Analysis

Mutations in protein-coding regions can lead to large biological changes and are associated with genetic conditions, including cancers and Mendelian diseases, as well as drug resistance. Although whole genome and exome sequencing help to elucidate potential genotype-phenotype correlations, there is a large gap between the identification of new variants and deciphering their molecular consequences. A comprehensive understanding of these mechanistic consequences is crucial to better understand and treat diseases in a more personalized and effective way. This is particularly relevant considering estimates that over 80% of mutations associated with a disease are incorrectly assumed to be causative. A thorough analysis of potential effects of mutations is required to correctly identify the molecular mechanisms of disease and enable the distinction between disease-causing and non-disease-causing variation within a gene. Here we present an overview of our integrative mutation analysis platform, which focuses on refining the current genotype-phenotype correlation methods by using the wealth of protein structural information.

Detection of low-level HCV variants in DAA treated patients: comparison amongst three different NGS data analysis protocols

BACKGROUND

Notwithstanding the efforts of direct-acting antivirals (DAAs) for the treatment of chronically infected hepatitis C virus (HCV) patients, concerns exist regarding the emergence of resistance-associated substitutions (RAS) related to therapy failure. Sanger sequencing is still the reference technique used for the detection of RAS and it detects viral variants present up to 15%, meaning that minority variants are undetectable, using this technique. To date, many studies are focused on the analysis of the impact of HCV low variants using next-generation sequencing (NGS) techniques, but the importance of these minority variants is still debated, and importantly, a common data analysis method is still not defined.

METHODS

Serum samples from four patients failing DAAs therapy were collected at baseline and failure, and amplification of NS3, NS5A and NS5B genes was performed on each sample. The genes amplified were sequenced using Sanger and NGS Illumina sequencing and the data generated were analyzed with different approaches. Three different NGS data analysis methods, two homemade in silico pipeline and one commercially available certified user-friendly software, were used to detect low-level variants.

RESULTS

The NGS approach allowed to infer also very-low level virus variants. Moreover, data processing allowed to generate high accuracy data which results in reduction in the error rates for each single sequence polymorphism. The results improved the detection of low-level viral variants in the HCV quasispecies of the analyzed patients, and in one patient a low-level RAS related to treatment failure was identified. Importantly, the results obtained from only two out of the three data analysis strategies were in complete agreement in terms of both detection and frequency of RAS.

CONCLUSIONS

These results highlight the need to find a robust NGS data analysis method to standardize NGS results for a better comprehension of the clinical role of low-level HCV variants. Based on the extreme importance of data analysis approaches for wet-data interpretation, a detailed description of the used pipelines and further standardization of the in silico analysis could allow increasing diagnostic laboratory networking to unleash true potentials of NGS.

mmCSM-AB: guiding rational antibody engineering through multiple point mutations

While antibodies are becoming an increasingly important therapeutic class, especially in personalized medicine, their development and optimization has been largely through experimental exploration. While there have been many efforts to develop computational tools to guide rational antibody engineering, most approaches are of limited accuracy when applied to antibody design, and have largely been limited to analysing a single point mutation at a time. To overcome this gap, we have curated a dataset of 242 experimentally determined changes in binding affinity upon multiple point mutations in antibody-target complexes (89 increasing and 153 decreasing binding affinity). Here, we have shown that by using our graph-based signatures and atomic interaction information, we can accurately analyse the consequence of multi-point mutations on antigen binding affinity. Our approach outperformed other available tools across cross-validation and two independent blind tests, achieving Pearson's correlations of up to 0.95. We have implemented our new approach, mmCSM-AB, as a web-server that can help guide the process of affinity maturation in antibody design. mmCSM-AB is freely available at http://biosig.unimelb.edu.au/mmcsm_ab/.

