Recent advances in drug discovery of benzothiadiazine and related analogs as HCV NS5B polymerase inhibitors

In silico design of a lipid-like compound targeting KRAS4B-G12D through non-covalent bonds

One of the most common drivers in human cancer is the peripheral membrane protein KRAS4B, able to promote oncogenic signalling. To signal, oncogenic KRAS4B not only requires a sufficient nucleotide exchange, but also needs to recruit effectors by exposing its effector-binding sites while anchoring to the phospholipid bilayer where KRAS4B-mediated signalling events occur. The enzyme phosphodiesterase-δ plays an important role in sequestering KRAS4B from the cytoplasm and targeting it to cellular membranes of different cell species. In this work, we present an in silico design of a lipid-like compound that has the remarkable feature of being able to target both an oncogenic KRAS4B-G12D mutant and the phosphodiesterase-δ enzyme. This double action is accomplished by adding a lipid tail (analogous to the farnesyl group of the KRAS4B protein) to an previously known active compound (2H-1,2,4-benzothiadiazine, 3,4-dihydro-,1,1-dioxide). The proposed lipid-like molecule was found to lock KRAS4B-G12D in its GDP-bound state by adjusting the effector-binding domain to be blocked by the interface of the lipid bilayer. Meanwhile, it can tune GTP-bound KRAS4B-G12D to shift from the active orientation state to the inactive state. The proposed compound is also observed to stably accommodate itself in the prenyl-binding pocket of phosphodiesterase-δ, which impairs KRAS4B enrichment at the lipid bilayer, potentially reducing the proliferation of KRAS4B inside the cytoplasm and its anchoring at the bilayer. In conclusion, we report a potential inhibitor of KRAS4B-G12D with a lipid tail attached to a specific warhead, a compound which has not yet been considered for drugs targeting RAS mutants. Our work provides new ways to target KRAS4B-G12D and can also foster drug discovery efforts for the targeting of oncogenes of the RAS family and beyond.

Screening and identification of 3-aryl-quinolin-2-one derivatives as antiviral agents against influenza A

Quinolin-2-one represents an important and valuable chemical motif that possesses a wide variety of biological activities; however, the anti-influenza activities of quinolin-2-one-containing compounds were rarely reported. Herein, we describe the screening and identification of 3-aryl-quinolin-2-one derivatives as a novel class of antiviral agents. The 3-aryl-quinolinone derivatives were synthesized via an efficient copper-catalyzed reaction cascade that we previously developed. Using this synthetic method, preliminary structure-activity relationships of this scaffold against the influenza A virus infection were systematically explored. The most potent compound 34 displayed IC₅₀ values of 2.14 and 4.88 μM against the replication of H3N2 (A/HK/8/68) and H1N1 (A/WSN/33) strains, respectively, without apparent cytotoxicity on MDCK cells. We further demonstrated that 27 and 34 potently inhibited the plaque formation of the IAV, rendering this scaffold attractive for pursuing novel anti-influenza agents.

Simplified, interpretable graph convolutional neural networks for small molecule activity prediction

We here present a streamlined, explainable graph convolutional neural network (gCNN) architecture for small molecule activity prediction. We first conduct a hyperparameter optimization across nearly 800 protein targets that produces a simplified gCNN QSAR architecture, and we observe that such a model can yield performance improvements over both standard gCNN and RF methods on difficult-to-classify test sets. Additionally, we discuss how reductions in convolutional layer dimensions potentially speak to the “anatomical” needs of gCNNs with respect to radial coarse graining of molecular substructure. We augment this simplified architecture with saliency map technology that highlights molecular substructures relevant to activity, and we perform saliency analysis on nearly 100 data-rich protein targets. We show that resultant substructural clusters are useful visualization tools for understanding substructure-activity relationships. We go on to highlight connections between our models’ saliency predictions and observations made in the medicinal chemistry literature, focusing on four case studies of past lead finding and lead optimization campaigns.

