Expanding the HP1a-binding consensus and molecular grammar for heterochromatin assembly.

The recruitment of Heterochromatin Protein 1 (HP1) partners is essential for heterochromatin assembly and function, yet our knowledge regarding their organization in heterochromatin remains limited. Here we show that interactors engage the Drosophila HP1 (HP1a) dimer through a degenerate and expanded form of the previously identified PxVxL motif, which we now term HP1a Access Codes (HACs). These HACs reside in disordered regions, possess high conservation among Drosophila homologs, and contain alternating hydrophobic residues nested in a cluster of positively charged amino acids.

Small molecule modulation of protein corona for deep plasma proteome profiling.

The protein corona formed on nanoparticles (NPs) has potential as a valuable diagnostic tool for improving plasma proteome coverage. Here, we show that spiking small molecules, including metabolites, lipids, vitamins, and nutrients into plasma can induce diverse protein corona patterns on otherwise identical NPs, significantly enhancing the depth of plasma proteome profiling. The protein coronas on polystyrene NPs when exposed to plasma treated with an array of small molecules allows for the detection of 1793 proteins marking an 8.

Regulating transport efficiency through the nuclear pore complex: The role of binding affinity with FG-Nups.

Macromolecules are transported through the nuclear pore complex (NPC) via a series of transient binding and unbinding events with FG-Nups, which are intrinsically disordered proteins anchored to the pore's inner wall. Prior studies suggest that the weak and transient nature of this binding is crucial for maintaining the transported molecules' diffusivity. In this study, we explored the relationship between binding kinetics and transport efficiency using Brownian dynamics simulations.

Bacterial community dynamics as a result of growth-yield trade-off and multispecies metabolic interactions toward understanding the gut biofilm niche.

Bacterial communities are ubiquitous, found in natural ecosystems, such as soil, and within living organisms, like the human microbiome. The dynamics of these communities in diverse environments depend on factors such as spatial features of the microbial niche, biochemical kinetics, and interactions among bacteria. Moreover, in many systems, bacterial communities are influenced by multiple physical mechanisms, such as mass transport and detachment forces.

A Suite of Foundation Models Captures the Contextual Interplay Between Codons.

In the canonical genetic code, many amino acids are assigned more than one codon. Work by us and others has shown that the choice of these synonymous codon is not random, and carries regulatory and functional consequences. Existing protein foundation models ignore this context-dependent role of coding sequence in shaping the protein landscape of the cell.

Metabolic interactions shape emergent biofilm structures in a conceptual model of gut mucosal bacterial communities.

The gut microbiome plays a major role in human health; however, little is known about the structural arrangement of microbes and factors governing their distribution. In this work, we present an in silico agent-based model (ABM) to conceptually simulate the dynamics of gut mucosal bacterial communities. We explored how various types of metabolic interactions, including competition, neutralism, commensalism, and mutualism, affect community structure, through nutrient consumption and metabolite exchange.

Deciphering the intrinsically disordered characteristics of the FG-Nups through the lens of polymer physics.

The nuclear pore complex (NPC) is a critical gateway regulating molecular transport between the nucleus and cytoplasm. It allows small molecules to pass freely, while larger molecules require nuclear transport receptors to traverse the barrier. This selective permeability is maintained by phenylalanine-glycine-rich nucleoporins (FG-Nups), intrinsically disordered proteins that fill the NPC's central channel.

Fine-tuning protein embeddings for functional similarity evaluation.

Motivation: Proteins with unknown function are frequently compared to better characterized relatives, either using sequence similarity, or recently through similarity in a learned embedding space. Through comparison, protein sequence embeddings allow for interpretable and accurate annotation of proteins, as well as for downstream tasks such as clustering for unsupervised discovery of protein families. However, it is unclear whether embeddings can be deliberately designed to improve their use in these downstream tasks.

HGTDR: Advancing drug repurposing with heterogeneous graph transformers.

Motivation: Drug repurposing is a viable solution for reducing the time and cost associated with drug development. However, thus far, the proposed drug repurposing approaches still need to meet expectations. Therefore, it is crucial to offer a systematic approach for drug repurposing to achieve cost savings and enhance human lives.

Integrin mechanosensing relies on a pivot-clip mechanism to reinforce cell adhesion.

Cells intricately sense mechanical forces from their surroundings, driving biophysical and biochemical activities. This mechanosensing phenomenon occurs at the cell-matrix interface, where mechanical forces resulting from cellular motion, such as migration or matrix stretching, are exchanged through surface receptors, primarily integrins, and their corresponding matrix ligands. A pivotal player in this interaction is the αβ integrin and fibronectin (FN) bond, known for its role in establishing cell adhesion sites for migration.

