The importance of protein domain mutations in cancer therapy.

Cancer is a complex disease that is caused by multiple genetic factors. Researchers have been studying protein domain mutations to understand how they affect the progression and treatment of cancer. These mutations can significantly impact the development and spread of cancer by changing the protein structure, function, and signalling pathways. As a result, there is a growing interest in how these mutations can be used as prognostic indicators for cancer prognosis. Recent studies have shown that protein domain mutations can provide valuable information about the severity of the disease and the patient's response to treatment. They may also be used to predict the response and resistance to targeted therapy in cancer treatment. The clinical implications of protein domain mutations in cancer are significant, and they are regarded as essential biomarkers in oncology. However, additional techniques and approaches are required to characterize changes in protein domains and predict their functional effects. Machine learning and other computational tools offer promising solutions to this challenge, enabling the prediction of the impact of mutations on protein structure and function. Such predictions can aid in the clinical interpretation of genetic information. Furthermore, the development of genome editing tools like CRISPR/Cas9 has made it possible to validate the functional significance of mutants more efficiently and accurately. In conclusion, protein domain mutations hold great promise as prognostic and predictive biomarkers in cancer. Overall, considerable research is still needed to better define genetic and molecular heterogeneity and to resolve the challenges that remain, so that their full potential can be realized.

Unveiling the vulnerabilities of synthetic lethality in triple-negative breast cancer

Triple-negative breast cancer (TNBC) is the most invasive molecular subtype of breast cancer (BC), accounting for about nearly 15% of all BC cases reported annually. The absence of the three major BC hormone receptors, Estrogen (ER), Progesterone (PR), and Human Epidermal Growth Factor 2 (HER2) receptor, accounts for the characteristic “Triple negative” phraseology. The absence of these marked receptors makes this cancer insensitive to classical endocrine therapeutic approaches. Hence, the available treatment options remain solemnly limited to only conventional realms of chemotherapy and radiation therapy. Moreover, these therapeutic regimes are often accompanied by numerous treatment side-effects that account for early distant metastasis, relapse, and shorter overall survival in TNBC patients. The rigorous ongoing research in the field of clinical oncology has identified certain gene-based selective tumor-targeting susceptibilities, which are known to account for the molecular fallacies and mutation-based genetic alterations that develop the progression of TNBC. One such promising approach is synthetic lethality, which identifies novel drug targets of cancer, from undruggable oncogenes or tumor-suppressor genes, which cannot be otherwise clasped by the conventional approaches of mutational analysis. Herein, a holistic scientific review is presented, to undermine the mechanisms of synthetic lethal (SL) interactions in TNBC, the epigenetic crosstalks encountered, the role of Poly (ADP-ribose) polymerase inhibitors (PARPi) in inducing SL interactions, and the limitations faced by the lethal interactors. Thus, the future predicament of synthetic lethal interactions in the advancement of modern translational TNBC research is assessed with specific emphasis on patient-specific personalized medicine (AU)

Potential biomarkers uncovered by bioinformatics analysis in sotorasib resistant-pancreatic ductal adenocarcinoma.

