A Review on the Salt Bridge Between ASP177 and ARG163 of Wild-Type Rabbit Prion Protein

Prion diseases are invariably fatal and highly infectious neurodegenerative diseases that affect a wide variety of mammalian species such as sheep and goats, cattle, deer, elks, humans and mice etc., but rabbits have a low susceptibility to be infected by prion diseases with respect to other species. The stability of rabbit prion protein is due to its highly ordered {\beta}2-{\alpha}2 loop (PLoS One 5(10) e13273 (2010); Journal of Biological Chemistry 285(41) 31682-31693 (2010)) and a hydrophobic staple helix-capping motif (PNAS 107(46) 19808-19813 (2010); PLoS One 8 (5) e63047 (2013)). The {\beta}2-{\alpha}2 loop and the tail of Helix 3 it interacts with have been a focus in prion protein structure studies. For this loop we found a salt bridge linkage ASP177-ARG163 (O-N) (Journal of Theoretical Biology 342 (7 February 2014) 70-82 (2014)). Some scientists said on the 2FJ3.pdb NMR file of the rabbit prion protein, the distance of ASP177-ARG163 (O-N) gives the salt bridge of about 10 {\AA} which is nearly null in terms of energy and such a salt bridge is not observed in their work. But, from the 3O79.pdb X-ray file of the rabbit prion protein, we can clearly observe this salt bridge. This article analyses the NMR and X-ray structures and gives an answer to the above question: the salt bridge presents at pH 6.5 in the X-ray structure is simply gone at pH 4.5 in the NMR structure is simply due to the different pH values that impact electrostatics at the salt bridge and hence also impact the structures. Moreover, some molecular dynamics simulation results of the X-ray structure are reported in this article to reveal the secrets of the structural stability of rabbit prion protein.Comment: arXiv admin note: text overlap with arXiv:1407.622

A survey and a molecular dynamics study on the (central) hydrophobic region of prion proteins

Prion diseases are invariably fatal neurodegenerative diseases that affect humans and animals. Unlike most other amyloid forming neurodegenerative diseases, these can be highly infectious. Prion diseases occur in a variety of species. They include the fatal human neurodegenerative diseases Creutzfeldt-Jakob Disease (CJD), Fatal Familial Insomnia (FFI), Gerstmann-Straussler-Scheinker syndrome (GSS), Kuru, the bovine spongiform encephalopathy (BSE or 'mad-cow' disease) in cattle, the chronic wasting disease (CWD) in deer and elk, and scrapie in sheep and goats, etc. Transmission across the species barrier to humans, especially in the case of BSE in Europe, CWD in North America, and variant CJDs (vCJDs) in young people of UK, is a major public health concern. Fortunately, scientists reported that the (central) hydrophobic region of prion proteins (PrP) controls the formation of diseased prions. This article gives a detailed survey on PrP hydrophobic region and does molecular dynamics studies of human PrP(110-136) to confirm some findings from the survey. The structural bioinformatics presented in this article can be helpful as a reference in three-dimensional images for laboratory experimental works to study PrP hydrophobic region

Molecular Dynamics Studies on the Buffalo Prion Protein

It was reported that buffalo is a low susceptibility species resisting to prion diseases, which are invariably fatal and highly infectious neurodegenerative diseases that affect a wide variety of species. In molecular structures, TSE neurodegenerative diseases are caused by the conversion from a soluble normal cellular prion protein, predominantly with alpha-helices, into insoluble abnormally folded infectious prions, rich in beta-sheets. This paper studies the molecular structure and structural dynamics of buffalo prion protein, in order to reveal the reason why buffalo are resistant to prion diseases. We first did molecular modeling of a homology structure constructed by one mutation at residue 143 from the Nuclear Magnetic Resonance structure of bovine and cattle PrP(124-227); immediately we found for buffalo PrPC(124-227) there are 5 hydrogen bonds at Asn143, but at this position bovine/cattle do not have such hydrogen bonds. Same as that of rabbits, dogs or horses, our molecular dynamics studies also confirmed there is a strong salt bridge ASP178-ARG164 (O-N) keeping the beta2-alpha2 loop linked in buffalo. We also found there is a very strong hydrogen bond SER170-TYR218 linking this loop with the C-terminal end of alpha-helix H3. Other information such as (i) there is a very strong salt bridge HIS187-ARG156 (N-O) linking alpha-helices H2 and H1 (if mutation H187R is made at position 187 then the hydrophobic core of PrPC will be exposed), (ii) at D178, there is a hydrogen bond Y169-D178 and a polar contact R164-D178 for BufPrPC instead of a polar contact Q168-D178 for bovine PrPC, (iii) BufPrPC owns 3-10 helices at 125-127, 152-156 and in the beta2-alpha2 loop respectively, and (iv) in beta2-alpha2 loop there are strong pi-contacts, etc, has been discovered

The LBFGS Quasi-Newtonian Method for Molecular Modeling Prion AGAAAAGA Amyloid Fibrils