Deep Plasma Proteome Profiling by Modulating Single Nanoparticle Protein Corona with Small Molecules.

The protein corona, a dynamic biomolecular layer that forms on nanoparticle (NP) surfaces upon exposure to biological fluids is emerging as a valuable diagnostic tool for improving plasma proteome coverage analyzed by liquid chromatography-mass spectrometry (LC-MS/MS). Here, we show that spiking small molecules, including metabolites, lipids, vitamins, and nutrients (namely, glucose, triglyceride, diglycerol, phosphatidylcholine, phosphatidylethanolamine, L-α-phosphatidylinositol, inosine 5'-monophosphate, and B complex), into plasma can induce diverse protein corona patterns on otherwise identical NPs, significantly enhancing the depth of plasma proteome profiling. The protein coronas on polystyrene NPs when exposed to plasma treated with an array of small molecules (n=10) allowed for detection of 1793 proteins marking an 8.

Deep Learning for Perfusion Cerebral Blood Flow (CBF) and Volume (CBV) Predictions and Diagnostics.

Dynamic susceptibility contrast magnetic resonance perfusion (DSC-MRP) is a non-invasive imaging technique for hemodynamic measurements. Various perfusion parameters, such as cerebral blood volume (CBV) and cerebral blood flow (CBF), can be derived from DSC-MRP, hence this non-invasive imaging protocol is widely used clinically for the diagnosis and assessment of intracranial pathologies. Currently, most institutions use commercially available software to compute the perfusion parametric maps.

Exploring the performance and explainability of fine-tuned BERT models for neuroradiology protocol assignment.

Background: Deep learning has demonstrated significant advancements across various domains. However, its implementation in specialized areas, such as medical settings, remains approached with caution. In these high-stake environments, understanding the model's decision-making process is critical.

Antimicrobial peptide interactions with bacterial cell membranes.

Antimicrobial peptides (AMPs) are potential alternatives for common antibiotics because of their greater activity and efficiency against a broad range of viruses, bacteria, fungi, and parasites. In this project, two antimicrobial peptides including magainin 2 and protegrin 1 with α-helix and β-sheet secondary structures were selected to investigate their interactions with different lipid bilayers such as 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphocholine (POPC), 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphoserine (POPS), 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphoglycerol (POPG), and 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphoethanolamine (POPE), POPC/POPG (7:3), POPC/POPS (7:3), POPG/POPE(1:3), and POPG/POPE(3:1). The obtained structures of the AMPs illustrated that protegrin 1 cannot maintain its secondary structure in the solution phase in contrast to magainin 2.

The Effectiveness of Integrated Group Therapy on Prolonged Grief Disorder of Bereaved People from COVID-19 Randomized Controlled Trial.

This study aimed to evaluate the integrated cognitive-behavioral group therapy and Gestalt empty chair technique on bereaved individuals with COVID-19-caused PGD (prolonged grief disease). Thirty-six patients with PGD resultant from COVID-19 were randomly assigned intervention and control groups. The intervention group underwent 16 90-minute integrated group therapy sessions twice a week.

Force transmission and SUN-KASH higher-order assembly in the LINC complex models.

The linkers of the nucleoskeleton and cytoskeleton (LINC) complex comprises Sad-1 and UNC-84 (SUN) and Klarsicht, ANC-1, SYNE homology (KASH) domain proteins, whose conserved interactions provide a physical coupling between the cytoskeleton and the nucleoskeleton, thereby mediating the transfer of physical forces across the nuclear envelope. The LINC complex can perform distinct cellular functions by pairing various KASH domain proteins with the same SUN domain protein. Recent studies have suggested a higher-order assembly of SUN and KASH instead of a more widely accepted linear trimer model for the LINC complex.

Mercapto-pyrimidines are reversible covalent inhibitors of the papain-like protease (PLpro) and inhibit SARS-CoV-2 (SCoV-2) replication.

The papain-like protease (PLpro) plays a critical role in SARS-CoV-2 (SCoV-2) pathogenesis and is essential for viral replication and for allowing the virus to evade the host immune response. Inhibitors of PLpro have great therapeutic potential, however, developing them has been challenging due to PLpro's restricted substrate binding pocket. In this report, we screened a 115 000-compound library for PLpro inhibitors and identified a new pharmacophore, based on a mercapto-pyrimidine fragment that is a reversible covalent inhibitor (RCI) of PLpro and inhibits viral replication in cells.

On the interactions of peptides with gold nanoparticles: effects of sequence and size.