Background: Mutant KRAS-induced tumorigenesis is prevalent in lung, colon, and pancreatic ductal adenocarcinomas. For the past 3 decades, KRAS mutants seem undruggable due to their high-affinity GTP-binding pocket and smooth surface. Structure-based drug design helped in the design and development of first-in-class KRAS G12C inhibitor sotorasib (AMG 510) which was then approved by the FDA. Recent reports state that AMG 510 is becoming resistant in non-small-cell lung cancer (NSCLC), pancreatic ductal adenocarcinoma (PDAC), and lung adenocarcinoma patients, and the crucial drivers involved in this resistance mechanism are unknown. Methods: In recent years, RNA-sequencing (RNA-seq) data analysis has become a functional tool for profiling gene expression. The present study was designed to find the crucial biomarkers involved in the sotorasib (AMG 510) resistance in KRAS G12C-mutant MIA-PaCa2 cell pancreatic ductal adenocarcinoma cells. Initially, the GSE dataset was retrieved from NCBI GEO, pre-processed, and then subjected to differentially expressed gene (DEG) analysis using the limma package. Then the identified DEGs were subjected to protein-protein interaction (PPI) using the STRING database, followed by cluster analysis and hub gene analysis, which resulted in the identification of probable markers. Results: Furthermore, the enrichment and survival analysis revealed that the small unit ribosomal protein (RP) RPS3 is the crucial biomarker of the AMG 510 resistance in KRAS G12C-mutant MIA-PaCa2 cell pancreatic ductal adenocarcinoma cells. Conclusion: Finally, we conclude that RPS3 is a crucial biomarker in sotorasib resistance which evades apoptosis by MDM2/4 interaction. We also suggest that the combinatorial treatment of sotorasib and RNA polymerase I machinery inhibitors could be a possible strategy to overcome resistance and should be studied in in vitro and in vivo settings in near future.

Rice WRKY13 TF protein binds to motifs in the promoter region to regulate downstream disease resistance-related genes.

In plants, pathogen resistance is brought about by the binding of certain transcription factor (TF) proteins to the cis-elements of certain target genes. These cis-elements are present upstream in the motif of the promoters of each gene. This ensures the binding of a specific TF to a specific promoter, therefore regulating the expression of that gene. Therefore, the study of each promoter sequence of all the rice genes would help identify the target genes of a specific TF. Rice 1 kb upstream promoter sequences of 55,986 annotated genes were analyzed using the Perl program algorithm to detect WRKY13 binding motifs (bm). The resulting genes were grouped using Gene Ontology and gene set enrichment analysis. A gene with more than 4 TF bm in their promoter was selected. Ten genes reported to have a role in rice disease resistance were selected for further analysis. Cis-acting regulatory element analysis was carried out to find the cis-elements and confirm the presence of the corresponding motifs in the promoter sequences of these genes. The 3D structure of WRKY13 TF and the corresponding ten genes were built, and the interacting residues were determined. The binding capacity of WRKY13 to the promoter of these selected genes was analyzed using docking studies. WRKY13 was considered for docking analysis based on the prior reports of autoregulation. Molecular dynamic simulations provided more details regarding the interactions. Expression data revealed the expression of the genes that helped provide the mechanism of interaction. Further co-expression network helped to characterize the interaction of these selected disease resistance-related genes with the WRKY13 TF protein. This study suggests downstream target genes that are regulated by the WRKY13 TF. The molecular mechanism involving the gene network regulated by WRKY13 TF in disease resistance against rice fungal pathogens is explored.

Investigating the binding affinity of andrographolide against human SARS-CoV-2 spike receptor-binding domain through docking and molecular dynamics simulations.

SARS-CoV-2 is a positive-sense single-stranded RNA virus that causes a deadly coronavirus disease (COVID-19) in humans. The infection of SARS-CoV-2 in humans involves a viral surface spike glycoprotein containing the receptor-binding domain (RBD). The interactions of SARS-CoV-2 with the host angiotensin-converting enzyme 2 (ACE2) receptor are mediated by RBD. It binds to the host ACE2 and influences viral replication and disease pathogenesis. Therefore, targeting the RBD to prevent SARS-CoV-2 infections is of utmost importance. In this study, we used docking and molecular dynamics simulations to understand the binding effect of andrographolide on the SARS-CoV-2 spike protein. During docking, a strong binding affinity was observed between the ligand and the target receptor protein. MD results demonstrated higher conformational fluctuations in the ligand-free protein compared to the bound form. Several residues in the active sites make conformational rearrangements for the S protein to interact with the ligand. While RBD experiences conformational transition to gain more stability upon binding with the ligand. This binding is strengthened via several non-covalent interactions that make the complex structure more stable with higher binding affinity. Overall findings of the study may shed some valuable insights concerning the development of potential therapeutics in the strategies for COVID-19 prevention.

