Identification of Residues Potentially Involved in Optical Shifts in the Water-Soluble Chlorophyll -Binding Protein through Molecular Dynamics Simulations.

Reversible light and thermally induced spectral shifts are universally observed in a wide variety of pigment-protein complexes at temperatures ranging from cryogenic to ambient. In this paper, we employed large-scale molecular dynamics (MD) simulations of a prototypical pigment-protein complex to better understand these shifts at a molecular scale. Although multiple mechanisms have been proposed over the years, no verification of these proposals via MD simulations has thus far been performed; our work represents the first step in this direction.

Inferring Pathways of Oxidative Folding from Prefolding Free Energy Landscapes of Disulfide-Rich Toxins.

Short, cysteine-rich peptides can exist in stable or metastable structural ensembles due to the number of possible patterns of formation of their disulfide bonds. One interesting subset of this peptide group is the conotoxins, which are produced by aquatic snails in the family . The μ conotoxins, which are antagonists and blockers of the voltage-gated sodium channel, exist in a folding spectrum: on one end of the spectrum are more hirudin-like folders, which form disulfide bonds and then reshuffle them, leading to an ensemble of kinetically trapped isomers, and on the other end are more BPTI-like folders, which form the native disulfide bonds one by one in a particular order, leading to a preponderance of conformations existing in a single stable state.

Exploring the Role of Glycans in the Interaction of SARS-CoV-2 RBD and Human Receptor ACE2.

COVID-19 is a highly infectious respiratory disease caused by the novel coronavirus SARS-CoV-2. It has become a global pandemic and its frequent mutations may pose new challenges for vaccine design. During viral infection, the Spike RBD of SARS-CoV-2 binds the human host cell receptor ACE2, enabling the virus to enter the host cell.

The SARS-CoV-2 Spike variant D614G favors an open conformational state.

The COVID-19 (coronavirus disease 2019) pandemic underwent a rapid transition with the emergence of a dominant viral variant (from the "D-form" to the "G-form") that carried an amino acid substitution D614G in its "Spike" protein. The G-form is more infectious in vitro and is associated with increased viral loads in the upper airways. To gain insight into the molecular-level underpinnings of these characteristics, we used microsecond all-atom simulations.

Effects of pH on an IDP conformational ensemble explored by molecular dynamics simulation.

The conformational ensemble of intrinsically disordered proteins, such as α-synuclein, are responsible for their function and malfunction. Misfolding of α-synuclein can lead to neurodegenerative diseases, and the ability to study their conformations and those of other intrinsically disordered proteins under varying physiological conditions can be crucial to understanding and preventing pathologies. In contrast to well-folded peptides, a consensus feature of IDPs is their low hydropathy and high charge, which makes their conformations sensitive to pH perturbation.

The SARS-CoV-2 Spike Variant D614G Favors an Open Conformational State.

The COVID-19 pandemic underwent a rapid transition with the emergence of a SARS-CoV-2 variant that carried the amino acid substitution D614G in the Spike protein that became globally prevalent. The G-form is both more infectious in vitro and associated with increased viral loads in infected people. To gain insight into the mechanism underlying these distinctive characteristics, we employed multiple replicas of microsecond all-atom simulations to probe the molecular-level impact of this substitution on Spike closed and open states.

Machine Learning Algorithm Identifies an Antibiotic Vocabulary for Permeating Gram-Negative Bacteria.

Drug discovery faces a crisis. The industry has used up the "obvious" space in which to find novel drugs for biomedical applications, and productivity is declining. One strategy to combat this is rational approaches to expand the search space without relying on chemical intuition, to avoid rediscovery of similar spaces.

Graph-Directed Approach for Downselecting Toxins for Experimental Structure Determination.

Conotoxins are short, cysteine-rich peptides of great interest as novel therapeutic leads and of great concern as lethal biological agents due to their high affinity and specificity for various receptors involved in neuromuscular transmission. Currently, of the approximately 6000 known conotoxin sequences, only about 3% have associated structural characterization, which leads to a bottleneck in rapid high-throughput screening (HTS) for identification of potential leads or threats. In this work, we combine a graph-based approach with homology modeling to expand the library of conotoxin structures and to identify those conotoxin sequences that are of the greatest value for experimental structural characterization.

Discovery of Self-Assembling π-Conjugated Peptides by Active Learning-Directed Coarse-Grained Molecular Simulation.

Electronically active organic molecules have demonstrated great promise as novel soft materials for energy harvesting and transport. Self-assembled nanoaggregates formed from π-conjugated oligopeptides composed of an aromatic core flanked by oligopeptide wings offer emergent optoelectronic properties within a water-soluble and biocompatible substrate. Nanoaggregate properties can be controlled by tuning core chemistry and peptide composition, but the sequence-structure-function relations remain poorly characterized.

