Ab initio modeling of a potent isophthalamide-based BACE-1 inhibitor: amino acid decomposition analysis

MESPool: Molecular Edge Shrinkage Pooling for hierarchical molecular representation learning and property prediction

Identifying task-relevant structures is important for molecular property prediction. In a graph neural network (GNN), graph pooling can group nodes and hierarchically represent the molecular graph. However, previous pooling methods either drop out node information or lose the connection of the original graph; therefore, it is difficult to identify continuous subtructures. Importantly, they lacked interpretability on molecular graphs. To this end, we proposed a novel Molecular Edge Shrinkage Pooling (MESPool) method, which is based on edges (or chemical bonds). MESPool preserves crucial edges and shrinks others inside the functional groups and is able to search for key structures without breaking the original connection. We compared MESPool with various well-known pooling methods on different benchmarks and showed that MESPool outperforms the previous methods. Furthermore, we explained the rationality of MESPool on some datasets, including a COVID-19 drug dataset.

BACE1 inhibitors: Current status and future directions in treating Alzheimer's disease

Alzheimer's disease (AD) is an irreversible, progressive neurodegenerative brain disorder with no current cure. One of the important therapeutic approaches of AD is the inhibition of β-site APP cleaving enzyme-1 (BACE1), which is involved in the rate-limiting step of the cleavage process of the amyloid precursor protein (APP) leading to the generation of the neurotoxic amyloid β (Aβ) protein after the γ-secretase completes its function. The produced insoluble Aβ aggregates lead to plaques deposition and neurodegeneration. BACE1 is, therefore, one of the attractive targets for the treatment of AD. This approach led to the development of potent BACE1 inhibitors, many of which were advanced to late stages in clinical trials. Nonetheless, the high failure rate of lead drug candidates targeting BACE1 brought to the forefront the need for finding new targets to uncover the mystery behind AD. In this review, we aim to discuss the most promising classes of BACE1 inhibitors with a description and analysis of their pharmacodynamic and pharmacokinetic parameters, with more focus on the lead drug candidates that reached late stages of clinical trials, such as MK8931, AZD-3293, JNJ-54861911, E2609, and CNP520. In addition, the manuscript discusses the safety concerns and insignificant physiological effects, which were highlighted for the most successful BACE1 inhibitors. Furthermore, the review demonstrates with increasing evidence that despite tremendous efforts and promising results conceived with BACE1 inhibitors, the latest studies suggest that their clinical use for treating Alzheimer's disease should be reconsidered. Finally, the review sheds light on alternative therapeutic options for targeting AD.

Factors Influencing the Potency of Alzheimer Inhibitors: Computational and Docking Studies

Density functional theory (B3LYP/6-31G [d]) is performed to study the effect of molecular and electronic structures of the investigated β-secretase 1 (BACE1) Alzheimer's inhibitors on their biological activities and discuss the correlation between their inhibition efficiencies and quantum chemical descriptors. IC50 values of the investigated compounds are mostly affected by the substituted R2 phenyl moiety. The calculations show that the presence of electron withdrawing group increases the half maximal inhibitory concentration (IC50). Structure-activity relationship studies show that the electronic descriptors, energy of high occupied molecular orbital, ΔE, lipophilicity, hardness, and ionization potential index, are the most significant descriptors for the correlation with IC50. Molecular docking simulation is performed to explain the mode of interaction between the most potent drug and the binding sites of the BACE1 target. A good correlation between the experimental and the theoretical data confirms that the quantum chemical methods are successful tools for the discovery of novel BACE1 drugs.