Construction and analysis of brain networks from different neuroimaging techniques.

OBJECTIVES: The human brain is one of the most complicated biological structure in the entire universe. It is incredibly challenging to see how it functions, mainly during scatter-brain, and when diseases occur in human beings. The notable contribution from consultants, academic institutions, researchers, and others have contributed significant findings in the field of neuroscience and made substantial changes in different dimensions. The exploration of the brain is becoming an emerging area due to the rapid advancement of neuroimaging techniques. METHODS: Brain disorder is one such significant disease that is very difficult to diagnose, notably, which influence many people worldwide. RESULTS: In this review, we explore various tools and software to construc and analyze brain networks and different brain scanning methods. Further, this study addresses the research work related to brain networks, including various graph theory methods. More specifically, we present the different diagnostics techniques in brain disorders. CONCLUSION: This review provides a detailed understanding of brain scans, tools, and brain network construction methods. Lastly, applications of complex network theory will contribute new insights about brain structure and function.

Molecular dynamic study on PTEN frameshift mutations in breast cancer provide c2 domain as a potential biomarker.

PTEN is a tumour suppressor gene known for regulating apoptosis, cell growth, and many other pathways. It is one of the most frequently mutated genes comprising the phosphatase domain (PD) and C terminal domain (C2). Direct therapeutic methods are not applicable for targeting PTEN because once gets mutated, it needs restoration. For mutant detection and restoration using PTEN mRNA there is a need to explore various mutations taking place in PTEN, identify their particular domains, and study their interactions within the cellular system. Here, we have tried to highlight a few such regions in the mutated PTEN of breast cancer patients. In this study, we have selected the top-most-occurring PTEN mutation in breast cancer and compared them to determine the specific properties of each mutation and its effect on functionality. Molecular dynamic simulation for 50 ns was performed on five structures to compare the structural behaviour of mutated PTEN in the system. Our finding suggests that frameshift mutations are more damaging and affect the c2 domain. Frameshift mutant fs_ACTT is the highest occurring as well as the most damaging mutation in all the compared structures. Docking study shows that substitution mutations D92H and R130Q causes loss of binding ability towards PIP2 in normal PTEN, interfering the dephosphorylation process. Overall, the C2 domain is more frequently mutated, and the amino acid residues in the C2 domain show more fluctuations compared to the other regions. Our study can provide the basis for selecting frequently mutated C2 domain as a potential therapeutic marker.Communicated by Ramaswamy H. Sarma.

DCMP: database of cancer mutant protein domains.

Protein domains are functional and structural units of proteins. They are responsible for a particular function that contributes to protein's overall role. Because of this essential role, the majority of the genetic variants occur in the domains. In this study, the somatic mutations across 21 cancer types were mapped to the individual protein domains. To map the mutations to the domains, we employed the whole human proteome to predict the domains in each protein sequence and recognized about 149 668 domains. A novel Perl-API program was developed to convert the protein domain positions into genomic positions, and users can freely access them through GitHub. We determined the distribution of protein domains across 23 chromosomes with the help of these genomic positions. Interestingly, chromosome 19 has more number of protein domains in comparison with other chromosomes. Then, we mapped the cancer mutations to all the protein domains. Around 46-65% of mutations were mapped to their corresponding protein domains, and significantly mutated domains for all the cancer types were determined using the local false discovery ratio (locfdr). The chromosome positions for all the protein domains can be verified using the cross-reference ensemble database. Database URL: https://dcmp.vit.ac.in/.

Exploring the conformational dynamics and flexibility of intrinsically disordered HIV-1 Nef protein using molecular dynamic network approaches.

