Design of novel HIV-1 protease inhibitors incorporating isophthalamide-derived P2-P3 ligands: Synthesis, biological evaluation and X-ray structural studies of inhibitor-HIV-1 protease complex

Advanced molecular mechanisms of modified DRV compounds in targeting HIV-1 protease mutations and interrupting monomer dimerization

HIV-1 protease (PR) plays a crucial role in the treatment of HIV as a key target. The global issue of emerging drug resistance is escalating, and PR mutations pose a substantial challenge to the effectiveness of inhibitors. HIV-1 PR is an ideal model for studying drug resistance to inhibitors. The inhibitor, darunavir (DRV), exhibits a high genetic barrier to viral resistance, but with mutations of residues in the PR, there is also some resistance to DRV. Inhibitors can impede PR in two ways: one involves binding to the active site of the dimerization protease, and the other involves binding to the PR monomer, thereby preventing dimerization. In this study, we aimed to investigate the inhibitory effect of DRV with a modified inhibitor on PR, comparing the differences between wild-type and mutated PR, using molecular dynamics simulations. The inhibitory effect of the inhibitors on PR monomers was subsequently investigated. And molecular mechanics Poisson-Boltzmann surface area evaluated the binding free energy. The energy contribution of individual residues in the complex was accurately calculated by the alanine scanning binding interaction entropy method. The results showed that these inhibitors had strong inhibitory effects against PR mutations, with GRL-142 exhibiting potent inhibition of both the PR monomer and dimer. Improved inhibitors could strengthen hydrogen bonds and interactions with PR, thereby boosting inhibition efficacy. The binding of the inhibitor and mutation of the PR affected the distance between D25 and I50, preventing their dimerization and the development of drug resistance. This study could accelerate research targeting HIV-1 PR inhibitors and help to further facilitate drug design targeting both mechanisms.

Exploration of imatinib and nilotinib-derived templates as the P2-Ligand for HIV-1 protease inhibitors: Design, synthesis, protein X-ray structural studies, and biological evaluation

Structure-based design, synthesis, X-ray structural studies, and biological evaluation of a new series of potent HIV-1 protease inhibitors are described. These inhibitors contain various pyridyl-pyrimidine, aryl thiazole or alkylthiazole derivatives as the P2 ligands in combination with darunavir-like hydroxyethylamine sulfonamide isosteres. These heterocyclic ligands are inherent to kinase inhibitor drugs, such as nilotinib and imatinib. These ligands are designed to make hydrogen bonding interactions with the backbone atoms in the S2 subsite of HIV-1 protease. Various benzoic acid derivatives have been synthesized and incorporation of these ligands provided potent inhibitors that exhibited subnanomolar level protease inhibitory activity and low nanomolar level antiviral activity. Two high resolution X-ray structures of inhibitor-bound HIV-1 protease were determined. These structures provided important ligand-binding site interactions for further optimization of this class of protease inhibitors.

Improved 3D-QSAR Prediction by Multiple Conformational Alignments and Molecular Docking Studies to Design and Discover HIV-I Protease Inhibitors

BACKGROUND

Inhibition of HIV-I protease enzyme is a strategic step for providing better treatment in retrovirus infections, which avoids resistance and possesses less toxicity.

OBJECTIVES

In the course of our research to discover new and potent protease inhibitors, 3D-QSAR (CoMFA and CoMSIA) models were generated using 3 different alignment techniques, including multifit alignment, docking based and Distill based alignment for 63 compounds. Novel molecules were designed from the output of this study.

METHODS

A total of 3 alignment methods were used to generate CoMFA and CoMSIA models. A Distill based alignment method was considered a better method according to different validation parameters. A 3D-QSAR model was generated and contour maps were discussed. The biological activity of designed molecules was predicted using the generated QSAR model to validate QSAR. The newly designed molecules were docked to predict binding affinity.

RESULTS

In CoMFA, leave one out cross-validated coefficient (q²), conventional coefficient (r²) and predicted correlation coefficient (r²_Predicted) values were found to be 0.721, 0.991 and 0.780, respectively. The best obtained CoMSIA model also showed significant cross-validated coefficient (q²), conventional coefficient (r²) and predicted correlation coefficient (r²_Predicted) values of 0.714, 0.987 and 0.721, respectively. Steric and electrostatic contour maps generated from CoMFA and hydrophobic and hydrogen bond donor and hydrogen bond acceptor contour maps from CoMSIA models were used to design new and bioactive protease inhibitors by incorporating bioisosterism and knowledge-based structure-activity relationship.