Factors Influencing the Prevalence of Resistance-Associated Substitutions in NS5A Protein in Treatment-Naive Patients with Chronic Hepatitis C

Direct-acting antivirals (DAAs) revolutionized treatment of hepatitis C virus (HCV) infection. Resistance-associated substitutions (RASs) present at the baseline impair response to DAA due to rapid selection of resistant HCV strains. NS5A is indispensable target of the current DAA treatment regimens. We evaluated prevalence of RASs in NS5A in DAA-naïve patients infected with HCV 1a (n = 19), 1b (n = 93), and 3a (n = 90) before systematic DAA application in the territory of the Russian Federation. Total proportion of strains carrying at least one RAS constituted 35.1% (71/202). In HCV 1a we detected only M28V (57.9%) attributed to a founder effect. Common RASs in HCV 1b were R30Q (7.5%), L31M (5.4%), P58S (4.4%), and Y93H (5.4%); in HCV 3a, A30S (31.0%), A30K (5.7%), S62L (8.9%), and Y93H (2.2%). Prevalence of RASs in NS5A of HCV 1b and 3a was similar to that worldwide, including countries practicing massive DAA application, i.e., it was not related to treatment. NS5A with and without RASs exhibited different co-variance networks, which could be attributed to the necessity to preserve viral fitness. Majority of RASs were localized in polymorphic regions subjected to immune pressure, with selected substitutions allowing immune escape. Altogether, this explains high prevalence of RAS in NS5A and low barrier for their appearance in DAA-inexperienced population.

GSK2818713, a Novel Biphenylene Scaffold-Based Hepatitis C NS5A Replication Complex Inhibitor with Broad Genotype Coverage

Pan-genotype NS5A inhibitors underpin hugely successful hepatitis C virus (HCV) therapy. The discovery of GSK2818713 (13), a nonstructural protein 5A (NS5A) HCV inhibitor characterized by a significantly improved genotype coverage relative to first-generation NS5A inhibitor daclatasvir (DCV), is detailed herein. The SAR analysis revealed cooperative potency effects of the biphenylene, bicyclic pyrrolidine (Aoc), and methyl-threonine structural motifs. Relative to DCV, 13 improved activity against genotype 1a (gt1a) and gt1b NS5A variants as well as HCV chimeric replicons containing NS5A fragments from genotypes 2-6. Long-term treatment of subgenomic replicons with 13 potently and durably decreased HCV RNA levels for gt1a, gt2a, and gt3a. These properties, suitable pharmacokinetics, and the lack of cross-resistance resulted in the selection of 13 as a preclinical candidate.

Structure guided prediction of Pyrazinamide resistance mutations in pncA

Pyrazinamide plays an important role in tuberculosis treatment; however, its use is complicated by side-effects and challenges with reliable drug susceptibility testing. Resistance to pyrazinamide is largely driven by mutations in pyrazinamidase (pncA), responsible for drug activation, but genetic heterogeneity has hindered development of a molecular diagnostic test. We proposed to use information on how variants were likely to affect the 3D structure of pncA to identify variants likely to lead to pyrazinamide resistance. We curated 610 pncA mutations with high confidence experimental and clinical information on pyrazinamide susceptibility. The molecular consequences of each mutation on protein stability, conformation, and interactions were computationally assessed using our comprehensive suite of graph-based signature methods, mCSM. The molecular consequences of the variants were used to train a classifier with an accuracy of 80%. Our model was tested against internationally curated clinical datasets, achieving up to 85% accuracy. Screening of 600 Victorian clinical isolates identified a set of previously unreported variants, which our model had a 71% agreement with drug susceptibility testing. Here, we have shown the 3D structure of pncA can be used to accurately identify pyrazinamide resistance mutations. SUSPECT-PZA is freely available at: http://biosig.unimelb.edu.au/suspect_pza/.

A Comprehensive Computational Platform to Guide Drug Development Using Graph-Based Signature Methods

High-throughput computational techniques have become invaluable tools to help increase the overall success, process efficiency, and associated costs of drug development. By designing ligands tailored to specific protein structures in a disease of interest, an understanding of molecular interactions and ways to optimize them can be achieved prior to chemical synthesis. This understanding can help direct crucial chemical and biological experiments by maximizing available resources on higher quality leads. Moreover, predicting molecular binding affinity within specific biological contexts, as well as ligand pharmacokinetics and toxicities, can aid in filtering out redundant leads early on within the process. We describe a set of computational tools which can aid in drug discovery at different stages, from hit identification (EasyVS) to lead optimization and candidate selection (CSM-lig, mCSM-lig, Arpeggio, pkCSM). Incorporating these tools along the drug development process can help ensure that candidate leads are chemically and biologically feasible to become successful and tractable drugs.

