A Simple Method for Discovering Druggable, Specific Glycosaminoglycan-Protein Systems. Elucidation of Key Principles from Heparin/Heparan Sulfate-Binding Proteins

Glycosaminoglycans (GAGs) affect human physiology and pathology by modulating more than 500 proteins. GAG-protein interactions are generally assumed to be ionic and nonspecific, but specific interactions do exist. Here, we present a simple method to identify the GAG-binding site (GBS) on proteins that in turn helps predict high specific GAG–protein systems. Contrary to contemporary thinking, we found that the electrostatic potential at basic arginine and lysine residues neither identifies the GBS consistently, nor its specificity. GBSs are better identified by considering the potential at neutral hydrogen bond donors such as asparagine or glutamine sidechains. Our studies also reveal that an unusual constellation of ionic and non-ionic residues in the binding site leads to specificity. Nature engineers the local environment of Asn45 of antithrombin, Gln255 of 3-O-sulfotransferase 3, Gln163 and Asn167 of 3-O-sulfotransferase 1 and Asn27 of basic fibroblast growth factor in the respective GBSs to induce specificity. Such residues are distinct from other uncharged residues on the same protein structure in possessing a significantly higher electrostatic potential, resultant from the local topology. In contrast, uncharged residues on nonspecific GBSs such as thrombin and serum albumin possess a diffuse spread of electrostatic potential. Our findings also contradict the paradigm that GAG-binding sites are simply a collection of contiguous Arg/Lys residues. Our work demonstrates the basis for discovering specifically interacting and druggable GAG-protein systems based on the structure of protein alone, without requiring access to any structure-function relationship data

Glycosaminoglycans: What Remains To Be Deciphered?

Glycosaminoglycans (GAGs) are complex polysaccharides exhibiting a vast structural diversity and fulfilling various functions mediated by thousands of interactions in the extracellular matrix, at the cell surface, and within the cells where they have been detected in the nucleus. It is known that the chemical groups attached to GAGs and GAG conformations comprise “glycocodes” that are not yet fully deciphered. The molecular context also matters for GAG structures and functions, and the influence of the structure and functions of the proteoglycan core proteins on sulfated GAGs and vice versa warrants further investigation. The lack of dedicated bioinformatic tools for mining GAG data sets contributes to a partial characterization of the structural and functional landscape and interactions of GAGs. These pending issues will benefit from the development of new approaches reviewed here, namely (i) the synthesis of GAG oligosaccharides to build large and diverse GAG libraries, (ii) GAG analysis and sequencing by mass spectrometry (e.g., ion mobility-mass spectrometry), gas-phase infrared spectroscopy, recognition tunnelling nanopores, and molecular modeling to identify bioactive GAG sequences, biophysical methods to investigate binding interfaces, and to expand our knowledge and understanding of glycocodes governing GAG molecular recognition, and (iii) artificial intelligence for in-depth investigation of GAGomic data sets and their integration with proteomics

Glycosaminoglycans: What Remains To Be Deciphered?

Glycosaminoglycans (GAGs) are complex polysaccharides exhibiting a vast structural diversity and fulfilling various functions mediated by thousands of interactions in the extracellular matrix, at the cell surface, and within the cells where they have been detected in the nucleus. It is known that the chemical groups attached to GAGs and GAG conformations comprise “glycocodes” that are not yet fully deciphered. The molecular context also matters for GAG structures and functions, and the influence of the structure and functions of the proteoglycan core proteins on sulfated GAGs and vice versa warrants further investigation. The lack of dedicated bioinformatic tools for mining GAG data sets contributes to a partial characterization of the structural and functional landscape and interactions of GAGs. These pending issues will benefit from the development of new approaches reviewed here, namely (i) the synthesis of GAG oligosaccharides to build large and diverse GAG libraries, (ii) GAG analysis and sequencing by mass spectrometry (e.g., ion mobility-mass spectrometry), gas-phase infrared spectroscopy, recognition tunnelling nanopores, and molecular modeling to identify bioactive GAG sequences, biophysical methods to investigate binding interfaces, and to expand our knowledge and understanding of glycocodes governing GAG molecular recognition, and (iii) artificial intelligence for in-depth investigation of GAGomic data sets and their integration with proteomics