Combinatorial diversity of Syk recruitment driven by its multivalent engagement with FcεRIγ.

Syk/Zap70 family kinases are essential for signaling via multichain immune-recognition receptors such as tetrameric (αβγ2) FcεRI. Syk activation is generally attributed to binding of its tandem SH2 domains to dual phosphotyrosines within FcεRIγ-ITAMs (immunoreceptor tyrosine-based activation motifs). However, the mechanistic details of Syk docking on γ homodimers are unresolved.

Snails In Silico: A Review of Computational Studies on the Conopeptides.

Marine cone snails are carnivorous gastropods that use peptide toxins called conopeptides both as a defense mechanism and as a means to immobilize and kill their prey. These peptide toxins exhibit a large chemical diversity that enables exquisite specificity and potency for target receptor proteins. This diversity arises in terms of variations both in amino acid sequence and length, and in posttranslational modifications, particularly the formation of multiple disulfide linkages.

Patchy Particle Model of the Hierarchical Self-Assembly of π-Conjugated Optoelectronic Peptides.

Self-assembling peptides containing aromatic groups are an attractive target for bioelectronic materials design because of their ease of manufacture, biocompatibility, aqueous solubility, and chemical tunability. Microscopic understanding of the properties that control assembly is a prerequisite for rational design. In this work, we study the assembly of a family of DXXX-Π-XXXD oligopeptides possessing a π-conjugated core flanked by Asp-terminated tetrapeptide wings that display pH-triggered assembly into supramolecular aggregates.

Modulation of polypeptide conformation through donor-acceptor transformation of side-chain hydrogen bonding ligands.

Synthetic polypeptides have received increasing attention due to their ability to form higher ordered structures similar to proteins. The control over their secondary structures, which enables dynamic conformational changes, is primarily accomplished by tuning the side-chain hydrophobic or ionic interactions. Herein we report a strategy to modulate the conformation of polypeptides utilizing donor-acceptor interactions emanating from side-chain H-bonding ligands.

Control of the hierarchical assembly of π-conjugated optoelectronic peptides by pH and flow.

Self-assembled nanoaggregates of π-conjugated peptides possess optoelectronic properties due to electron delocalization over the conjugated peptide groups that make them attractive candidates for the fabrication of bioelectronic materials. We present a computational and theoretical study to resolve the microscopic effects of pH and flow on the non-equilibrium morphology and kinetics of early-stage assembly of an experimentally-realizable optoelectronic peptide that displays pH triggerable assembly. Employing coarse-grained molecular dynamics simulations, we probe the effects of pH on growth kinetics and aggregate morphology to show that control of the peptide protonation state by pH can be used to modulate the assembly rates, degree of molecular alignment, and resulting morphologies within the self-assembling nanoaggregates.

Coarse-Grained Molecular Simulation of the Hierarchical Self-Assembly of π-Conjugated Optoelectronic Peptides.

Self-assembled aggregates of peptides containing aromatic groups possess optoelectronic properties that make them attractive targets for the fabrication of biocompatible electronics. Molecular-level understanding of the influence of microscopic peptide chemistry on the properties of the aggregates is vital for rational peptide design. In this study, we construct a coarse-grained model of Asp-Phe-Ala-Gly-OPV3-Gly-Ala-Phe-Asp (DFAG-OPV3-GAFD) peptides containing OPV3 (distyrylbenzene) π-conjugated cores explicitly parameterized against all-atom calculations and perform molecular dynamics simulations of the self-assembly of hundreds of molecules over hundreds of nanoseconds.

Helical antimicrobial polypeptides with radial amphiphilicity.

α-Helical antimicrobial peptides (AMPs) generally have facially amphiphilic structures that may lead to undesired peptide interactions with blood proteins and self-aggregation due to exposed hydrophobic surfaces. Here we report the design of a class of cationic, helical homo-polypeptide antimicrobials with a hydrophobic internal helical core and a charged exterior shell, possessing unprecedented radial amphiphilicity. The radially amphiphilic structure enables the polypeptide to bind effectively to the negatively charged bacterial surface and exhibit high antimicrobial activity against both gram-positive and gram-negative bacteria.

Machine learning of single molecule free energy surfaces and the impact of chemistry and environment upon structure and dynamics.

The conformational states explored by polymers and proteins can be controlled by environmental conditions (e.g., temperature, pressure, and solvent) and molecular chemistry (e.