Structure-activity relationships of fluorene compounds inhibiting HCV variants

Approximately 71 million people suffer from hepatitis C virus (HCV) infection worldwide. Persistent HCV infection causes liver diseases such as chronic hepatitis, liver cirrhosis, and hepatocellular carcinoma, resulting in approximately 400,000 deaths annually. Effective direct-acting antiviral agents (DAAs) have been developed and are currently used for HCV treatment targeting the following three proteins: NS3/4A proteinase that cleaves the HCV polyprotein into various functional proteins, RNA-dependent RNA polymerase (designated as NS5B), and NS5A, which is required for the formation of double membrane vesicles serving as RNA replication organelles. At least one compound inhibiting NS5A is included in current HCV treatment regimens due to the high efficacy and low toxicity of drugs targeting NS5A. Here we report fluorene compounds showing strong inhibitory effects on GT 1b and 3a of HCV. Moreover, some compounds were effective against resistance-associated variants to DAAs. The structure-activity relationships of the compounds were analyzed. Furthermore, we investigated the molecular bases of the inhibitory activities of some compounds by the molecular docking method.

Optimization of a sensitive and robust strategy for micellar electrokinetic chromatographic analysis of sofosbuvir in combination with its co-formulated hepatitis C antiviral drugs

Based on our previous work with "pseudostationary-ion exchanger sweeping", we use this strategy to develop a sensitive, reliable and robust method for the analysis of the newly-FDA approved hepatitis C antiviral drugs namely; sofosbuvir (SOV), daclatasvir (DAC), ledipasvir (LED) and velpatasvir (VEP) in their pure forms and co-formulated pharmaceutical dosage forms using micellar electrokinetic chromatography (MEKC) as a separation method. For the first time, a successful separation of all the investigated compounds was achieved in less than 8 min using a basic background electrolyte (BGE) composed of 25 mmol L^-1 SDS + 20% (v/v) ACN (acetonitrile) in 10 mmol L^-1 disodium tetraborate buffer (final apparent pH is 9.90). A special focus was given to optimize the composition of the sample matrix to maintain the solubility of the analytes within the sample zone while gaining additional benefits regarding analyte zone focusing. It was found that replacing phosphoric acid (as a sample matrix) with a zwitterionic/isoelectric buffering compound (L-glutamic acid) has a substantial positive impact on the obtained enrichment efficiency. The interplay of other enrichment principles such as the retention factor gradient effect (RFGE) is also discussed. A full validation study is performed based on the pharmacopeial and ICH guidelines. The obtained limits of detection and quantitation are as low as 0.63 and 1.3 μg mL^-1; respectively for SOV and DAC and 1.3 and 2.5 μg mL^-1; respectively for LED and VEP using UV-DAD as a detection method. The selectivity of the developed method for determination of the studied compounds in their pharmaceutical dosage forms or in the presence of ribavirin (RIB) or elbasvir (ELB), which are other prescribed medications in the treatment regimen of patients with hepatitis C virus infection, is demonstrated. It is shown that with acidic sample matrix and basic BGE, an efficient and precise approach was designed in which analyte adsorption on the capillary wall was minimized while keeping repeatable peak height, peak area and migration time together with the highest possible enrichment efficiency.