Intrinsically disordered proteins represent a class of proteins that lack fixed and well-defined three-dimensional structures in solution. HIV-1 Nef is an intrinsically disordered peripheral membrane protein involved in the replication and pathogenesis of HIV-1 infection. Nef controls expression levels of cell surface CD4 molecules that are essential for adaptive immunity. Despite the lack of fixed and stable structures, Nef physically interacts with the host cellular proteins (AP-1/MHC-I) and modulates intracellular trafficking pathways. Therefore, it is essential to understand how this dynamic conformational flexibility affects Nef structures and function. In this study, we combined all-atom molecular dynamics (MD) simulations and dynamic network approaches to better understand the structure and dynamics of Nef in two different forms, the free unbound and the bound state. Using the MD simulation approach, we show that the intrinsically disordered Nef exhibit a large dynamic field with more atomic fluctuations and lesser thermodynamic stability in the unbound conditions. The conformations of Nef change over time, and this protein remains more compact, folded, and stable in the bound form. The dynamic network analysis revealed regions of the protein capable of modulating the conformational behavior of the disordered Nef. The average betweenness centrality (BC) unveiled residues that are critical for mediating protein-protein interactions. The average shortest path length (L) and the perturbation response scanning exposed residues that are likely to be important in steering protein conformational changes. Overall, the study demonstrates how all-atom MD simulations combined with the dynamic network approach can be used to gain further insights into the structure and dynamics-function relationship of intrinsically disordered HIV-1 Nef. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s13205-021-02698-8.

Global and regional connectivity analysis of resting-state function MRI brain images using graph theory in Parkinson's disease.

OBJECTIVES: Parkinson's disease (PD) is the second most common neurodegenerative disorder which resists around 10 million people worldwide. It develops when nerve cells in a region of the brain that regulates movement become damaged; the symptoms usually begin gradually and become critical over time. In this study, we proposed to investigate the topological properties of functional brain networks within healthy controls (HCs) and PD patients. Also, we evaluated the gender difference among PD patients through graph theoretical approach. MATERIALS AND METHODS: The rs-fMRI (resting-state functional magnetic resonance imaging) data of fifty-one PD patients and healthy controls was applied to generate the brain functional connectome. The functional whole-brain connectome was constructed by thresholding partial correlation matrices of 160 regions from Dosenbach brain atlas. From the graph theory approach, global and nodal metrics were analysed, and we observed considerable changes in PD patients in comparison with healthy controls. RESULTS: Findings suggest that there is a significant difference in the topological characteristics of PD patients, and this was found to be evident in the default mode network (DMN) and occipital regions. CONCLUSION: This study provides essential insights from network changes to the clinically relevant information for the PD progression.

Computational investigations on the dynamic binding effect of molecular tweezer CLR01 toward intrinsically disordered HIV-1 Nef.

Intrinsically disordered proteins (IDPs) are highly flexible molecules that undergo disorder to order transition through their interaction with other molecules. IDPs play a vital role in several biological processes ranging from molecular recognition to several human diseases through the protein-protein interaction. The dynamic flexibility of IDPs and their implications in several human diseases enable these molecules to serve as novel therapeutic targets. However, the challenging task is to develop novel drugs against IDPs because of their lack of stable structures and the nature of high conformational flexibility. In this study, we have calculated the dynamic binding effect of the supramolecular tweezer CLR01 against the intrinsically disordered HIV-1 Nef by employing molecular docking and dynamics simulation approaches. From docking results, we predicted the strong binding affinity of the tweezer with the target residues of Nef. The docking results were further validated from the molecular dynamics simulation studies confirming the conformational stability of Nef upon tweezer binding. These findings provide useful insights into the development of potent inhibitors for targeting Nef protein functions.

Gene Prioritization in Parkinson's Disease Using Human Protein-Protein Interaction Network.

