Machine learning-guided design of potent darunavir analogs targeting HIV-1 proteases: A computational approach for antiretroviral drug discovery.

In the pursuit of novel antiretroviral therapies for human immunodeficiency virus type-1 (HIV-1) proteases (PRs), recent improvements in drug discovery have embraced machine learning (ML) techniques to guide the design process. This study employs ensemble learning models to identify crucial substructures as significant features for drug development. Using molecular docking techniques, a collection of 160 darunavir (DRV) analogs was designed based on these key substructures and subsequently screened using molecular docking techniques. Chemical structures with high fitness scores were selected, combined, and one-dimensional (1D) screening based on beyond Lipinski's rule of five (bRo5) and ADME (absorption, distribution, metabolism, and excretion) prediction implemented in the Combined Analog generator Tool (CAT) program. A total of 473 screened analogs were subjected to docking analysis through convolutional neural networks scoring function against both the wild-type (WT) and 12 major mutated PRs. DRV analogs with negative changes in binding free energy ( ΔΔ G bind ) compared to DRV could be categorized into four attractive groups based on their interactions with the majority of vital PRs. The analysis of interaction profiles revealed that potent designed analogs, targeting both WT and mutant PRs, exhibited interactions with common key amino acid residues. This observation further confirms that the ML model-guided approach effectively identified the substructures that play a crucial role in potent analogs. It is expected to function as a powerful computational tool, offering valuable guidance in the identification of chemical substructures for synthesis and subsequent experimental testing.

Machine learning-based QSAR and LB-PaCS-MD guided design of SARS-CoV-2 main protease inhibitors.

The global outbreak of the COVID-19 pandemic caused by the SARS-CoV-2 virus had led to profound respiratory health implications. This study focused on designing organoselenium-based inhibitors targeting the SARS-CoV-2 main protease (Mpro). The ligand-binding pathway sampling method based on parallel cascade selection molecular dynamics (LB-PaCS-MD) simulations was employed to elucidate plausible paths and conformations of ebselen, a synthetic organoselenium drug, within the Mpro catalytic site. Ebselen effectively engaged the active site, adopting proximity to H41 and interacting through the benzoisoselenazole ring in a π-π T-shaped arrangement, with an additional π-sulfur interaction with C145. In addition, the ligand-based drug design using the QSAR with GFA-MLR, RF, and ANN models were employed for biological activity prediction. The QSAR-ANN model showed robust statistical performance, with an r2training exceeding 0.98 and an RMSEtest of 0.21, indicating its suitability for predicting biological activities. Integration the ANN model with the LB-PaCS-MD insights enabled the rational design of novel compounds anchored in the ebselen core structure, identifying promising candidates with favorable predicted IC50 values. The designed compounds exhibited suitable drug-like characteristics and adopted an active conformation similar to ebselen, inhibiting Mpro function. These findings represent a synergistic approach merging ligand and structure-based drug design; with the potential to guide experimental synthesis and enzyme assay testing.

Synthesis and biological evaluation of 2'-hydroxychalcone derivatives as AMPK activators.

A series of 2'-hydroxychalcone derivatives with various substituents on B-ring were synthesized and evaluated for AMP-activated protein kinase (AMPK) activation activity in podocyte cells. The results displayed that hydroxy, methoxy and methylenedioxy groups on B-ring could enhance the activitiy better than O-saturated alkyl, O-unsaturated alkyl or other alkoxy groups. Compounds 27 and 29 possess the highest fold change of 2.48 and 2.73, respectively, which were higher than those of reference compound (8) (1.28) and metformin (1.88). Compounds 27 and 29 were then subjected to a concentration-response study to obtain the EC50 values of 2.0 and 4.8 µM, respectively and MTT assays also showed that cell viability was not influenced by the exposure of podocytes to compounds 27 and 29 at concentrations up to 50 µM. In addition, compound 27 was proved to activate AMPK via calcium/calmodulin-dependent protein kinase kinase ß (CaMKKß)-dependent pathway without affecting intracellular calcium levels. The computational study showed that the potent compounds exhibited stronger ligand-binding strength to CaMKKß, particularly compounds 27 (-8.4 kcal/mol) and 29 (-8.0 kcal/mol), compared to compound 8 (-7.5 kcal/mol). Fragment molecular orbital (FMO) calculation demonstrated that compound 27 was superior to compound 29 due to the presence of methyl group, which amplified the binding by hydrophobic interactions. Therefore, compound 27 would represent a promising AMPK activator for further investigation of the treatment of diabetes and diabetic nephropathy.