Developments in the treatment of HCV genotype 3 infection

Introduction: Unlike other hepatitis C virus (HCV) genotypes (GTs), patients infected with GT3 are associated with an increased risk of accelerated liver disease progression. Although early immuno-modulator therapies yielded moderate sustained virologic response (SVR) rates, treatment of GT3 patients has proven more challenging in the era of direct-acting antivirals (DAAs). Areas covered: The review provides an overview of the evolution of therapies against GT3 since the approval of the first immunomodulatory agent nearly 30 years ago. Expert opinion: A greater choice of treatment options is now available for HCV GT3-infected patients. In treatment-naïve patients with or without compensated cirrhosis, SVR rates are comparably high approaching 100% irrespective of treatment option. For treatment-experienced patients, choosing the right therapy is important, especially for those with advanced liver disease. For the few patients who fail with multiple persistent highly resistant DAA substitutions, retreatment options are limited. Additional real-world treatment comparisons are required to confirm differences in SVR in these more difficult-to-treat patients. This also includes patients infected with GT3 subtypes such as GT3b where multiple DAA-resistant substitutions occur naturally. In the absence of new drugs with non-overlapping drug-resistant profiles, an interferon-based therapy may still be beneficial in select patient populations with high-level multiple DAA-resistant substitutions.

Initial- and re-treatment effectiveness of glecaprevir and pibrentasvir for Japanese patients with chronic hepatitis C virus-genotype 1/2/3 infections

BACKGROUND

Glecaprevir and pibrentasvir (GLE/PIB) are potent antiviral agents for hepatitis C virus (HCV) pan-genotypic infections; however, their clinical effectiveness and safety remain limited in the real-world. This study aimed to evaluate viral responses and the safety of GLE/PIB for patients with chronic HCV-1/2/3 infections during both initial- (Arm A) and re-treatment (Arm B) with all-oral direct-acting antiviral agents (DAAs).

METHODS

This prospective-observational cohort study included Japanese patients with chronic HCV-1/2/3 infections (n = 271: 183 in Arm A and 83 in Arm B), who had started receiving GLE/PIB. Primary end point was a sustained virological response (SVR) rate at week 12 (SVR12) after the end of GLE/PIB treatment (EOT).

RESULTS

SVR12 was achieved by 99.4% of patients (180/181: modified intention-to-treat (mITT) analysis excluding 2 patients lost to follow-up) in Arm A. One patient with an HCV-3b infection who discontinued at week 8 failed to achieve SVR12. SVR12 was achieved by 97.7% of patients (85/87: mITT excluding 1 patient lost to follow-up) in Arm B. Virological relapse occurred in 2 patients with HCV-1b, presenting common 5 loci of resistance-associated substitutions (RASs) including A92 RASs in the NS5A lesion at baseline. Any adverse events (AEs) (grade ≥ 3) occurred in 8 patients (3.0%). 8 patients (3.0%) discontinued due to AEs, however, all of them achieved SVR12.

CONCLUSIONS

Initial and re-treatment with GLE/PIB are effective and safe for Japanese patients with HCV-1/2/3 in real-life settings. Further studies are required to elucidate the mechanism underlying treatment failures of GLE/PIB to completely eradicate HCV worldwide.

Long-term persistence of HCV NS5A resistance-associated substitutions after treatment with the HCV NS5A inhibitor, ledipasvir, without sofosbuvir

BACKGROUND

Data on persistence of NS5A resistance-associated substitutions (RASs) may have implications for resistance testing approaches and selection of initial and retreatment strategies.

METHODS

Long-term persistence of NS5A RASs in HCV genotype (GT) 1 infected subjects (n=76) who did not achieve sustained virological response after receiving ledipasvir (LDV) without sofosbuvir (SOF) and were subsequently enrolled in an ongoing 3-year follow-up registry study was investigated by population or deep sequencing.

RESULTS

Of the 76 subjects enrolled, 67 and 9 subjects had GT1a and GT1b infection, respectively. At pretreatment, NS5A RASs were detected in 14% of subjects (11/76) by population sequencing, with three subjects having >1 RAS. All RASs that were detected at pretreatment persisted and were observed at the 96 week visit in the follow-up study (FU96). For the remaining subjects with no detectable RASs at pretreatment, RASs were detected in 98% (63/64) of subjects at virological failure in the parent study and persisted at detectable levels through FU96 in 86% of subjects by deep sequencing (1% cutoff). However, a decline in the quasispecies frequency of most RASs and the number of RASs per subject was observed over time. Phenotypic analysis demonstrated that the majority of NS5A RASs confer similar levels of resistance to LDV and daclatasvir.

