A Causal Regulation Modeling Algorithm for Temporal Events with Application to Escherichia coli's Aerobic to Anaerobic Transition.

Time-series experiments are crucial for understanding the transient and dynamic nature of biological phenomena. These experiments, leveraging advanced classification and clustering algorithms, allow for a deep dive into the cellular processes. However, while these approaches effectively identify patterns and trends within data, they often need to improve in elucidating the causal mechanisms behind these changes. Building on this foundation, our study introduces a novel algorithm for temporal causal signaling modeling, integrating established knowledge networks with sequential gene expression data to elucidate signal transduction pathways over time. Focusing on Escherichia coli's (E. coli) aerobic to anaerobic transition (AAT), this research marks a significant leap in understanding the organism's metabolic shifts. By applying our algorithm to a comprehensive E. coli regulatory network and a time-series microarray dataset, we constructed the cross-time point core signaling and regulatory processes of E. coli's AAT. Through gene expression analysis, we validated the primary regulatory interactions governing this process. We identified a novel regulatory scheme wherein environmentally responsive genes, soxR and oxyR, activate fur, modulating the nitrogen metabolism regulators fnr and nac. This regulatory cascade controls the stress regulators ompR and lrhA, ultimately affecting the cell motility gene flhD, unveiling a novel regulatory axis that elucidates the complex regulatory dynamics during the AAT process. Our approach, merging empirical data with prior knowledge, represents a significant advance in modeling cellular signaling processes, offering a deeper understanding of microbial physiology and its applications in biotechnology.

In silico identification of a novel Cdc2-like kinase 2 (CLK2) inhibitor in triple negative breast cancer.

Dysregulation of RNA splicing processes is intricately linked to tumorigenesis in various cancers, especially breast cancer. Cdc2-like kinase 2 (CLK2), an oncogenic RNA-splicing kinase pivotal in breast cancer, plays a significant role, particularly in the context of triple-negative breast cancer (TNBC), a subtype marked by substantial medical challenges due to its low survival rates. In this study, we employed a structure-based virtual screening (SBVS) method to identify potential CLK2 inhibitors with novel chemical structures for treating TNBC. Compound 670551 emerged as a novel CLK2 inhibitor with a 50% inhibitory concentration (IC50) value of 619.7 nM. Importantly, Compound 670551 exhibited high selectivity for CLK2 over other protein kinases. Functionally, this compound significantly reduced the survival and proliferation of TNBC cells. Results from a cell-based assay demonstrated that this inhibitor led to a decrease in RNA splicing proteins, such as SRSF4 and SRSF6, resulting in cell apoptosis. In summary, we identified a novel CLK2 inhibitor as a promising potential treatment for TNBC therapy.

An ensemble machine learning model generates a focused screening library for the identification of CDK8 inhibitors.

The identification of an effective inhibitor is an important starting step in drug development. Unfortunately, many issues such as the characterization of protein binding sites, the screening library, materials for assays, etc., make drug screening a difficult proposition. As the size of screening libraries increases, more resources will be inefficiently consumed. Thus, new strategies are needed to preprocess and focus a screening library towards a targeted protein. Herein, we report an ensemble machine learning (ML) model to generate a CDK8-focused screening library. The ensemble model consists of six different algorithms optimized for CDK8 inhibitor classification. The models were trained using a CDK8-specific fragment library along with molecules containing CDK8 activity. The optimized ensemble model processed a commercial library containing 1.6 million molecules. This resulted in a CDK8-focused screening library containing 1,672 molecules, a reduction of more than 99.90%. The CDK8-focused library was then subjected to molecular docking, and 25 candidate compounds were selected. Enzymatic assays confirmed six CDK8 inhibitors, with one compound producing an IC50 value of ≤100 nM. Analysis of the ensemble ML model reveals the role of the CDK8 fragment library during training. Structural analysis of molecules reveals the hit compounds to be structurally novel CDK8 inhibitors. Together, the results highlight a pipeline for curating a focused library for a specific protein target, such as CDK8.

