Study of Parasitic Infections, Cancer, and other Diseases with Mass-Spectrometry and Quantitative Proteome-Disease Relationships

Abstract

We can understand Mass-Spectra Quantitative Proteome-Disease Relationships (MS-QPDRs) as models useful to detect Disease Biomarkers or to predict Drug Toxicity effects based on Mass-Spectra outcomes from samples of human body tissues, parasites, or other organisms. MS-QPDR development and practical use is an emerging area combining Proteomics and Bioinformatics; which involves computational, molecular, and legal sciences. We detect, at least two tendencies on QPDR development. The first tendency (type 1) uses Statistical, Artificial Intelligence, Machine Learning and/or Non-Linear Signal processing to fish for single MS biomarker signals directly within MS data. A recent alternative (type 2) uses Graph Theory to construct Complex Network representations of MS data. Next, we can calculate graph parameters called Mass-Spectra Topological Indices (MS-TIs) useful to describe the graph. The last step is similar to the first tendency but it uses MS-TIs as inputs (instead of MS signals) to seek the MS-QPDR model. There are many examples of QPDR models based on scheme 1. However, there has been little effort to seek QPDR models with scheme 2. On the other hand, MS-QPDR models can be obtained from different body fluids; the case of Human Blood Proteome (BP) is one of the most interesting. The outcomes obtained by Mass Spectrometry (MS) analysis of Serum Protein Profile (SPP) of Blood Proteome (BP) are very useful for the early detection of diseases and drug induced toxicities. In the present work we review, discuss, and outline some perspectives on the use of QPDR models based on the two types of schemes. We also refer to the recent implementation of the internet portal called BioAims for QPDR analysis (http://miaja.tic.udc.es/Bio-AIMS/ ) for free use by the research community.

A New Method for Predicting the Subcellular Localization of Eukaryotic Proteins with Both Single and Multiple Sites: Euk-mPLoc 2.0

“…According to its original definition, the PseAAC is actually formulated by a set of discrete numbers [16] as long as it is different from the classical amino acid composition (AAC) and that it is derived from a protein sequence that is able to harbor some sort of its sequence order and pattern information, or able to reflect some physicochemical and biochemical properties of the constituent amino acids. Since the concept of PseAAC was proposed, it has been widely used to deal with many protein-related problems and sequence-related systems (see, e.g., [21] , [22] , [23] , [24] , [25] , [26] , [27] , [28] , [29] , [30] , [31] , [32] , [33] , [34] , [35] , [36] , [37] , [38] , [39] , [40] , [41] , [42] and a long list of PseAAC-related references cited in a recent review [20] ). As summarized in [20] , until now 16 different PseAAC modes have been used to represent the samples of proteins for predicting their attributes.…”

Computer-Aided Drug Design Methodologies Toward the Design of Anti-Hepatitis C Agents

“…In all these cases we can find models that use the structural parameters of molecular systems like drugs, protein structure, RNA secondary structure, protein-protein interaction networks (PINs), genes network as input to predict the properties of such system (output). That is why, the editor González-Díaz has extended the discussion to different collective of authors editing special issues on CADD techniques (including QSAR and others), which have been published on journals such as the Current Topics in Medicinal Chemistry [19][20][21][22][23][24][25][26][27][28], Current Proteomics [29][30][31][32][33][34][35][36], Current Drug Metabolism [37][38][39][40][41][42][43][44][45], Current Pharmaceutical Design [46][47][48][49][50][51][52][53][54][55], and Current Bioinformatics [56][57][58][59][60][61][62][63]…”

Bio-AIMS Collection of Chemoinformatics Web Tools based on Molecular Graph Information and Artificial Intelligence Models

“…Thus, it is possible to predict the function of a protein based on its three-dimensional (3D) structure, the function of a DNA secondary structure, the interaction of drugs with multiple molecular targets [4,5]. Several applications have been published in Medicinal Chemistry [6][7][8][9][10][11][12], Proteomics [13][14][15][16][17][18], Drug Metabolism [19][20][21][22][23], Pharmaceutical Design [24][25][26][27][28], Bioinfonnatics [29][30][31][32][33][34], Nanotoxity [35,36].…”