Experimental X-ray crystallography, NMR (Nuclear Magnetic Resonance) spectroscopy, dual polarization interferometry, etc are indeed very powerful tools to determine the 3-Dimensional structure of a protein (including the membrane protein); theoretical mathematical and physical computational approaches can also allow us to obtain a description of the protein 3D structure at a submicroscopic level for some unstable, noncrystalline and insoluble proteins. X-ray crystallography finds the X-ray final structure of a protein, which usually need refinements using theoretical protocols in order to produce a better structure. This means theoretical methods are also important in determinations of protein structures. Optimization is always needed in the computer-aided drug design, structure-based drug design, molecular dynamics, and quantum and molecular mechanics. This paper introduces some optimization algorithms used in these research fields and presents a new theoretical computational method - an improved LBFGS Quasi-Newtonian mathematical optimization method - to produce 3D structures of Prion AGAAAAGA amyloid fibrils (which are unstable, noncrystalline and insoluble), from the potential energy minimization point of view. Because the NMR or X-ray structure of the hydrophobic region AGAAAAGA of prion proteins has not yet been determined, the model constructed by this paper can be used as a reference for experimental studies on this region, and may be useful in furthering the goals of medicinal chemistry in this field

Unifying Large Language Models and Knowledge Graphs: A Roadmap

Large language models (LLMs), such as ChatGPT and GPT4, are making new waves in the field of natural language processing and artificial intelligence, due to their emergent ability and generalizability. However, LLMs are black-box models, which often fall short of capturing and accessing factual knowledge. In contrast, Knowledge Graphs (KGs), Wikipedia and Huapu for example, are structured knowledge models that explicitly store rich factual knowledge. KGs can enhance LLMs by providing external knowledge for inference and interpretability. Meanwhile, KGs are difficult to construct and evolving by nature, which challenges the existing methods in KGs to generate new facts and represent unseen knowledge. Therefore, it is complementary to unify LLMs and KGs together and simultaneously leverage their advantages. In this article, we present a forward-looking roadmap for the unification of LLMs and KGs. Our roadmap consists of three general frameworks, namely, 1) KG-enhanced LLMs, which incorporate KGs during the pre-training and inference phases of LLMs, or for the purpose of enhancing understanding of the knowledge learned by LLMs; 2) LLM-augmented KGs, that leverage LLMs for different KG tasks such as embedding, completion, construction, graph-to-text generation, and question answering; and 3) Synergized LLMs + KGs, in which LLMs and KGs play equal roles and work in a mutually beneficial way to enhance both LLMs and KGs for bidirectional reasoning driven by both data and knowledge. We review and summarize existing efforts within these three frameworks in our roadmap and pinpoint their future research directions.Comment: 29 pages, 25 figure

A Survey on Temporal Knowledge Graph Completion: Taxonomy, Progress, and Prospects

Temporal characteristics are prominently evident in a substantial volume of knowledge, which underscores the pivotal role of Temporal Knowledge Graphs (TKGs) in both academia and industry. However, TKGs often suffer from incompleteness for three main reasons: the continuous emergence of new knowledge, the weakness of the algorithm for extracting structured information from unstructured data, and the lack of information in the source dataset. Thus, the task of Temporal Knowledge Graph Completion (TKGC) has attracted increasing attention, aiming to predict missing items based on the available information. In this paper, we provide a comprehensive review of TKGC methods and their details. Specifically, this paper mainly consists of three components, namely, 1)Background, which covers the preliminaries of TKGC methods, loss functions required for training, as well as the dataset and evaluation protocol; 2)Interpolation, that estimates and predicts the missing elements or set of elements through the relevant available information. It further categorizes related TKGC methods based on how to process temporal information; 3)Extrapolation, which typically focuses on continuous TKGs and predicts future events, and then classifies all extrapolation methods based on the algorithms they utilize. We further pinpoint the challenges and discuss future research directions of TKGC

Molecular dynamics studies on the NMR and X-ray structures of rabbit prion protein wild-type and mutants

Prion diseases are invariably fatal and highly infectious neurodegenerative diseases that affect a wide variety of mammalian species such as sheep, goats, mice, humans, chimpanzees, hamsters, cattle, elks, deer, minks, cats, chicken, pigs, turtles, etc. These neurodegenerative diseases are caused by the conversion from a soluble normal cellular protein into insoluble abnormally folded infectious prions and the conversion is believed to involve conformational change from a predominantly alpha-helical protein to one rich in beta-sheet structure. Such conformational changes may be amenable to study by molecular dynamics (MD) techniques. For rabbits, classical studies show they have a low susceptibility to be infected, but in 2012 it was reported that rabbit prion can be generated (though not directly) and the rabbit prion is infectious and transmissible (Proceedings of the National Academy of Sciences USA 109(13): 5080-5). This paper studies the NMR and X-ray molecular structures of rabbit prion protein wild-type and mutants by MD techniques, in order to understand the specific mechanism of rabbit prion protein and rabbit prions.Comment: (The 2nd version of arXiv1304.7633

Molecular dynamics studies on the NMR structures of rabbit prion protein wild type and mutants: surface electrostatic charge distributions

Prion diseases are invariably fatal and highly infectious neurodegenerative diseases that affect a wide variety of mammalian species such as sheep and goats, cattle, deer and elk, and humans. But for rabbits, studies have shown that they have a low susceptibility to be infected by prion diseases. This paper does molecular dynamics (MD) studies of rabbit NMR structures (of the wild type and its two mutants of two surface residues), in order to understand the specific mechanism of rabbit prion proteins (RaPrPC). Protein surface electrostatic charge distributions are specially focused to analyze the MD trajectories. This paper can conclude that surface electrostatic charge distributions indeed contribute to the structural stability of wild-type RaPrPC; this may be useful for the medicinal treatment of prion diseases