CONCLUSIONS

The majority of NS5A RASs can persist at detectable levels for >96 weeks post-treatment in subjects who failed treatment with regimens containing an NS5A inhibitor without SOF, suggesting relatively high fitness of NS5A RASs even in the absence of drug pressure.

DynaMut: predicting the impact of mutations on protein conformation, flexibility and stability

Proteins are highly dynamic molecules, whose function is intrinsically linked to their molecular motions. Despite the pivotal role of protein dynamics, their computational simulation cost has led to most structure-based approaches for assessing the impact of mutations on protein structure and function relying upon static structures. Here we present DynaMut, a web server implementing two distinct, well established normal mode approaches, which can be used to analyze and visualize protein dynamics by sampling conformations and assess the impact of mutations on protein dynamics and stability resulting from vibrational entropy changes. DynaMut integrates our graph-based signatures along with normal mode dynamics to generate a consensus prediction of the impact of a mutation on protein stability. We demonstrate our approach outperforms alternative approaches to predict the effects of mutations on protein stability and flexibility (P-value < 0.001), achieving a correlation of up to 0.70 on blind tests. DynaMut also provides a comprehensive suite for protein motion and flexibility analysis and visualization via a freely available, user friendly web server at http://biosig.unimelb.edu.au/dynamut/.

mCSM-PPI2: predicting the effects of mutations on protein-protein interactions

Protein-protein Interactions are involved in most fundamental biological processes, with disease causing mutations enriched at their interfaces. Here we present mCSM-PPI2, a novel machine learning computational tool designed to more accurately predict the effects of missense mutations on protein-protein interaction binding affinity. mCSM-PPI2 uses graph-based structural signatures to model effects of variations on the inter-residue interaction network, evolutionary information, complex network metrics and energetic terms to generate an optimised predictor. We demonstrate that our method outperforms previous methods, ranking first among 26 others on CAPRI blind tests. mCSM-PPI2 is freely available as a user friendly webserver at http://biosig.unimelb.edu.au/mcsm_ppi2/.

Dehydrojuncusol, a Natural Phenanthrene Compound Extracted from Juncus maritimus, Is a New Inhibitor of Hepatitis C Virus RNA Replication

Recent emergence of direct-acting antivirals (DAAs) targeting hepatitis C virus (HCV) proteins has considerably enhanced the success of antiviral therapy. However, the appearance of DAA-resistant-associated variants is a cause of treatment failure, and the high cost of DAAs renders the therapy not accessible in countries with inadequate medical infrastructures. Therefore, the search for new inhibitors with a lower cost of production should be pursued. In this context, the crude extract of Juncus maritimus Lam. was shown to exhibit high antiviral activity against HCV in cell culture. Bio-guided fractionation allowed the isolation and identification of the active compound, dehydrojuncusol. A time-of-addition assay showed that dehydrojuncusol significantly inhibited HCV infection when added after virus inoculation of HCV genotype 2a (50% effective concentration [EC₅₀] = 1.35 µM). This antiviral activity was confirmed with an HCV subgenomic replicon, and no effect on HCV pseudoparticle entry was observed. Antiviral activity of dehydrojuncusol was also demonstrated in primary human hepatocytes. No in vitro toxicity was observed at active concentrations. Dehydrojuncusol is also efficient on HCV genotype 3a and can be used in combination with sofosbuvir. Interestingly, dehydrojuncusol was able to inhibit RNA replication of two frequent daclatasvir-resistant mutants (L31M or Y93H in NS5A). Finally, mutants resistant to dehydrojuncusol were obtained and showed that the HCV NS5A protein is the target of the molecule. In conclusion, dehydrojuncusol, a natural compound extracted from J. maritimus, inhibits infection of different HCV genotypes by targeting the NS5A protein and is active against resistant HCV variants frequently found in patients with treatment failure.IMPORTANCE Tens of millions of people are infected with hepatitis C virus (HCV) worldwide. Recently marketed direct-acting antivirals (DAAs) targeting HCV proteins have enhanced the efficacy of treatment. However, due to its high cost, this new therapy is not accessible to the vast majority of infected patients. Furthermore, treatment failures have also been reported due to the appearance of viral resistance. Here, we report on the identification of a new HCV inhibitor, dehydrojuncusol, that targets HCV NS5A and is able to inhibit RNA replication of replicons harboring resistance mutations to anti-NS5A DAAs used in current therapy. Dehydrojuncusol is a natural compound isolated from Juncus maritimus, a halophilic plant species that is very common in coastlines worldwide. This molecule might serve as a lead for the development of a new therapy that is more accessible to hepatitis C patients in the future.

