Structural and sequence similarities of hydra xeroderma pigmentosum A protein to human homolog suggest early evolution and conservation

MLapRVFL: Protein sequence prediction based on Multi-Laplacian Regularized Random Vector Functional Link

Protein sequence classification is a crucial research field in bioinformatics, playing a vital role in facilitating functional annotation, structure prediction, and gaining a deeper understanding of protein function and interactions. With the rapid development of high-throughput sequencing technologies, a vast amount of unknown protein sequence data is being generated and accumulated, leading to an increasing demand for protein classification and annotation. Existing machine learning methods still have limitations in protein sequence classification, such as low accuracy and precision of classification models, rendering them less valuable in practical applications. Additionally, these models often lack strong generalization capabilities and cannot be widely applied to various types of proteins. Therefore, accurately classifying and predicting proteins remains a challenging task. In this study, we propose a protein sequence classifier called Multi-Laplacian Regularized Random Vector Functional Link (MLapRVFL). By incorporating Multi-Laplacian and L2,1-norm regularization terms into the basic Random Vector Functional Link (RVFL) method, we effectively improve the model's generalization performance, enhance the robustness and accuracy of the classification model. The experimental results on two commonly used datasets demonstrate that MLapRVFL outperforms popular machine learning methods and achieves superior predictive performance compared to previous studies. In conclusion, the proposed MLapRVFL method makes significant contributions to protein sequence prediction.

The XPA Protein-Life under Precise Control

Nucleotide excision repair (NER) is a central DNA repair pathway responsible for removing a wide variety of DNA-distorting lesions from the genome. The highly choreographed cascade of core NER reactions requires more than 30 polypeptides. The xeroderma pigmentosum group A (XPA) protein plays an essential role in the NER process. XPA interacts with almost all NER participants and organizes the correct NER repair complex. In the absence of XPA's scaffolding function, no repair process occurs. In this review, we briefly summarize our current knowledge about the XPA protein structure and analyze the formation of contact with its protein partners during NER complex assembling. We focus on different ways of regulation of the XPA protein's activity and expression and pay special attention to the network of post-translational modifications. We also discuss the data that is not in line with the currently accepted hypothesis about the functioning of the XPA protein.

DNA Repair Repertoire of the Enigmatic Hydra

Since its discovery by Abraham Trembley in 1744, hydra has been a popular research organism. Features like spectacular regeneration capacity, peculiar tissue dynamics, continuous pattern formation, unique evolutionary position, and an apparent lack of organismal senescence make hydra an intriguing animal to study. While a large body of work has taken place, particularly in the domain of evolutionary developmental biology of hydra, in recent years, the focus has shifted to molecular mechanisms underlying various phenomena. DNA repair is a fundamental cellular process that helps to maintain integrity of the genome through multiple repair pathways found across taxa, from archaea to higher animals. DNA repair capacity and senescence are known to be closely associated, with mutations in several repair pathways leading to premature ageing phenotypes. Analysis of DNA repair in an animal like hydra could offer clues into several aspects including hydra’s purported lack of organismal ageing, evolution of DNA repair systems in metazoa, and alternative functions of repair proteins. We review here the different DNA repair mechanisms known so far in hydra. Hydra genes from various DNA repair pathways show very high similarity with their vertebrate orthologues, indicating conservation at the level of sequence, structure, and function. Notably, most hydra repair genes are more similar to deuterostome counterparts than to common model invertebrates, hinting at ancient evolutionary origins of repair pathways and further highlighting the relevance of organisms like hydra as model systems. It appears that hydra has the full repertoire of DNA repair pathways, which are employed in stress as well as normal physiological conditions and may have a link with its observed lack of senescence. The close correspondence of hydra repair genes with higher vertebrates further demonstrates the need for deeper studies of various repair components, their interconnections, and functions in this early metazoan.

Characterizing the Binding Interactions between DNA-Binding Proteins, XPA and XPE: A Molecular Dynamics Approach

The scaffold nature of Xeroderma pigmentosum complementation group A (XPA) protein makes it an important member of nucleotide excision repair (NER) that removes bulky DNA lesions with the help of various protein-protein interactions (PPI) and DNA-protein interactions. However, many structural insights of XPA's interaction and the binding patterns with other NER proteins are yet to be understood. Here, we have studied one such crucial PPI of XPA with another NER protein, Xeroderma pigmentosum complementation group A (XPE), by using the previously identified binding site of XPA (residues 185-226) in the Assisted Model Building With Energy Refinement force-field-mediated dynamic system. We studied the relationship between XPA_185-226-XPE complex using three different docked models. The major residues observed in all of the models that were responsible for the PPI of this complex were Arg20, Arg47, Asp51, and Leu57 from XPE and the residues Leu191, Gln192, Val193, Trp194, Glu198, Glu202, Glu205, Arg207, Glu209, Gln216, and Phe219 from XPE_185-226. During the simulation study, the orientation of XPA was also noted to be changed by almost 180° in models 1 and 3, which remain unchanged in model 2, indicating that XPA interacts with XPE with its N-terminal end facing downward and C-terminal end facing upward. The same was concurrent with the binding of DNA-binding domain region of XPA (aa98-239) with XPE. The N-terminal of XPE was stretched for accommodating XPA. Using the per-residue energy decomposition analysis for the interface residues of all models, the binding affinity between these proteins were found to be dependent on R20, R47, and L57 of XPE and the residues L191, V193, W194, E198, E202, E205, R207, and F219 of XPA. The net binding free energy of the XPA_185-226-XPE protein complex was found to be -48.3718 kcal mol^-1 for model 1, -49.09 kcal mol^-1 for model 2, and -56.51 kcal mol^-1 for model 3.

DNA repair enzyme APE1 from evolutionarily ancient Hydra reveals redox activity exclusively found in mammalian APE1

Only mammalian apurinic/apyrimidinic endonuclease1 (APE1) has been reported to possess both DNA repair and redox activities. C terminal of the protein is required for base excision repair, while the redox activity resides in the N terminal due to cysteine residues at specific positions. APE1s from other organisms studied so far lack the redox activity in spite of having the N terminal domain. We find that APE1 from the Cnidarian Hydra exhibits both endonuclease and redox activities similar to mammalian APE1. We further show the presence of the three indispensable cysteines in Hydra APE1 for redox activity by site directed mutagenesis. Importance of redox domain but not the repair domain of APE1 in regeneration has been demonstrated by using domain-specific inhibitors. Our findings clearly demonstrate that the redox function of APE1 evolved very early in metazoan evolution and is not a recent acquisition in mammalian APE1 as believed so far.

Protein sequence classification with improved extreme learning machine algorithms

Precisely classifying a protein sequence from a large biological protein sequences database plays an important role for developing competitive pharmacological products. Comparing the unseen sequence with all the identified protein sequences and returning the category index with the highest similarity scored protein, conventional methods are usually time-consuming. Therefore, it is urgent and necessary to build an efficient protein sequence classification system. In this paper, we study the performance of protein sequence classification using SLFNs. The recent efficient extreme learning machine (ELM) and its invariants are utilized as the training algorithms. The optimal pruned ELM is first employed for protein sequence classification in this paper. To further enhance the performance, the ensemble based SLFNs structure is constructed where multiple SLFNs with the same number of hidden nodes and the same activation function are used as ensembles. For each ensemble, the same training algorithm is adopted. The final category index is derived using the majority voting method. Two approaches, namely, the basic ELM and the OP-ELM, are adopted for the ensemble based SLFNs. The performance is analyzed and compared with several existing methods using datasets obtained from the Protein Information Resource center. The experimental results show the priority of the proposed algorithms.