In silico screening and computational evaluation of novel promising USP14 inhibitors targeting the palm-thumb pocket

Protein degradation and synthesis are essential for regulating various biological activities within the body. As a member of deubiquitinating enzymes (DUBs), ubiquitin-specific protease 14 (USP14) plays a critical role in regulating protein degradation and maintaining cellular protein homeostasis. However, abnormal expression of USP14 has been associated with a variety of malignant tumors and other diseases. In this study, we conducted hierarchical virtual screening against the palm-thumb pocket of USP14, which resulted in the identification of two promising hits with novel scaffolds. We systematically evaluated the potential of these two hits in terms of their binding affinity and selectivity at the computational level. The results indicated that they had stronger binding affinities than previously reported molecules, as evidenced by lower docking scores and binding free energies. The binding stability analysis and hotspot residue prediction based on the MD simulations further revealed that they were capable of stably binding to the palm-thumb pocket of USP14 via crucial interactions with the residues GLN197, TYR476, ASP199, PHE331, TYR436 and HIS426. More importantly, both candidates exhibit higher selectivity for USP14 over several other USP family members (USP5, USP7 and USP15). Our findings are hoped to be a good starting point for the development of selective USP14 inhibitors.

QSAR study of tetrahydropteridin derivatives as polo-like kinase 1(PLK1) Inhibitors with molecular docking and dynamics study

PLK1 is the key target for dealing with different cancer because it plays an important role in cell proliferation. According to the regulation of OECD, a QSAR model was developed from a dataset of 68 tetrahydropteridin derivatives. Three descriptors (maxHaaCH, ATSC7i, AATS7m) were considered for the development of the QSAR model. The reliability and predictability of the developed QSAR model were evaluated by various statistical parameters (r² = 0.8213, r²_ext = 0.8771 and CCC_ext = 0.9364). The maxHaaCH descriptor is positively correlated to pIC₅₀ whereas, the ATSC7i and AATS7m are negatively correlated with pIC₅₀. The QSAR model explains all the structural features and shows a good correlation with the activity. Based on molecular modelling techniques, five compounds (D1-D5) were designed. Molecular docking and dynamics studies of the most active compound were performed with PDB ID: 2RKU. The results of the present investigation may be employed to identify and develop effective inhibitors for the treatment of PLK1-related pathophysiological disorders.

Theoretically exploring selective-binding mechanisms of BRD4 through integrative computational approaches

The origin of cancer is related to the dysregulation of multiple signal pathways and of physiological processes. Bromodomain-containing protein 4 (BRD4) has become an attractive target for the development of anticancer and anti-inflammatory agents since it can epigenetically regulate the transcription of growth-promoting genes. The synthesized BRD4 inhibitors with new chemical structures can reduce the drug resistance, but their binding modes and the inhibitory mechanism remain unclear. Here, we initially constructed robust QSAR models based on 68 reported tetrahydropteridin analogues using topomer CoMFA and HQSAR. On the basis of QSAR results, we designed 16 novel tetrahydropteridin analogues with modified structures and carried out docking studies. Instead of significant hydrogen bondings with amino acid residue Asn140 as reported in previous research, the molecular docking modelling suggested a novel docking pose that involves the amino acid residues (Trp81, Pro82, Val87, Leu92, Leu94, Cys136, Asp144, and Ile146) at the active site of BRD4. The MD simulations, free energy calculations, and residual energy contributions all indicate that hydrophobic interactions are decisive factors affecting bindings between inhibitors and BRD4. The current study provides new insights that can aid the discovery of BRD4 inhibitors with enhanced anti-cancer ability.

A computational approach for designing novel SARS-CoV-2 Mpro inhibitors: combined QSAR, molecular docking, and molecular dynamics simulation techniques

The promising compound T₂₁ for treating COVID-19 at the active site of SARS-CoV-2 M^pro.