Identification of Potential Inhibitors of Cathepsin-B using Shape & Pharmacophore-based Virtual Screening, Molecular Docking and Explicit Water Thermodynamics

Identification of TBK1 inhibitors against breast cancer using a computational approach supported by machine learning

Introduction: The cytosolic Ser/Thr kinase TBK1 is of utmost importance in facilitating signals that facilitate tumor migration and growth. TBK1-related signaling plays important role in tumor progression, and there is need to work on new methods and workflows to identify new molecules for potential treatments for TBK1-affecting oncologies such as breast cancer. Methods: Here, we propose the machine learning assisted computational drug discovery approach to identify TBK1 inhibitors. Through our computational ML-integrated approach, we identified four novel inhibitors that could be used as new hit molecules for TBK1 inhibition. Results and Discussion: All these four molecules displayed solvent based free energy values of -48.78, -47.56, -46.78 and -45.47 Kcal/mol and glide docking score of -10.4, -9.84, -10.03, -10.06 Kcal/mol respectively. The molecules displayed highly stable RMSD plots, hydrogen bond patterns and MMPBSA score close to or higher than BX795 molecule. In future, all these compounds can be further refined or validated by in vitro as well as in vivo activity. Also, we have found two novel groups that have the potential to be utilized in a fragment-based design strategy for the discovery and development of novel inhibitors targeting TBK1. Our method for identifying small molecule inhibitors can be used to make fundamental advances in drug design methods for the TBK1 protein which will further help to reduce breast cancer incidence.

Revealing the degrading-possibility of methyl red by two azoreductases of Anoxybacillus sp. PDR2 based on molecular docking

Azo dyes, as the most widely used synthetic dyes, are considered to be one of the culprits of water resources and environmental pollution. Anoxybacillus sp. PDR2 is a thermophilic bacterium with the ability to degrade azo dyes, whose genome contains two genes encoding azoreductases (named AzoPDR2-1 and AzoPDR2-2). In this study, through response surface methodology (RSM), when the initial pH, inoculation volume and Mg2+ addition amount were 7.18, 10.72% and 0.1 g/L respectively, the decolorization rate of methyl red (MR) (200 mg/L) could reach its maximum (98.8%). The metabolites after biodegradation were detected by UV-Vis spectroscopy, Fourier transform infrared spectroscopy (FTIR), and liquid chromatography mass spectrometry (LC-MS/MS), indicating that MR was successfully decomposed into 4-aminobenzoic acid and other small substrates. In homologous modeling, it was found that both azoreductases were flavin-dependent azoreductases, and belonged to the α/β structure, using the Rossmann fold. In their docking results with the cofactor flavin mononucleotide (FMN), FMN bound to the surface of the protein dimer. Nicotinamide adenine dinucleotide (NADH) was superimposed on the plane of the pyrazine ring between FMN and the activity pocket of protein. Besides, both azoreductase complexes (azoreductase-FMN-NADH) exhibited a substrate preference for MR. Asn104 and Tyr74 played an important role in the combination of the azoreductase AzoPDR2-1 complex and the azoreductase AzoPDR2-2 complex with MR, respectively. This provided assistance for studying the mechanism of azoreductase biodegradation of azo dyes in thermophilic bacteria.

The application of WaterMap-guided structure-based virtual screening in novel drug discovery

INTRODUCTION

Nowadays, it is widely accepted that water molecules play a key role in binding a ligand to a molecular target. Neglecting water molecules in the process of molecular recognition was the result of several failures of the structure-based drug discovery campaigns. The application of WaterMap, in particular WaterMap-guided molecular docking, enables the reasonably accurate and quick description of the location and energetics of water molecules at the ligand-protein interface.

AREAS COVERED

In this review, the authors shortly discuss the importance of water in drug design and discovery and provide a brief overview of the computational approaches used to predict the solvent-related effects for the purposes of presenting WaterMap in the context of other available techniques and tools. A concise description of WaterMap concept is followed by the presentation of WaterMap-assisted virtual screening literature published between 2013 and 2023.

EXPERT OPINION

In recent years, WaterMap software has been extensively used to support structure-based drug design, in particular structure-based virtual screening. Indeed, it is a useful tool to rescore docking results considering water molecules in the binding pocket. Although WaterMap allows for the consideration of the dynamic behavior of water molecules in the binding site, for best accuracy, its application in conjunction with other techniques such as molecular mechanics-generalized Born surface area of FEP (Free Energy Perturbation) is recommended.

