New binding site conformations of the dengue virus NS3 protease accessed by molecular dynamics simulation

Aminopyrimidine Derivatives as Multiflavivirus Antiviral Compounds Identified from a Consensus Virtual Screening Approach

Around three billion people are at risk of infection by the dengue virus (DENV) and potentially other flaviviruses. Worldwide outbreaks of DENV, Zika virus (ZIKV), and yellow fever virus (YFV), the lack of antiviral drugs, and limitations on vaccine usage emphasize the need for novel antiviral research. Here, we propose a consensus virtual screening approach to discover potential protease inhibitors (NS3pro) against different flavivirus. We employed an in silico combination of a hologram quantitative structure-activity relationship (HQSAR) model and molecular docking on characterized binding sites followed by molecular dynamics (MD) simulations, which filtered a data set of 7.6 million compounds to 2,775 hits. Lastly, docking and MD simulations selected six final potential NS3pro inhibitors with stable interactions along the simulations. Five compounds had their antiviral activity confirmed against ZIKV, YFV, DENV-2, and DENV-3 (ranging from 4.21 ± 0.14 to 37.51 ± 0.8 μM), displaying aggregator characteristics for enzymatic inhibition against ZIKV NS3pro (ranging from 28 ± 7 to 70 ± 7 μM). Taken together, the compounds identified in this approach may contribute to the design of promising candidates to treat different flavivirus infections.

Designing drugs when there is low data availability: one-shot learning and other approaches to face the issues of a long-term concern

INTRODUCTION

Modern drug discovery generally is accessed by useful information from previous large databases or uncovering novel data. The lack of biological and/or chemical data tends to slow the development of scientific research and innovation. Here, approaches that may help provide solutions to generate or obtain enough relevant data or improve/accelerate existing methods within the last five years were reviewed.

AREAS COVERED

One-shot learning (OSL) approaches, structural modeling, molecular docking, scoring function space (SFS), molecular dynamics (MD), and quantum mechanics (QM) may be used to amplify the amount of available data to drug design and discovery campaigns, presenting methods, their perspectives, and discussions to be employed in the near future.

EXPERT OPINION

Recent works have successfully used these techniques to solve a range of issues in the face of data scarcity, including complex problems such as the challenging scenario of drug design aimed at intrinsically disordered proteins and the evaluation of potential adverse effects in a clinical scenario. These examples show that it is possible to improve and kickstart research from scarce available data to design and discover new potential drugs.

Ligand Accessibility Insights to the Dengue Virus NS3-NS2B Protease Assessed by Long-Timescale Molecular Dynamics Simulations

Dengue is a tropical disease caused by the dengue virus (DENV), with an estimate of 300 million new cases every year. Due to the limited vaccine efficiency and absence of effective antiviral treatment, new drug candidates are urgently needed. DENV NS3-NS2B protease complex is essential for viral post-translational processing and maturation, and this enzyme has been extensively studied as a relevant drug target. Crystal structures often underestimate NS3-NS2B flexibility, whereas they can adopt different conformational states depending on the bound substrate. We conducted molecular dynamics simulations (∼30 μs) with a non- and covalently bound inhibitor to understand the conformational changes in the DENV-3 NS3-NS2B complex. Our results show that the open-closing movement of the protease exposes multiple druggable subpockets that can be investigated in later drug discovery efforts.

Virtual Screening for Potential Inhibitors of Human Hexokinase II for the Development of Anti-Dengue Therapeutics

