Combined 3D-QSAR, molecular docking, molecular dynamics simulation, and binding free energy calculation studies on the 5-hydroxy-2H-pyridazin-3-one derivatives as HCV NS5B polymerase inhibitors

Analyzing energetics and dynamics of hepatitis C virus polymerase interactions with marine bacterial compounds: a computational study

Hepatitis C Virus (HCV) is a significant health concern affecting a large portion of the global population and is a major cause of acute liver diseases, including cirrhosis. The variability in the HCV genome mainly results from the rapid replication facilitated by the NS5B polymerase, making it a prime target for anti-HCV drug development. This study explores potential compounds from marine bacteria that could inhibit the HCV NS5B polymerase by virtual screening, analyzing the energetics, and dynamic behavior of target-compound complexes. Virtual screening with the Lipinski filter was employed to select compounds from the marine bacteria database that demonstrated strong binding affinity to NS5B. The top four (CMNPD27216, CMNPD21066, CMNPD21065, and CMNPD27283) compounds, ranked by their re-docking scores, underwent additional evaluation. Molecular dynamics simulations for 200 ns were conducted to assess the dynamic stability of these complexes in a solvent environment. Furthermore, methods such as MM-GBSA, PCA, and free energy landscape analysis were used to analyze the system's energetics and identify stable conformations by locating transition states. The findings suggest that these compounds exhibit promising binding capabilities to HCV polymerase and could be considered for future experimental validation.

An in silico comparative study of curcumin and 2-deoxyuridine nucleoside derivatives: Reveals the role of angiogenin in ER stress-induced apoptosis signaling

Angiogenin (ANG) protein plays a crucial role in angiogenesis, neovascularization, and cancer metastasis in NSCLC (non-small cell lung cancer) via non-coding tiRNA. It protects the cell under ER (endoplasmic reticulum) stress-induced apoptosis through the translational reprogramming process. Although B82 (Curcumin derivatives) induces ER stress-induced apoptosis, its mechanism of action was not studied. Therefore, it was hypothesized that the ribonucleolytic activity of ANG may be regulated by B82, resulting in modulated ER stress signaling for apoptosis. Hence, we designed and proposed a synthesis scheme for RNA-based anti-angiogenic derivatives of 2-deoxyuridine nucleoside forming peptide bond with amino acids like serine (Ser-3) and para-hydroxy-phenyl glycine (Normtyr-1) and compared B82 with them to know the binding affinity with ANG, anti-angiogenic potential, and its probable mechanism of anti-RNase activity through MD simulation study. Therefore, using Gromos96 43a1 and 43a2 force fields, MD simulation was performed to investigate binding affinity, ligand-induced molecular surface area change, conformational change, and dynamics of catalytic site residues to predict ligand binding to ANG in this study. The obtained binding free energy (∆G_bind ) result showed the total average ∆G_bind as -113.480 ± 1.682 (Normtyr-1) > -53.038 ± 33.069 (B82) > -27.909 ± 16.438 (Ser-3) kJ/mole specify role of B82 in regulating ER stress signaling induced apoptosis through ANG ribonucleolytic activity inhibition, suitability of 43a2 force fields and methodology in ligand screening. It shows the crucial role of Leu115 and His13 residue involvement in total ∆G_bind contribution. Hence, based on the MD result, novel conformation of catalytic residues, and ∆G_bind , a promising combination candidate could be proposed for metastatic NSCLC therapy.

A Multi-target Drug Designing for BTK, MMP9, Proteasome and TAK1 for the Clinical Treatment of Mantle Cell Lymphoma

BACKGROUND

Mantle cell lymphoma (MCL) is a type of non-Hodgkin lymphoma characterized by the mutation and overexpression of the cyclin D1 protein by the reciprocal chromosomal translocation t(11;14)(q13:q32).

AIM

The present study aims to identify potential inhibition of MMP9, Proteasome, BTK, and TAK1 and determine the most suitable and effective protein target for the MCL.