Identification of selective dual-specificity tyrosine phosphorylation-regulated kinase 1A (DYRK1A) inhibitors and their effects on tau and microtubule.

The overexpression of dual-specificity tyrosine phosphorylation-regulated kinase 1A (DYRK1A), commonly observed in neurodegenerative diseases like Alzheimer's disease (AD) and Down syndrome (DS), can induce the formation of neurofibrillary tangles (NFTs) and amyloid plaques. Hence, designing a selective DYRK1A inhibitor would result in a promising small molecule for treating neurodegenerative diseases. Developing selective inhibitors for DYRK1A has been a difficult challenge due to the highly preserved ATP-binding site of protein kinases. In this study, we employed a structure-based virtual screening (SBVS) campaign targeting DYRK1A from a database containing 1.6 million compounds. Enzymatic assays were utilized to verify inhibitory properties, confirming that Y020-3945 and Y020-3957 showed inhibitory activity towards DYRK1A. In particular, the compounds exhibited high selectivity for DYRK1A over a panel of 120 kinases, reduced the phosphorylation of tau, and reversed the tubulin polymerization for microtubule stability. Additionally, treatment with the compounds significantly reduced the secretion of inflammatory cytokines IL-6 and TNF-α activated by DYRK1A-assisted NFTs and Aß oligomers. These identified inhibitors possess promising therapeutic potential for conditions associated with DYRK1A in neurodegenerative diseases. The results showed that Y020-3945 and Y020-3957 demonstrated structural novelty compared to known DYRK1A inhibitors, making them a valuable addition to developing potential treatments for neurodegenerative diseases.

In silico identification and biological evaluation of a selective MAP4K4 inhibitor against pancreatic cancer.

Inhibiting a specific target in cancer cells and reducing unwanted side effects has become a promising strategy in pancreatic cancer treatment. MAP4K4 is associated with pancreatic cancer development and correlates with poor clinical outcomes. By phosphorylating MKK4, proteins associated with cell apoptosis and survival are translated. Therefore, inhibiting MAP4K4 activity in pancreatic tumours is a new therapeutic strategy. Herein, we performed a structure-based virtual screening to identify MAP4K4 inhibitors and discovered the compound F389-0746 with a potent inhibition (IC50 120.7 nM). The results of kinase profiling revealed that F389-0746 was highly selective to MAP4K4 and less likely to cause side effects. Results of in vitro experiments showed that F389-0746 significantly suppressed cancer cell growth and viability. Results of in vivo experiments showed that F389-0746 displayed comparable tumour growth inhibition with the group treated with gemcitabine. These findings suggest that F389-0746 has promising potential to be further developed as a novel pancreatic cancer treatment.

Design, synthesis, and biological evaluation of indolin-2-one derivatives as novel cyclin-dependent protein kinase 8 (CDK8) inhibitors.

Cyclin-dependent protein kinase 8 (CDK8) plays important roles in regulating fibrotic growth factors and inflammatory signaling pathways. Long-term chronic inflammation of the lungs can lead to idiopathic pulmonary fibrosis (IPF). Abnormal alveolar epithelial regeneration leads to the release of various fibrotic growth factors and the activation of inflammatory cells. CDK8 regulates profibrotic cytokines broadly implicated in the pathogenesis of fibrosis. Therefore, inhibition of CDK8 is considered a promising strategy for treating IPF. Here, CDK8 inhibitors were designed and optimized using a fragment-based drug design strategy. Testing results revealed that 71% of the synthesized compounds inhibited CDK8 activity better than the original compound E966-0530. Of these compounds, compound 4k exhibited the strongest CDK8 enzyme-inhibiting activity (IC50 =129 nM). Notably, it displayed a 13-fold increase in potency when compared to E966-0530. Experiments on toxicity and inhibition of epithelial-mesenchymal transition (EMT) protein expressions showed that compound 4k can inhibit EMT protein expressions, but with no significant cytotoxicity for alveolar epithelial cells. Compound 4k showed a potent inhibitory effect in cell migration assays. Furthermore, compound 4k significantly inhibited the phosphorylation of p-Smad3 and RNA Pol II, which are critical mediators in the fibrotic response signaling pathway. Compound 4k remarkably reduced TGF-ß1-induced oxidative stress. The above results reveal optimized CDK8 inhibitors with potential use for IPF therapeutic treatment.