Preferential Door for Ligand Binding and Unbinding Pathways in Inhibited Human Acetylcholinesterase.

Rising global population and increased food demands have resulted in the increased use of organophosphate pesticides (OPs), leading to toxin accumulation and transmission to humans. Pralidoxime (2-PAM), an FDA-approved drug, serves as an antidote for OP therapy. However, the atomic-level detoxification mechanisms regarding the design of novel antidotes remain unclear. This is the first study to examine the binding and unbinding pathways of 2-PAM to human acetylcholinesterase (HuAChE) through three identified doors using an enhanced sampling method called ligand-binding parallel cascade selection molecular dynamics (LB-PaCS-MD). Remarkably, LB-PaCS-MD could identify a predominant in-line binding mechanism through the acyl door at 63.79% ± 6.83%, also implicating it in a potential unbinding route (90.14% ± 4.22%). Interestingly, crucial conformational shifts in key residues, W86, Y341, and Y449, and the Ω loop significantly affect door dynamics and ligand binding modes. The LB-PaCS-MD technique can study ligand-binding pathways, thereby contributing to the design of antidotes and covalent drugs.

FMO-guided design of darunavir analogs as HIV-1 protease inhibitors.

The prevalence of HIV-1 infection continues to pose a significant global public health issue, highlighting the need for antiretroviral drugs that target viral proteins to reduce viral replication. One such target is HIV-1 protease (PR), responsible for cleaving viral polyproteins, leading to the maturation of viral proteins. While darunavir (DRV) is a potent HIV-1 PR inhibitor, drug resistance can arise due to mutations in HIV-1 PR. To address this issue, we developed a novel approach using the fragment molecular orbital (FMO) method and structure-based drug design to create DRV analogs. Using combinatorial programming, we generated novel analogs freely accessible via an on-the-cloud mode implemented in Google Colab, Combined Analog generator Tool (CAT). The designed analogs underwent cascade screening through molecular docking with HIV-1 PR wild-type and major mutations at the active site. Molecular dynamics (MD) simulations confirmed the assess ligand binding and susceptibility of screened designed analogs. Our findings indicate that the three designed analogs guided by FMO, 19-0-14-3, 19-8-10-0, and 19-8-14-3, are superior to DRV and have the potential to serve as efficient PR inhibitors. These findings demonstrate the effectiveness of our approach and its potential to be used in further studies for developing new antiretroviral drugs.

Alpha and gamma mangostins inhibit wild-type B SARS-CoV-2 more effectively than the SARS-CoV-2 variants and the major target is unlikely the 3C-like protease.