Structure of benzothiadiazine at zwitterionic phospholipid cell membranes

The use of drugs derived from benzothiadiazine, which is a bicyclic heterocyclic benzene derivative, has become a widespread treatment for diseases such as hypertension (treated with diuretics such as bendroflumethiazide or chlorothiazide), low blood sugar (treated with non-diuretic diazoxide), or the human immunodeficiency virus, among others. In this work, we have investigated the interactions of benzothiadiazine with the basic components of cell membranes and solvents, such as phospholipids, cholesterol, ions, and water. The analysis of the mutual microscopic interactions is of central importance to elucidate the local structure of benzothiadiazine as well as the mechanisms responsible for the access of benzothiadiazine to the interior of the cell. We have performed molecular dynamics simulations of benzothiadiazine embedded in three different model zwitterionic bilayer membranes made by dimyristoylphosphatidylcholine, dioleoylphosphatidylcholine, 1,2-dioleoyl-sn-glycero-3-phosphoserine, and cholesterol inside aqueous sodium-chloride solution in order to systematically examine microscopic interactions of benzothiadiazine with the cell membrane at liquid-crystalline phase conditions. From data obtained through radial distribution functions, hydrogen-bonding lengths, and potentials of mean force based on reversible work calculations, we have observed that benzothiadiazine has a strong affinity to stay at the cell membrane interface although it can be fully solvated by water in short periods of time. Furthermore, benzothiadiazine is able to bind lipids and cholesterol chains by means of single and double hydrogen-bonds of different characteristic lengths.

Novel inhibitors against wild-type and mutated HCV NS3 serine protease: an in silico study

In 2011, the FDA approved boceprevir as a hepatitis C virus (HCV) NS3 serine protease inhibitor. The sustained virological response rate for treatment with this approved compound is considerably low. Patients have not responded as much as expected to boceprevir therapy. In this in silico study, modified boceprevir compounds are suggested and tested on wild-type HCV NS3 protease and 19 mutated HCV NS3 proteases using molecular docking. Results reveal the superiority of two of the proposed modified compounds to boceprevir. One of which appears to be more potent than boceprevir itself concerning activity against wild-type NS3 and most of the examined mutated NS3 proteases.

Novel Guanosine Derivatives as Anti-HCV NS5b Polymerase: A QSAR and Molecular Docking Study

BACKGROUND

IDX-184 is a guanosine derivative having a potent inhibitory performance against HCV NS5b polymerase.

OBJECTIVE

To test three different groups of 2'C - modified analogues of guanosine nucleotide against HCV polymerase.

METHOD

Using combined Quantitative Structure-Activity Relationships (QSAR) and molecular docking, the suggested compounds are studied.

RESULTS

Examining the docked structures of the compounds with experimentally solved NS5b structure (PDB ID: 2XI3) revealed that most of the compounds have the same mode of interaction as that of guanosine nucleotide and hence, NS5b inhibition is possible.

CONCLUSION

It is revealed that sixteen modifications have a better binding affinity to NS5b compared to guanosine. In addition, seven more compounds are better in NS5b binding compared to the approved drug, sofosbuvir, and the compound under clinical trials, IDX-184. Hence, these compounds could be potent HCV NS5b inhibitors. Summary Points: Novel guanosine modifications were introduced in silico and optimized using QM. QSAR and docking calculations are performed to test the binding affinity of the compounds to HCV NS5b active site. Comparison between the binding affinities and the mode of interactions of the compounds and both GTP and IDX-184 is performed. Structural mining to quantify the mode of binding of the compounds to NS5b active site pocket.

A review on HCV inhibitors: Significance of non-structural polyproteins

Hepatitis C virus (HCV) mortality and morbidity is a world health misery with an approximate 130–150 million chronically HCV tainted and suffering individuals and it initiate critical liver malfunction like cirrhosis, hepatocellular carcinoma or liver HCV cancer. HCV NS5B protein one of the best studied therapeutic target for the identification of new drug candidates to be added to the combination or multiple combination medication recently approved. During the past few years, NS5B has thus been an important object of attractive medicinal chemistry endeavors, which induced to the surfacing of betrothal preclinical drug molecules. In this scenario, the current review set limit to discuss research published on NS5B and few other therapeutic functional inhibitors concentrating on hit investigation, hit to lead optimization, ADME parameters evaluation, and the SAR data which was out for each compound type and similarity taken into consideration. The discussion outlined in this specific review will surly helpful and vital tool for those medicinal chemists investigators working with HCV research programs mainly pointing on NS5B and set broad spectrum identification of creative anti HCV compounds. This mini review also tells each and every individual compound ability related how much they are active against NS5B and few other targets.

