Application of 3D-QSAR, Pharmacophore, and Molecular Docking in the Molecular Design of Diarylpyrimidine Derivatives as HIV-1 Nonnucleoside Reverse Transcriptase Inhibitors

Exploration of N-Arylsulfonyl-indole-2-carboxamide Derivatives as Novel Fructose-1,6-bisphosphatase Inhibitors by Molecular Simulation

A series of N-arylsulfonyl-indole-2-carboxamide derivatives have been identified as potent fructose-1,6-bisphosphatase (FBPase) inhibitors (FBPIs) with excellent selectivity for the potential therapy of type II diabetes mellitus. To explore the structure–activity relationships (SARs) and the mechanisms of action of these FBPIs, a systematic computational study was performed in the present study, including three-dimensional quantitative structure–activity relationship (3D-QSAR) modeling, pharmacophore modeling, molecular dynamics (MD), and virtual screening. The constructed 3D-QSAR models exhibited good predictive ability with reasonable parameters using comparative molecular field analysis (q² = 0.709, R² = 0.979, r_pre² = 0.932) and comparative molecular similarity indices analysis (q² = 0.716, R² = 0.978, r_pre² = 0.890). Twelve hit compounds were obtained by virtual screening using the best pharmacophore model in combination with molecular dockings. Three compounds with relatively higher docking scores and better ADME properties were then selected for further studies by docking and MD analyses. The docking results revealed that the amino acid residues Met18, Gly21, Gly26, Leu30, and Thr31 at the binding site were of great importance for the effective bindings of these FBPIs. The MD results indicated that the screened compounds VS01 and VS02 could bind with FBPase stably as its cognate ligand in dynamic conditions. This work identified several potential FBPIs by modeling studies and might provide important insights into developing novel FBPIs.

Comparison of various methods for validity evaluation of QSAR models

BACKGROUND

Quantitative structure-activity relationship (QSAR) modeling is one of the most important computational tools employed in drug discovery and development. The external validation of QSAR models is the main point to check the reliability of developed models for the prediction activity of not yet synthesized compounds. It was performed by different criteria in the literature.

METHODS

In this study, 44 reported QSAR models for biologically active compounds reported in scientific papers were collected. Various statistical parameters of external validation of a QSAR model were calculated, and the results were discussed.

RESULTS

The findings revealed that employing the coefficient of determination (r²) alone could not indicate the validity of a QSAR model. The established criteria for external validation have some advantages and disadvantages which should be considered in QSAR studies.

CONCLUSION

This study showed that these methods alone are not only enough to indicate the validity/invalidity of a QSAR model.

Novel insecticidal 1,6-dihydro-6-iminopyridazine derivatives as competitive antagonists of insect RDL GABA receptors

BACKGROUND

The ionotropic γ-aminobutyric acid (GABA) receptor (iGABAR) is an important target for insecticides and parasiticides. Our previous studies showed that competitive antagonists (CAs) of insect iGABARs have the potential to be used for developing novel insecticides and that the structural modification of gabazine (a representative CA of mammalian iGABARs) could lead to the identification of novel CAs of insect iGABARs.

RESULTS

In the present study, a novel series of 1,3-di- and 1,3,5-trisubstituted 1,6-dihydro-6-iminopyridazines (DIPs) was designed using a versatile strategy and synthesized using facile methods. Electrophysiological studies showed that several target DIPs (30 μM) exhibited excellent antagonistic activities against common cutworm and housefly iGABARs consisting of RDL subunits. The IC₅₀ values of 3-(4-methoxyphenyl), 3-(4-trifluoromethoxyphenyl), 3-(4-biphenylylphenyl), 3-(2-naphthyl), 3-(3,4-methylenedioxyphenyl), and 3,5-(4-methoxyphenyl) analogs ranged from 2.2 to 24.8 μM. Additionally, several 1,3-disubstituted DIPs, especially 3-(4-trifluoromethoxyphenyl) and 3-(3,4-methylenedioxyphenyl) analogs, exhibited moderate insecticidal activity against common cutworm larvae, with >60% mortality at a concentration of 100 mg kg^-1 . Molecular docking studies showed that the oxygen atom on the three-substituted aromatic ring could form a hydrogen bond with Arg254, which may enhance the activity of these DIPs against housefly iGABARs.