METHODOLOGY

Nine known inhibitors for MMP9, 24 for proteasome, 15 for BTK and 14 for TAK1 were screened. SB-3CT (PubChem ID: 9883002), oprozomib (PubChem ID: 25067547), zanubrutinib (PubChem ID: 135565884) and TAK1 inhibitor (PubChem ID: 66760355) were recognized as drugs with high binding capacity with their respective protein receptors. 41, 72, 102 and 3 virtual screened compounds were obtained after the similarity search with compound (PubChem ID:102173753), PubChem compound SCHEMBL15569297 (PubChem ID:72374403), PubChem compound SCHEMBL17075298 (PubChem ID:136970120) and compound CID: 71814473 with best virtual screened compounds.

RESULT

MMP9 inhibitors show commendable affinity and good interaction profile of compound holding PubChem ID:102173753 over the most effective established inhibitor SB-3CT. The pharmacophore study of the best virtual screened compound reveals its high efficacy based on various interactions. The virtual screened compound's better affinity with the target MMP9 protein was deduced using toxicity and integration profile studies.

CONCLUSION

Based on the ADMET profile, the compound (PubChem ID: 102173753) could be a potent drug for MCL treatment. Similar to the established SB-3CT, the compound was non-toxic with LD50 values for both the compounds lying in the same range.

A computational study on the interactions between a layered imine-based COF structure and selected anticancer drugs

The covalent organic frameworks (COFs) are important materials in drug delivery. Herein, the interactions between an imine-based COF with selected commercially available anticancer drugs are studied. Molecular dynamics (MD) simulation studies were used. The studies were carried out in four different temperatures to find out the impact of the temperature on the binding free energies between the drugs and COF structure. It was found that the effect of temperature on binding free energy is ignorable. Between the hydrogen bonding, electrostatic, and van der Waals interactions, the last one is the most important one to keep the drug and COF next to each other. Also, the van der Waals interaction is keeping the layers of COF next to each other to create cavities. The cavities can be loaded with different drugs and the system can be used in drug delivery systems. Based on the obtained results, the drugs that are more lipophilic prefer to adhere more strongly to the COF in comparison with hydrophilic drugs.

Revealing the Inhibition Mechanism of RNA-Dependent RNA Polymerase (RdRp) of SARS-CoV-2 by Remdesivir and Nucleotide Analogues: A Molecular Dynamics Simulation Study

Antiviral drug therapy against SARS-CoV-2 is not yet established and posing a serious global health issue. Remdesivir is the first antiviral compound approved by the US FDA for the SARS-CoV-2 treatment for emergency use, targeting RNA-dependent RNA polymerase (RdRp) enzyme. In this work, we have examined the action of remdesivir and other two ligands screened from the library of nucleotide analogues using docking and molecular dynamics (MD) simulation studies. The MD simulations have been performed for all the ligand-bound RdRp complexes for the 30 ns time scale. This is one of the earlier reports to perform the MD simulations studies using the SARS-CoV-2 RdRp crystal structure (PDB ID 7BTF). The MD trajectories were analyzed and Molecular Mechanics Poisson-Boltzmann Surface Area (MM-PBSA) calculations were performed to calculate the binding free energy. The binding energy data reveal that compound-17 (-59.6 kcal/mol) binds more strongly as compared to compound-8 (-46.3 kcal/mol) and remdesivir (-29.7 kcal/mol) with RdRp. The detailed analysis of trajectories shows that the remdesivir binds in the catalytic site and forms a hydrogen bond with the catalytic residues from 0 to 0.46 ns. Compound-8 binds in the catalytic site but does not form direct hydrogen bonds with catalytic residues. Compound-17 showed the formation of hydrogen bonds with catalytic residues throughout the simulation process. The MD simulation results such as hydrogen bonding, the center of mass distance analysis, snapshots at a different time interval, and binding energy suggest that compound-17 binds strongly with RdRp of SARS-CoV-2 and has the potential to develop as a new antiviral against COVID-19. Further, the frontier molecular orbital analysis and molecular electrostatic potential (MESP) iso-surface analysis using DFT calculations shed light on the superior binding of compound-17 with RdRp compared to remdesivir and compound-8. The computed as well as the experimentally reported pharmacokinetics and toxicity parameters of compound-17 is encouraging and therefore can be one of the potential candidates for the treatment of COVID-19.