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Hepatitis C infection causes severe liver cirrhosis and carcinoma.

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The new acute HCV infections are raising every year and mortality rate become serious concern.

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The plausible list of anti-HCV drugs and clinical agents were listed in this review.

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The divergent medicinal scaffolds as anti-HCV agents were presented as per their targets.

Quantitative Structure-Activity Relationship Model for HCVNS5B inhibitors based on an Antlion Optimizer-Adaptive Neuro-Fuzzy Inference System

The global prevalence of hepatitis C Virus (HCV) is approximately 3% and one-fifth of all HCV carriers live in the Middle East, where Egypt has the highest global incidence of HCV infection. Quantitative structure-activity relationship (QSAR) models were used in many applications for predicting the potential effects of chemicals on human health and environment. The adaptive neuro-fuzzy inference system (ANFIS) is one of the most popular regression methods for building a nonlinear QSAR model. However, the quality of ANFIS is influenced by the size of the descriptors, so descriptor selection methods have been proposed, although these methods are affected by slow convergence and high time complexity. To avoid these limitations, the antlion optimizer was used to select relevant descriptors, before constructing a nonlinear QSAR model based on the PIC50 and these descriptors using ANFIS. In our experiments, 1029 compounds were used, which comprised 579 HCVNS5B inhibitors (PIC50 < ~14) and 450 non-HCVNS5B inhibitors (PIC50 > ~14). The experimental results showed that the proposed QSAR model obtained acceptable accuracy according to different measures, where [Formula: see text] was 0.952 and 0.923 for the training and testing sets, respectively, using cross-validation, while [Formula: see text] was 0.8822 using leave-one-out (LOO).

Zika virus: novel guanosine derivatives revealed strong binding and possible inhibition of the polymerase

Aim: During the last 2 years, the zika virus (ZIKV) outbreak has rapidly spread worldwide to more than 80 countries. In the last decade, nucleotide inhibitors (NIs) have been widely studied against different viruses such as HCV and human coronaviruses. Materials & methods: In this study, four novel guanosine derivatives were tested in silico against ZIKV polymerase. Discussion: The modified guanosines at position 2′ in the ribose ring gave comparable binding energies to that of GTP; hence, it could compete with GTP for the ZIKV polymerase active site and halt viral replication. Conclusion: The suggested guanosine derivatives had a higher affinity than ribavirin (wide range antiviral drug) in binding to ZIKV polymerase.

Chemical genetics-based development of small molecules targeting hepatitis C virus

Hepatitis C virus (HCV) infection is a major worldwide problem that has emerged as one of the most significant diseases affecting humans. There are currently no vaccines or efficient therapies without side effects, despite today's advanced medical technology. Currently, the common therapy for most patients (i.e. genotype 1) is combination of HCV-specific direct-acting antivirals (DAAs). Up to 2011, the standard of care (SOC) was a combination of peg-IFNα with ribavirin (RBV). After approval of NS3/4A protease inhibitor, SOC was peg-IFNα and RBV with either the first-generation DAAs boceprevir or telaprevir. In the past several years, various novel small molecules have been discovered and some of them (i.e., HCV polymerase, protease, helicase and entry inhibitors) have undergone clinical trials. Between 2013 and 2016, the second-generation DAA drugs simeprevir, asunaprevir, daclatasvir, dasabuvir, sofosbuvir, and elbasvir were approved, as well as the combinational drugs Harvoni^®, Zepatier^®, Technivie^®, and Epclusa^®. A number of reviews have been recently published describing the structure-activity relationship (SAR) in the development of HCV inhibitors and outlining current therapeutic approaches to hepatitis C infection. Target identification involves studying a drug's mechanism of action (MOA), and a variety of target identification methods have been developed in the past few years. Chemical biology has emerged as a powerful tool for studying biological processes using small molecules. The use of chemical genetic methods is a valuable strategy for studying the molecular mechanisms of the viral lifecycle and screening for anti-viral agents. Two general screening approaches have been employed: forward and reverse chemical genetics. This review reveals information on the small molecules in HCV drug discovery by using chemical genetics for targeting the HCV protein and describes successful examples of targets identified with these methods.