CONCLUSION

This systematic study indicated that the presence of a carboxyl side chain shorter by one methylene than that of gabazine at the 1-position of the pyridazine ring is effective for maintaining the stable binding of these DIPs in insect iGABARs. Our study provides important information for the design of novel insect iGABAR CAs. © 2022 Society of Chemical Industry.

ELIXIR-A: An Interactive Visualization Tool for Multi-Target Pharmacophore Refinement

Pharmacophore modeling is an important step in computer-aided drug design for identifying interaction points between the receptor and ligand complex. Pharmacophore-based models can be used for de novo drug design, lead identification, and optimization in virtual screening as well as for multi-target drug design. There is a need to develop a user-friendly interface to filter the pharmacophore points resulting from multiple ligand conformations. Here, we present ELIXIR-A, a Python-based pharmacophore refinement tool, to help refine the pharmacophores between multiple ligands from multiple receptors. Furthermore, the output can be easily used in virtual pharmacophore-based screening platforms, thereby contributing to the development of drug discovery.

In Silico Screening of Novel α1-GABAA Receptor PAMs towards Schizophrenia Based on Combined Modeling Studies of Imidazo [1,2-a]-Pyridines

The ionotropic GABAA receptor (GABAAR) has been proven to be an important target of atypical antipsychotics. A novel series of imidazo [1,2-a]-pyridine derivatives, as selective positive allosteric modulators (PAMs) of α1-containing GABAARs with potent antipsychotic activities, have been reported recently. To better clarify the pharmacological essentiality of these PAMs and explore novel antipsychotics hits, three-dimensional quantitative structure-activity relationships (3D-QSAR), molecular docking, pharmacophore modeling, and molecular dynamics (MD) were performed on 33 imidazo [1,2-a]-pyridines. The constructed 3D-QSAR models exhibited good predictive abilities. The dockings results and MD simulations demonstrated that hydrogen bonds, π-π stackings, and hydrophobic interactions play essential roles in the binding of these novel PAMs in the GABAAR binding pocket. Four hit compounds (DS01-04) were then screened out by the combination of the constructed models and computations, including the pharmacophore model, Topomer Search, molecular dockings, ADME/T predictions, and MD simulations. The compounds DS03 and DS04, with higher docking scores and better predicted activities, were also found to be relatively stable in the binding pocket by MD simulations. These results might provide a significant theoretical direction or information for the rational design and development of novel α1-GABAAR PAMs with antipsychotic activities.

Exploration of Novel Xanthine Oxidase Inhibitors Based on 1,6-Dihydropyrimidine-5-Carboxylic Acids by an Integrated in Silico Study

Xanthine oxidase (XO) is an important target for the effective treatment of hyperuricemia-associated diseases. A series of novel 2-substituted 6-oxo-1,6-dihydropyrimidine-5-carboxylic acids (ODCs) as XO inhibitors (XOIs) with remarkable activities have been reported recently. To better understand the key pharmacological characteristics of these XOIs and explore more hit compounds, in the present study, the three-dimensional quantitative structure-activity relationship (3D-QSAR), molecular docking, pharmacophore modeling, and molecular dynamics (MD) studies were performed on 46 ODCs. The constructed 3D-QSAR models exhibited reliable predictability with satisfactory validation parameters, including q2 = 0.897, R2 = 0.983, rpred2 = 0.948 in a CoMFA model, and q2 = 0.922, R2 = 0.990, rpred2 = 0.840 in a CoMSIA model. Docking and MD simulations further gave insights into the binding modes of these ODCs with the XO protein. The results indicated that key residues Glu802, Arg880, Asn768, Thr1010, Phe914, and Phe1009 could interact with ODCs by hydrogen bonds, π-π stackings, or hydrophobic interactions, which might be significant for the activity of these XOIs. Four potential hits were virtually screened out using the constructed pharmacophore model in combination with molecular dockings and ADME predictions. The four hits were also found to be relatively stable in the binding pocket by MD simulations. The results in this study might provide effective information for the design and development of novel XOIs.