Dengue fever, which is a disease caused by the dengue virus (DENV), is a major unsolved issue in many tropical and sub-tropical regions of the world. The absence of treatment that effectively prevent further viral propagation inside the human’s body resulted in a high number of deaths globally each year. Thus, novel anti-dengue therapies are required for effective treatment. Human hexokinase II (HKII), which is the first enzyme in the glycolytic pathway, is an important drug target due to its significant impact on viral replication and survival in host cells. In this study, 23.1 million compounds were computationally-screened against HKII using the Ultrafast Shape Recognition with a CREDO Atom Types (USRCAT) algorithm. In total, 300 compounds with the highest similarity scores relative to three reference molecules, known as Alpha-D-glucose (GLC), Beta-D-glucose-6-phosphate (BG6), and 2-deoxyglucose (2DG), were aligned. Of these 300 compounds, 165 were chosen for further structure-based screening, based on their similarity scores, ADME analysis, the Lipinski’s Rule of Five, and virtual toxicity test results. The selected analogues were subsequently docked against each domain of the HKII structure (PDB ID: 2NZT) using AutoDock Vina programme. The three top-ranked compounds for each query were then selected from the docking results based on their binding energy, the number of hydrogen bonds formed, and the specific catalytic residues. The best docking results for each analogue were observed for the C-terminus of Chain B. The top-ranked analogues of GLC, compound 10, compound 26, and compound 58, showed predicted binding energies of −7.2, −7.0, and −6.10 kcal/mol and 7, 5, and 2 hydrogen bonds, respectively. The analogues of BG6, compound 30, compound 36, and compound 38, showed predicted binding energies of −7.8, −7.4, and −7.0 kcal/mol and 11, 9, and 5 hydrogen bonds, while the top three analogues of 2DG, known as compound 1, compound 4, and compound 31, showed predicted binding energies of −6.8, −6.3, and −6.3 kcal/mol and 4, 3, and 1 hydrogen bonds, sequentially. The highest-ranked compounds in the docking analysis were then selected for molecular dynamics simulation, where compound 10, compound 30, and compound 1, which are the analogues of GLC, BG6, and 2DG, have shown strong protein-ligand stability with an RMSD value of ±5.0 A° with a 5 H bond, ±4.0 A° with an 8 H bond, and ±0.5 A° with a 2 H bond, respectively, compared to the reference molecules throughout the 20 ns simulation time. Therefore, by using the computational studies, we proposed novel compounds, which may act as potential drugs against DENV by inhibiting HKII’s activity.

MD simulations reveal alternate conformations of the oxyanion hole in the Zika virus NS2B/NS3 protease

Recent crystallography studies have shown that the binding site oxyanion hole plays an important role in inhibitor binding, but can exist in two conformations (active/inactive). We have undertaken molecular dynamics (MD) calculations to better understand oxyanion hole dynamics and thermodynamics. We find that the Zika virus (ZIKV) NS2B/NS3 protease maintains a stable closed conformation over multiple 100-ns conventional MD simulations in both the presence and absence of inhibitors. The S1, S2, and S3 pockets are stable as well. However, in two of eight simulations, the A132-G133 peptide bond in the binding pocket of S1' spontaneously flips to form a 3₁₀ -helix that corresponds to the inactive conformation of the oxyanion hole, and then maintains this conformation until the end of the 100-ns conventional MD simulations without inversion of the flip. This conformational change affects the S1' pocket in ZIKV NS2B/NS3 protease active site, which is important for small molecule binding. The simulation results provide evidence at the atomic level that the inactive conformation of the oxyanion hole is more favored energetically when no specific interactions are formed between substrate/inhibitor and oxyanion hole residues. Interestingly, however, transition between the active and inactive conformation of the oxyanion hole can be observed by boosting the valley potential in accelerated MD simulations. This supports a proposed induced-fit mechanism of ZIKV NS2B/NS3 protease from computational methods and provides useful direction to enhance inhibitor binding predictions in structure-based drug design.

