Docking-based 3D-QSAR study of HIV-1 integrase inhibitors

A mini-review on integrase inhibitors: The cornerstone of next-generation HIV treatment

Integrase inhibitors represent one of the most remarkable and effective advances in the treatment of HIV-1 infection. Their lack of human cellular equivalence has established integrase as a unique and ideal target for HIV-1 treatment. Over the last two decades, a variety of drugs and small molecule inhibitors have been developed to control or treat HIV infection. Many of these FDA-approved drugs are considered first-line options for AIDS patients. Unfortunately, resistance to these drugs has dictated the development of novel and more efficacious antiretroviral drugs. In this review article, we illustrate the key classes of antiretroviral integrase inhibitors available. We provide a comprehensive analysis of recent advancements in the development of integrase inhibitors, focusing on novel compounds and their distinct mechanisms of action. Our literature review highlights emerging allosteric integrase inhibitors that offer improved efficacy, resistance profiles, and pharmacokinetics. By integrating these recent advancements and clinical insights, this review aims to provide a thorough and updated understanding of integrase inhibitors, emphasizing their evolving role in HIV treatment.

Computer-Aided and AILDE Approaches to Design Novel 4-Hydroxyphenylpyruvate Dioxygenase Inhibitors

4-Hydroxyphenylpyruvate dioxygenase (HPPD) is a pivotal enzyme in tocopherol and plastoquinone synthesis and a potential target for novel herbicides. Thirty-five pyridine derivatives were selected to establish a Topomer comparative molecular field analysis (Topomer CoMFA) model to obtain correlation information between HPPD inhibitory activity and the molecular structure. A credible and predictive Topomer CoMFA model was established by "split in two R-groups" cutting methods and fragment combinations (q² = 0.703, r² = 0.957, ONC = 6). The established model was used to screen out more active compounds and was optimized through the auto in silico ligand directing evolution (AILDE) platform to obtain potential HPPD inhibitors. Twenty-two new compounds with theoretically good HPPD inhibition were obtained by combining the high-activity contribution substituents in the existing molecules with the R-group search via Topomer search. Molecular docking results revealed that most of the 22 fresh compounds could form stable π-π interactions. The absorption, distribution, metabolism, excretion and toxicity (ADMET) prediction and drug-like properties made 9 compounds potential HPPD inhibitors. Molecular dynamics simulation indicated that Compounds Y12 and Y14 showed good root mean square deviation (RMSD) and root mean square fluctuation (RMSF) values and stability. According to the AILDE online verification, 5 new compounds with potential HPPD inhibition were discovered as HPPD inhibitor candidates. This study provides beneficial insights for subsequent HPPD inhibitor design.

Evaluation of novel HIV-1 protease inhibitors with DRV-resistance by utilizing 3D-QSAR molecular docking and molecular dynamics simulation

Molecular dynamics simulations were performed to explore the interaction mode of DRV derivatives binding to target proteins and to identify new potential HIV-1 PR inhibitors with stronger activity.

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.

Potential therapeutic approaches for a sleeping pathogen: tuberculosis a case for bioinorganic chemistry

Mycobacterium tuberculosis (Mtb) has an old history as a human pathogen and still kills over one million people every year. One key feature of this bacterium is its dormancy: a phenomenon responsible for major changes in its metabolism and replication that have been associated with the need for a lengthy therapy for Mtb. This process is regulated by key heme-based sensors, particularly DosT and DevS (DosS), among other co-regulators, and also linked to nitrogen utilization (nitrate/nitrite) and stringent responses. In face of the current threat of tuberculosis, there is an urgent need to develop new therapeutic agents capable of targeting the dormant state, associated with the need for a lengthy therapy. Interestingly, many of those key proteins are indeed metallo-containing or metallo-dependent biomolecules, opening exciting bioinorganic opportunities. Here, we critically reviewed a series of small molecules targeting key proteins involved in these processes, including DosT/DevS/DevR, RegX3, MprA, MtrA, NarL, PknB, Rel, PPK, nitrate and nitrite reductases, GlnA1, aiming for new opportunities and alternative therapies. In the battle against Mycobacterium tuberculosis, new drug targets must be searched, in particular  those involved in dormancy. A series of exciting cases for drug development involving metallo-containing or metallo-dependent biomolecules are reviewed, opening great opportunities for the bioinorganic chemistry community.