Peptide-based self-assembly and synthesis techniques have emerged as a viable approach to designing active and stable inorganic nanostructures in aqueous media. In the present study, we use all-atom molecular dynamic (MD) simulations to study the interactions of ten short peptides (namely A3, AgBP1, AgBP2, AuBP1, AuBP2, GBP1, Midas2, Pd4, Z1, and Z2) with different gold nanoparticles (of different diameters ranging from 2 to 8 nm). Our MD simulation results imply that the gold nanoparticles have a remarkable effect on the stability and conformational properties of peptides.

A covalent inhibitor targeting the papain-like protease from SARS-CoV-2 inhibits viral replication.

Covalent inhibitors of the papain-like protease (PLpro) from SARS-CoV-2 have great potential as antivirals, but their non-specific reactivity with thiols has limited their development. In this report, we performed an 8000 molecule electrophile screen against PLpro and identified an α-chloro amide fragment, termed compound 1, which inhibited SARS-CoV-2 replication in cells, and also had low non-specific reactivity with thiols. Compound 1 covalently reacts with the active site cysteine of PLpro, and had an IC50 of 18 μM for PLpro inhibition.

Adsorption Process of Various Antimicrobial Peptides on Different Surfaces of Cellulose.

Current antimicrobial challenges in hospitals, pharmaceutical production units, and food packaging have motivated the development of antimicrobial agents, among them the antimicrobial compounds based on cellulose and peptides. Herein, we develop molecular dynamics (MD) models to dissect and characterize the adsorption process of antimicrobial peptides (AMPs) such as protegrin 1, magainin 2, and cyclic indolicidin on various surfaces of cellulose including [-1-10], [1-10], [-100], [100], [-110], and [110]. Our results suggest that the magainin 2 antimicrobial peptide loses most of its initial helix form, spreads on the cellulose surface, and makes the most rigid structure with [110] surface.

Smartphone-assisted lab-in-a-tube device using gold nanocluster-based aptasensor for detection of MUC1-overexpressed tumor cells.

Developing smartphone technology for point-of-care diagnosis is one of the current favorable trends in the field of biosensors. In fact, using smartphones can provide better accessibility and facility for rapid diagnosis of diseases. On the other hand, the detection of circulating tumor cells (CTCs) is one of the recent methods for the early diagnosis of cancer.

Gut-on-a-chip models for dissecting the gut microbiology and physiology.

Microfluidic technologies have been extensively investigated in recent years for developing organ-on-a-chip-devices as robust models aiming to recapitulate organ 3D topography and its physicochemical cues. Among these attempts, an important research front has focused on simulating the physiology of the gut, an organ with a distinct cellular composition featuring a plethora of microbial and human cells that mutually mediate critical body functions. This research has led to innovative approaches to model fluid flow, mechanical forces, and oxygen gradients, which are all important developmental cues of the gut physiological system.

GO Bench: shared hub for universal benchmarking of machine learning-based protein functional annotations.

Motivation: Gene annotation is the problem of mapping proteins to their functions represented as Gene Ontology (GO) terms, typically inferred based on the primary sequences. Gene annotation is a multi-label multi-class classification problem, which has generated growing interest for its uses in the characterization of millions of proteins with unknown functions. However, there is no standard GO dataset used for benchmarking the newly developed new machine learning models within the bioinformatics community.

On the Sensitivity and Affinity of Gold, Silver, and Platinum Surfaces against the SARS-CoV-2 Virus: A Comparative Computational Study.

The novel coronavirus disease and its complications have motivated the design of new sensors with the highest sensitivity, and affinity for the detection of the SARS-CoV-2 virus is considered in many research studies. In this research article, we employ full atomistic molecular dynamics (MD) models to study the interactions between the receptor binding domain (RBD) and spike protein of the coronavirus and different metals such as gold (Au), platinum (Pt), and silver (Ag) to analyze their sensitivity against this virus. The comparison between the RBD interactions with ACE2 (angiotensin-converting enzyme 2) and different metals indicates that metals have remarkable effects on the structural features and dynamical properties of the RBD.

On the potentials of sialic acid derivatives as inhibitors for the mumps virus: A molecular dynamics and quantum chemistry investigation.

Mumps virus is an infectious pathogen causing major health problems for humans such as encephalitis, orchitis, and parotitis. Therefore, designing an inhibitor for this virus is of great medical and public health importance. With this goal in mind, we investigate the affinity of different sialic acid-based compounds (ligands) against the hemagglutinin-neuraminidase (HN) protein of the mumps virus, using a combination of molecular dynamics (MD) simulations and quantum chemistry calculations.