Design, synthesis, biological assessment and molecular docking studies of new 2-aminoimidazole-quinoxaline hybrids as potential anticancer agents

In a search for novel antiproliferative agents, a series of quinoxaline derivatives containing 2-aminoimidazole (8a-8x) were designed and synthesized. The structures of synthesized compounds were confirmed by IR, ¹H NMR, ¹³C NMR, Mass Spectroscopy and analyzed using HSQC, COSY, ROESY, HMBC techniques. The anticancer activity of all derivatives were evaluated for colon cancer and breast cancer cell lines by the MTT assay and acridine orange/ethidium bromide double staining method. The anti-cancer effect in human colon cancer (HCT-116) and breast cancer (MCF-7) cell lines exhibited that compounds 8a, 8s, 8t, 8w, 8x appeared as potent antiproliferative agents and especially inhibited the human colon cancer cell proliferation with percentage of inhibition by over 50%. The most active compound was (E)-4-phenyl-1-((quinoxalin-2-ylmethylene)amino)-1H-imidazol-2-amine (8a) with the highest inhibition for MCF-7 (83.3%) and HCT-116 (70%) cell lines after 48 and 24h, respectively. Molecular docking studies of these derivatives within c-kit active site as a validated target might be suggested them as appropriate candidates for further efforts toward more potent anticancer compounds.

Investigation of naphthofuran moiety as potential dual inhibitor against BACE-1 and GSK-3β: molecular dynamics simulations, binding energy, and network analysis to identify first-in-class dual inhibitors against Alzheimer's disease

BACE-1 and GSK-3β are potential therapeutic drug targets for Alzheimer's disease. Recently, both the targets received attention for designing dual inhibitors for Alzheimer's disease. Until now, only two-scaffold triazinone and curcumin have been reported as BACE-1 and GSK-3β dual inhibitors. Docking, molecular dynamics, clustering, binding energy, and network analysis of triazinone derivatives with BACE-1 and GSK-3β was performed to get molecular insight into the first reported dual inhibitor. Further, we designed and evaluated a naphthofuran series for its ability to inhibit BACE-1 and GSK-3β with the computational approaches. Docking study of naphthofuran series showed a good binding affinity towards both the targets. Molecular dynamics, binding energy, and network analysis were performed to compare their binding with the targets and amino acids responsible for binding. Naphthofuran series derivatives showed good interaction within the active site residues of both of the targets. Hydrogen bond occupancy and binding energy suggested strong binding with the targets. Dual-inhibitor binding was mostly governed by the hydrophobic interactions for both of the targets. Per residue energy decomposition and network analysis identified the key residues involved in the binding and inhibiting BACE-1 and GSK-3β. The results indicated that naphthofuran series derivative 11 may be a promising first-in-class dual inhibitor against BACE-1 and GSK-3β. This naphthofuran series may be further explored to design better dual inhibitors. Graphical abstract Naphthofuran derivative as a dual inhibitor for BACE-1 and GSK-3β.

Hydroxycinnamic acid as a novel scaffold for the development of cyclooxygenase-2 inhibitors

The most active hydroxycinnamic acid derivative, caffeic acid diethyl ester (CA-DE), demonstrated 88.5/30.5% inhibition at 100/20 μM against COX-2 and negligible COX-1 inhibitory effect. CA-DE showed preferred interactions with COX-2 active site.

Comparative amino acid decomposition analysis of potent type I p38α inhibitors

Background and purpose of the study

p38α is a member of mitogen-activated protein kinases (MAPK) considered as a prominent target in development of anti-inflammatory agents. Any abnormality in the phosphorylation process leads to the different human diseases such as cancer, diabetes and inflammatory diseases. Several small molecule p38α inhibitors have been developed up to now. In this regard, structural elucidation of p38 inhibitors needs to be done enabling us in rational lead development strategies.

Methods

Various interactions of three potent inhibitors with p38α active site have been evaluated in terms of binding energies and bond lengths via density function theory and MD simulations.

Results

Our comparative study showed that both ab initio and MD simulation led to the relatively similar results in pharmacophore discrimination of p38α inhibitors.

Conclusion

The results of the present study may find their usefulness in pharmacophore based modification of p38α inhibitors.