CONCLUSION

The results from both these approaches, ligand-based drug design and structure-based drug design, are adequate and promising to discover protease inhibitors.

Recombinant expression of HIV-1 protease using soluble fusion tags in Escherichia coli: A vital tool for functional characterization of HIV-1 protease

HIV-1 protease expression in the laboratory is demanding because of its high cytotoxicity, making it difficult to express in bacterial expression systems such as Escherichia coli. To overcome these challenges, HIV-1 protease fusion with solubility enhancing tags helps to mitigate its cytotoxic effect and drive its expression as a soluble protein. Therefore, this review focuses on the expression of bioactive HIV-1 protease using solubility-enhancing fusion tags in Escherichia coli and summarises the characteristic features of the different common fusion tags that have been used in the expression of HIV-1 protease. This review will assist researchers with their choice of protein fusion tag for HIV-1 protease expression.

Neto JDB, de Abreu FC, Figueiredo IM, Carinhanha C. Santos J, Pessoa CDÓ, da Silva-Júnior EF, de Araújo-Júnior JX, M. de Aquino T. Synthesis of hybrids thiazole–quinoline, thiazole–indole and their analogs: in vitro anti-proliferative effects on cancer cell lines, DNA binding properties and molecular modeling

A quinoline–thiazole hybrid was synthesized, which showed cytotoxicity against the HL-60 cell line. Electrochemical and spectroscopic experiments suggested DNA as the biological target.

Design, synthesis and biological evaluation of HIV-1 protease inhibitors with morpholine derivatives as P2 ligands in combination with cyclopropyl as P1' ligand

A series of novel HIV-1 protease inhibitors has been designed and synthesized, which contained morpholine derivatives as the P2 ligands and hydrophobic cyclopropyl as the P1' ligand at the meantime in this study, with the aim of improving the interactions between the active sites of HIV-1 protease and the inhibitors. Twenty-eight compounds were synthesized and assessed, among which inhibitors m18 and m1 exhibited excellent inhibitory effect on the activity of HIV-1 protease with IC₅₀ value of 47 nM and 53 nM, respectively. The molecular modeling of m1 revealed possible hydrogen bondings or van der Waals between the inhibitor and the protease, worthy of in-depth study.

Highly Selective and Potent Human β-Secretase 2 (BACE2) Inhibitors against Type 2 Diabetes: Design, Synthesis, X-ray Structure and Structure-Activity Relationship Studies

Herein we present the design, synthesis, and biological evaluation of potent and highly selective β-secretase 2 (memapsin 1, beta-site amyloid precursor protein cleaving enzyme 2, or BACE 2) inhibitors. BACE2 has been recognized as an exciting new target for type 2 diabetes. The X-ray structure of BACE1 bound to inhibitor 2 a {N³ -[(1S,2R)-1-benzyl-2-hydroxy-3-[[(1S,2S)-2-hydroxy-1-(isobutylcarbamoyl)propyl]amino]propyl]-5-[methyl(methylsulfonyl)amino]-N¹ -[(1R)-1-phenylpropyl]benzene-1,3-dicarboxamide} containing a hydroxyethylamine isostere was determined. Based on this structure, a computational docking study was performed which led to inhibitor 2 a-bound BACE2 models. These were used to optimize the potency and selectivity of inhibitors. A systematic structure-activity relationship study led to the identification of determinants of the inhibitors' potency and selectivity toward the BACE2 enzyme. Inhibitors 2 d [N³ -[(1S,2R)-1-benzyl-2-hydroxy-3-[[(1S,2S)-2-hydroxy-1-(isobutylcarbamoyl)pentyl]amino]propyl]-N¹ -methyl-N¹ -[(1R)-1-phenylpropyl]benzene-1,3-dicarboxamide; K_i =0.031 nm, selectivity over BACE1: ≈174 000-fold] and 3 l [N¹ -((2S,3R)-3-hydroxy-1-phenyl-4-((3-(trifluoromethyl)benzyl)amino)butan-2-yl)-N³ ,5-dimethyl-N³ -((R)-1-phenylethyl)isophthalamide; K_i =1.6 nm, selectivity over BACE1: >500-fold] displayed outstanding potency and selectivity. Inhibitor 3 l is nonpeptide in nature and may pave the way to the development of a new class of potent and selective BACE2 inhibitors with clinical potential.