In Silico Design of Peptide-Based SARS-CoV-2 Fusion Inhibitors That Target WT and Mutant Versions of SARS-CoV-2 HR1 Domains

In 2019, novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) began infecting humans, resulting in the COVID-19 pandemic. While the push for development of vaccines has yielded some positive results, the emergence of additional variants has led to concerns surrounding sustained vaccine effectiveness as the variants become the dominant strains. This work was undertaken to develop peptide-based antivirals capable of targeting both the wildtype (WT) heptad repeat 1 (HR1) domain of SARS-CoV-2 and the new HR1 variants which have developed. In silico protein mutagenesis, structural characterization, and protein–protein molecular docking were utilized to determine molecular interactions which facilitated binding of peptide-based antivirals targeting the HR1 domains. Molecular dynamics simulations were utilized to predict the final binding affinities of the top five peptide inhibitors designed. This work demonstrated the importance of hydrophobic interactions in the hydrophobic gorge and in the rim of the HR1 domain. Additionally, the placement of charged residues was shown to be essential in maximizing electrostatic interactions. The top five designed peptide inhibitors were all demonstrated to maintain good binding affinity to the WT and the variant HR1 SARS-CoV-2 domains. Therefore, the peptide inhibitors designed in this work could serve as potent antivirals which are effective in targeting both the original SARS-CoV-2 and the HR1 variants that have developed.

Three Major Phosphoacceptor Sites in HIV-1 Capsid Protein Enhances its Structural Stability and Resistance Against the Inhibitor: Explication Through Molecular Dynamics Simulation, Molecular Docking and DFT Analysis

BACKGROUND

Human Immunodeficiency Virus 1 (HIV-1) is a lentivirus, which causes various HIV-associated infections. The HIV-1 core dissociation is essential for viral cDNA synthesis and phosphorylation of HIV-1 capsid protein (HIV-1 CA) plays an important role in it.

OBJECTIVE

The aim of this study was to explicate the role of three phosphoserine sites i.e. Ser109, Ser149 and Ser178 in the structural stability of HIV-1 CA, and it's binding with GS-CA1, a novel potent inhibitor.

METHODS

Eight complexes were analyzed and Molecular Dynamics (MD) simulations were performed to observe the stability of HIV-1 CA in the presence and absence of phosphorylation of serine residues at four different temperatures i.e. 300K, 325K, 340K and 350K, along with molecular docking and DFT analysis.

RESULTS

The structures showed maximum stability in the presence of phosphorylated serine residue. However, GS-CA1 docked most strongly with the native structure of HIV-1 CA i.e. binding affinity was -8.5 kcal/mol (Ki = 0.579 µM).

CONCLUSION

These results suggest that the phosphorylation of these three serine residues weakens the binding of GS-CA1 with CA and casts derogatory effect on inhibition potential of this inhibitor, but it supports the stability of HIV-1 CA structure that can enhance regulation and replication of HIV-1 in host cells.

3D-QSAR, molecular docking and molecular dynamics simulations analyses of a series of heteroaryldihydropyrimidine derivatives as hepatitis B virus capsid assembly inhibitors

In silico design of heteroaryldihydropyrimidine-based selective HBV capsid assembly inhibitors.

Recent discoveries in HIV-1 reverse transcriptase inhibitors

HIV-1 reverse transcriptase inhibitors (RTIs) are indispensable components of highly active antiretroviral therapy (HAART), which has achieved great success in controlling AIDS epidemic in reducing drastically the morbidity and mortality of HIV-infected patients. RTIs are divided into two categories, nucleoside reverse transcriptase inhibitors (NRTIs) and nonnucleoside reverse transcriptase inhibitors (NNRTIs). In this review, the recent discoveries in NRTIs and NNRTIs, including approved anti-HIV drugs and noteworthy drug candidates in different development stages, are summarized, and their future direction is prospected.

Molecular docking based design of Inhibitors for viral Non-Nucleosidase as potential anti-retroviral agents

Reverse Transcriptase (RT) inhibitors are highly promising agents for use as an effective anti-retroviral therapy (HAART) which is typically a combination of three or four antiretroviral drugs. We used direct drug design approach to discover new chemical entities for the target protein. The validated template of the protein targeting reverse transcriptase PDB ID 1JKH was extracted for three sites hydrophobic, steric, and electronic parameters explain the interactions at the active site by the inhibitors. We used the Zinc library of compounds to explore the possible leads for HAART through RT inhibition. We report 12 new chemical entities with possible activity against the targeted viral protein. These leads will provide new therapeutic means in antiretroviral therapy.