O-methylated flavonol as a multi-kinase inhibitor of leukemogenic kinases exhibits a potential treatment for acute myeloid leukemia.

BACKGROUND: Acute myeloid leukemia (AML) is a heterogeneous disease with poor overall survival characterized by various genetic changes. The continuous activation of oncogenic pathways leads to the development of drug resistance and limits current therapeutic efficacy. Therefore, a multi-targeting inhibitor may overcome drug resistance observed in AML treatment. Recently, groups of flavonoids, such as flavones and flavonols, have been shown to inhibit a variety of kinase activities, which provides potential opportunities for further anticancer applications. PURPOSE: In this study, we evaluated the anticancer effects of flavonoid compounds collected from our in-house library and investigated their potential anticancer mechanisms by targeting multiple kinases for inhibition in AML cells. METHODS: The cytotoxic effect of the compounds was detected by cell viability assays. The kinase inhibitory activity of the selected compound was detected by kinase-based and cell-based assays. The binding conformation and interactions were investigated by molecular docking analysis. Flow cytometry was used to evaluate the cell cycle distribution and cell apoptosis. The protein and gene expression were estimated by western blotting and qPCR, respectively. RESULTS: In this study, an O-methylated flavonol (compound 11) was found to possess remarkable cytotoxic activity against AML cells compared to treatment in other cancer cell lines. The compound was demonstrated to act against multiple kinases, which play critical roles in survival signaling in AML, including FLT3, MNK2, RSK, DYRK2 and JAK2 with IC50 values of 1 - 2 µM. Compared to our previous flavonoid compounds, which only showed inhibitions against MNKs or FLT3, compound 11 exhibited multiple kinase inhibitory abilities. Moreover, compound 11 showed effectiveness in inhibiting internal tandem duplications of FLT3 (FLT3-ITDs), which accounts for 25% of AML cases. The interactions between compound 11 and targeted kinases were investigated by molecular docking analysis. Mechanically, compound 11 caused dose-dependent accumulation of leukemic cells at the G0/G1 phase and followed by the cells undergoing apoptosis. CONCLUSION: O-methylated flavonol, compound 11, can target multiple kinases, which may provide potential opportunities for the development of novel therapeutics for drug-resistant AMLs. This work provides a good starting point for further compound optimization.

Identification of a dual FLT3 and MNK2 inhibitor for acute myeloid leukemia treatment using a structure-based virtual screening approach.

Fms-like tyrosine kinase 3 (FLT3) is considered a promising therapeutic target for acute myeloid leukemia (AML) in the clinical. However, monotherapy with FLT3 inhibitor is usually accompanied by drug resistance. Dual inhibitors might be therapeutically beneficial to patients with AML due to their ability to overcome drug resistance. Mitogen-activated protein kinase (MAPK)-interacting kinases (MNKs) phosphorylate eukaryotic translation initiation factor 4E (eIF4E), which brings together the RAS/RAF/ERK and PI3K/AKT/mTOR oncogenic pathways. Therefore, dual inhibition of FLT3 and MNK2 might have an additive effect against AML. Herein, a structure-based virtual screening approach was performed to identify dual inhibitors of FLT3 and MNK2 from the ChemDiv database. Compound K783-0308 was identified as a dual inhibitor of FLT3 and MNK2 with IC50 values of 680 and 406 nM, respectively. In addition, the compound showed selectivity for both FLT3 and MNK2 in a panel of 82 kinases. The structure-activity relationship analysis and common interactions revealed interactions between K783-0308 analogs and FLT3 and MNK2. Furthermore, K783-0308 inhibited MV-4-11 and MOLM-13 AML cell growth and induced G0/G1 cell cycle arrest. Taken together, the dual inhibitor K783-0308 showed promising results and can be potentially optimized as a lead compound for AML treatment.