Molecular modeling and docking revealed superiority of IDX-184 as HCV polymerase inhibitor

Aim: IDX-184 is a nonstructural 5b nucleoside inhibitor (NI) that was under clinical trials against HCV. This work adopts a molecular modeling approach in order to study the interaction between IDX-184 and HCV polymerase from four different genotypes. Methods: Comparisons to the native nucleotide (Guanosine triphosphate) and other NIs were performed using interaction descriptors, calculated using semiempirical quantum mechanics and molecular docking. Results: IDX-184 shows potent binding to the active site of the polymerases. In addition, IDX-184 was better than Sofosbuvir and Ribavirin when docked into polymerase active site (even with experimentally solved structure). Conclusion: Analysis of the interaction descriptors and docking complexes suggests IDX-184 as a superior NI against the studied HCV subtypes.

Discovery of benzophosphadiazine drug candidate IDX375: A novel hepatitis C allosteric NS5B RdRp inhibitor

Hepatitis C virus (HCV) NS5B RNA-dependent RNA polymerase (RdRp) plays a central role in virus replication. NS5B has no functional equivalent in mammalian cells, and as a consequence is an attractive target for selective inhibition. This paper describes the discovery of a novel family of HCV NS5B non-nucleoside inhibitors inspired by the bioisosterism between sulfonamide and phosphonamide. Systematic structural optimization in this new series led to the identification of IDX375, a potent non-nucleoside inhibitor that is selective for genotypes 1a and 1b. The structure and binding domain of IDX375 were confirmed by X-ray co-crystalisation study.

Synthesis and biological evaluation of novel isoxazolines linked via piperazine to 2- benzoisothiazoles as potent apoptotic agents

Synthesis of 3-(4-((3-Phenyl-4,5-dihydroisoxazol-5-yl)methyl)piperazin-1-yl) benzoisothiazole derivatives (5a-i), which constitute a new class of isoxazolines, has been accomplished in regio-selective manner. These derivatives have been prepared by employing the reaction between substituted aldoximes (4a-i) and 3-(4-Allylpiperazin-1-yl) benzoisothiazole in presence of chloramine-T which afforded in good yields. These compounds were screened for cytotoxic activity on tumor cells. Four among the nine synthesized compounds were found to exhibit potent cytotoxic and antineoplastic activities in comparison to tumor necrosis factor-related apoptosis inducing ligand (TRAIL) protein in mammalian cancer cells. The rest of the derivatives showed moderate activity.

Zika viral polymerase inhibition using anti-HCV drugs both in market and under clinical trials

In the last few months, a new Zika virus (ZIKV) outbreak evolved in America. In accordance, World Health Organization (WHO) in February 2016 declared it as Public Health Emergency of International Concern (PHEIC). ZIKV infection was reported in more than 60 countries and the disease was spreading since 2007 but with little momentum. Many antiviral drugs are available in market or in laboratories under clinical trials, could affect ZIKV infection. In silico docking study were performed on the ZIKV polymerase to test some of Hepatitis C Virus (HCV) drugs (approved and in clinical trials). The results show potency of almost all of the studied compounds on ZIKV polymerase and hence inhibiting the propagation of the disease. In addition, the study suggested two nucleotide inhibitors (IDX-184 and MK0608) that may be tested as drugs against ZIKV infection. J. Med. Virol. 88:2044-2051, 2016. © 2016 Wiley Periodicals, Inc.

IDX-184 is a superior HCV direct-acting antiviral drug: a QSAR study

Abstract

Quantitative structure-activity relationship (QSAR) parameters are good indicators for the reactivity of direct-acting antiviral drugs. Since molecular structure is related to molecular function, careful selection of molecular substitutions will result in more drugs that are potent. In this work, QSAR parameters are selected in order to compare the four drugs used as nucleotide inhibitors (NIs) for non-structural 5B (NS5B) RNA-dependent RNA polymerase (RdRp) of hepatitis C virus (HCV). These drugs are: ribavirin (widely used over the last 20 years), sofosbuvir (approved on December 2013 by FDA), and finally IDX-184 and R7128 (phase IIb of clinical trial drugs). The nucleotide analogues uracil (U), guanine (G), and cytosine (C) from which these drugs are fabricated are also compared to that group of drugs. QSAR parameters suggested that the drug IDX-184 is the best among all of the studied NIs. It also shows that NIs are always more reactive than their parent nucleotide.