Synthesis and Structure-Activity relationship of 1-(5-isoquinolinesulfonyl)piperazine analogues as inhibitors of Mycobacterium tuberculosis IMPDH

Tuberculosis (TB) is a major infectious disease associated increasingly with drug resistance. Thus, new anti-tubercular agents with novel mechanisms of action are urgently required for the treatment of drug-resistant TB. In prior work, we identified compound 1 (cyclohexyl(4-(isoquinolin-5-ylsulfonyl)piperazin-1-yl)methanone) and showed that its anti-tubercular activity is attributable to inhibition of inosine-5′-monophosphate dehydrogenase (IMPDH) in Mycobacterium tuberculosis. In the present study, we explored the structure–activity relationship around compound 1 by synthesizing and evaluating the inhibitory activity of analogues against M. tuberculosis IMPDH in biochemical and whole-cell assays. X-ray crystallography was performed to elucidate the mode of binding of selected analogues to IMPDH. We establish the importance of the cyclohexyl, piperazine and isoquinoline rings for activity, and report the identification of an analogue with IMPDH-selective activity against a mutant of M. tuberculosis that is highly resistant to compound 1. We also show that the nitrogen in urea analogues is required for anti-tubercular activity and identify benzylurea derivatives as promising inhibitors that warrant further investigation.

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Forty-eight analogues of 1-(5-isoquinolinesulfonyl)piperazine were synthesized.

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Biochemical, whole-cell, and X-ray studies were performed to elucidate the IMPDH inhibition.

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Piperazine and isoquinoline rings were essential for target-selective whole-cell activity.

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Compound 47 showed improved IC₅₀ against the MtbIMPDH and maintained on-target whole-cell activity.

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Compound 21 showed activity against IMPDH in both wild type M. tuberculosis and a resistant mutant of compound 1.

Phosphorylated tyrosine 93 of hepatitis C virus nonstructural protein 5A is essential for interaction with host c-Src and efficient viral replication

The hepatitis C virus (HCV) nonstructural protein 5A (NS5A) plays a key role in viral replication and virion assembly, and the regulation of the assembly process critically depends on phosphorylation of both serine and threonine residues in NS5A. We previously identified SRC proto-oncogene, nonreceptor tyrosine kinase (c-Src), as an essential host component of the HCV replication complex consisting of NS5A, the RNA-dependent RNA polymerase NS5B, and c-Src. Pulldown assays revealed an interaction between NS5A and the Src homology 2 (SH2) domain of c-Src; however, the precise binding mode remains undefined. In this study, using a variety of biochemical and biophysical techniques, along with molecular dynamics simulations, we demonstrate that the interaction between NS5A and the c-Src SH2 domain strictly depends on an intact phosphotyrosine-binding competent SH2 domain and on tyrosine phosphorylation within NS5A. Detailed analysis of c-Src SH2 domain binding to a panel of phosphorylation-deficient NS5A variants revealed that phosphorylation of Tyr-93 located within domain 1 of NS5A, but not of any other tyrosine residue, is crucial for complex formation. In line with these findings, effective replication of subgenomic HCV replicons as well as production of infectious virus particles in mammalian cell culture models were clearly dependent on the presence of tyrosine at position 93 of NS5A. These findings indicate that phosphorylated Tyr-93 in NS5A plays an important role during viral replication by facilitating NS5A's interaction with the SH2 domain of c-Src.