A novel dual HDAC and HSP90 inhibitor, MPT0G449, downregulates oncogenic pathways in human acute leukemia in vitro and in vivo.

Acute leukemia is a highly heterogeneous disease; therefore, combination therapy is commonly used for patient treatment. Drug-drug interaction is a major concern of combined therapy; hence, dual/multi-target inhibitors have become a dominant approach for cancer drug development. HDACs and HSP90 are involved in the activation of various oncogenic signaling pathways, including PI3K/AKT/mTOR, JAK/STAT, and RAF/MEK/ERK, which are also highly enriched in acute leukemia gene expression profiles. Therefore, we suggest that dual HDAC and HSP90 inhibitors could represent a novel therapeutic approach for acute leukemia. MPT0G449 is a dual effect inhibitor, and it showed cytotoxic effectiveness in acute leukemia cells. Molecular docking analysis indicated that MPT0G449 possessed dual HDAC and HSP90 inhibitory abilities. Furthermore, MPT0G449 induced G2 arrest and caspase-mediated cell apoptosis in acute leukemia cells. The oncogenic signaling molecules AKT, mTOR, STAT3, STAT5, MEK, and ERK were significantly downregulated after MPT0G449 treatment in HL-60 and MOLT-4 cells. In vivo xenograft models confirmed the antitumor activity and showed the upregulation of acetyl-histone H3 and HSP70, biomarkers of pan-HDAC and HSP90 inhibition, with MPT0G449 treatment. These findings suggest that the dual inhibition of HDAC and HSP90 can suppress the expression of oncogenic pathways in acute leukemia, and MPT0G449 represents a novel therapeutic for anticancer treatment.

Investigation of Selected Flavonoid Derivatives as Potent FLT3 Inhibitors for the Potential Treatment of Acute Myeloid Leukemia.

Acute myeloid leukemia (AML) is an aggressive disease with a poor prognosis and a high degree of relapse seen in patients. Overexpression of FMS-like tyrosine kinase 3 (FLT3) is associated with up to 70% of AML patients. Wild-type FLT3 induces proliferation and inhibits apoptosis in AML cells, while uncontrolled proliferation of FLT3 kinase activity is also associated with FLT3 mutations. Therefore, inhibiting FLT3 activity is a promising AML therapy. Flavonoids are a group of phytochemicals that can target protein kinases, suggesting their potential antitumor activities. In this study, several plant-derived flavonoids have been identified with FLT3 inhibitory activity. Among these compounds, compound 40 (5,7,4'-trihydroxy-6-methoxyflavone) exhibited the most potent inhibition against not only FLT3 (IC50 = 0.44 µM) but also FLT3-D835Y and FLT3-ITD mutants (IC50 = 0.23 and 0.39 µM, respectively). The critical interactions between the FLT3 binding site and the compounds were identified by performing a structure-activity relationship analysis. Furthermore, the results of cellular assays revealed that compounds 28, 31, 32, and 40 exhibited significant cytotoxicity against two human AML cell lines (MOLM-13 and MV-4-11), and compounds 31, 32, and 40 resulted in cell apoptosis and G0/G1 cell cycle arrest. Collectively, these flavonoids have the potential to be further optimized as FLT3 inhibitors and provide valuable chemical information for the development of new AML drugs.

Identification of a dual TAOK1 and MAP4K5 inhibitor using a structure-based virtual screening approach.

