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Modelling and Simulation of Nanosystems for Delivering Drugs to the Brain
Published in Carla Vitorino, Andreia Jorge, Alberto Pais, Nanoparticles for Brain Drug Delivery, 2021
Tânia F. G. G. Cova, Sandra C.C. Nunes
Soft matter nanomaterials including those for drug delivery applications are affected by a delicate balance between enthalpic and entropic contributions, requiring specific computational methods to predict their behaviour. Computational simulations are thus invaluable for solving these type of issues which are prohibitive for experimental validation [5]. Molecular dynamics (MD), in particular, has provided the means to systematically sample the conformational ensemble of complex systems [19, 30–32]. High-throughput screening based on MD involves one simulation per molecule, remaining computationally expensive in atomistic resolution. The use of coarse-grained models has been adopted as an alternative for establishing high-throughput schemes, allowing to agglomerate multiple atoms into one bead in order to reduce the number of degrees of freedom, accelerate sampling of conformational space, and reduce the size of chemical space. MD based on coarse-grained force fields has been particularly useful to explore the permeability of drugs through the BBB by inducing structural changes and controlling the opening of tight junctions caused by a shock wave-induced microbubble implosion [33–35].
Disease Prediction and Drug Development
Published in Arvind Kumar Bansal, Javed Iqbal Khan, S. Kaisar Alam, Introduction to Computational Health Informatics, 2019
Arvind Kumar Bansal, Javed Iqbal Khan, S. Kaisar Alam
Systematic algorithm generates possible binding confirmations by exploring all degrees of freedom. There are three major types of systematic search methods: 1) exhaustive search; 2) fragment-based methods and 3) conformational ensemble. In exhaustive search methods, possible translations and rotations of rotatable bonds are performed, and the corresponding binding score is computed. The problem with the exhaustive search is that it is computationally very expensive as the size of the binding area increases. In the fragment-based method, the binding area is divided into multiple rigid fragments, then the binding conformation is incrementally extended one fragment at a time. In the conformational ensemble method, pregenerated conformations are matched and ranked using binding-energy scores.
Rebellion of the deregulated regulators: What is the clinical relevance of studying intrinsically disordered proteins?
Published in Expert Review of Proteomics, 2022
The situation has changed at the end of the last century, when the crucial importance of protein dynamics and structural flexibility in the form of intrinsically disordered proteins (IDPs) and intrinsically disordered regions (IDRs) was recognized (reviewed by Turoverov et al. [8]). It is now accepted that different parts of a protein molecule can be (dis)ordered to different degree. This inherent spatiotemporal heterogeneity defines protein multifunctionality that can be described by a general ‘protein structure-function continuum’ model, where a protein molecule represents a dynamic conformational ensemble of multiple different forms characterized by a broad spectrum of structural features and different functional potentials [9]. Furthermore, a recent discovery of numerous membrane-less organelles (MLOs), which are abundantly present in the living cells, have multiple crucial functions, and play important roles in the spatio-temporal organization of the intracellular space, highlights a new crucial role of many IDPs/IDRs that can undergo liquid-liquid phase separation (LLPS) and thereby control the biogenesis of these phase separated liquid droplets or biomolecular condensates [8,10].
Role of structural disorder in the multi-functionality of flavivirus proteins
Published in Expert Review of Proteomics, 2022
Shivani Krishna Kapuganti, Aparna Bhardwaj, Prateek Kumar, Taniya Bhardwaj, Namyashree Nayak, Vladimir N. Uversky, Rajanish Giri
Conventionally, the activity of a protein was attributed to the unique tertiary structure assumed by it as a result of specific folding process. This constituted a protein structure-function paradigm that was prevailing in protein science for more than 100 years. However, the notion of intrinsically disordered proteins (IDPs) and intrinsically disordered regions (IDRs) in proteins (which, in their unbound state, do not assume an ordered structure under physiological conditions) having a biologically functional role has been gaining popularity for the last two decades. It is widely accepted now that the unstructured and highly flexible nature of IDPs/IDRs allows them to interact with various cellular factors and remain functional in the hostile environment of different cellular compartments. Viruses, with their miniscule genomes encoding miniature proteomes, where each protein evolved to conduct multiple functions, are heavily dependent on intrinsic disorder. As a matter of fact, multifunctional viral proteins serve as illustrative examples of the novel protein structure-function continuum model [3,135–138], where structures of functional proteins can be envisioned as a complex mosaic of regions with different degree of folding such as; foldons, non-foldons, unfoldons, semi-foldons, inducible foldons, and inducible morphing foldons [139] and with different associated functionalities. As a result, a given protein exists as a highly dynamic conformational ensemble containing multiple proteoforms (here, proteoforms refers to all the different molecular forms that a protein, arising from a single gene, can adopt) characterized by a broad spectrum of structural features and possessing various functional potentials. Furthermore, the functionality of these highly dynamic conformational ensembles is fine-tuned by various post-translational modifications and alternative splicing, and such ensembles can undergo dramatic changes at interaction with their specific partners.
Binding symmetry and surface flexibility mediate antibody self-association
Published in mAbs, 2019
Joseph D. Schrag, Marie-Ève Picard, Francis Gaudreault, Louis-Patrick Gagnon, Jason Baardsnes, Mahder S. Manenda, Joey Sheff, Christophe Deprez, Cassio Baptista, Hervé Hogues, John F. Kelly, Enrico O. Purisima, Rong Shi, Traian Sulea
SAP and DI were calculated as previously described16,17 on the entire panel of variants. SAP calculations were performed using a sphere of radius 5 Å. Surfaces were generated using an in-house molecular surface generator. The different functional forms of DI were evaluated, and only the form with best predictive power is reported. DI was calibrated against sedimentation velocity AUC measurements (% dimer) using least-square linear regression in R.81 Median SAP values were based on conformational ensembles generated by MD, whereas DI values were calculated on static structures. The structure of the Fab of the variants was modeled using as template X-ray structures either: 1) the antigen-bound conformation (parental bH1-Fab, PDB code 3BDY), or 2) the dimerizing conformation (bH1-Fab variant WH33-FH98-MH99-RL30b, chains H and L, this study). The residues were mutated with the PyMOL program (Schrödinger, Inc., New York, NY) and the first rotameric state with steric clearance was selected. The backbone atoms were kept in their initial state. Conformational ensembles of the variants were then generated via MD simulations. Initial structures for MD were prepared first with the Sybyl program (Tripos, Inc., St. Louis, MO) to add missing atoms and then using the tleap program from AMBER 16 software.82 The AMBER FF99SB force field,83 was used to perform the MD simulations. Each system was solvated in a truncated octahedron TIP3P water box.84 The distance between the wall of the box and the closest atom of the solute was 12.0 Å. Counterions (Na+, Cl−) were added up to a final concentration of 0.1 M to maintain electroneutrality of the systems. Each system was minimized first, applying harmonic restraints with force constants of 1 kcal/(mol Å2) to all solute atoms, followed by heating from 10 to 150 K for 30 ps in the canonical ensemble (NVT) and from 150 to 300 K for 100 ps in the isothermal–isobaric ensemble (NPT). Each system was equilibrated to adjust the solvent density under 1 atm pressure through 1 ns of NPT simulation. A 30-ns NVT production run was obtained with snapshots collected every 10 ps. For all simulations, a 2-fs time step and an 8-Å nonbonded cutoff were used.