Exploring Proteomic Drug Targets, Therapeutic Strategies and Protein - Protein Interactions in Cancer: Mechanistic View

Systematic investigation of machine learning on limited data: A study on predicting protein-protein binding strength

The application of machine learning techniques in biological research, especially when dealing with limited data availability, poses significant challenges. In this study, we leveraged advancements in method development for predicting protein-protein binding strength to conduct a systematic investigation into the application of machine learning on limited data. The binding strength, quantitatively measured as binding affinity, is vital for understanding the processes of recognition, association, and dysfunction that occur within protein complexes. By incorporating transfer learning, integrating domain knowledge, and employing both deep learning and traditional machine learning algorithms, we mitigated the impact of data limitations and made significant advancements in predicting protein-protein binding affinity. In particular, we developed over 20 models, ultimately selecting three representative best-performing ones that belong to distinct categories. The first model is structure-based, consisting of a random forest regression and thirteen handcrafted features. The second model is sequence-based, employing an architecture that combines transferred embedding features with a multilayer perceptron. Finally, we created an ensemble model by averaging the predictions of the two aforementioned models. The comparison with other predictors on three independent datasets confirms the significant improvements achieved by our models in predicting protein-protein binding affinity. The programs for running these three models are available at https://github.com/minghuilab/BindPPI.

Liquid biopsy in the setting of leptomeningeal metastases: a systematic review and meta-analysis

PURPOSE

The blood-brain barrier can prevent circulating tumor DNA (ctDNA) derived from the central nervous system from entering the blood making it challenging to evaluate molecular features of leptomeningeal metastasis (LM). Accordingly, we sought to systematically compare the diagnostic power or significance of ctDNA derived from cerebrospinal fluid (CSF) compared to plasma ctDNA in patients with LM.

METHODS

A systematic review and meta-analysis was performed under the PRISMA guideline. We used PubMed, EMBASE, and the EuroPMC to search the literature using combinations of the following terms: circulating tumor DNA, ctDNA, circulating tumor cell, brain metastasis, leptomeningeal metastasis, outcome(s), and prognosis. We included all available English language studies that compared the diagnostic significance of CSF derived and serum ctDNA. All eligible studies level of bias was assessed using the New Castle Ottawa Scale (NOS).

RESULTS

Our meta-analysis from 6 included studies (n = 226) that confirmed the diagnostic power of liquid biopsies in detecting genomic alteration is better when taking a CSF-derived samples than from the plasma (RR 1.46 [0.93; 2.29]; I2 = 92%; p-value < 0.01).

CONCLUSION

CSF ctDNA is better at describing molecular landscape for LM; such an understanding may ultimately help inform patient treatment and responses to therapy.

Anti-Cancer Roles of Probiotic-Derived P8 Protein in Colorectal Cancer Cell Line DLD-1

A novel probiotics-derived protein, P8, suppresses the growth of colorectal cancer (CRC). P8 can penetrate the cell membrane via endocytosis and cause cell cycle arrest in DLD-1 cells through down-regulation of CDK1/Cyclin B1. However, neither the protein involved in the endocytosis of P8 nor the cell cycle arrest targets of P8 are known. We identified two P8-interacting target proteins [importin subunit alpha-4 (KPNA3) and glycogen synthase kinase-3 beta (GSK3β)] using P8 as a bait in pull-down assays of DLD-1 cell lysates. Endocytosed P8 in the cytosol was found to bind specifically to GSK3β, preventing its inactivation by protein kinases AKT/CK1ε/PKA. The subsequent activation of GSK3β led to strong phosphorylation (S^33,37/T⁴¹) of β-catenin, resulting in its subsequent degradation. P8 in the cytosol was also found to be translocated into the nucleus by KPNA3 and importin. In the nucleus, after its release, P8 binds directly to the intron regions of the GSK3β gene, leading to dysregulation of GSK3β transcription. GSK3β is a key protein kinase in Wnt signaling, which controls cell proliferation during CRC development. P8 can result in a cell cycle arrest morphology in CRC cells, even when they are in the Wnt ON signaling state.

Computational Evaluation of Peptide-Protein Binding Affinities: Application of Potential of Mean Force Calculations to SH2 Domains

Many biological functions are mediated by protein-protein interactions (PPIs), often involving specific structural modules, such as SH2 domains. Inhibition of PPIs is a pharmaceutical strategy of growing importance. However, a major challenge in the design of PPI inhibitors is the large interface involved in these interactions, which, in many cases, makes inhibition by small organic molecules ineffective. Peptides, which cover a wide range of dimensions and can be opportunely designed to mimic protein sequences at PPI interfaces, represent a valuable alternative to small molecules. Computational techniques able to predict the binding affinity of peptides for the target domain or protein represent a crucial stage in the workflow for the design of peptide-based drugs. This chapter describes a protocol to obtain the potential of mean force (PMF) for peptide-SH2 domain binding, starting from umbrella sampling (US) molecular dynamics (MD) simulations. The PMF profiles can be effectively used to predict the relative standard binding free energies of different peptide sequences.

Emerging Therapeutic Agents for Colorectal Cancer

There are promising new therapeutic agents for CRC patients, including novel small-molecule inhibitors and immune checkpoint blockers. We focused on emerging CRC’s therapeutic agents that have shown the potential for progress in clinical practice. This review provides an overview of tyrosine kinase inhibitors targeting VEGF and KIT, BRAF and MEK inhibitors, TLR9 agonist, STAT3 inhibitors, and immune checkpoint blockers (PD1/PDL-1 inhibitors), for which recent advances have been reported. These new agents have the potential to provide benefits to CRC patients with unmet medical needs.