Graphical Abstract

The active site environment of 12 amino acids coordinated with IDX-184 through two Mg²⁺. The interaction with HCV subtypes 1a, 2b, and 3b is better than 4a subtype.

Discovery of Novel Hepatitis C Virus NS5B Polymerase Inhibitors by Combining Random Forest, Multiple e-Pharmacophore Modeling and Docking

The NS5B polymerase is one of the most attractive targets for developing new drugs to block Hepatitis C virus (HCV) infection. We describe the discovery of novel potent HCV NS5B polymerase inhibitors by employing a virtual screening (VS) approach, which is based on random forest (RB-VS), e-pharmacophore (PB-VS), and docking (DB-VS) methods. In the RB-VS stage, after feature selection, a model with 16 descriptors was used. In the PB-VS stage, six energy-based pharmacophore (e-pharmacophore) models from different crystal structures of the NS5B polymerase with ligands binding at the palm I, thumb I and thumb II regions were used. In the DB-VS stage, the Glide SP and XP docking protocols with default parameters were employed. In the virtual screening approach, the RB-VS, PB-VS and DB-VS methods were applied in increasing order of complexity to screen the InterBioScreen database. From the final hits, we selected 5 compounds for further anti-HCV activity and cellular cytotoxicity assay. All 5 compounds were found to inhibit NS5B polymerase with IC50 values of 2.01-23.84 μM and displayed anti-HCV activities with EC50 values ranging from 1.61 to 21.88 μM, and all compounds displayed no cellular cytotoxicity (CC50 > 100 μM) except compound N2, which displayed weak cytotoxicity with a CC50 value of 51.3 μM. The hit compound N2 had the best antiviral activity against HCV, with a selective index of 32.1. The 5 hit compounds with new scaffolds could potentially serve as NS5B polymerase inhibitors through further optimization and development.

Quantitative structure and bioactivity relationship study on HCV NS5B polymerase inhibitors

Several QSAR (quantitative structure-activity relationship) models for predicting the inhibitory activity of 333 hepatitis C virus (HCV) NS5B polymerase inhibitors were developed. All the inhibitors are HCV polymerase non-nucleoside analogue inhibitors (NNIs) fitting into the pocket of the NNI III binding site. For each molecule, global descriptors and 2D property autocorrelation descriptors were calculated from the program ADRIANA.Code. Pearson correlation analysis was used to select the significant descriptors for building models. The whole dataset was split into a training set and a test set randomly or using a Kohonen's self-organizing map (SOM). Then, the inhibitory activity of 333 HCV NS5B polymerase inhibitors was predicted using multilinear regression (MLR) analysis and support vector machine (SVM) method, respectively. For the test set of the best model (Model 2B), correlation coefficient of 0.91 was achieved. Some molecular descriptors, such as molecular complexity (Complexity), the number of hydrogen bonding donors (HDon) and the solubility of the molecule in water (log S) were found to be very important factors which determined the bioactivity of the HCV NS5B inhibitors. Some other molecular properties such as electrostatic and charge properties also played important roles in the interaction between the ligand and the protein. The selected molecular descriptors were further confirmed by analysing the interaction between two representative inhibitors and the polymerase in their crystal structures.

Molecular modeling comparison of the performance of NS5b polymerase inhibitor (PSI-7977) on prevalent HCV genotypes

The current available treatment for hepatitis C virus (HCV)-the causative of liver cirrhosis and development of liver cancer-is a dual therapy using modified interferon and ribavirin. While this regimen increases the sustained viral response rate up to 40-80 % in different genotypes, unfortunately, it is poorly tolerated by patients. PSI-7977, a prodrug for PSI-7409, is a Non-Structural 5b (NS5b) polymerase nucleoside inhibitor that is currently in phase III clinical trials. The activated PSI-7977 is a direct acting antiviral (DAA) drug that acts on NS5b polymerase of HCV through a coordination bond with the two Mg(+2) present at the GDD active site motif. The present work utilizes a molecular modeling approach for studying the interaction between the activated PSI-7977 and the 12 amino acids constituting a 5 Å region surrounding the GDD active triad motif for HCV genotypes 1a, 2b, 3b and 4a. The analysis of the interaction parameters suggests that PSI-7977 is probably a better DAA drug for HCV genotypes 1a and 3b rather than genotypes 2b and 4a.