A 30 kDa polyethylene glycol-enfuvirtide complex enhances the exposure of enfuvirtide in lymphatic viral reservoirs in rats

HIV therapy with anti-retroviral drugs is limited by the poor exposure of viral reservoirs, such as lymphoid tissue, to these small molecule drugs. We therefore investigated the effect of PEGylation on the anti-retroviral activity and subcutaneous lymphatic pharmacokinetics of the peptide-based fusion inhibitor enfuvirtide in thoracic lymph duct cannulated rats. Both the peptide and the PEG were quantified in plasma and lymph via ELISA. Conjugation to a single 5 kDa linear PEG decreased anti-HIV activity three-fold compared to enfuvirtide. Whilst plasma and lymphatic exposure to peptide mass was moderately increased, the loss of anti-viral activity led to an overall decrease in exposure to enfuvirtide activity. A 20 kDa 4-arm branched PEG conjugated with an average of two enfuvirtide peptides decreased peptide activity by six-fold. Plasma and lymph exposure to enfuvirtide, however, increased significantly such that anti-viral activity was increased two- and six-fold respectively. The results suggest that a multi-enfuvirtide-PEG complex may optimally enhance the anti-retroviral activity of the peptide in plasma and lymph.

Overview of HCV Life Cycle with a Special Focus on Current and Possible Future Antiviral Targets

Hepatitis C infection is the leading cause of liver diseases worldwide and a major health concern that affects an estimated 3% of the global population. Novel therapies available since 2014 and 2017 are very efficient and the WHO considers HCV eradication possible by the year 2030. These treatments are based on the so-called direct acting antivirals (DAAs) that have been developed through research efforts by academia and industry since the 1990s. After a brief overview of the HCV life cycle, we describe here the functions of the different targets of current DAAs, the mode of action of these DAAs and potential future inhibitors.

Exploring Protein Supersecondary Structure Through Changes in Protein Folding, Stability, and Flexibility

The ability to predict how mutations affect protein structure, folding, and flexibility can elucidate the molecular mechanisms leading to disruption of supersecondary structures, the emergence of phenotypes, as well guiding rational protein engineering. The advent of fast and accurate computational tools has enabled us to comprehensively explore the landscape of mutation effects on protein structures, prioritizing mutations for rational experimental validation.Here we describe the use of two complementary web-based in silico methods, DUET and DynaMut, developed to infer the effects of mutations on folding, stability, and flexibility and how they can be used to explore and interpret these effects on protein supersecondary structures.

Visualisation and analysis of hepatitis C virus non-structural proteins using super-resolution microscopy

Hepatitis C virus (HCV) RNA replication occurs in the cytosol of infected cells within a specialised membranous compartment. How the viral non-structural (NS) proteins are associated and organised within these structures remains poorly defined. We employed a super-resolution microscopy approach to visualise NS3 and NS5A in HCV infected cells. Using single molecule localisation microscopy, both NS proteins were resolved as clusters of localisations smaller than the diffraction-limited volume observed by wide-field. Analysis of the protein clusters identified a significant difference in size between the NS proteins. We also observed a reduction in NS5A cluster size following inhibition of RNA replication using daclatasvir, a phenotype which was maintained in the presence of the Y93H resistance associated substitution and not observed for NS3 clusters. These results provide insight into the NS protein organisation within hepatitis C virus RNA replication complexes and the mode of action of NS5A inhibitors.

Sulfur(vi) fluoride exchange as a key reaction for synthesizing biaryl sulfate core derivatives as potent hepatitis C virus NS5A inhibitors and their structure-activity relationship studies