Theoretical Studies on the Selectivity Mechanisms of Glycogen Synthase Kinase 3β (GSK3β) with Pyrazine ATP-competitive Inhibitors by 3DQSAR, Molecular Docking, Molecular Dynamics Simulation and Free Energy Calculations

Background

Glycogen synthase kinase-3 (GSK3) is associated with various key biological processes and has been considered as an important therapeutic target for the treatment of many diseases. Great efforts have been made on the development of GSK3 inhibitors, especially ATP-competitive GSK3β inhibitor, but it is still a great challenge to develop selective GSK3β inhibitors because of the high sequence homology with other kinases.

Objective

In order to reveal the selectivity mechanisms of GSK3β inhibition at the molecular level, a series of ATP-competitive GSK3β inhibitor was analyzed by a systematic computational method, combining 3D-QSAR, molecular docking, molecular dynamic simulations and free energy calculations.

Methods

Firstly, 3D-QSAR with CoMFA was built to explore the general structure activity relationships. Secondly, CDOCKER and Flexible docking were employed to predicted the reasonable docking poses of all studied inhibitors. And then, both GSK3β and CDK2 complexes were selected to conduct molecular dynamics simulations. Finally, the free energy calculations were employed to find the key selective-residues.

Results

CoMFA model suggested the steric, hydrophobic fields play key roles in the bioactivities of inhibitors, and the binding mechanisms were well analyzed through molecular docking. The binding free energies predicted are in good agreement with the experimental bioactivities and the free energy calculations showed that the binding of GSK3β/inhibitors was mainly contributed from hydrogen bonding and hydrophobic interaction.

Conclusion

Some key residues for selective binding were highlighted, which may afford important guidance for the rational design of novel ATP-competitive GSK3β inhibitors.

QSAR Studies on Thiazole Derivatives as HCV NS5A Inhibitors via CoMFA and CoMSIA Methods

Background:

Hepatitis C Virus (HCV) infection is the major cause of hepatitis after transfusion. And HCV Nonstructural Protein 5A (NS5A) inhibitors have become a new hotspot in the study of HCV inhibitors due to their strong antiviral activity, rapid speed of viral removing and broad antiviral spectrum.

Methods:

Forty-five NS5A inhibitors were chosen to process three-dimensional quantitative structure- activity relationship (3D-QSAR) by using comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) models. A training set consisting of 30 compounds was applied to establish the models and a test set consisting of 15 compounds was applied to do the external validation.

Results:

The CoMFA model predicted a q2 value of 0.607 and an r2 value of 0.934. And the CoMSIA model predicted a q2 value of 0.516 and an r2 value of 0.960 established on the effects of steric, electrostatic, hydrophobic and hydrogen-bond acceptor. 0.713 and 0.939 were the predictive correlation co-efficients (r2pred) of CoMFA and CoMSIA models, respectively.

Conclusion:

These conclusions provide a theoretical basis for drug design and screening of HCV NS5A complex inhibitors.

Recent Developments and Applications of the MMPBSA Method

The Molecular Mechanics Poisson-Boltzmann Surface Area (MMPBSA) approach has been widely applied as an efficient and reliable free energy simulation method to model molecular recognition, such as for protein-ligand binding interactions. In this review, we focus on recent developments and applications of the MMPBSA method. The methodology review covers solvation terms, the entropy term, extensions to membrane proteins and high-speed screening, and new automation toolkits. Recent applications in various important biomedical and chemical fields are also reviewed. We conclude with a few future directions aimed at making MMPBSA a more robust and efficient method.

Speeding up Early Drug Discovery in Antiviral Research: A Fragment-Based in Silico Approach for the Design of Virtual Anti-Hepatitis C Leads

Hepatitis C constitutes an unresolved global health problem. This infectious disease is caused by the hepatotropic hepatitis C virus (HCV), and it can lead to the occurrence of life-threatening medical conditions, such as cirrhosis and liver cancer. Nowadays, major clinical concerns have arisen because of the appearance of multidrug resistance (MDR) and the side effects especially associated with long-term treatments. In this work, we report the first multitasking model for quantitative structure-biological effect relationships (mtk-QSBER), focused on the simultaneous exploration of anti-HCV activity and in vitro safety profiles related to the absorption, distribution, metabolism, elimination, and toxicity (ADMET). The mtk-QSBER model was created from a data set formed by 40 158 cases, displaying accuracy higher than 95% in both training and prediction (test) sets. Several molecular fragments were selected, and their quantitative contributions to anti-HCV activity and ADMET profiles were calculated. By combining the analysis of the fragments with positive contributions and the physicochemical meanings of the different molecular descriptors in the mtk-QSBER, six new molecules were designed. These new molecules were predicted to exhibit potent anti-HCV activity and desirable in vitro ADMET properties. In addition, the designed molecules have good druglikeness according to the Lipinski's rule of five and its variants.

