Virtual screening and molecular growth guide the design of inhibitors for the influenza virus drug-resistant mutant M2-V27A/S31N

The influenza A virus matrix protein 2 (AM2) protein is a proton-gated, proton-selective ion channel essential for influenza replication that has been identified as an antiviral target. The drug-resistance of the M2-V27A/S31N strain, which has been growing more prevalent in recent years and has the potential to spread globally, prevents current amantadine inhibitors from having the desired impact. In this study, we compiled the most common influenza A virus strains from 2001-2020 from the U.S. National Center for Biotechnology Information database and hypothesized that M2-V27A/S31N would become a common strain. The lead compound ZINC299830590 was screened for M2-V27A/S31N in the ZINC15 database using a pharmacophore model and molecular descriptors. This lead compound was then optimized by molecular growth, which allowed us to identify important amino acid residues and create interactions with them to produce compound 4. Molecular dynamics simulation showed that the complex of compound 4 and M2-V27A/S31N had certain degrees of stability and flexibility. The binding free energy of compound 4 was calculated using the MM/PB(GB)SA method and totaled -106.525 kcal/mol. Finally, physicochemical and pharmacokinetic profiles were predicted using the Absorption, Distribution, Metabolism, Excretion, and Toxicity model, which indicated the good bioavailability of compound 4. These results provide the basis for further in vivo and in vitro studies to demonstrate that compound 4 is a promising drug candidate against M2-V27A/S31N.Communicated by Ramaswamy H. Sarma.

Exploring transmembrane allostery in the MexB: DB08385 variant as a promising inhibitor-like candidate against Pseudomonas aeruginosa antibiotic resistance: a computational study

Pseudomonas aeruginosa, a formidable pathogen renowned for its antimicrobial resistance, poses a significant threat to immunocompromised individuals. In this regard, the MexAB-OprM efflux pump acts as a pivotal line of defense by extruding antimicrobials from bacterial cells. The inner membrane homotrimeric protein MexB captures antibiotics and translocates them into the outer membrane OprM channel protein connected through the MexA adaptor protein. Despite extensive efforts, competitive inhibitors targeting the tight (T) protomer of the MexB protein have not received FDA approval for medical use. Over the past few years, allosteric inhibitors have become popular as alternatives to the classical competitive inhibitor-based approach because of their higher specificity, lower dosage, and reduced toxicological effects. Hence, in this study, we unveiled the existence of a transmembrane allosteric binding pocket of MexB inspired by the recent discovery of an important allosteric inhibitor, BDM88855, for the homolog AcrB protein. While repurposing BDM88855 proved ineffective in controlling the MexB loose (L) protomer, our investigation identified a promising alternative: a chlorine-containing variant of DB08385 (2-Cl DB08385 or Variant 1). Molecular dynamics simulations, including binding free energy estimation coupled with heterogeneous dielectric implicit membrane model (implicit-membrane MM/PBSA), interaction entropy (IE) analysis and potential of mean force (PMF) calculation, demonstrated Variant 1's superior binding affinity to the transmembrane pocket, displaying the highest energy barrier in the ligand unbinding process. To elucidate the allosteric crosstalk between the transmembrane and porter domain of MexB, we employed the 'eigenvector centrality' measure in the linear mutual information obtained from the protein correlation network. Notably, this study confirmed the presence of an allosteric transmembrane site in the MexB L protomer. In addition to this, Variant 1 emerged as a potent regulator of allosteric crosstalk, inducing an 'O-L intermediate state' in the MexB L protomer. This induced state might hold the potential to diminish substrate intake into the access pocket, leading to the ineffective efflux of antibiotics.

Understanding the impact of binding free energy and kinetics calculations in modern drug discovery

INTRODUCTION

For rational drug design, it is crucial to understand the receptor-drug binding processes and mechanisms. A new era for the use of computer simulations in predicting drug-receptor interactions at an atomic level has begun with remarkable advances in supercomputing and methodological breakthroughs.

AREAS COVERED

End-point free energy calculation methods such as Molecular Mechanics/Poisson Boltzmann Surface Area (MM/PBSA) or Molecular-Mechanics/Generalized Born Surface Area (MM/GBSA), free energy perturbation (FEP), and thermodynamic integration (TI) are commonly used for binding free energy calculations in drug discovery. In addition, kinetic dissociation and association rate constants (k off and k on ) play critical roles in the function of drugs. Nowadays, Molecular Dynamics (MD) and enhanced sampling simulations are increasingly being used in drug discovery. Here, the authors provide a review of the computational techniques used in drug binding free energy and kinetics calculations.