Parkinson's disease (PD) is the second-most common neurodegenerative disorder, and the actual cause of this disease is still unknown. Identifying the target genes that are associated with disease plays an essential role in the treatment of PD. Various genetic studies have determined the significant target genes for disease progression, although this continues to be challenging in the field of drug designing. In this study, we proposed a network-based approach to identify target genes for PD using gene mutation, gene expression, and gene deletion analysis. The subnetwork of PD genes was constructed from human protein-protein interaction network, and the potential genes were identified using network centrality measures. Two genes, PARK1 and PARK2, were identified as target genes by integrating gene mutation and expression data into the subnetwork. Gene deletion analysis was carried out to determine the significant target, and results revealed that VDAC1 and ATP5C1 genes were crucial for the Parkinson's subnetwork. Thus, findings from the network-based approach will provide additional insight for understanding the disease mechanism of PD. Future enhancement of this study may help in predicting disease biomarkers as well as designing novel compounds in rational drug designing.

Dynamic conformational flexibility and molecular interactions of intrinsically disordered proteins.

Intrinsically disordered proteins (IDPs) are highly flexible and undergo disorder to order transition upon binding. They are highly abundant in human proteomes and play critical roles in cell signaling and regulatory processes. This review mainly focuses on the dynamics of disordered proteins including their conformational heterogeneity, protein-protein interactions, and the phase transition of biomolecular condensates that are central to various biological functions. Besides, the role of RNA-mediated chaperones in protein folding and stability of IDPs were also discussed. Finally, we explored the dynamic binding interface of IDPs as novel therapeutic targets and the effect of small molecules on their interactions.

Breast cancer mutation in GATA3 zinc finger 1 induces conformational changes leading to the closer binding of ZnFn2 with a wrapping architecture.

GATA3 is a transcription factor, known to regulate the transcriptional network and several pathways using two zinc fingers. Its mutation is associated with a higher risk of breast cancer. The molecular mechanisms of these mutations are poorly understood. It recognizes -GATA- sites on the DNA, using its two zinc fingers ZnFn1 and ZnFn2. Mutations in ZnFn2 have been studied in the past and well known but recently ZnFn1 mutations are also being reported very frequently in breast cancer patients and there is very less knowledge available regarding the binding modes and mechanism. Here, we have investigated the structural and functional impact of GATA3 mutation M294K on the DNA-binding property. The structure was obtained and mutation was induced before subjecting it to the molecular docking followed by MD simulation. Our findings indicate that the somatic mutation M294K, reported in the GATA3 gene destabilizes the unbound structure but, when it forms the DNA-complex, its overall structural stability is restored by the wrapping architecture of ZnFn2 around the DNA in the palindromic region, leading to the enhanced kinetic stability. The mutation not only affects the ZnFn1 region alone but also influences the whole complex by inducing the conformational changes in the linker region between the two zinc fingers, bringing the two zinc fingers to closer proximity representing the flexibility in binding sites. Our findings provide a better understanding of ZnFn1 mutations and the possibility of a different strategy to target these genes for their clinical relevance.Communicated by Ramaswamy H. Sarma.

Understanding contact patterns of protein structures from protein contact map and investigation of unique patterns in the globin-like folded domains.

Proteins are biochemical compounds made up of one or more polypeptides in a specific order, typically folded into a functionally active form. Proteins are categorized into four different structural classes according to the topology of α-helices and ß-strands. In this study, we modeled these four structural classes as an undirected network depicting amino acids as nodes and interaction between them as edges. Results infer that basic protein classes can be easily recognized as well as distinguished by utilizing protein contact maps (PCM). Toward studying the globin-like fold, the helix-loop-helix region contacts were seen to be of a unique pattern, and these remained in all the folds. Further, the averaged diagonal contacts were analyzed and identified those contacts in α/ß proteins were higher in comparison with the other class. Interesting, we noticed that anti-parallel beta sheets were dominant in all-ß and α + ß classes that lead to similar diagonal patterns. Network properties of all four basic classes were analyzed and found to possess small-world property. Findings infer that PCM may assist classify protein structure classes and it also helps in evaluating the predicted protein structures.