Salt Bridges and Conformational Flexibility: Effect on Protein Stability

Karshikoff, Andrey; Jelesarov, Ilian

doi:10.1080/13102818.2008.10817520

Cited by 24 publications

(15 citation statements)

References 25 publications

(14 reference statements)

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“…Similarly, the crystal structure of the AHL pore exhibited 297 salt bridges while the MD generated ensemble had an average of 346 ± 12 salt bridges, indicating a 17% increase. Similar observations have been made for other systems – salt bridges which were previously not present in the crystal structures of proteins were observed to be formed during the course of an MD simulation (Karshikoff & Jelesarov, 2008). Figure 3 d shows that the number of intra-protein hydrogen bonds in the AHL crystal structure and the MD generated ensemble were 986 and 1053 ± 25 respectively, and that in the AHL crystal structure and the MD generated ensemble were 467 and 651 ± 19 respectively, indicating a 6% and 39% increase for the MD simulated conformations of ClyA and AHL, respectively.…”

Section: Resultssupporting

confidence: 85%

AnIn silicoAlgorithm for Identifying Amino Acids that Stabilize Oligomeric Membrane-Toxin Pores through Electrostatic Interactions

Desikan

Maiti

Ayappa

2019

Preprint

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Pore forming toxins (PFTs) are a class of proteins which have specifically evolved to form unregulated pores in target plasma membranes, and represent the single largest class of bacterial virulence factors. With increasingly prevalent antibiotic-resistant bacterial strains, next generation therapies are being developed to target bacterial PFTs rather than the pathogens themselves. However, structure-based design of inhibitors that could block pore formation are hampered by a paucity of structural information about pore intermediates. On similar lines, observations of the inter-subunit interfaces in fully-formed pore complexes to identify druggable residues, whose interactions could potentially be blocked to hamper pore formation or destabilize pore assemblies, are often limited because of the presence of a large number of protein-protein interaction sites across pore inter-subunit interfaces. Narrowing down the list of plausible target residues requires a quantitative assessment of their contributions towards pore stability, which cannot be gleaned from a single, static, crystal or cryo-EM pore structure.We overcome this limitation by developing an in silico screening algorithm that employs fully atomistic molecular dynamics simulations coupled with knowledge-based screening to identify residues engaged in persistent and stabilizing electrostatic interactions across inter-subunit interfaces in membrane-inserted PFT pores. Application of this algorithm to prototypical α-PFT (cytolysin A) and β-PFT (α-hemolysin) pores yielded a small predicted subset of highly interacting residues, blocking of which could destabilize pore complexes as shown in previous mutagenesis experiments for some of these predicted residues. The algorithm also yielded a novel set of residues in both cytolysin A and α-hemolysin pores for which no mutagenesis and stability data exists to the best of our knowledge, and therefore could serve as hitherto un-CONTACT Rajat Desikan, recognised potential targets for PFT inhibitors. The algorithm worked equally well for both α and β-PFT pores, and could thus be potentially applicable to all pores with known structures to generate a database of pore-destabilizing mutations, which could then serve as a starting point for experimental validation and structure-based PFT-inhibitor design. ABBREVIATIONSAHL α-hemolysin ClyA Cytolysin A DMPC 1,2-dimyristoyl-sn-glycero-3-phosphocholine PDB Protein data bank PFT(s) Pore-forming toxin(s) MD Molecular dynamics RSA Relative solvent accessibility RMSD Root mean square deviation SASA solvent accessible surface area

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Section: Resultssupporting

confidence: 85%

AnIn silicoAlgorithm for Identifying Amino Acids that Stabilize Oligomeric Membrane-Toxin Pores through Electrostatic Interactions

Desikan

Maiti

Ayappa

2019

Preprint

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“…Due to the size of proteins and their complexity, this is mainly the inherently directional nature of these interactions [49] that distinguishes HMI from isotropic (non-directional) interactions. Hydrophobic (Van der Waals), dispersive (London), and steric (6/12 potentials) are isotropic while hydrogen bonding, Ar-H [19], and salt bridge interactions [4,40,50], all of which we are including as HMIs, are directional [5,46]). Because we analyzed distances between 2 and 6 Å, we were able to largely obviate the need for a specific distance metric, thereby avoiding some controversies in this area as this length regime includes everything from long covalent disulfide bonds to water-mediated hydrogen bonds [15].…”