Targeting NMDA receptor in Alzheimer's disease: identifying novel inhibitors using computational approaches

The glutamate-gated ion channels known as N-methyl-d-aspartate receptors (NMDARs) are important for both normal and pathological brain function. Subunit-selective antagonists have high therapeutic promise since many pathological conditions involve NMDAR over activation, although few clinical successes have been reported. Allosteric inhibitors of GluN2B-containing receptors are among the most potential NMDAR targeting drugs. Since the discovery of ifenprodil, a variety of GluN2B-selective compounds have been discovered, each with remarkably unique structural motifs. These results expand the allosteric and pharmacolog-ical spectrum of NMDARs and provide a new structural basis for the development of next-generation GluN2B antagonists that have therapeutic potential in brain diseases. Small molecule therapeutic inhibitors targeting NMDA have recently been developed to target CNS disorders such as Alzheimer's disease. In the current study, a cheminformatics method was used to discover potential antagonists and to identify the structural requirements for Gly/NMDA antagonism. In this case we have created a useful pharmacophore model with solid statistical values. Through pharmacophore mapping, the verified model was used to filter out virtual matches from the ZINC database. Assessing receptor-ligand binding mechanisms and affinities used molecular docking. To find the best hits, the GlideScore and the interaction of molecules with important amino acids were considered essential features. We found some molecular inhibitors, namely, ZINC13729211, ZINC07430424, ZINC08614951, ZINC60927204, ZINC12447511, and ZINC18889258 with high binding affinity using computational methods. The molecules in our studies showed characteristics such as good stability, hydrogen bonding and higher binding affinities in the solvation-based assessment method than ifenprodil with acceptable ADMET profile. Moreover, these six leads have been proposed as potential new perspectives for exploring potent Gly/NMDA receptor antagonists. In addition, it can be tested in the laboratory for potential therapeutic strategies for both in vitro and in vivo research.

Synthesis, In Silico and In Vitro Characterization of Novel N,N-Substituted Pyrazolopyrimidine Acetamide Derivatives for the 18KDa Translocator Protein (TSPO)

The translocator protein (TSPO) is an interesting biological target for molecular imaging and therapy because the overexpression of TSPO is associated with microglial activation caused by neuronal damage or neuroinflammation, and these activated microglia are involved in various central nervous system (CNS) diseases. The TSPO is a target for neuroprotective treatment, which is used with the aim of reducing microglial cell activation. The novel N,N-disubstituted pyrazolopyrimidine acetamides scaffold (GMA 7-17), which bears a fluorine atom and is directly linked to the phenyl moiety, was synthesized, and each of the novel ligands was characterized in vitro. All of the newly synthesized ligands displayed picomolar to nanomolar affinity for the TSPO. Particularly, an in vitro affinity study led to the discovery of 2-(5,7-diethyl-2-(4-fluorophenyl)pyrazolo [1,5-a]pyrimidin-3-yl)-N-ethyl-N-phenylacetamide GMA 15 (Ki = 60 pM), a novel TSPO ligand that exhibits a 61-fold enhancement in affinity compared to the reference standard DPA-714 (Ki = 3.66 nM). Molecular dynamic (MD) studies of the highest affinity binder, GMA 15, were carried out to check its time-dependent stability with the receptor compared to DPA-714 and PK11195. The hydrogen bond plot also indicated that GMA 15 formed higher hydrogen bonds compared to DPA-714 and PK11195. We anticipate that further optimization to enhance the potency in a cellular assay needs to be followed, but our strategy of identifying potential TSPO binding novel scaffolds may open up a new avenue to develop novel TSPO ligands suited for potential molecular imaging and a wide range of therapeutic applications.

Identifying novel and potent inhibitors of EGFR protein for the drug development against the breast cancer

The epidermal growth factor receptor (EGFR) has been shown to be extremely important in numerous signaling pathways, particularly those involved in cancer progression. Many therapeutic inhibitors, consisting of both small molecules and monoclonal antibodies, have been developed to target inflammatory, triple-negative and metastatic breast cancer. With the emergence of resistance in breast cancer treatment strategies, there is a need to develop novel drug targets that not only overcome resistance, but also exhibit low toxicity and high specificity. The work presented here focuses on the identification of new inhibitors against the EGFR protein using combined computational approaches. Using a comprehensive machine learning-based virtual screening approach complemented by other computational approaches, we identified six new molecules from the ZINC database. The gold docking score of these six novel molecules is 125.95, 125.38, 123.13, 119.71, 115.64 and 113.73, respectively, while the gold score of the control group is 120.74. In addition, we also analyzed the FEC value of these compounds and found that the values of compounds 1, 2, 3 and 4 (-61.82, -63.98, -67.98 and -63.32, respectively) were higher are than those of the control group (-61.05). Furthermore, these molecules showed highly stable RMSD plots and good interaction of hydrogen bonds. The identified inhibitors provided interesting insights for understanding the electronic, hydrophobic, steric and structural requirements for EGFR inhibitory activity. Distinguishing these novel molecules could lead to the development of new drugs useful in treating breast cancer.Communicated by Ramaswamy H. Sarma.