Optimization Rules for SARS-CoV-2 Mpro Antivirals: Ensemble Docking and Exploration of the Coronavirus Protease Active Site

Coronaviruses are viral infections that have a significant ability to impact human health. Coronaviruses have produced two pandemics and one epidemic in the last two decades. The current pandemic has created a worldwide catastrophe threatening the lives of over 15 million as of July 2020. Current research efforts have been focused on producing a vaccine or repurposing current drug compounds to develop a therapeutic. There is, however, a need to study the active site preferences of relevant targets, such as the SARS-CoV-2 main protease (SARS-CoV-2 M^pro), to determine ways to optimize these drug compounds. The ensemble docking and characterization work described in this article demonstrates the multifaceted features of the SARS-CoV-2 M^pro active site, molecular guidelines to improving binding affinity, and ultimately the optimization of drug candidates. A total of 220 compounds were docked into both the 5R7Z and 6LU7 SARS-CoV-2 M^pro crystal structures. Several key preferences for strong binding to the four subsites (S1, S1′, S2, and S4) were identified, such as accessing hydrogen binding hotspots, hydrophobic patches, and utilization of primarily aliphatic instead of aromatic substituents. After optimization efforts using the design guidelines developed from the molecular docking studies, the average docking score of the parent compounds was improved by 6.59 −log₁₀(Kd) in binding affinity which represents an increase of greater than six orders of magnitude. Using the optimization guidelines, the SARS-CoV-2 M^pro inhibitor cinanserin was optimized resulting in an increase in binding affinity of 4.59 −log₁₀(Kd) and increased protease inhibitor bioactivity. The results of molecular dynamic (MD) simulation of cinanserin-optimized compounds CM02, CM06, and CM07 revealed that CM02 and CM06 fit well into the active site of SARS-CoV-2 M^pro [Protein Data Bank (PDB) accession number 6LU7] and formed strong and stable interactions with the key residues, Ser-144, His-163, and Glu-166. The enhanced binding affinity produced demonstrates the utility of the design guidelines described. The work described herein will assist scientists in developing potent COVID-19 antivirals.

Novel mTOR Inhibitor Enhances the Sensitivity of Hepatocellular Carcinoma Cells to Molecular Targeting Agents

Background

Although molecular-targeted agents are still the first choice for advanced hepatocellular carcinoma (HCC) treatment, the therapeutic efficacy of these agents is not satisfactory. Recently, the mammalian target of rapamycin (mTOR) is considered to be a promising molecular target that can enhance the sensitivity of HCC cells to antitumor therapy. However, the reported mTOR inhibitors have some shortcomings, and novel mTOR inhibitors need to be developed to enhance the antitumor effect of molecularly targeted agents on advanced HCC.

Methods

In this study, five small-molecular compounds that could serve as potential mTOR-specific inhibitors were identified by virtual screening. The activity of tert-butyl (4-(9-(2-(1,3-dioxolan-2-yl)ethyl)-6-morpholino-9H-purin-2-yl)phenyl)carbamate (compound 4) was measured by enzyme test and Western blot, and its antitumor effect on HCC was examined in nude mice subcutaneous tumor model.

Results

The results showed that 4 is the most effective one in inhibiting the activation of mTOR kinase (mTOR IC₅₀ = 17.52±3.67 nmol/L) among the five lead compounds. Further research in this study indicated that treatment with 4 enhanced the sensitivity of HCC cells to the molecular-targeted agents, such as sorafenib, regorafenib, lenvatinib, anlotinib, and apatinib. In addition, this research indicated that mTOR was correlated with the poor prognosis in patients with advanced HCC who received sorafenib.

Conclusion

Our study identified a new type of small-molecular inhibitors of mTOR and confirmed their ability to enhance the antitumor effect of molecular-targeted agents on advanced HCC.