Section: Donors Directmentioning

confidence: 99%

“…Obviously, our method is not without its limitations. This model is simply too simple to differentiate hydrogen bonds from salt bridges, which tend to have only slightly shorter interaction distances [40,50], and we focus exclusively on intra-chain interactions [59]. It is also worth noting that the ambiguity present in several atom types (e.g., carboxylates of aspartate and glutamate, or histidine nitrogen atoms) necessitates ambiguity in donor and acceptor assignments, and also ambiguity in finding interactions between atoms which may in their natural state be matched donors or acceptors.…”

Section: Donors Directmentioning

confidence: 99%

A Geometric Definition of Short to Medium Range Hydrogen-Mediated Interactions in Proteins

et al. 2020

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We present a method to rapidly identify hydrogen-mediated interactions in proteins (e.g., hydrogen bonds, hydrogen bonds, water-mediated hydrogen bonds, salt bridges, and aromatic π-hydrogen interactions) through heavy atom geometry alone, that is, without needing to explicitly determine hydrogen atom positions using either experimental or theoretical methods. By including specific real (or virtual) partner atoms as defined by the atom type of both the donor and acceptor heavy atoms, a set of unique angles can be rapidly calculated. By comparing the distance between the donor and the acceptor and these unique angles to the statistical preferences observed in the Protein Data Bank (PDB), we were able to identify a set of conserved geometries (15 for donor atoms and 7 for acceptor atoms) for hydrogen-mediated interactions in proteins. This set of identified interactions includes every polar atom type present in the Protein Data Bank except OE1 (glutamate/glutamine sidechain) and a clear geometric preference for the methionine sulfur atom (SD) to act as a hydrogen bond acceptor. This method could be readily applied to protein design efforts.

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“…Salt bridges are formed between two oppositely charged amino acid residues that is, Asp or Glu with Arg, Lys, or His, that are within a 4.0 Å distance . Depending upon the flexibility of protein in solution, the disruption and reformation of salt bridges occur . Salt Bridge analysis was performed using VMD plugin .…”

Section: Methodsmentioning

confidence: 99%

Potential role of salt‐bridges in the hinge‐like movement of apicomplexa specific β‐hairpin of Plasmodium and Toxoplasma profilins: A molecular dynamics simulation study

Kadirvel

Anishetty

2018

J of Cellular Biochemistry

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Profilin is one of the actin-binding proteins that regulate dynamics of actin polymerization. It plays a key role in cell motility and invasion. It also interacts with several other proteins notably through its poly-L-proline (PLP) binding site. Profilin in apicomplexa is characterized by a unique mini-domain consisting of a large β-hairpin extension and an acidic loop which is relatively longer in Plasmodium species. Profilin is essential for the invasive blood stages of Plasmodium falciparum. In the current study, unbound profilins from Plasmodium falciparum (Pf), Toxoplasma gondii (Tg), and Homo sapiens (Hs) were subjected to molecular dynamics (MD) simulations for a timeframe of 100 ns each to understand the conformational dynamics of these proteins. It was found that the β-hairpin of profilins from Pf and Tg shows a hinge-like movement. This movement in Pf profilin may possibly be driven by the loss of a salt-bridge within profilin. The impact of this conformational change on actin binding was assessed by docking three dimensional (3D) structures of profilin from Pf and Tg with their corresponding actins using ClusPro2.0. The stability of docked Pf profilin-actin complex was assessed through a 50 ns MD simulation. As Hs profilin I does not have the apicomplexa specific mini-domain, MD simulation was performed for this protein and its dynamics was compared to that of profilins from Pf and Tg. Using an immunoinformatics approach, potential epitope regions were predicted for Pf profilin. This has a potential application in the design of vaccines as they mapped to its unique mini-domain.

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Salt Bridges and Conformational Flexibility: Effect on Protein Stability

Cited by 24 publications

References 25 publications

AnIn silicoAlgorithm for Identifying Amino Acids that Stabilize Oligomeric Membrane-Toxin Pores through Electrostatic Interactions

AnIn silicoAlgorithm for Identifying Amino Acids that Stabilize Oligomeric Membrane-Toxin Pores through Electrostatic Interactions

A Geometric Definition of Short to Medium Range Hydrogen-Mediated Interactions in Proteins

Potential role of salt‐bridges in the hinge‐like movement of apicomplexa specific β‐hairpin of Plasmodium and Toxoplasma profilins: A molecular dynamics simulation study

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