EXPERT OPINION

The applications of computational methods in drug discovery and design are expanding, thanks to improved predictions of the binding free energy and kinetic rates of drug molecules. Recent microsecond-timescale enhanced sampling simulations have made it possible to accurately capture repetitive ligand binding and dissociation, facilitating more efficient and accurate calculations of ligand binding free energy and kinetics.

Elucidation of 7,8-dihydroxy flavone in complexing with the oxidative stress-inducing enzymes, its impact on radical quenching and DNA damage: an in silico and in vitro approach

Oxidative stress (OS) has been attributed to the progression of various disorders, including cancer, diabetes, and cardiovascular diseases. Several antioxidant compounds and free radical quenchers have been shown to mitigate oxidative stress. However, large-scale randomized controlled trials of such compounds on chronic disease aversion have yielded paradoxical and disappointing results due to the constrained cognizance of their oxidative mechanisms and therapeutic targets. The current study sought to identify the potential therapeutic targets of 7,8-Dihydroxyflavone (7,8-DHF) by analyzing its interactions with the enzymes implicated in oxidative stress and also to explore its radicle quenching potential and prophylactic impact on the H2O2-induced DNA damage. Through the in silco approach, we investigated the antioxidant potential of 7,8-DHF by evaluating its interactions with the human oxidative stress-inducing enzymes such as myeloperoxidase (MPO), NADPH oxidase (NOX), nitric oxide synthase (NOS), and xanthine oxidase (XO) and a comparative analysis of those interactions with known antioxidants (Ascorbic acid, Melatonin, Tocopherol) used as controls. The best-scoring complex was adopted for the simulation analysis in investigating protein-ligand conformational dynamics. The in vitro radicle quenching potential was evaluated by performing a spectrum of antioxidant assays, and radical quenching was observed in a dose-dependent fashion with IC50 values of < 60 µM/mL. Further, we probed its anti-hemolytic potential and prophylactic impact in avian erythrocytes subjected to H2O2-induced hemolysis and DNA damage by implementing hemolysis and comet assays. The protective effect was more pronounced at higher concentrations of the drug.Communicated by Ramaswamy H. Sarma.

A synergistic investigation of azo-thiazole derivatives incorporating thiazole moieties: a comprehensive exploration of their synthesis, characterization, computational insights, solvatochromism, and multimodal biological activity assessment

In the present study, a novel series of azo-thiazole derivatives (3a-c) containing a thiazole moiety was successfully synthesized. The structure of these derivatives was examined by spectroscopic techniques, including 1H NMR, 13C NMR, FT-IR, and HRMS. Further, the novel synthesized compounds were evaluated for their in vitro biological activities, such as antibacterial and anti-inflammatory activities, and an in silico study was performed. The antibacterial results demonstrated that compounds 3a and 3c (MIC = 10 μg mL-1) have a notable potency against Staphylococcus aureus compared to azithromycin (MIC = 40 μg mL-1). Alternatively, compound 3b displayed a four-fold higher potency (24 recovery days, 1.83 mg day-1) than Hamazine (28 recovery days, 4.14 mg day-1) in promoting burn wound healing, and it also exhibited a comparable inhibitory activity against screened bacterial pathogens compared to the reference drug. Docking on 1KZN, considering the excellent impact of compounds on the crystal structure of E. coli1KZN, a 24 kDa domain, in complex with clorobiocin, indicated the close binding of compounds 3a-c with the active site of the 1KZN protein, which is consistent with their observed biological activity. Additionally, we conducted molecular dynamics simulations on the docked complexes of compounds 3a-c with 1KZN retrieved from the PDB to assess their stability and molecular interactions. Furthermore, we assessed their electrochemical characteristics via DFT calculations. Employing PASS and pkCSM platforms, we gained insights into controlling the bioactivity and physicochemical features of these compounds, highlighting their potential as new active agents.