Virtual Screening and Optimization of Novel mTOR Inhibitors for Radiosensitization of Hepatocellular Carcinoma

Background

Radiotherapy has an ameliorative effect on a wide variety of tumors, but hepatocellular carcinoma (HCC) is insensitive to this treatment. Overactivated mammalian target of rapamycin (mTOR) plays an important part in the resistance of HCC to radiotherapy; thus, mTOR inhibitors have potential as novel radiosensitizers to enhance the efficacy of radiotherapy for HCC.

Methods

A lead compound was found based on pharmacophore modeling and molecular docking, and optimized according to the differences between the ATP-binding pockets of mTOR and PI3K. The radiosensitizing effect of the optimized compound (2a) was confirmed by colony formation assays and DNA double-strand break assays in vitro. The discovery and preclinical characteristics of this compound are described.

Results

The key amino acid residues in mTOR were identified, and a precise virtual screening model was constructed. Compound 2a, with a 4,7-dihydro-[1,2,4]triazolo[1,5-a]pyrimidine scaffold, exhibited promising potency against mTOR (mTOR IC₅₀=7.1 nmol/L (nM)) with 126-fold selectivity over PI3Kα. Moreover, 2a significantly enhanced the sensitivity of HCC to radiotherapy in vitro in a dose-dependent manner.

Conclusion

A new class of selective mTOR inhibitors was developed and their radiosensitization effects were confirmed. This study also provides a basis for developing mTOR-specific inhibitors for use as radiosensitizers for HCC radiotherapy.

In silico Design of Novel HIV-1 NNRTIs Based on Combined Modeling Studies of Dihydrofuro[3,4-d]pyrimidines

A novel series of dihydrofuro[3,4-d]pyrimidine (DHPY) analogs have recently been recognized as promising HIV-1 non-nucleoside reverse transcriptase (RT) inhibitors (NNRTIs) with potent antiviral activity. To better understand the pharmacological essentiality of these DHPYs and design novel NNRTI leads, in this work, a systematic in silico study was performed on 52 DHPYs using three-dimensional quantitative structure-activity relationship (3D-QSAR), molecular docking, virtual screening, absorption-distribution-metabolism-excretion (ADME) prediction, and molecular dynamics (MD) methods. The generated 3D-QSAR models exhibited satisfactory parameters of internal validation and well-externally predictive capacity, for instance, the q2, R2, andr pred 2 of the optimal comparative molecular similarity indices analysis model were 0.647, 0.970, and 0.751, respectively. The docking results indicated that residues Lys101, Tyr181, Tyr188, Trp229, and Phe227 played important roles for the DHPY binding. Nine lead compounds were obtained by the virtual screening based on the docking and pharmacophore model, and three new compounds with higher docking scores and better ADME properties were subsequently designed based on the screening and 3D-QSAR results. The MD simulation studies further demonstrated that the newly designed compounds could stably bind with the HIV-1 RT. These hit compounds were supposed to be novel potential anti-HIV-1 inhibitors, and these findings could provide significant information for designing and developing novel HIV-1 NNRTIs.

In Silico Studies against Viral Sexually Transmitted Diseases

Sexually Transmitted Diseases (STDs) refer to a variety of clinical syndromes and infections caused by pathogens that can be acquired and transmitted through sexual activity. Among STDs widely reported in the literature, viral sexual diseases have been increasing in a number of cases globally. This emphasizes the need for prevention and treatment. Among the methods widely used in drug planning are Computer-Aided Drug Design (CADD) studies and molecular docking which have the objective of investigating molecular interactions between two molecules to better understand the three -dimensional structural characteristics of the compounds. This review will discuss molecular docking studies applied to viral STDs, such as Ebola virus, Herpes virus and HIV, and reveal promising new drug candidates with high levels of specificity to their respective targets.

Study on the interactions of pyrimidine derivatives with FAK by 3D-QSAR, molecular docking and molecular dynamics simulation

Focal adhesion kinase (FAK) is a kind of tyrosine kinase that modulates integrin and growth factor signaling pathways.