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.

Molecular docking study of lamellarin analogues and identification of potential inhibitors of HIV-1 integrase strand transfer complex by virtual screening

Molecular docking has been applied to elucidate the binding of lamellarin analogues with HIV-1 integrase strand transfer complex (PDB ID: 5U1C). The results suggest hydrogen bond interaction with residue Glu92 is key, and stabilisation by π-π stacking interactions with DNA base is chiefly influential to strand transfer activity. Other residues involved in hydrogen bonding are Cys65, His67, Asp64, Asp116 and chelation with Mg2+ ion was seen for certain analogues. Furthermore, hydrophobic interactions can be accounted for several amino acids including Asp64, Cys65, Asp116, His67, Glu92, Tyr143, Phe121, Gly118, Pro142 and Val72, as well as the DNA base. The molecular docking results are in line with the reported literatures of other inhibitors and strand transfer activity observed previously by Faulkner. We further employed molecular docking simulation to virtually screen and identified 4 novel potential inhibitors of HIV-1 integrase strand transfer complex from a Chembridge diversity collection of 25,132 small molecule compounds; Chembridge ID compound codes: 22850303, 27553460, 24578440 and 27591056. The candidates clearly formed hydrogen bonding interactions with important residues: His67 and Glu92. In addition, hydrophobic interactions were seen with residues similar to interactions with lamellarin analogues. The calculated drug-like scores are suggestive of these compounds to have clinical potential and ADMET predictions implied of their acceptable pharmacokinetic and toxicity profiles.

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.

Recent Developments in 3D QSAR and Molecular Docking Studies of Organic and Nanostructures

The development of quantitative structure–activity relationship (QSAR) methods is going very fast for the last decades. OSAR approach already plays an important role in lead structure optimization, and nowadays, with development of big data approaches and computer power, it can even handle a huge amount of data associated with combinatorial chemistry. One of the recent developments is a three-dimensional QSAR, i.e., 3D QSAR. For the last two decades, 3D-OSAR has already been successfully applied to many datasets, especially of enzyme and receptor ligands. Moreover, quite often 3D QSAR investigations are going together with protein–ligand docking studies and this combination works synergistically. In this review, we outline recent advances in development and applications of 3D QSAR and protein–ligand docking approaches, as well as combined approaches for conventional organic compounds and for nanostructured materials, such as fullerenes and carbon nanotubes.

The conformational feasibility for the formation of reaching dimer in ASV and HIV integrase: a molecular dynamics study

Retroviral integrases are reported to form alternate dimer assemblies like the core-core dimer and reaching dimer. The core-core dimer is stabilized predominantly by an extensive interface between two catalytic core domains. The reaching dimer is stabilized by N-terminal domains that reach to form intermolecular interfaces with the other subunit's core and C-terminal domains (CTD), as well as CTD-CTD interactions. In this study, molecular dynamics (MD), Brownian dynamics (BD) simulations, and free energy analyses, were performed to elucidate determinants for the stability of the reaching dimer forms of full-length Avian Sarcoma Virus (ASV) and Human Immunodeficiency Virus (HIV) IN, and to examine the role of the C-tails (the last ~16-18 residues at the C-termini) in their structural dynamics. The dynamics of an HIV reaching dimer derived from small angle X-ray scattering and protein crosslinking data, was compared with the dynamics of a core-core dimer model derived from combining the crystal structures of two-domain fragments. The results showed that the core domains in the ASV reaching dimer express free dynamics, whereas those in the HIV reaching dimer are highly stable. BD simulations suggest a higher rate of association for the HIV core-core dimer than the reaching dimer. The predicted stability of these dimers was therefore ranked in the following order: ASV reaching dimer < HIV reaching dimer < composite core-core dimer. Analyses of MD trajectories have suggested residues that are critical for intermolecular contacts in each reaching dimer. Tests of these predictions and insights gained from these analyses could reveal a potential pathway for the association and dissociation of full-length IN multimers.

