Biology subjects

Panchenko, A.

Publications and source records attributed to Panchenko, A..

7 recordsLinked to original sources

bioRxiv2025

Looking Across Protein Domains to Identify Driver Mutations in Cancer

Cancer can develop through the accumulation of somatic mutations that drive uncontrolled cell proliferation. A central objective in cancer research is to identify mutations that provide a selective growth advantage to tumor cells, so called driver mutations. Many computational methods infer driver missense mutations in proteins by assessing their recurrence. However, such approach suffers from the limited capacity to detect those driver mutations that occur infrequently across tumor samples. One strategy to overcome this limitation is to aggregate mutations from proteins sharing the same protein domain. Here we constructed a benchmark of cancer driver and passenger mutations, based on the known experimental and clinical studies, and systematically evaluated the applicability of methods that aggregate mutations across different mutation types and protein domains. We found that accounting for evidence mutations from different types of amino acid substitutions occurring in the same protein position enhances the classification performance. Furthermore, accounting for evidence mutations from paralogous proteins in the domain family increased the precision but compromised the overall classification accuracy. In addition, the performance of domain-based approaches was shown to crucially depend on the similarity between the target and evidence proteins.

cancer biology↗

bioRxiv2025

G34R cancer mutation alters the conformational ensemble and dynamics of the histone H3.3 tails

In recent years, mutations in the histone variant H3.3 have been discovered in pediatric and adult gliomas and osteosarcomas. One of these is the G34R mutation in the H3.3 N-terminal tail. While this mutation is known to disrupt epigenomic pathways, the effects on nucleosome structure itself have not been explored. In light of recent studies, that have demonstrated that the interaction of the H3 tail with nucleosomal and linker DNA is driven in large part by arginine residues, we sought to determine if the G34R cancer mutation and adjacent G33R mutation, not observed in cancer, directly alter nucleosome structural dynamics. Using NMR spectroscopy and molecular dynamics simulations, we investigate the effects of these mutations on the H3 tail in the context of the nucleosome. Our results show that both of these mutations enhance the association of the H3 tails with DNA and decrease the conformational dynamics around the site of mutation. Moreover, our results reveal that both mutations lead to changes in the conformational ensemble of the entire tail, re-positioning it on the nucleosomal DNA as well as promoting intra-tail interactions. This has implications for the accessibility of the H3 tail to effector proteins and for changes in higher-order chromatin structure resulting from a shift in intra-versus inter-nucleosome contacts mediated by the H3 tail.

biophysics↗

bioRxiv2024

Are the Next-Generation Pathogenicity Predictors Applicable to Cancer?

Next-generation pathogenicity predictors are designed to identify pathogenic mutations in genetic disorders but are increasingly used to detect driver mutations in cancer. Despite this, their suitability for cancer is not fully established. Here we have assessed the effectiveness of next-generation pathogenicity predictors when applied to cancer by using a comprehensive experimental benchmark of cancer driver and neutral mutations. Our findings indicate that state-of-the-art methods AlphaMissense and VARITY demonstrate commendable performance despite generally underperforming compared to cancer-specific methods. This is notable considering that these methods do not explicitly incorporate cancer-specific information in their training and have made concerted efforts to prevent data leakage from the human-curated training and test sets. Nevertheless, it should be mentioned that a significant limitation of using pathogenicity predictors for cancer arises from their inability to detect cancer potential driver mutations specific for a particular cancer type.

cancer biology↗

bioRxiv2023

Detection of new pioneer transcription factors as cell-type specific nucleosome binders

Wrapping of DNA into nucleosomes restricts accessibility to the DNA and may affect the recognition of binding motifs by transcription factors. A certain class of transcription factors, the pioneer transcription factors, can specifically recognize their DNA binding sites on nucleosomes, may initiate local chromatin opening and facilitate the binding of co-factors in a cell-type-specific manner. For the majority of human pioneer transcription factors, the locations of their binding sites, mechanisms of binding and regulation remain unknown. We have developed a computational method to predict the cell-type-specific ability of transcription factors to bind nucleosomes by integrating ChIP-seq, MNase-seq and DNase-seq data with details of nucleosome structure. We have demonstrated the ability of our approach in discriminating pioneer from canonical transcription factors and predicted new potential pioneer transcription factors in H1, K562, HepG2 and HeLa cell lines. Lastly, we systemically analyzed the interaction modes between various pioneer transcription factors and detected several clusters of distinctive binding sites on nucleosomal DNA.

