Every year, more than 19 million cancer cases are diagnosed, and this number continues to increase annually. Since standard treatment options have varying success rates for different types of cancer, understanding the biology of an individual's tumour becomes crucial, especially for cases that are difficult to treat. Personalised high-throughput profiling, using next-generation sequencing, allows for a comprehensive examination of biopsy specimens. Furthermore, the widespread use of this technology has generated a wealth of information on cancer-specific gene alterations. However, there exists a significant gap between identified alterations and their proven impact on protein function. Here, we present a bioinformatics pipeline that enables fast analysis of a missense mutation's effect on stability and function in known oncogenic proteins. This pipeline is coupled with a predictor that summarises the outputs of different tools used throughout the pipeline, providing a single probability score, achieving a balanced accuracy above 86%. The pipeline incorporates a virtual screening method to suggest potential FDA/EMA-approved drugs to be considered for treatment. We showcase three case studies to demonstrate the timely utility of this pipeline. To facilitate access and analysis of cancer-related mutations, we have packaged the pipeline as a web server, which is freely available at https://loschmidt.chemi.muni.cz/predictonco/ .Scientific contributionThis work presents a novel bioinformatics pipeline that integrates multiple computational tools to predict the effects of missense mutations on proteins of oncological interest. The pipeline uniquely combines fast protein modelling, stability prediction, and evolutionary analysis with virtual drug screening, while offering actionable insights for precision oncology. This comprehensive approach surpasses existing tools by automating the interpretation of mutations and suggesting potential treatments, thereby striving to bridge the gap between sequencing data and clinical application.

• Keywords
• Bioinformatics, Cancer, Function, High-performance computing, Machine learning, Molecular modelling, Oncology, Personalised medicine, Single nucleotide polymorphism, Stability, Treatment,
• Publication type
• Journal Article MeSH

Core mitochondrial processes such as the electron transport chain, protein translation and the formation of Fe-S clusters (ISC) are of prokaryotic origin and were present in the bacterial ancestor of mitochondria. In animal and fungal models, a family of small Leu-Tyr-Arg motif-containing proteins (LYRMs) uniformly regulates the function of mitochondrial complexes involved in these processes. The action of LYRMs is contingent upon their binding to the acylated form of acyl carrier protein (ACP). This study demonstrates that LYRMs are structurally and evolutionarily related proteins characterized by a core triplet of α-helices. Their widespread distribution across eukaryotes suggests that 12 specialized LYRMs were likely present in the last eukaryotic common ancestor to regulate the assembly and folding of the subunits that are conserved in bacteria but that lack LYRM homologues. The secondary reduction of mitochondria to anoxic environments has rendered the function of LYRMs and their interaction with acylated ACP dispensable. Consequently, these findings strongly suggest that early eukaryotes installed LYRMs in aerobic mitochondria as orchestrated switches, essential for regulating core metabolism and ATP production.

• Keywords
• LECA, LYRM proteins, acyl-ACP, mitochondrial evolution,
• MeSH
• Eukaryota metabolism   MeSH
• Phylogeny MeSH
• Humans MeSH
• Mitochondrial Proteins * metabolism   genetics   MeSH
• Mitochondria * metabolism   MeSH
• Evolution, Molecular MeSH
• Models, Molecular MeSH
• Acyl Carrier Protein metabolism   genetics   MeSH
• Amino Acid Sequence MeSH
• Animals MeSH
• Check Tag
• Humans MeSH
• Animals MeSH
• Publication type
• Journal Article MeSH

Xmipp is an open-source software package consisting of multiple programs for processing data originating from electron microscopy and electron tomography, designed and managed by the Biocomputing Unit of the Spanish National Center for Biotechnology, although with contributions from many other developers over the world. During its 25 years of existence, Xmipp underwent multiple changes and updates. While there were many publications related to new programs and functionality added to Xmipp, there is no single publication on the Xmipp as a package since 2013. In this article, we give an overview of the changes and new work since 2013, describe technologies and techniques used during the development, and take a peek at the future of the package.

• Keywords
• Cryo-EM, Scipion, Xmipp, single-particle analysis,
• Publication type
• Journal Article MeSH