Designing proteins: Mimicking natural protein sequence heterogeneity.

This study presents an enhanced protein design algorithm that aims to emulate natural heterogeneity of protein sequences. Initial analysis revealed that natural proteins exhibit a permutation composition lower than the theoretical maximum, suggesting a selective utilization of the 20-letter amino acid alphabet. By not constraining the amino acid composition of the protein sequence but instead allowing random reshuffling of the composition, the resulting design algorithm generates sequences that maintain lower permutation compositions in equilibrium, aligning closely with natural proteins.

Machine learning in biological physics: From biomolecular prediction to design.

Machine learning has been proposed as an alternative to theoretical modeling when dealing with complex problems in biological physics. However, in this perspective, we argue that a more successful approach is a proper combination of these two methodologies. We discuss how ideas coming from physical modeling neuronal processing led to early formulations of computational neural networks, e.

Unraveling the Nano-Bio Interface Interactions of a Lipase Adsorbed on Gold Nanoparticles under Laser Excitation.

The complex nature and structure of biomolecules and nanoparticles and their interactions make it challenging to achieve a deeper understanding of the dynamics at the nano-bio interface of enzymes and plasmonic nanoparticles subjected to light excitation. In this study, circular dichroism (CD) and Raman spectroscopic experiments and molecular dynamics (MD) simulations were used to investigate the potential changes at the nano-bio interface upon plasmonic excitation. Our data showed that photothermal and thermal heating induced distinct changes in the secondary structure of a model nanobioconjugate composed of lipase fromfraction B (CALB) and gold nanoparticles (AuNPs).

Correction to "Targeting the Spike: Repurposing Mithramycin and Dihydroergotamine to Block SARS-CoV-2 Infection".

[This corrects the article DOI: 10.1021/acsomega.3c02921.

Assessment of the MARTINI 3 Performance for Short Peptide Self-Assembly.

The coarse-grained MARTINI force field, initially developed for membranes, has proven to be an exceptional tool for investigating supramolecular peptide assemblies. Over the years, the force field underwent refinements to enhance accuracy, enabling, for example, the reproduction of protein-ligand interactions and constant pH behavior. However, these protein-focused improvements seem to have compromised its ability to model short peptide self-assembly.

Targeting the Spike: Repurposing Mithramycin and Dihydroergotamine to Block SARS-CoV-2 Infection.

The urgency to find complementary therapies to current SARS-CoV-2 vaccines, whose effectiveness is preserved over time and not compromised by the emergence of new and emerging variants, has become a critical health challenge. We investigate the possibility of jamming the opening of the Receptor Binding Domain (RBD) of the spike protein of SARS-CoV-2 with small compounds. Through in silico screening, we identified two potential candidates that would lock the Receptor Binding Domain (RBD) in a closed configuration, preventing the virus from infecting the host cells.

Bioinspired Polyethylene Glycol Coatings for Reduced Nanoparticle-Protein Interactions.

Nanoparticles (NPs) and other engineered nanomaterials have great potential as nanodrugs or nanomedical devices for biomedical applications. However, the adsorption of proteins in blood circulation or similar physiological fluids can significantly alter the surface properties and therapeutic response induced by most nanomaterials. For example, interaction with proteins can change the bloodstream circulation time and availability of therapeutic NPs or hinder the accumulation in their desired target organs.

Ultrasensitive detection of SARS-CoV-2 spike protein by graphene field-effect transistors.

COVID-19, caused by the severe acute respiratory syndrome-coronavirus 2 (SARS-CoV-2), originated a global health crisis, causing over 2 million casualties and altering human daily life all over the world. This pandemic emergency revealed the limitations of current diagnostic tests, highlighting the urgency to develop faster, more precise and sensitive sensors. Graphene field effect transistors (GFET) are analytical platforms that enclose all these requirements.

Insights into Hepatitis C Virus E2 Interactions with Human Cellular Receptor CD81 at Different pHs from Molecular Simulations.

Hepatitis C virus (HCV) is the second viral agent that causes the majority of chronic hepatic infections worldwide, following Hepatitis B virus (HBV) infection. HCV infection comprises several steps, from the attachment to the receptors to the delivery of the viral genetic material and replication inside the cells. Tetraspanin CD81 is a key entry factor for HCV as it accompanies the virus during attachment and internalization through clathrin-mediated endocytosis.

Key aspects of the past 30 years of protein design.

Proteins are the workhorse of life. They are the building infrastructure of living systems; they are the most efficient molecular machines known, and their enzymatic activity is still unmatched in versatility by any artificial system. Perhaps proteins' most remarkable feature is their modularity.