Background: Anti-SARS-CoV-2 and immunomodulatory drugs are important for treating clinically severe patients with respiratory distress symptoms. Alpha- and gamma-mangostins (AM and GM) were previously reported as potential 3C-like protease (3CLpro) and Angiotensin-converting enzyme receptor 2 (ACE2)-binding inhibitors in silico. Objective: We aimed to evaluate two active compounds, AM and GM, from Garcinia mangostana for their antivirals against SARS-CoV-2 in live virus culture systems and their cytotoxicities using standard methods. Also, we aimed to prove whether 3CLpro and ACE2 neutralization were major targets and explored whether any additional targets existed. Methods: We tested the translation and replication efficiencies of SARS-CoV-2 in the presence of AM and GM. Initial and subgenomic translations were evaluated by immunofluorescence of SARS-CoV-2 3CLpro and N expressions at 16 h after infection. The viral genome was quantified and compared with the untreated group. We also evaluated the efficacies and cytotoxicities of AM and GM against four strains of SARS-CoV-2 (wild-type B, B.1.167.2, B.1.36.16, and B.1.1.529) in Vero E6 cells. The potential targets were evaluated using cell-based anti-attachment, time-of-drug addition, in vitro 3CLpro activities, and ACE2-binding using a surrogated viral neutralization test (sVNT). Moreover, additional targets were explored using combinatorial network-based interactions and Chemical Similarity Ensemble Approach (SEA). Results: AM and GM reduced SARS-CoV-2 3CLpro and N expressions, suggesting that initial and subgenomic translations were globally inhibited. AM and GM inhibited all strains of SARS-CoV-2 at EC50 of 0.70-3.05 µM, in which wild-type B was the most susceptible strain (EC50 0.70-0.79 µM). AM was slightly more efficient in the variants (EC50 0.88-2.41 µM), resulting in higher selectivity indices (SI 3.65-10.05), compared to the GM (EC50 0.94-3.05 µM, SI 1.66-5.40). GM appeared to be more toxic than AM in both Vero E6 and Calu-3 cells. Cell-based anti-attachment and time-of-addition suggested that the potential molecular target could be at the post-infection. 3CLpro activity and ACE2 binding were interfered with in a dose-dependent manner but were insufficient to be a major target. Combinatorial network-based interaction and chemical similarity ensemble approach (SEA) suggested that fatty acid synthase (FASN), which was critical for SARS-CoV-2 replication, could be a target of AM and GM. Conclusion: AM and GM inhibited SARS-CoV-2 with the highest potency at the wild-type B and the lowest at the B.1.1.529. Multiple targets were expected to integratively inhibit viral replication in cell-based system.

Evaluating solubility, stability, and inclusion complexation of oxyresveratrol with various ß-cyclodextrin derivatives using advanced computational techniques and experimental validation.

Oxyresveratrol (OXY), a natural stilbenoid in mulberry fruits, is known for its diverse pharmacological properties. However, its clinical use is hindered by low water solubility and limited bioavailability. In the present study, the inclusion complexes of OXY with ß-cyclodextrin (ßCD) and its three analogs, dimethyl-ß-cyclodextrin (DMßCD), hydroxypropyl-ß-cyclodextrin (HPßCD) and sulfobutylether-ß-cyclodextrin (SBEßCD), were investigated using in silico and in vitro studies. Molecular docking revealed two binding orientations of OXY, namely, 4',6'-dihydroxyphenyl (A-form) and 5,7-benzenediol ring (B-form). Molecular Dynamics simulations suggested the formation of inclusion complexes with ßCDs through two distinct orientations, with OXY/SBEßCD exhibiting maximum atom contacts and the lowest solvent-exposed area in the hydrophobic cavity. These results corresponded well with the highest binding affinity observed in OXY/SBEßCD when assessed using the MM/GBSA method. Beyond traditional simulation methods, Ligand-binding Parallel Cascade Selection Molecular Dynamics method was employed to investigate how the drug enters and accommodates within the hydrophobic cavity. The in silico results aligned with stability constants: SBEßCD (2060 M-1), HPßCD (1860 M-1), DMßCD (1700 M-1), and ßCD (1420 M-1). All complexes exhibited a 1:1 binding mode (AL type), with SBEßCD enhancing OXY solubility (25-fold). SEM micrographs, DSC thermograms, FT-IR and 1H NMR spectra confirm the inclusion complex formation, revealing novel surface morphologies, distinctive thermal behaviors, and new peaks. Notably, the inhibitory impact on the proliferation of breast cancer cell lines, MCF-7, exhibited by inclusion complexes particularly OXY/DMßCD, OXY/HPßCD, and OXY/SBEßCD were markedly superior compared to that of OXY alone.