Structure and sequence based functional annotation of Zika virus NS2b protein: Computational insights

While Zika virus (ZIKV) outbreaks are a growing concern for global health, a deep understanding about the virus is lacking. Here we report a contribution to the basic science on the virus- a detailed computational analysis of the non structural protein NS2b. This protein acts as a cofactor for the NS3 protease (NS3Pro) domain that is important on the viral life cycle, and is an interesting target for drug development. We found that ZIKV NS2b cofactor is highly similar to other virus within the Flavivirus genus, especially to West Nile Virus, suggesting that it is completely necessary for the protease complex activity. Furthermore, the ZIKV NS2b has an important role to the function and stability of the ZIKV NS3 protease domain even when presents a low conservation score. In addition, ZIKV NS2b is mostly rigid, which could imply a non dynamic nature in substrate recognition. Finally, by performing a computational alanine scanning mutagenesis, we found that residues Gly 52 and Asp 83 in the NS2b could be important in substrate recognition.

Mycobacterium tuberculosis Prolyl Oligopeptidase Induces In vitro Secretion of Proinflammatory Cytokines by Peritoneal Macrophages

Tuberculosis (TB) is a disease that leads to death over 1 million people per year worldwide and the biological mediators of this pathology are poorly established, preventing the implementation of effective therapies to improve outcomes in TB. Host-bacterium interaction is a key step to TB establishment and the proteases produced by these microorganisms seem to facilitate bacteria invasion, migration and host immune response evasion. We presented, for the first time, the identification, biochemical characterization, molecular dynamics (MDs) and immunomodulatory properties of a prolyl oligopeptidase (POP) from Mycobacterium tuberculosis (POPMt). POP is a serine protease that hydrolyzes substrates with high specificity for proline residues and has already been characterized as virulence factor in infectious diseases. POPMt reveals catalytic activity upon N-Suc-Gly-Pro-Leu-Gly-Pro-AMC, a recognized POP substrate, with optimal activity at pH 7.5 and 37°C. The enzyme presents K_M and K_cat/K_M values of 108 μM and 21.838 mM^-1 s^-1, respectively. MDs showed that POPMt structure is similar to that of others POPs, which consists of a cylindrical architecture divided into an α/β hydrolase catalytic domain and a β-propeller domain. Finally, POPMt was capable of triggering in vitro secretion of proinflammatory cytokines by peritoneal macrophages, an event dependent on POPMt intact structure. Our data suggests that POPMt may contribute to an inflammatory response during M. tuberculosis infection.

Identification of new potent inhibitors of dengue virus NS3 protease from traditional Chinese medicine database

Dengue virus (DENV) has emerged as an increasing fitness problem in the world for which no specialized drug is available. The non-structural protein NS3 protease of DENV has already been recognized as a potential therapeutic target for the discovery and development of novel antiviral agents against DENV infections. In this study, we employed the virtual screening technique to explore the potent inhibitors of DENV NS2B/NS3pro from Traditional Chinese Medicine (TCM) database. Total 200 inhibitors from TCM against DENV NS3pro were screened and only five TCM compounds like eriodictyol 7-O-glucuronide, luteolin 8-C-beta-glucopyranoside, (-)-epicatechin-3-O-gallate, 6-O-trans-p-coumaroylgeniposide and luteolin-7-O-glucoside were selected for further analysis which showed binding energies, -7.000, -7.380, -7.380, -7.440 and -7.440 kcal/mol, respectively. The findings of this study suggest that these five TCM compounds can be considered as potent inhibitors for DENV NS2B/NS3pro for the development of anti-dengue drugs.

Molecular docking NS4B of DENV 1-4 with known bioactive phyto-chemicals

Dengue disease is a global disease that has no effective treatment. The dengue virus (DENV) NS4B is a target for designing specific antivirals due to its importance in viral replication. Medicinal plants have been a savior for dengue virus as they consist of a class of phytochemicals having anti-viral activity and can pose a new approach ofstrong drug against viruses. The present study analyzes the activity of compounds against NS4B of DENV (1-4) serotypes. In this study Catechin, Cianidanol, Epicatechin, Eupatoretin, Glabranin, Laurifolin, DL-Catechin, astherapeutic agents were filtered by using Lipinski rule's five and the drug-likeness property of these agents were used for assessment of pharmacological properties. The molecular docking results presented the 2-D structures of bioactive complex, which interacted with especially conserved residues of target domains. Interestingly, we find the Catechin, Laurifolin, Cianidanol have highest binding energy against NS4B in DENV-1,2,4 which is evident by the formation of more hydrogen bonds with the amino acid residues at the binding site of the receptor. Our results revealed that the bioactive compound, especially Catechin has significant anti-dengue activities. In addition, this study may be helpful in further experimental investigations.