Grafting density induced reentrant disorder-order-disorder transition in planar di-block copolymer brushes.

By means of multiscale molecular simulation, we show that solvophilic-solvophobic AB diblock copolymer brushes in the semi-dilute regime present a re-entrant disorder/order/disorder transition. The latter is fully controllable through two parameters: the grafting density and the solvophobic to solvophilic ratio of the tethered macromolecules. Upon increasing density, chains first aggregate into patches, then further order into a crystalline phase and finally melt into a disordered phase.

H-Bonding-mediated binding and charge reorganization of proteins on gold nanoparticles.

Once introduced into the human body, nanoparticles often interact with blood proteins, which in turn undergo structural changes upon adsorption. Although protein corona formation is a widely studied phenomenon, the structure of proteins adsorbed on nanoparticles is far less understood. We propose a model to describe the interaction between human serum albumin (HSA) and nanoparticles (NPs) with arbitrary coatings.

Identification of Protein Functional Regions.

Protein sequence stores the information relative to both functionality and stability, thus making it difficult to disentangle the two contributions. However, the identification of critical residues for function and stability has important implications for the mapping of the proteome interactions, as well as for many pharmaceutical applications, e. g.

In Silico Evidence That Protein Unfolding is a Precursor of Protein Aggregation.

We present a computational study on the folding and aggregation of proteins in an aqueous environment, as a function of its concentration. We show how the increase of the concentration of individual protein species can induce a partial unfolding of the native conformation without the occurrence of aggregates. A further increment of the protein concentration results in the complete loss of the folded structures and induces the formation of protein aggregates.

Proteins are Solitary! Pathways of Protein Folding and Aggregation in Protein Mixtures.

We present a computational and experimental study on the folding and aggregation in solutions of multiple protein mixtures at different concentrations. We show how in protein mixtures each component is capable of maintaining its folded state at densities greater than the one at which they would precipitate in single-species solutions. We demonstrate the generality of our observation over many different proteins using computer simulations capable of fully characterizing the cross-aggregation phase diagram of all the mixtures.

Limiting the valence: advancements and new perspectives on patchy colloids, soft functionalized nanoparticles and biomolecules.

Limited bonding valence, usually accompanied by well-defined directional interactions and selective bonding mechanisms, is nowadays considered among the key ingredients to create complex structures with tailored properties: even though isotropically interacting units already guarantee access to a vast range of functional materials, anisotropic interactions can provide extra instructions to steer the assembly of specific architectures. The anisotropy of effective interactions gives rise to a wealth of self-assembled structures both in the realm of suitably synthesized nano- and micro-sized building blocks and in nature, where the isotropy of interactions is often a zero-th order description of the complicated reality. In this review, we span a vast range of systems characterized by limited bonding valence, from patchy colloids of new generation to polymer-based functionalized nanoparticles, DNA-based systems and proteins, and describe how the interaction patterns of the single building blocks can be designed to tailor the properties of the target final structures.

The role of directional interactions in the designability of generalized heteropolymers.

Heteropolymers are important examples of self-assembling systems. However, in the design of artificial heteropolymers the control over the single chain self-assembling properties does not reach that of the natural bio-polymers, and in particular proteins. Here, we introduce a sufficiency criterion to identify polymers that can be designed to adopt a predetermined structure and show that it is fulfilled by polymers made of monomers interacting through directional (anisotropic) interactions.

Computational protein design: a review.

Proteins are one of the most versatile modular assembling systems in nature. Experimentally, more than 110 000 protein structures have been identified and more are deposited every day in the Protein Data Bank. Such an enormous structural variety is to a first approximation controlled by the sequence of amino acids along the peptide chain of each protein.

Transferable coarse-grained potential for de novo protein folding and design.

Protein folding and design are major biophysical problems, the solution of which would lead to important applications especially in medicine. Here we provide evidence of how a novel parametrization of the Caterpillar model may be used for both quantitative protein design and folding. With computer simulations it is shown that, for a large set of real protein structures, the model produces designed sequences with similar physical properties to the corresponding natural occurring sequences.

Sequence controlled self-knotting colloidal patchy polymers.

Knotted chains are a promising class of polymers with many applications for materials science and drug delivery. Here we introduce an experimentally realizable model for the design of chains with controllable topological properties. Recently, we have developed a systematic methodology to construct self-assembling chains of simple particles, with final structures fully controlled by the sequence of particles along the chain.