Applications of computer-aided approaches in the development of hepatitis C antiviral agents

INTRODUCTION

Hepatitis C virus (HCV) is a global health problem that causes several chronic life-threatening liver diseases. The numbers of people affected by HCV are rising annually. Since 2011, the FDA has approved several anti-HCV drugs; while many other promising HCV drugs are currently in late clinical trials. Areas covered: This review discusses the applications of different computational approaches in HCV drug design. Expert opinion: Molecular docking and virtual screening approaches have emerged as a low-cost tool to screen large databases and identify potential small-molecule hits against HCV targets. Ligand-based approaches are useful for filtering-out compounds with rich physicochemical properties to inhibit HCV targets. Molecular dynamics (MD) remains a useful tool in optimizing the ligand-protein complexes and understand the ligand binding modes and drug resistance mechanisms in HCV. Despite their varied roles, the application of in-silico approaches in HCV drug design is still in its infancy. A more mature application should aim at modelling the whole HCV replicon in its active form and help to identify new effective druggable sites within the replicon system. With more technological advancements, the roles of computer-aided methods are only going to increase several folds in the development of next-generation HCV drugs.

Application of Docking Methodologies in QSAR-Based Studies

The computational strategies permeate all aspects of drug discovery such as virtual screening techniques. Virtual screening can be classified into ligand based and structure based methods. The ligand based method such as Quantitative Structure Activity Relationship (QSAR) is used when a set of active ligand compounds is recognized and slight or no structural information is available for the receptors. In structure based drug design, the most widespread method is molecular docking. It is widely accepted that drug activity is obtained through the molecular binding of one ligand to receptor. In their binding conformations, the molecules exhibit geometric and chemical complementarity, both of which are essential for successful drug activity. The molecular docking approach can be used to model the interaction between a small drug molecule and a protein, which allow us to characterize the performance of small molecules in the binding site of target proteins as well as to clarify fundamental biochemical processes.

Phosphine-catalyzed [3 + 2] cycloaddition of phthalazinium dicyanomethanides with allenoates: highly efficient synthesis of 1,2,3,10b-tetrahydropyrrolo[2,1-a]phthalazine derivatives

The phosphine-catalyzed [3 + 2] cycloaddition has been achieved at room temperature, providing novel heterocyclic compounds, 1,2,3,10b-tetrahydropyrrolo[2,1-a]phthalazine derivatives, as single (Z)-isomers in excellent yields (88–99% yield).

Multiple e-pharmacophore modeling, 3D-QSAR, and high-throughput virtual screening of hepatitis C virus NS5B polymerase inhibitors

The hepatitis C virus (HCV) NS5B RNA-dependent RNA polymerase (RdRP) is a crucial and unique component of the HCV RNA replication machinery and a validated target for drug discovery. Multiple crystal structures of NS5B inhibitor complexes have facilitated the identification of novel compound scaffolds through in silico analysis. With the goal of discovering new NS5B inhibitor leads, HCV NS5B crystal structures bound with inhibitors in the palm and thumb allosteric pockets in combination with ligands with known inhibitory potential were explored for a comparative pharmacophore analyses. The energy-based and 3D-QSAR-based pharmacophore models were validated using enrichment analysis, and the six models thus developed were employed for high-throughput virtual screening and docking to identify nonpeptidic leads. The hits derived at each stage were analyzed for diversity based on the six pharmacophore models, followed by molecular docking and filtering based on their interaction with amino acids in the NS5B allosteric pocket and 3D-QSAR predictions. The resulting 10 hits displaying diverse scaffold were then screened employing biochemical and cell-based NS5B and anti-HCV inhibition assays. Of these, two molecules H-5 and H-6 were the most promising, exhibiting IC50 values of 28.8 and 47.3 μM against NS5B polymerase and anti-HCV inhibition of 96% and 86% at 50 μM, respectively. The identified leads comprised of benzimidazole (H-5) and pyridine (H-6) scaffolds thus constitute prototypical molecules for further optimization and development as NS5B inhibitors.