Identification of The Fipronil Resistance Associated Mutations in Nilaparvata lugens GABA Receptors by Molecular Modeling

Fipronil, as the first commercialized member of phenylpyrazole insecticides, has been widely used to control planthoppers in China due to its high insecticidal activity and low toxicity to mammals. However, insects have developed resistance to phenylpyrazoles after their long-term use. The resistance mechanism of insects to fipronil has not been well identified, which limited the development of phenylpyrazole insecticides. In the present study, we aimed to elucidate the related fipronil-resistance mechanism in N. lugens GABA receptors by homology modeling, molecular docking, and molecular dynamics. The results indicated that fipronil showed the weakest interaction with the mutant (R0'Q + A2'S) GABA receptors, which is consistent with the experimental study. The binding poses of fipronil were found to be changed when mutations were conducted. These findings verified the novel fipronil-resistance mechanism in silico and provide important information for the design of novel GABAR-targeting insecticides.

In silico study of 3-hydroxypyrimidine-2,4-diones as inhibitors of HIV RT-associated RNase H using molecular docking, molecular dynamics, 3D-QSAR, and pharmacophore models

Rational design and virtual screening of novel inhibitors of HIV reverse transcriptase associated ribonuclease H based on a combined molecular modeling study.

4-Aryl-5-carbamoyl-3-isoxazolols as competitive antagonists of insect GABA receptors: Synthesis, biological activity, and molecular docking studies

Competitive antagonists (CAs) of ionotropic GABA receptors (GABARs) reportedly exhibit insecticidal activity and have potential for development as novel insecticides for overcoming emerging resistance to traditional GABAR-targeting insecticides. Our previous studies demonstrated that 4,5-disubstituted 3-isoxazolols or 3-isothiazolols are an important class of insect GABAR CAs. In the present study, we synthesized a series of 4-aryl-5-carbamoyl-3-isoxazolols and examined their antagonism of insect GABARs expressed in Xenopus oocytes. Several of these 3-isoxazolols exhibited potent antagonistic activities against housefly and common cutworm GABARs, with IC₅₀ values in the low-micromolar range in both receptors. 4-(3-Amino-4-methylphenyl)-5-carbamoyl-3-isoxazolol (3u) displayed the highest antagonism, with IC₅₀ values of 2.0 and 0.9 μM in housefly and common cutworm GABARs, respectively. Most of the synthesized 3-isoxazolols showed moderate larvicidal activities against common cutworms, with more than 50% mortality at 100 μg/g. These results indicate that 4-monocyclic aryl-5-carbamoyl-3-isoxazolol is a promising scaffold for insect GABAR CA discovery and provide important information for the design and development of GABAR-targeting insecticides with a novel mode of action.

In silico studies of diarylpyridine derivatives as novel HIV-1 NNRTIs using docking-based 3D-QSAR, molecular dynamics, and pharmacophore modeling approaches

A series of novel diarylpyridine derivatives has recently been identified as HIV-1 non-nucleoside reverse transcriptase inhibitors (NNRTIs), and most of them exhibited potent activities against HIV-1 strains, with EC₅₀ values in the low nanomolar range. However, the three-dimensional quantitative structure–activity relationships (3D-QSARs) and pharmacophore characteristics of these compounds remain to be studied. In the present study, forty-two diarylpyridine derivatives were firstly docked into HIV-1 reverse transcriptase, and molecular dynamics (10 ns) simulations were further performed to validate the reliability of the docking results, which indicated that residues Lys101, Tyr181, Tyr188, Phe227, and Trp229 might play important roles in binding with these diarylpyridines. The “U”-shaped docking conformations of all compounds were then used to construct 3D-QSAR and pharmacophore models. The satisfactory statistical parameters of CoMFA (q_loo² = 0.665, r_ncv² = 0.989, r_pred² = 0.962, etc.) and CoMSIA (q_loo² = 0.727, r_ncv² = 0.988, r_pred² = 0.912, etc.) models demonstrated that both constructed models had excellent predictability, and their contour maps gave insights into the structural requirements of the diarylpyridines for the anti-HIV-1 activity. A docking-conformation-based pharmacophore model, containing three hydrophobic centers, three hydrogen-bond acceptors, and three hydrogen-bond donors, was also established. The observations in this study might provide important information for the rational design and development of novel HIV-1 NNRTIs.

Computational modeling approaches were successfully applied to a series of diarylpyridine derivatives as novel HIV-1 NNRTIs.