Molecular features related to HIV integrase inhibition obtained from structure- and ligand-based approaches

Among several biological targets to treat AIDS, HIV integrase is a promising enzyme that can be employed to develop new anti-HIV agents. The aim of this work is to propose a mechanistic interpretation of HIV-1 integrase inhibition and to rationalize the molecular features related to the binding affinity of studied ligands. A set of 79 HIV-1 integrase inhibitors and its relationship with biological activity are investigated employing 2D and 3D QSAR models, docking analysis and DFT studies. Analyses of docking poses and frontier molecular orbitals revealed important features on the main ligand-receptor interactions. 2D and 3D models presenting good internal consistency, predictive power and stability were obtained in all cases. Significant correlation coefficients (r(2) = 0.908 and q(2)= 0.643 for 2D model; r(2)= 0.904 and q(2)= 0.719 for 3D model) were obtained, indicating the potential of these models for untested compounds. The generated holograms and contribution maps revealed important molecular requirements to HIV-1 IN inhibition and several evidences for molecular modifications. The final models along with information resulting from molecular orbitals, 2D contribution and 3D contour maps should be useful in the design of new inhibitors with increased potency and selectivity within the chemical diversity of the data.

Docking-based CoMFA and CoMSIA study of azaindole carboxylic acid derivatives as promising HIV-1 integrase inhibitors

Three-dimensional quantitative structure-activity relationship (3D-QSAR) studies were performed based on a series of azaindole carboxylic acid derivatives that had previously been reported as promising HIV-1 integrase inhibitors. Docking studies to explore the binding mode were performed based on the highly active molecule 36. The best docked conformation of molecule 36 was used as template for alignment. The comparative molecular field analysis (CoMFA) model (including steric and electrostatic fields) yielded the cross validation q (2) = 0.655, non-cross validation r (2) = 0.989 and predictive r (2) pred = 0.979. The best comparative molecular similarity indices analysis (CoMSIA) model (including steric, electrostatic, hydrophobic and hydrogen-bond acceptor fields) yielded the cross validation q (2) = 0.719, non-cross validation r (2) = 0.992 and predictive r (2) pred = 0.953. A series of new azaindole carboxylic acid derivatives were designed and the HIV-1 integrase inhibitory activities of these designed compounds were predicted based on the CoMFA and CoMSIA models.

Pharmacophore modelling and electronic feature analysis of hydroxamic acid derivatives, the HIV integrase inhibitors

Hydroxamic acid derivatives with metal ion binding properties were collected from the literature to generate a pharmacophore and 3D-QSAR model for HIV strand transfer inhibition. The derived pharmacophore model (AAAHRR) recognizes both metal ion binding site and hydrophobic group. The QSAR model generated using this hypothesis expressed statistical significance (r(2) = 0.971 for the training set and q(2) = 0.913 for the test set). The ability of this pharmacophore model to retrieve other metal ion binding inhibitors was examined by screening the ChemBank database (ligandinfo) incorporated with 10 known strand transfer inhibitors. The studied favourable and unfavourable contours of chemical features (H-bond donor, acceptor and hydrophobic sites) revealed the role of hydrophobic substitution at the fluorobenzene ring and cyclization of the metal ion binding hydroxamic acid in effective integrase inhibition. Analysis of the frontier orbitals, HOMO and LUMO revealed that the nucleophilic / electrophilic interactions depend on the significant overlapping observed at the azaindole and hydroxamic acid groups. In essence, the generated pharmacophore model is competent enough to disclose the essential site-specific interactions involved in the inhibition of HIV integrase, and hence can be used in virtual screening to identify novel scaffolds as leads with increased anti-viral potency.

Prediction of bioactivity of HIV-1 integrase ST inhibitors by multilinear regression analysis and support vector machine

In this study, four computational quantitative structure-activity relationship models were built to predict the biological activity of HIV-1 integrase strand transfer (ST) inhibitors. 551 Inhibitors whose bioactivities were detected by radiolabeling method were collected. The molecules were represented with 20 selected MOE descriptors. All inhibitors were divided into a training set and a test set with two methods: (1) by a Kohonen's self-organizing map (SOM); (2) by a random selection. For every training set and test set, a multilinear regression (MLR) analysis and a support vector machine (SVM) were used to establish models, respectively. For the test set divided by SOM, the correlation coefficients (rs) were over 0.91, and for the test set split randomly, the rs were over 0.86.