The STE20 kinase family is a complex signalling cascade that regulates cytoskeletal organisation and modulates the stress response. This signalling cascade includes various kinase mediators, such as TAOK1 and MAP4K5. The dysregulation of the STE20 kinase pathway is linked with cancer malignancy. A small-molecule inhibitor targeting the STE20 kinase pathway has therapeutic potential. In this study, a structure-based virtual screening (SBVS) approach was used to identify potential dual TAOK1 and MAP4K5 inhibitors. Enzymatic assays confirmed three potential dual inhibitors (>50% inhibition) from our virtual screening, and analysis of the TAOK1 and MAP4K5 binding sites indicated common interactions for dual inhibition. Compound 1 revealed potent inhibition of colorectal and lung cancer cell lines. Furthermore, compound 1 arrested cancer cells in the G0/G1 phase, which suggests the induction of apoptosis. Altogether, we show that the STE20 signalling mediators TAOK1 and MAP4K5 are promising targets for drug research.

Biological Evaluation of Selected Flavonoids as Inhibitors of MNKs Targeting Acute Myeloid Leukemia.

Excessive eIF4E phosphorylation by mitogen-activated protein kinase (MAPK)-interacting kinases 1 and 2 (MNK1 and MNK2; collectively, MNKs) has been associated with oncogenesis. The overexpression of eIF4E in acute myeloid leukemia (AML) is related to cancer cell growth and survival. Thus, the inhibition of MNKs and eIF4E phosphorylation are potential therapeutic strategies for AML. Herein, a structure-based virtual screening approach was performed to identify potential MNK inhibitors from natural products. Three flavonoids, apigenin, hispidulin, and luteolin, showed MNK2 inhibitory activity with IC50 values of 308, 252, and 579 nM, respectively. A structure-activity relationship analysis was performed to disclose the molecular interactions. Furthermore, luteolin exhibited substantial inhibitory efficacy against MNK1 (IC50 = 179 nM). Experimental results from cellular assays showed that hispidulin and luteolin inhibited the growth of MOLM-13 and MV4-11 AML cells by downregulating eIF4E phosphorylation and arresting the cell cycle at the G0/G1 phase. Therefore, hispidulin and luteolin showed promising results as lead compounds for the potential treatment for AML.

Relationships between residue Voronoi volume and sequence conservation in proteins.

BACKGROUND: Functional and biophysical constraints can cause different levels of sequence conservation in proteins. Previously, structural properties, e.g., relative solvent accessibility (RSA) and packing density of the weighted contact number (WCN), have been found to be related to protein sequence conservation (CS). The Voronoi volume has recently been recognized as a new structural property of the local protein structural environment reflecting CS. However, for surface residues, it is sensitive to water molecules surrounding the protein structure. Herein, we present a simple structural determinant termed the relative space of Voronoi volume (RSV); it uses the Voronoi volume and the van der Waals volume of particular residues to quantify the local structural environment. METHODS: RSV (range, 0-1) is defined as (Voronoi volume-van der Waals volume)/Voronoi volume of the target residue. The concept of RSV describes the extent of available space for every protein residue. RESULTS: RSV and Voronoi profiles with and without water molecules (RSVw, RSV, VOw, and VO) were compared for 554 non-homologous proteins. RSV (without water) showed better Pearson's correlations with CS than did RSVw, VO, or VOw values. The mean correlation coefficient between RSV and CS was 0.51, which is comparable to the correlation between RSA and CS (0.49) and that between WCN and CS (0.56). CONCLUSIONS: RSV is a robust structural descriptor with and without water molecules and can quantitatively reflect evolutionary information in a single protein structure. Therefore, it may represent a practical structural determinant to study protein sequence, structure, and function relationships.

Functional investigation of transmembrane helix 3 in H⁺-translocating pyrophosphatase.