HR-LCMS and evaluation of anti-diabetic activity of Hemidesmus indicus (anantmool): Kinetic study, and molecular modelling approach

This study delved into the exploration of novel antidiabetic medications acquired from natural resources, utilizing the Ayurvedic Rasayana herb Hemidesmus indicus through cutting-edge chemoprofiling and molecular modelling techniques. The methanolic extract of Hemidesmus indicus root exhibited the highest extractive yield (24.70 ± 0.08 %) and contained substantial levels of total phenolic and flavonoid content as 154.15 ± 1.24 mg Gallic Acid Equivalent/g extract and 70.61 ± 0.35 Quercetin Equivalent/g extract respectively. Invitro study revealed the potent inhibitory potential of methanolic extract of the herb against essential carbohydrate hydrolytic enzymes α-amylase (IC₅₀ = 4.19 ± 0.04 mg/ml) and α-glucosidase (IC₅₀ = 5.78 ± 0.10 mg/ml). Further, the enzyme kinetic study demonstrated the competitive mode of inhibition of both enzymes. HR-LCMS analysis identified the major phytoconstituents present in the extracts, including Solanocapsine, Cyclovirobuxine C, Lucidine B, Zygadenine, Aspidospermidine, silychristin, 3beta-3-Hydroxy-18-lupen-21-one, Manglupenone, and 19-Noretiocholanolone. Molecular docking, molecular dynamic simulation, and MM/GBSA analysis have proved stable, rigid, compact, and folded form of complexes during the entire 100 ns simulation, illustrating Zygadenine, Solanocapsine, and Cyclovirobuxine C as the superior inhibitors of α-A protein, while Zygadenine, Plumieride, and Phlegmarine exhibited greater inhibitory behaviour towards α-G protein than the FDA-approved drug acarbose. Collectively, our findings indicate that the Hemidesmus indicus could be a promising source of α-A and α-G inhibitors, potentially serving as a lead in order to develop medications for type-2 diabetes.

Exploring the therapeutic mechanisms of Gleditsiae Spina acting on pancreatic cancer via network pharmacology, molecular docking and molecular dynamics simulation

Pancreatic cancer is one of the most aggressive tumors and also has a low survival rate. The dried spines of Gleditsia sinensis Lam are known as "Gleditsiae Spina" and they mostly contain flavonoids, phenolic acids, terpenoids, steroids, and other chemical components. In this study, the potential active components and molecular mechanisms of Gleditsiae Spina for treating pancreatic cancer were systematically revealed by network pharmacology, molecular docking and molecular dynamics simulations (MDs). RAC-alpha serine/threonine-protein kinase (AKT1), cellular tumor antigen p53 (TP53), tumor necrosis factor α (TNFα), interleukin-6 (IL6) and vascular endothelial growth factor A (VEGFA) were common targets of Gleditsiae Spina, human cytomegalovirus infection signaling pathway, AGE-RAGE signaling pathway in diabetic complications, and MAPK signaling pathway were critical pathways of fisetin, eriodyctiol, kaempferol and quercetin in the treatment of pancreatic cancer. Molecular dynamics simulations (MDs) results showed that eriodyctiol and kaempferol have long-term stable hydrogen bonds and high binding free energy for TP53 (-23.64 ± 0.03 kcal mol-1 and -30.54 ± 0.02 kcal mol-1, respectively). Collectively, our findings identify active components and potential targets in Gleditsiae Spina for the treatment of pancreatic cancer, which may help to explore leading compounds and potential drugs for pancreatic cancer.

Computer-aided drug design for the pain-like protease (PLpro) inhibitors against SARS-CoV-2

A new coronavirus, known as Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), is a highly contagious virus and has caused a massive worldwide health crisis. While large-scale vaccination efforts are underway, the management of population health, economic impact and asof-yet unknown long-term effects on physical and mental health will be a key challenge for the next decade. The papain-like protease (PL^pro) of SARS-CoV-2 is a promising target for antiviral drugs. This report used pharmacophore-based drug design technology to identify potential compounds as PL^pro inhibitors against SARS-CoV-2. The optimal pharmacophore model was fully validated using different strategies and then was employed to virtually screen out 10 compounds with inhibitory. Molecular docking and non-bonding interactions between the targeted protein PL^pro and compounds showed that UKR1129266 was the best compound. These results provided a theoretical foundation for future studies of PL^pro inhibitors against SARS-CoV-2.