Design computacional de biopolímeros derivados da cutina

Orientador: Miguel Angel San Miguel BarreraTese (doutorado) - Universidade Estadual de Campinas, Instituto de QuímicaResumo: Neste trabalho focamos em estudar o comportamento estrutural de algums polímeros de cutina, quando depositados em uma superfície de mica. Estudamos o comportamento estrutural de um ponto de vista teórico, usando a dinâmica molecular clássica em suas diferentes modalidades de campos de força. Utilizamos variados tipos de campos de força disponíveis na literatura, como: (1) campo de força atomístico (AFF), (2) campo de força coarse-grained (CGFF) e (3) campo de força reativo (RFF). Desta forma, conseguiremos estudar propriedades do sistema que estão em diferentes escalas temporais. Os monômeros de cutina usados especificamente para este trabalho foram: ácido aleurítico (9,10,16 tri-hidroxi-hexadecanoico, ALE), e ácido palmítico (hexadecanóico, PAL). Com a dinâmica molecular AFF, resolvemos o problema da densidade superficial efetiva (p), que ocorre nos monômeros de cutina quando são depositados em uma superfície de suporte. Definida a densidade efetiva (p), continuamos estudando o comportamento dos monômeros ALE e PAL, quando depositados em suas formas puras como em suas misturas 75:25 (75% ALE e 25% PAL) e 25:75 (25% ALE e 75% PAL). Além disso, estudamos o comportamento dos grupos funcionais que poderiam favorecer uma reação de esterificação nos sistemas puros de ALE e nas misturas 75:25 e 25:75. Com a dinâmica molecular CGFF, estudamos os sistemas puros de ALE e PAL. Com esse campo de força conseguimos observar propriedades que não foram observadas com a dinâmica AFF, devido à sua limitação de escala de tempo. Tivemos que desenvolver os parâmetros do campo de força CGFF para nossos sistemas, uma vez que os parâmetros CGFF não têm uma boa transferibilidade. Com a dinâmica molecular RFF, respaldamos nossos estudos sobre as reações de esterificação desenvolvidos com dinâmica AFFAbstract: In this work, we focus on studying the structural behavior of some cutin polymers when deposited on a mica surface. We study structural behavior from a theoretical point of view, using classical molecular dynamics in its different force field modalities. We use various types of force fields available in the literature, such as (1) atomistic force field (AFF), (2) coarse-grained force field (CGFF) and (3) reactive force field (RFF). In this way, we will be able to study system properties that are at different time scales. The cutin monomers used specifically for this work were: aleuritic acid (9,10,16 trihydroxyhexadecanoic acid, ALE), and palmitic acid (hexadecanoic acid, PAL). With AFF molecular dynamics, we solve the problem of effective surface density (p), which occurs in cutin monomers when they are deposited on a support surface. Having defined the effective density (p), we continue to study the behavior of monomers ALE and PAL when deposited in their pure forms as in their mixtures 75:25 (75% ALE and 25% PAL) and 25:75 (25% ALE and 75 % PAL). Besides, we study the behavior of functional groups that could favor an esterification reaction in pure ALE systems and the 75:25 and 25:75 mixtures. With CGFF molecular dynamics, we study the pure ALE and PAL systems. With this force field, we can observe properties that were not observed with the AFF dynamics, due to their time scale limitation. We had to develop the CGFF force field parameters for our systems since the CGFF parameters do not have good transferability. With RFF molecular dynamics, we support our studies on esterification reactions developed with AFF dynamicsDoutoradoFísico-QuímicaDoutor em CiênciasCAPE

Exploring the Multifaceted Roles of Glycosaminoglycans (GAGs) - New Advances and Further Challenges

Glycosaminoglycans are linear, anionic polysaccharides (GAGs) consisting of repeating disaccharides. GAGs are ubiquitously localized throughout the extracellular matrix (ECM) and to the cell membranes of cells in all tissues. They are either conjugated to protein cores in the form of proteoglycans, e.g., chondroitin/dermatan sulfate (CS/DS), heparin/heparan sulfate (Hep/HS) and keratan sulfate (KS), as well as non-sulfated hyaluronan (HA). By modulating biological signaling GAGs participate in the regulation of homeostasis and also participate in disease progression. The book, entitled “Exploring the multifaceted roles of glycosaminoglycans (GAGs)—new advances and further challenges”, features original research and review articles. These articles cover several GAG-related timely topics in structural biology and imaging; morphogenesis, cancer, and other disease therapy and drug developments; tissue engineering; and metabolic engineering. This book also includes an article illustrating how metabolic engineering can be used to create the novel chondroitin-like polysaccharide.A prerequisite for communicating in any discipline and across disciplines is familiarity with the appropriate terminology. Several nomenclature rules exist in the field of biochemistry. The historical description of GAGs follows IUPAC and IUB nomenclature. New structural depictions such as the structural nomenclature for glycan and their translation into machine-readable formats have opened the route for cross-references with popular bioinformatics resources and further connections with other exciting “omics” fields

Coarse-Grained Model of Glycosaminoglycans

Glycosaminoglycans (GAGs) represent a class of anionic periodic linear polysaccharides, which mediate cell communication processes by interactions with their protein targets in the extracellular matrix. Due to their high flexibility, charged nature, periodicity, and polymeric nature, GAGs are challenging systems for computational approaches. To deal with the length challenge, coarse-grained (CG) modeling could be a promising approach. In this work, we develop AMBER-compatible CG parameters for GAGs using all-atomic (AA) molecular dynamics (MD) simulations in explicit solvent and the Boltzmann conversion approach. We compare both global and local properties of GAGs obtained in the simulations with AA and CG approaches, and we conclude that our CG model is appropriate for the MD approach of long GAG molecules at long time scales