A quantum chemistry investigation of a potential inhibitory drug against the dengue virus

The total interaction energy of the inhibitor Bz-nKRR-H bound to a serine protease of the dengue virus is mainly due to the action of Asn152, Met49, Tyr161, Asp129 and Gly151 (Met84, Met75, Asp81, Asp79 and Asp80) residues at the NS3 (NS2B) subunit.

Molecular Dynamics: New Frontier in Personalized Medicine

The field of drug discovery has witnessed infinite development over the last decade with the demand for discovery of novel efficient lead compounds. Although the development of novel compounds in this field has seen large failure, a breakthrough in this area might be the establishment of personalized medicine. The trend of personalized medicine has shown stupendous growth being a hot topic after the successful completion of Human Genome Project and 1000 genomes pilot project. Genomic variant such as SNPs play a vital role with respect to inter individual's disease susceptibility and drug response. Hence, identification of such genetic variants has to be performed before administration of a drug. This process requires high-end techniques to understand the complexity of the molecules which might bring an insight to understand the compounds at their molecular level. To sustenance this, field of bioinformatics plays a crucial role in revealing the molecular mechanism of the mutation and thereby designing a drug for an individual in fast and affordable manner. High-end computational methods, such as molecular dynamics (MD) simulation has proved to be a constitutive approach to detecting the minor changes associated with an SNP for better understanding of the structural and functional relationship. The parameters used in molecular dynamic simulation elucidate different properties of a macromolecule, such as protein stability and flexibility. MD along with docking analysis can reveal the synergetic effect of an SNP in protein-ligand interaction and provides a foundation for designing a particular drug molecule for an individual. This compelling application of computational power and the advent of other technologies have paved a promising way toward personalized medicine. In this in-depth review, we tried to highlight the different wings of MD toward personalized medicine.

NMR and MD Studies Reveal That the Isolated Dengue NS3 Protease Is an Intrinsically Disordered Chymotrypsin Fold Which Absolutely Requests NS2B for Correct Folding and Functional Dynamics

Dengue genome encodes a two component protease complex (NS2B-NS3pro) essential for the viral maturation/infectivity, thus representing a key drug target. Previously, due to its “complete insolubility”, the isolated NS3pro could not be experimentally studied and it remains elusive what structure it adopts without NS2B and why NS2B is indispensable. Here as facilitated by our previous discovery, the isolated NS3pro has been surprisingly deciphered by NMR to be the first intrinsically-disordered chymotrypsin-like fold, which exists in a loosely-packed state with non-native long-range interactions as revealed by paramagnetic relaxation enhancement (PRE). The disordered NS3pro appears to be needed for binding a human host factor to trigger the membrane remodeling. Moreover, we have in vitro refolded the NS3pro in complex with either NS2B (48–100) or the full-length NS2B (1–130) anchored into the LMPC micelle, and the two complexes have similar activities but different dynamics. We also performed molecular dynamics (MD) simulations and the results revealed that NS2B shows the highest structural fluctuations in the complex, thus providing the dynamic basis for the observation on its conformational exchange between open and closed states. Remarkably, the NS2B cofactor plays a central role in maintaining the correlated motion network required for the catalysis as we previously decoded for the SARS 3CL protease. Indeed, a truncated NS2B (48–100;Δ77–84) with the flexible loop deleted is able to trap the NS2B-NS3pro complex in a highly dynamic and catalytically-impotent state. Taken together, our study implies potential strategies to perturb the NS2B-NS3pro interface for design of inhibitors for treating dengue infection.