Integration of immunoinformatics and cheminformatics to design and evaluate a multitope vaccine against Klebsiella pneumoniae and Pseudomonas aeruginosa coinfection

Introduction: Klebsiella pneumoniae (K. pneumoniae) and Pseudomonas aeruginosa (P. aeruginosa) are the most common Gram-negative bacteria associated with pneumonia and coinfecting the same patient. Despite their high virulence, there is no effective vaccine against them. Methods: In the current study, the screening of several proteins from both pathogens highlighted FepA and OmpK35 for K. pneumonia in addition to HasR and OprF from P. aeruginosa as promising candidates for epitope mapping. Those four proteins were linked to form a multitope vaccine, that was formulated with a suitable adjuvant, and PADRE peptides to finalize the multitope vaccine construct. The final vaccine's physicochemical features, antigenicity, toxicity, allergenicity, and solubility were evaluated for use in humans. Results: The output of the computational analysis revealed that the designed multitope construct has passed these assessments with satisfactory scores where, as the last stage, we performed a molecular docking study between the potential vaccine construct and K. pneumonia associated immune receptors, TLR4 and TLR2, showing affinitive to both targets with preferentiality for the TLR4 receptor protein. Validation of the docking studies has proceeded through molecular dynamics simulation, which estimated a strong binding and supported the nomination of the designed vaccine as a putative solution for K. pneumoniae and P. aeruginosa coinfection. Here, we describe the approach for the design and assessment of our potential vaccine.

HBD-2 variants and SARS-CoV-2: New insights into inter-individual susceptibility

Background

A deep understanding of the causes of liability to SARS-CoV-2 is essential to develop new diagnostic tests and therapeutics against this serious virus in order to overcome this pandemic completely. In the light of the discovered role of antimicrobial peptides [such as human b-defensin-2 (hBD-2) and cathelicidin LL-37] in the defense against SARS-CoV-2, it became important to identify the damaging missense mutations in the genes of these molecules and study their role in the pathogenesis of COVID-19.

Methods

We conducted a comprehensive analysis with multiple in silico approaches to identify the damaging missense SNPs for hBD-2 and LL-37; moreover, we applied docking methods and molecular dynamics analysis to study the impact of the filtered mutations.

Results

The comprehensive analysis reveals the presence of three damaging SNPs in hBD-2; these SNPs were predicted to decrease the stability of hBD-2 with a damaging impact on hBD-2 structure as well. G51D and C53G mutations were located in highly conserved positions and were associated with differences in the secondary structures of hBD-2. Docking-coupled molecular dynamics simulation analysis revealed compromised binding affinity for hBD-2 SNPs towards the SARS-CoV-2 spike domain. Different protein-protein binding profiles for hBD-2 SNPs, in relation to their native form, were guided through residue-wise levels and differential adopted conformation/orientation.

Conclusions

The presented model paves the way for identifying patients prone to COVID-19 in a way that would guide the personalization of both the diagnostic and management protocols for this serious disease.

Molecular basis of the potential interaction of SARS-CoV-2 spike protein to CD147 in COVID-19 associated-lymphopenia

Lymphopenia is considered one of the most characteristic clinical features of the coronavirus disease 2019 (COVID-19). SARS-CoV-2 infects host cells via the interaction of its spike protein with the human angiotensin-converting enzyme 2 (hACE2) receptor. Since T lymphocytes display a very low expression level of hACE2, a novel receptor might be involved in the entry of SARS-CoV-2 into T cells. The transmembrane glycoprotein CD147 is highly expressed by activated T lymphocytes, and was recently proposed as a probable route for SARS-CoV-2 invasion. To understand the molecular basis of the potential interaction of SARS-CoV-2 to CD147, we have investigated the binding of the viral spike protein to this receptor in-silico. The results showed that this binding is dominated by electrostatic interactions involving residues Arg403, Asn481, and the backbone of Gly502. The overall binding arrangement shows the CD147 C-terminal domain interacting with the spike external subdomain in the grove between the short antiparallel β strands, β1' and β2', and the small helix α1'. This proposed interaction was further confirmed using MD simulation and binding free energy calculation. These data contribute to a better understanding of the mechanism of infection of SARS-CoV-2 to T lymphocytes and could provide valuable insights for the rational design of adjuvant treatment for COVID-19. Communicated by Ramaswamy H. Sarma.

gmx_MMPBSA: A New Tool to Perform End-State Free Energy Calculations with GROMACS