Ligand and structure-based approaches for the exploration of structure-activity relationships of fusidic acid derivatives as antibacterial agents

Introduction: Fusidic acid (FA) has been widely applied in the clinical prevention and treatment of bacterial infections. Nonetheless, its clinical application has been limited due to its narrow antimicrobial spectrum and some side effects. Purpose: Therefore, it is necessary to explore the structure-activity relationships of FA derivatives as antibacterial agents to develop novel ones possessing a broad antimicrobial spectrum. Methods and result: First, a pharmacophore model was established on the nineteen FA derivatives with remarkable antibacterial activities reported in previous studies. The common structural characteristics of the pharmacophore emerging from the FA derivatives were determined as those of six hydrophobic centers, two atom centers of the hydrogen bond acceptor, and a negative electron center around the C-21 field. Then, seven FA derivatives have been designed according to the reported structure-activity relationships and the pharmacophore characteristics. The designed FA derivatives were mapped on the pharmacophore model, and the Qfit values of all FA derivatives were over 50 and FA-8 possessed the highest value of 82.66. The molecular docking studies of the partial target compounds were conducted with the elongation factor G (EF-G) of S. aureus. Furthermore, the designed FA derivatives have been prepared and their antibacterial activities were evaluated by the inhibition zone test and the minimum inhibitory concentration (MIC) test. The derivative FA-7 with a chlorine group as the substituent group at C-25 of FA displayed the best antibacterial property with an MIC of 3.125 µM. Subsequently, 3D-QSAR was carried on all the derivatives by using the CoMSIA mode of SYBYL-X 2.0. Conclusion: Hence, a computer-aided drug design model was developed for FA, which can be further used to optimize FA derivatives as highly potent antibacterial agents.

Nobiletin as a Neuroprotectant against NMDA Receptors: An In Silico Approach

Excitotoxicity is a type of neurodegenerative disorder. It caused by excessive glutamate receptor activation, which leads to neuronal malfunction and fatality. The N-methyl-D-aspartate (NMDA) receptors are found in glutamatergic neurons, and their excessive activation is primarily responsible for excitotoxicity. They are activated by both glutamate binding and postsynaptic depolarization, facilitating Ca²⁺ entry upon activation. Therefore, they are now widely acknowledged as being essential targets for excitotoxicity issues. Molecular docking and molecular dynamics (MD) simulation analyses have demonstrated that nobiletin efficiently targets the binding pocket of the NMDA receptor protein and exhibits stable dynamic behavior at the binding site. In this study, five potential neuroprotectants, nobiletin, silibinin, ononin, ginkgolide B, and epigallocatechin gallate (EGCG), were screened against the glutamate NMDA receptors in humans via computational methods. An in silico ADMET study was also performed, to predict the pharmacokinetics and toxicity profile for the expression of good drug-like behavior and a non-toxic nature. It was revealed that nobiletin fulfills the criteria for all of the drug-likeness rules (Veber, Lipinski, Ghose, Muegge, and Egan) and has neither PAINS nor structural alerts (Brenks). In conclusion, nobiletin demonstrated a possible promising neuroprotectant activities compared to other selected phytochemicals. Further, it can be evaluated in the laboratory for promising therapeutic approaches for in vitro and in vivo studies.

Identification of Novel Cathepsin B Inhibitors with Implications in Alzheimer's Disease: Computational Refining and Biochemical Evaluation

Amyloid precursor protein (APP), upon proteolytic degradation, forms aggregates of amyloid β (Aβ) and plaques in the brain, which are pathological hallmarks of Alzheimer’s disease (AD). Cathepsin B is a cysteine protease enzyme that catalyzes the proteolytic degradation of APP in the brain. Thus, cathepsin B inhibition is a crucial therapeutic aspect for the discovery of new anti-Alzheimer’s drugs. In this study, we have employed mixed-feature ligand-based virtual screening (LBVS) by integrating pharmacophore mapping, docking, and molecular dynamics to detect small, potent molecules that act as cathepsin B inhibitors. The LBVS model was generated by using hydrophobic (HY), hydrogen bond acceptor (HBA), and hydrogen bond donor (HBD) features, using a dataset of 24 known cathepsin B inhibitors of both natural and synthetic origins. A validated eight-feature pharmacophore hypothesis (Hypo III) was utilized to screen the Maybridge chemical database. The docking score, MM-PBSA, and MM-GBSA methodology was applied to prioritize the lead compounds as virtual screening hits. These compounds share a common amide scaffold, and showed important interactions with Gln23, Cys29, His110, His111, Glu122, His199, and Trp221. The identified inhibitors were further evaluated for cathepsin-B-inhibitory activity. Our study suggests that pyridine, acetamide, and benzohydrazide compounds could be used as a starting point for the development of novel therapeutics.