Design and Development of NS5B Polymerase Non‐nucleoside Inhibitors for the Treatment of Hepatitis C Virus Infection

The hepatitis C virus (HCV) infects an estimated 130–170 million people worldwide and is associated with life‐threatening liver diseases. The recent introduction of the first two HCV direct‐acting antivirals (DAAs) as a complement to the interferon/ribavirin standard of care has provided patients with improved outcomes. Still, 25–30% of subjects infected with genotype 1 HCV do not respond adequately to treatment owing to the emergence of resistant virus and many suffer from severe side effects. A paradigm shift towards the development of interferon‐free combinations of DAAs with complementary modes of action is currently taking place. Virally encoded proteins and enzymes have become the target of HCV drug discovery efforts and several promising new agents are currently being evaluated in the clinic for treatment of chronic HCV infection. The NS5B RNA‐dependent RNA polymerase is responsible for replication of viral RNA and plays a pivotal role in the virus life cycle. NS5B is undoubtedly the most druggable HCV target and is susceptible to several classes of allosteric inhibitors that bind to four distinct sites on the enzyme. This chapter describes successful strategies that have led to the discovery of HCV NS5B antivirals. It is divided according to allosteric sites and describes how each of the known families of inhibitors was discovered, characterized and optimized to provide clinical candidates. When available, the strategies adopted by medicinal chemists to optimize initial leads and address challenges and liabilities encountered on the path to candidate selection are described, along with reported clinical outcomes.

Structure-based discovery of pyrazolobenzothiazine derivatives as inhibitors of hepatitis C virus replication

The NS5B RNA-dependent RNA polymerase is an attractive target for the development of novel and selective inhibitors of hepatitis C virus replication. To identify novel structural hits as anti-HCV agents, we performed structure-based virtual screening of our in-house library followed by rational drug design, organic synthesis, and biological testing. These studies led to the identification of pyrazolobenzothiazine scaffold as a suitable template for obtaining novel anti-HCV agents targeting the NS5B polymerase. The best compound of this series was the meta-fluoro-N-1-phenyl pyrazolobenzothiazine derivative 4a, which exhibited an EC50 = 3.6 μM, EC90 = 25.6 μM, and CC50 > 180 μM in the Huh 9-13 replicon system, thus providing a good starting point for further hit evolution.

Synthesis and biological activity of novel 3-heteroaryl-2H-pyrido[4,3-e][1,2,4]thiadiazine and 3-heteroaryl-2H-benzo[e][1,2,4]thiadiazine 1,1-dioxides

ABSTRACT

A series of novel 1,2,4-thiadiazine 1,1-dioxides were synthesized by condensation of 2-chlorobenzenesulfonamide and 4-chloropyridine-3-sulfonamide with heterocyclic methyl carbimidates obtained from heterocyclic carbonitriles and used at the time of their creation. Substituted amidines were isolated as the intermediates in the reaction with 2-chlorobenzenesulfonamide. Those intermediates were successfully cyclized to corresponding 1,2,4-thiadiazine 1,1-dioxides in pyridine with the addition of DBU. The newly synthesized compounds were evaluated for their tuberculostatic and anticancer activities. Eight compounds were able to inhibit the growth of some renal and non-small cell lung cancer cell lines.

GRAPHICAL ABSTRACT

Classification of HCV NS5B polymerase inhibitors using support vector machine

Using a support vector machine (SVM), three classification models were built to predict whether a compound is an active or weakly active inhibitor based on a dataset of 386 hepatitis C virus (HCV) NS5B polymerase NNIs (non-nucleoside analogue inhibitors) fitting into the pocket of the NNI III binding site. For each molecule, global descriptors, 2D and 3D property autocorrelation descriptors were calculated from the program ADRIANA.Code. Three models were developed with the combination of different types of descriptors. Model 2 based on 16 global and 2D autocorrelation descriptors gave the highest prediction accuracy of 88.24% and MCC (Matthews correlation coefficient) of 0.789 on test set. Model 1 based on 13 global descriptors showed the highest prediction accuracy of 86.25% and MCC of 0.732 on external test set (including 80 compounds). Some molecular properties such as molecular shape descriptors (InertiaZ, InertiaX and Span), number of rotatable bonds (NRotBond), water solubility (LogS), and hydrogen bonding related descriptors performed important roles in the interactions between the ligand and NS5B polymerase.