Proteases: Pivot Points in Functional Proteomics

Proteases drive the life cycle of all proteins, ensuring the transportation and activation of newly minted, would-be proteins into their functional form while recycling spent or unneeded proteins. Far from their image as engines of protein digestion, proteases play fundamental roles in basic physiology and regulation at multiple levels of systems biology. Proteases are intimately associated with disease and modulation of proteolytic activity is the presumed target for successful therapeutics. "Proteases: Pivot Points in Functional Proteomics" examines the crucial roles of proteolysis across a wide range of physiological processes and diseases. The existing and potential impacts of proteolysis-related activity on drug and biomarker development are presented in detail. All told the decisive roles of proteases in four major categories comprising 23 separate subcategories are addressed. Within this construct, 15 sets of subject-specific, tabulated data are presented that include identification of proteases, protease inhibitors, substrates, and their actions. Said data are derived from and confirmed by over 300 references. Cross comparison of datasets indicates that proteases, their inhibitors/promoters and substrates intersect over a range of physiological processes and diseases, both chronic and pathogenic. Indeed, "Proteases: Pivot Points …" closes by dramatizing this very point through association of (pro)Thrombin and Fibrin(ogen) with: hemostasis, innate immunity, cardiovascular and metabolic disease, cancer, neurodegeneration, and bacterial self-defense.

Design, synthesis, and X-ray studies of potent HIV-1 protease inhibitors incorporating aminothiochromane and aminotetrahydronaphthalene carboxamide derivatives as the P2 ligands

We describe the design, synthesis, and biological evaluation of a series of novel HIV-1 protease inhibitors with carboxamide derivatives as the P2 ligands. We have specifically designed aminothiochromane and aminotetrahydronaphthalene-based carboxamide ligands to promote hydrogen bonding and van der Waals interactions in the active site of HIV-1 protease. Inhibitors 4e and 4j have shown potent enzyme inhibitory and antiviral activity. High resolution X-ray crystal structures of 4d- and 4k-bound HIV-1 protease revealed molecular insights into the ligand-binding site interactions.

Classification of HIV-1 Protease Inhibitors by Machine Learning Methods

HIV-1 protease plays an important role in the processing of virus infection. Protease is an effective therapeutic target for the treatment of HIV-1. Our data set is based on a selection of 4855 HIV-1 protease inhibitors (PIs) from ChEMBL. A series of 15 classification models for predicting the active inhibitors were built by machine learning methods, including k-nearest neighors (K-NN), decision tree (DT), random forest (RF), support vector machine (SVM), and deep neural network (DNN). The molecular structures were characterized by (1) fingerprint descriptors including MACCS fingerprints and PubChem fingerprints and (2) physicochemical descriptors calculated by CORINA Symphony. The prediction accuracies of all of the models are more than 70% on the test set; the best accuracy of 83.07% was obtained by model 4A, which was built by the SVM method based on MACCS fingerprint descriptors. Nine consensus models were built with three kinds of different descriptors, which combined all of the machine learning methods using the "consensus prediction". Model C3_a developed with MACCS fingerprint descriptors showed the highest accuracy on both training set (91.96%) and test set (83.15%). An external validation set including 35 989 compounds from DUD database and 239 active inhibitors from the recent literature was used to verify the performance of our model. The best prediction accuracy of 98.37% was obtained by model 3C, which was built by RF based on CORINA Symphony descriptors. In addition, from the analysis of molecular descriptors, it shows that the aromatic system and atoms related to hydrogen bonding provide important contributions to the bioactivity of PIs.

Diversity-Oriented Synthesis of Diol-Based Peptidomimetics as Potential HIV Protease Inhibitors and Antitumor Agents

Peptidomimetic HIV protease inhibitors are an important class of drugs used in the treatment of AIDS. The synthesis of a new type of diol-based peptidomimetics is described. Our route is flexible, uses d-glucal as an inexpensive starting material, and makes minimal use of protection/deprotection cycles. Binding affinities from molecular docking simulations suggest that these compounds are potential inhibitors of HIV protease. Moreover, the antiproliferative activities of compounds 33 a, 35 a, and 35 b on HT-29, M21, and MCF7 cancer cell lines are in the low micromolar range. The results provide a platform that could facilitate the development of medically relevant asymmetrical diol-based peptidomimetics.