H⁺-translocating pyrophosphatase (H⁺-PPase, EC 3.6.1.1) plays an important role in acidifying vacuoles by transporting protons across membranes at the expense of pyrophosphate (PP(i)) hydrolysis. Vigna radiata H⁺-PPase (VrH⁺-PPase) contains 16 transmembrane helices (TMs). The hydrophobicity of TM3 is relatively lower than that of most other TMs, and the amino acids in this TM are highly conserved in plants. Furthermore, TM5 and -6, which are the core TMs involving in H⁺-PPase functions, are near TM3. It is thus proposed that TM3 is associated with H⁺-PPase activity. To address this possibility, site-directed mutagenesis was applied in this investigation to determine the role of TM3 in VrH⁺-PPase. Upon alanine/serine substitution, T138 and S142, whose side chains face toward the center TMs, were found to be involved in efficient proton transport. G149/S153 and G160/A164 pairs at the crucial termini of the two GxxxG-like motifs are indispensable in maintaining enzymatic activities and conformational stability. Moreover, stability in the vicinity surrounding G149 is pivotal for efficient expression. S153, M161 and A164 are critical for the K⁺-mediated stimulation of H⁺-PPase. Taken together, our results demonstrate that TM3 plays essential roles in PP(i) hydrolysis, proton transport, expression, and K⁺ stimulation of H⁺-PPase.

Deriving protein dynamical properties from weighted protein contact number.

It has recently been shown that in proteins the atomic mean-square displacement (or B-factor) can be related to the number of the neighboring atoms (or protein contact number), and that this relationship allows one to compute the B-factor profiles directly from protein contact number. This method, referred to as the protein contact model, is appealing, since it requires neither trajectory integration nor matrix diagonalization. As a result, the protein contact model can be applied to very large proteins and can be implemented as a high-throughput computational tool to compute atomic fluctuations in proteins. Here, we show that this relationship can be further refined to that between the atomic mean-square displacement and the weighted protein contact-number, the weight being the square of the reciprocal distance between the contacting pair. In addition, we show that this relationship can be utilized to compute the cross-correlation of atomic motion (the B-factor is essentially the auto-correlation of atomic motion). For a nonhomologous dataset comprising 972 high-resolution X-ray protein structures (resolution <2.0 A and sequence identity <25%), the mean correlation coefficient between the X-ray and computed B-factors based on the weighted protein contact-number model is 0.61, which is better than those of the original contact-number model (0.51) and other methods. We also show that the computed correlation maps based on the weighted contact-number model are globally similar to those computed through normal model analysis for some selected cases. Our results underscore the relationship between protein dynamics and protein packing. We believe that our method will be useful in the study of the protein structure-dynamics relationship.

pKNOT: the protein KNOT web server.

Knotted proteins are more commonly observed in recent years due to the enormously growing number of structures in the Protein Data Bank (PDB). Studies show that the knot regions contribute to both ligand binding and enzyme activity in proteins such as the chromophore-binding domain of phytochrome, ketol-acid reductoisomerase or SpoU methyltransferase. However, there are still many misidentified knots published in the literature due to the absence of a convenient web tool available to the general biologists. Here, we present the first web server to detect the knots in proteins as well as provide information on knotted proteins in PDB-the protein KNOT (pKNOT) web server. In pKNOT, users can either input PDB ID or upload protein coordinates in the PDB format. The pKNOT web server will detect the knots in the protein using the Taylor's smoothing algorithm. All the detected knots can be visually inspected using a Java-based 3D graphics viewer. We believe that the pKNOT web server will be useful to both biologists in general and structural biologists in particular.

A simple way to compute protein dynamics without a mechanical model.

We found that in proteins the average atomic fluctuation is linearly related to the square of the atomic distance from the center of mass of the protein. Using this simple relation, we can accurately compute the temperature factors of proteins of a wide range of sizes and folds, and the correlation of the fluctuations in proteins. This simple relation provides a direct link between protein dynamics and the static protein's geometrical shape and offers a simple way to compute protein dynamics without either long time trajectory integration or any matrix operations.