The protein-protein interaction network of intestinal gastric cancer patients reveals hub proteins with potential prognostic value

BACKGROUND

Gastric cancer (GC) is the third leading cause of cancer worldwide. According to the Lauren classification, gastric adenocarcinoma is divided into two subtypes: diffuse and intestinal. The development of intestinal gastric cancer (IGC) can take years and involves multiple factors.

OBJECTIVE

To investigate the protein profile of tumor samples from patients with IGC in comparison with adjacent nontumor tissue samples.

METHODS

We used label-free nano-LC-MS/MS to identify proteins from the tissues samples. The results were analyzed using MetaCore™ software to access functional enrichment information. Protein-protein interactions (PPI) were predicted using STRING analysis. Hub proteins were determined using the Cytoscape plugin, CytoHubba. Survival analysis was performed using KM plotter. We identified 429 differentially expressed proteins whose pathways and processes were related to protein folding, apoptosis, and immune response.

RESULTS

The PPI network of these proteins showed enrichment modules related to the regulation of cell death, immune system, neutrophil degranulation, metabolism of RNA and chromatin DNA binding. From the PPI network, we identified 20 differentially expressed hub proteins, and assessed the prognostic value of the expression of genes that encode them. Among them, the expression of four hub genes was significantly associated with the overall survival of IGC patients.

CONCLUSIONS

This study reveals important findings that affect IGC development based on specific biological alterations in IGC patients. Bioinformatics analysis showed that the pathogenesis of IGC patients is complex and involves different interconnected biological processes. These findings may be useful in research on new targets to develop novel therapies to improve the overall survival of patients with IGC.

CRISPR: a journey of gene-editing based medicine

CRISPR (Clustered Regularly Interspaced Short Palindromic Repeat) is one of the hallmark of biological tools, contemplated as a valid and hopeful alternatives to genome editing. Advancements in CRISPR-based technologies have empowered scientists with an editing kit that allows them to employ their knowledge for deleting, replacing and lately "Gene Surgery", and provides unique control over genes in broad range of species, and presumably in humans. These fast-growing technologies have high strength and flexibility and are becoming an adaptable tool with implementations that are altering organism's genome and easily used for chromatin manipulation. In addition to the popularity of CRISPR in genome engineering and modern biology, this major tool authorizes breakthrough discoveries and methodological advancements in science. As scientists are developing new types of experiments, some of the applications are raising questions about what CRISPR can enable. The results of evidence-based research strongly suggest that CRISPR is becoming a practical tool for genome-engineering and to create genetically modified eukaryotes, which is needed to establish guidelines on new regulatory concerns for scientific communities.

Stability and sub-cellular localization of DNA polymerase β is regulated by interactions with NQO1 and XRCC1 in response to oxidative stress

Protein–protein interactions regulate many essential enzymatic processes in the cell. Somatic mutations outside of an enzyme active site can therefore impact cellular function by disruption of critical protein–protein interactions. In our investigation of the cellular impact of the T304I cancer mutation of DNA Polymerase β (Polβ), we find that mutation of this surface threonine residue impacts critical Polβ protein–protein interactions. We show that proteasome-mediated degradation of Polβ is regulated by both ubiquitin-dependent and ubiquitin-independent processes via unique protein–protein interactions. The ubiquitin-independent proteasome pathway regulates the stability of Polβ in the cytosol via interaction between Polβ and NAD(P)H quinone dehydrogenase 1 (NQO1) in an NADH-dependent manner. Conversely, the interaction of Polβ with the scaffold protein X-ray repair cross complementing 1 (XRCC1) plays a role in the localization of Polβ to the nuclear compartment and regulates the stability of Polβ via a ubiquitin-dependent pathway. Further, we find that oxidative stress promotes the dissociation of the Polβ/NQO1 complex, enhancing the interaction of Polβ with XRCC1. Our results reveal that somatic mutations such as T304I in Polβ impact critical protein–protein interactions, altering the stability and sub-cellular localization of Polβ and providing mechanistic insight into how key protein–protein interactions regulate cellular responses to stress.

MotifAnalyzer-PDZ: A computational program to investigate the evolution of PDZ-binding target specificity

Recognition of short linear motifs (SLiMs) or peptides by proteins is an important component of many cellular processes. However, due to limited and degenerate binding motifs, prediction of cellular targets is challenging. In addition, many of these interactions are transient and of relatively low affinity. Here, we focus on one of the largest families of SLiM-binding domains in the human proteome, the PDZ domain. These domains bind the extreme C-terminus of target proteins, and are involved in many signaling and trafficking pathways. To predict endogenous targets of PDZ domains, we developed MotifAnalyzer-PDZ, a program that filters and compares all motif-satisfying sequences in any publicly available proteome. This approach enables us to determine possible PDZ binding targets in humans and other organisms. Using this program, we predicted and biochemically tested novel human PDZ targets by looking for strong sequence conservation in evolution. We also identified three C-terminal sequences in choanoflagellates that bind a choanoflagellate PDZ domain, the Monsiga brevicollis SHANK1 PDZ domain (mbSHANK1), with endogenously-relevant affinities, despite a lack of conservation with the targets of a homologous human PDZ domain, SHANK1. All three are predicted to be signaling proteins, with strong sequence homology to cytosolic and receptor tyrosine kinases. Finally, we analyzed and compared the positional amino acid enrichments in PDZ motif-satisfying sequences from over a dozen organisms. Overall, MotifAnalyzer-PDZ is a versatile program to investigate potential PDZ interactions. This proof-of-concept work is poised to enable similar types of analyses for other SLiM-binding domains (e.g., MotifAnalyzer-Kinase). MotifAnalyzer-PDZ is available at http://motifAnalyzerPDZ.cs.wwu.edu.