Extremely potent, new hepatitis C virus (HCV) nonstructural 5A (NS5A) featuring substituted biaryl sulfate core structures was designed and synthesized. Based on the previously reported novel HCV NS5A inhibitors featuring biaryl sulfate core structures which exhibit two-digit picomolar half-maximal effective concentration (EC50) values against HCV genotype 1b and 2a, the new inhibitors equipped with the sulfate core structures containing diversely substituted aryl groups were explored. In this study, highly efficient, chemoselective coupling reactions between an arylsulfonyl fluoride and an aryl silyl ether, known as the sulfur(vi) fluoride exchange (SuFEx) reaction, were utilized. Among the inhibitors prepared based on the SuFEx chemistry, compounds 14, 15 and 29 exhibited two-digit picomolar EC50 values against GT-1b and single digit or sub nanomolar activities against the HCV GT-2a strain. Nonsymmetrical inhibitors containing an imidazole and amide moieties on each side of the sulfate core structures were also synthesized. In addition, a biotinylated probe targeting NS5A protein was prepared for labeling using the same synthetic methodology.

HCV NS5A dimer interface residues regulate HCV replication by controlling its self-interaction, hyperphosphorylation, subcellular localization and interaction with cyclophilin A

The HCV NS5A protein plays multiple roles during viral replication, including viral genome replication and virus particle assembly. The crystal structures of the NS5A N-terminal domain indicated the potential existence of the NS5A dimers formed via at least two or more distinct dimeric interfaces. However, it is unknown whether these different forms of NS5A dimers are involved in its numerous functions. To address this question, we mutated the residues lining the two different NS5A dimer interfaces and determined their effects on NS5A self-interaction, NS5A-cyclophilin A (CypA) interaction, HCV RNA replication and infectious virus production. We found that the mutations targeting either of two dimeric interfaces disrupted the NS5A self-interaction in cells. The NS5A dimer-interrupting mutations also inhibited both viral RNA replication and infectious virus production with some genotypic differences. We also determined that reduced NS5A self-interaction was associated with altered NS5A-CypA interaction, NS5A hyperphosphorylation and NS5A subcellular localization, providing the mechanistic bases for the role of NS5A self-interaction in multiple steps of HCV replication. The NS5A oligomers formed via different interfaces are likely its functional form, since the residues at two different dimeric interfaces played similar roles in different aspects of NS5A functions and, consequently, HCV replication. In conclusion, this study provides novel insight into the functional significance of NS5A self-interaction in different steps of the HCV replication, potentially, in the form of oligomers formed via multiple dimeric interfaces.

HCV NS5A is a multifunctional protein involved in both viral RNA replication and infectious virus production, and is a target of one of the most potent antivirals available to date. However, the mode of action of NS5A inhibitors is still unclear due to the lack of mechanistic detail regarding NS5A functions during HCV life cycles. In this study, we have provided evidence that surface-exposed NS5A residues involved in two different dimeric interactions in crystal structures are indeed involved in NS5A self-interactions in cells. We also showed that these NS5A residues play critical role in HCV RNA replication and infectious virus production by regulating NS5A hyperphosphorylation, its subcellular localization and its interaction with host protein CypA. Overall, our data support the functional significance of “NS5A oligomers” formed via multiple interfaces in HCV replication. We speculate that the NS5A inhibitors exploited the NS5A oligomer-dependent functions during HCV replication, rather than targeting individual NS5A, which consequently resulted in their high potency.

Epistatic Interactions in NS5A of Hepatitis C Virus Suggest Drug Resistance Mechanisms

Hepatitis C virus (HCV) causes a major health burden and can be effectively treated by direct-acting antivirals (DAAs). The non-structural protein 5A (NS5A), which plays a role in the viral genome replication, is one of the DAAs’ targets. Resistance-associated viruses (RAVs) harbouring NS5A resistance-associated mutations (RAMs) have been described at baseline and after therapy failure. A mutation from glutamine to arginine at position 30 (Q30R) is a characteristic RAM for the HCV sub/genotype (GT) 1a, but arginine corresponds to the wild type in the GT-1b; still, GT-1b strains are susceptible to NS5A-inhibitors. In this study, we show that GT-1b strains with R30Q often display other specific NS5A substitutions, particularly in positions 24 and 34. We demonstrate that in GT-1b secondary substitutions usually happen after initial R30Q development in the phylogeny, and that the chemical properties of the corresponding amino acids serve to restore the positive charge in this region, acting as compensatory mutations. These findings may have implications for RAVs treatment.