bioinformatics↗

bioRxiv2022

Histone variant H2A.Z modulates nucleosome dynamics to promote DNA accessibility

Nucleosomes containing the histone variant H2A.Z are important for gene transcription initiation and termination, chromosome segregation and DNA double-strand break repair, among other functions. However, the underlying mechanism of how H2A.Z influences nucleosome stability, dynamics and DNA accessibility remains elusive as experimental and computational evidence are inconclusive. Our modeling efforts of nucleosome stability and dynamics, along with comparisons with experimental data show that the incorporation of H2A.Z results in a substantial decrease of the energy barrier for DNA unwrapping. This leads to spontaneous DNA unwrapping of about forty base pairs in total, enhanced DNA accessibility, nucleosome gapping and histone plasticity, which otherwise is not observed for canonical nucleosomes. We demonstrate that both N- and C-terminal tails of H2A.Z play major roles in these events, whereas H3.3 variant exerts a negligible impact in modulating the DNA end unwrapping. In summary, our results indicate that H2A.Z deposition makes nucleosomes more mobile and DNA more accessible to transcriptional machinery and other chromatin components.

biophysics↗

bioRxiv2021

DNA methylation cues in nucleosome geometry, stability, and unwrapping

Cytosine methylation at the 5-carbon position is an essential DNA epigenetic mark in many eukaryotic organisms. Although countless structural and functional studies of cytosine methylation have been reported in both prokaryotes and eukaryotes, our understanding of how it influences the nucleosome assembly, structure, and dynamics remains obscure. Here we investigated the effects of cytosine methylation at CpG sites on nucleosome dynamics and stability. By applying long molecular dynamics simulations (five microsecond long trajectories, 60 microseconds in total), we generated extensive atomic level conformational full nucleosome ensembles. Our results revealed that methylation induces pronounced changes in geometry for both linker and nucleosomal DNA, leading to a more curved, under-twisted DNA, shifting the population equilibrium of sugar-phosphate backbone geometry. These conformational changes are associated with a considerable enhancement of interactions between methylated DNA and the histone octamer, doubling the number of contacts at some key arginines. H2A and H3 tails play important roles in these interactions, especially for DNA methylated nucleosomes. This, in turn, prevents a spontaneous DNA unwrapping of 3-4 helical turns for the methylated nucleosome with truncated histone tails, otherwise observed in the unmethylated system on several microsecond time scale.

biophysics↗

bioRxiv2017

Modeling Hormonal Control of Cambium Proliferation

Rise of atmospheric CO2 is one of the main causes of global warming. Catastrophic climate change can be avoided by reducing emissions and increasing sequestration of CO2. Trees are known to sequester CO2 during photosynthesis, and then store it as wood biomass. Thus, breeding of trees with higher wood yield would mitigate global warming as well as augment production of renewable construction materials, energy, and industrial feedstock. Wood is made of cellulose-rich xylem cells produced through proliferation of a specialized stem cell niche called cambium. Importance of cambium in xylem cells production makes it an ideal target for the tree breeding programs; however our knowledge about control of cambium proliferation remains limited. The morphology and regulation of cambium differs from stem cell niches that control axial growth. For this reason, translating the knowledge about axial growth to radial growth has limited use. Furthermore, genetic approaches cannot be easily applied because overlaying tissues conceal cambium from direct observation and complicate identification of mutants. To overcome the paucity of experimental tools in cambium biology, we constructed a Boolean network CARENET (CAmbium Regulation gene NETwork) for modelling cambium activity, which includes the key transcription factors WOX4 and HD-ZIP III as well as their potential regulators. Our simulations revealed that: (1) auxin, cytokinin, gibberellin, and brassinosteroids act cooperatively in promoting transcription of WOX4 and HD-ZIP III; (2) auxin and cytokinin pathways negatively regulate each other; (3) hormonal pathways act redundantly in sustaining cambium activity; (4) individual cells in the stem cell niches can have diverse molecular identities. CARENET can be extended to include components of other signalling pathways and be integrated with models of xylem and phloem differentiation. Such extended models would facilitate breeding trees with higher wood yield.

bioinformatics↗