A ligand-based approach for the in silico discovery of multi-target inhibitors for proteins associated with HIV infection

Acquired immunodeficiency syndrome (AIDS) is a dangerous disease, which damages the immune system cells to the point that the immune system can no longer fight against other infections that it would usually be able to prevent. The causal agent is the human immunodeficiency virus (HIV), and for this reason, the search for more effective chemotherapies against HIV is a challenge for the scientific community. Chemoinformatics and Quantitative Structure-Activity Relationship (QSAR) studies have played an essential role in the design of potent inhibitors for proteins associated with the HIV infection. However, all previous studies took into consideration the discovery of future drug candidates using homogeneous series of compounds against only one protein. This fact limits the use of more efficient anti-HIV chemotherapies. In this work, we develop the first ligand-based approach for the in silico design of multi-target (mt) inhibitors for seven key proteins associated with the HIV infection. Two mt-QSAR models were constructed from a large and heterogeneous database of compounds. The first model was based on linear discriminant analysis (mt-QSAR-LDA) employing fragment-based descriptors. The second model was obtained using artificial neural networks (mt-QSAR-ANN) with global 2D descriptors. Both models correctly classified more than 90% of active and inactive compounds in training and prediction sets. Some fragments were extracted and their contributions to anti-HIV activity through inhibition of the different proteins were calculated using the mt-QSAR-LDA model. New molecules designed from fragments with positive contributions were suggested and correctly predicted by the two models as possible potent and versatile anti-HIV agents.

Molecular docking, 3D-QSAR studies, and in silico ADME prediction of p-aminosalicylic acid derivatives as neuraminidase inhibitors

Neuraminidase (NA) is a major glycoprotein of influenza virus which is essential for viral infection. It offers a potential target for antiviral drug design and discovery. To develop novel potent neuraminidase inhibitors (NAI), Surflex-Dock was employed to dock 40 hydrophobic p-aminosalicylic acid derivatives into the active site of NA. The 3D-quantitative structure-activity relationship studies involving comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) were carried out on 40 molecules. Both CoMFA (q(2) = 0.628, r(2) = 0.697) and CoMSIA (q(2) = 0.746, r(2) = 0.816) gave reasonable results. A preliminary pharmacokinetic profile of these NAI was also performed on the basis of Volsurf predictions. The results obtained from this study will be useful in the design of novel potent NAI.

Computational investigation of the anti-HIV activity of Chinese medicinal formula Three-Huang Powder

An essential step in the life cycle of human immunodeficiency virus type 1 (HIV-1) is integration of the double-stranded retroviral DNA into the genome of the host cell. HIV-1 integrase, the enzyme that inserts the vital DNA into the host chromosome, is an attractive and rational target for anti-AIDS drug design because it is essential for HIV replication and there are no known counterparts in the host cell. Inhibitors of this enzyme have the great potential to complement the therapeutic use of HIV protease and reverse transcriptase inhibitors. Natural products have provided a source of new drug candidates for anti-AIDS therapy. Baicalein and baicalin, identified components of a Chinese herbal medicine Scutellaria baicalensis Georgi, have been shown to inhibit infectivity and replication of HIV. They are therefore promising lead compounds for developing new anti-AIDS drugs. To understand how the inhibitors work and therefore design more potent and specific inhibitors, we have used molecular modeling techniques to investigate the binding modes of these inhibitors. The three-dimensional structures of these inhibitors were first built. Then, computational binding studies of these inhibitors, based on the crystal structure of the HIV-1 integrase catalytic domain, were performed to study the complex structure. The preliminary results of our computational modeling study demonstrated that Baicalein binds to the active site region of the HIV-1 integrase. Our study will be of help to identify the pharmacophores of inhibitors binding to HIV-1 integrase and design new pharmaceuticals for the treatment of AIDS.