Molecular mechanics/Poisson-Boltzmann (Generalized-Born) surface area is one of the most popular methods to estimate binding free energies. This method has been proven to balance accuracy and computational efficiency, especially when dealing with large systems. As a result of its popularity, several programs have been developed for performing MM/PB(GB)SA calculations within the GROMACS community. These programs, however, present several limitations. Here we present gmx_MMPBSA, a new tool to perform end-state free energy calculations from GROMACS molecular dynamics trajectories. gmx_MMPBSA provides the user with several options, including binding free energy calculations with different solvation models (PB, GB, or 3D-RISM), stability calculations, computational alanine scanning, entropy corrections, and binding free energy decomposition. Noteworthy, several promising methodologies to calculate relative binding free energies such as alanine scanning with variable dielectric constant and interaction entropy have also been implemented in gmx_MMPBSA. Two additional tools-gmx_MMPBSA_test and gmx_MMPBSA_ana-have been integrated within gmx_MMPBSA to improve its usability. Multiple illustrating examples can be accessed through gmx_MMPBSA_test, while gmx_MMPBSA_ana provides fast, easy, and efficient access to different graphics plotted from gmx_MMPBSA output files. The latest version (v1.4.3, 26/05/2021) is available free of charge (documentation, test files, and tutorials included) at https://github.com/Valdes-Tresanco-MS/gmx_MMPBSA.

Genetic Algorithms Applied to Thermodynamic Rational Design of Mimetic Antibodies Based on the GB1 Domain of Streptococcal Protein G: An Atomistic Simulation Study

The development of mimetic antibodies (MA) capable of combining the high affinity and selectivity of antibodies with the small size of the peptides has enormous potential for applications in current biotechnology. In this work, we demonstrate that in silico MA design is possible through genetic algorithms (GA) developed from shell scripts capable of combining software commonly used for atomistic simulation. Our results demonstrate that, using the GB1 domain of the streptococcal G protein as a model, it is possible to optimize the molecular recognition capacity of a large MA population in a few generations. In the first case, GA was able to generate 10 MA with binding free energy (BFE) less than the vascular endothelial cell growth factor conjugated with the fms-type tyrosine kinase receptor. In the second case, it generated 13 MA with BFE less than that of the hepatitis C-E2 viral envelope conjugate with the antibody. Through the GA developed in this work, we demonstrate the use of a new protocol, capable of guiding experimental methods for the design of bioactive peptides that can assist in the development of new therapeutic molecules.

Inhibition mechanism and hot-spot prediction of nine potential drugs for SARS-CoV-2 Mpro by large-scale molecular dynamic simulations combined with accurate binding free energy calculations

Coronavirus disease 2019 (COVID-19), which is caused by a new coronavirus known as severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is spreading around the world. However, a universally effective treatment regimen has not been developed to date. The main protease (M^pro), a key enzyme of SARS-CoV-2, plays a crucial role in the replication and transcription of this virus in cells and has become the ideal target for rational antiviral drug design. In this study, we performed molecular dynamics simulations three times for these complexes of M^pro (monomeric and dimeric) and nine potential drugs that have a certain effect on the treatment of COVID-19 to explore their binding mechanism. In addition, a total of 12 methods for calculating binding free energy were employed to determine the optimal drug. Ritonavir, Arbidol, and Chloroquine consistently showed an outstanding binding ability to monomeric M^pro under various methods. Ritonavir, Arbidol, and Saquinavir presented the best performance when binding to a dimer, which was independent of the protonated state of Hie41 (protonated at N_ε) and Hid41 (protonated at N_δ), and these findings suggest that Chloroquine may not effectively inhibit the activity of dimeric M^proin vivo. Furthermore, three common hot-spot residues of Met165, Hie41, and Gln189 of monomeric M^pro systems dominated the binding of Ritonavir, Arbidol, and Chloroquine. In dimeric M^pro, Gln189, Met165, and Met49 contributed significantly to binding with Ritonavir, Arbidol, and Saquinavir; therefore, Gln189 and Met165 might serve as the focus in the discovery and development of anti-COVID-19 drugs. In addition, the van der Waals interaction played a significant role in the binding process, and the benzene ring of the drugs showed an apparent inhibitory effect on the normal function of M^pro. The binding cavity had great flexibility to accommodate these different drugs. The results would be notably helpful for enabling a detailed understanding of the binding mechanisms for these important drug-M^pro interactions and provide valuable guidance for the design of potent inhibitors.

Computational analysis of binding free energies, hotspots and the binding mechanism of Bcl-xL/Bcl-2 binding to Bad/Bax

Hierarchical clustering tree of residues providing contributions to system binding based on the binding free energy of specific residues for (A) Bcl-xL systems (B) Bcl-2 systems.