Protein-Protein and Protein-Peptide Docking with ClusPro Server

In silico study to explore the mechanism of Toxoplasma-induced inflammation and target therapy based on sero and salivary Toxoplasma

We aimed to assess salivary and seroprevalence of Toxoplasma immunoglobulins in risky populations and evaluate drug docking targeting TgERP. A cross-sectional study was conducted in Alexandria University hospitals' outpatient clinics. 192 participants were enrolled from September 2022 to November 2023. Anti-Toxoplasma IgG and IgM were determined in serum and saliva by ELISA. An in-Silico study examined TgERP's protein-protein interactions (PPIs) with pro-inflammatory cytokine receptors, anti-inflammatory cytokine, cell cycle progression regulatory proteins, a proliferation marker, and nuclear envelope integrity-related protein Lamin B1. Our findings revealed that anti-T. gondii IgG were detected in serum (66.1%) and saliva (54.7%), with 2.1% of both samples were positive for IgM. Salivary IgG had 75.59% sensitivity, 86.15% specificity, 91.40% PPV, 64.40% NPP, 79.17% accuracy and fair agreement with serum IgG. On the other hand, the sensitivity, specificity, PPV, NPV, and accuracy in detecting salivary IgM were 75.0%, 99.47%, 75.0%, 99.47%, and 98.96%. AUC 0.859 indicates good discriminatory power. Examined synthetic drugs and natural products can target specific amino acids residues of TgERP that lie at the same binding interface with LB1 and Ki67, subsequently, hindering their interaction. Hence, salivary samples can be a promising diagnostic approach. The studied drugs can counteract the pro-inflammatory action of TgERP.

Exploring the viability of Zeatin as a prospective therapeutic candidate for investigating the complex interplay between severe acute respiratory syndrome coronavirus (SARS-CoV) and Alzheimer's disease

The present research aims to explore the intricate link between SARS-CoV infection and susceptibility to Alzheimer's disease, focusing on the role of APOE4, a genetic factor associated with both conditions. Our research aims to uncover shared molecular pathways, considering APOE4's impact on lipid metabolism, immune responses, and neuroinflammation relevant to COVID-19 and AD. The Chyawanprash phytocompounds were subjected to in-silico ADMET profiling and Zeatin a neuroprotective cytokinin emerged as a promising regulator of the ACE2-SPIKE complex as it exhibits favourable pharmacological attributes, presenting as a non-substrate for Permeability glycoprotein, low Protein Binding Percentage, and distinctive toxicity endpoints. Therapeutic candidate. Zeatin's robust binding disrupts the intricate APOE4-ACE2-SPIKE interplay (AAS), offering a potential therapeutic avenue that is further corroborated by Molecular dynamic simulation as the system remained stable without any major fluctuation throughout the 100ns simulation. The AAS binding free energy, determined as -124.849 +/- 15.513 KJ/mol using MMPBSA assay, reveals significant contributions to complex stability from amino acids including, GLN41: 1.211 kcal/mol, GLU340: 1.188 kcal/mol, ALA344: 1.198 kcal/mol, while ARG38: 2.011 kcal/mol establishes pivotal strong bonds integral to the interaction between AAS and Zeatin. Rigorous cytotoxicity assessments reveal Zeatin's safety profile, highlighting its inhibitory effect on LN18 cell viability that sharply decreases to 32.47% at 200 µg/ml, underscoring its modulatory impact on cellular metabolism. These findings enhance our understanding of the convergent mechanisms linking SARS-CoV and AD, providing valuable insights for potential therapeutic interventions. Further research is warranted to elucidate the specific pathways and molecular mechanisms through which zeatin exerts its protective effects.

A PTP1B-Cdk3 Signaling Axis Promotes Cell Cycle Progression of Human Glioblastoma Cells through an Rb-E2F Dependent Pathway

PTP1B plays a key role in developing different types of cancer. However, the molecular mechanism underlying this effect is unclear. To identify molecular targets of PTP1B that mediate its role in tumorigenesis, we undertook a SILAC-based phosphoproteomic approach, which allowed us to identify Cdk3 as a novel PTP1B substrate. Substrate trapping experiments and docking studies revealed stable interactions between the PTP1B catalytic domain and Cdk3. In addition, we observed that PTP1B dephosphorylates Cdk3 at tyrosine residue 15 in vitro and interacts with it in human glioblastoma cells. Next, we found that pharmacological inhibition of PTP1B or its depletion with siRNA leads to cell cycle arrest with diminished activity of Cdk3, hypophosphorylation of Rb, and the downregulation of E2F target genes Cdk1, Cyclin A, and Cyclin E1. Finally, we observed that the expression of a constitutively active Cdk3 mutant bypasses the requirement of PTP1B for cell cycle progression and expression of E2F target genes. These data delineate a novel signaling pathway from PTP1B to Cdk3 required for efficient cell cycle progression in an Rb-E2F dependent manner in human GB cells.

Riding the wave of innovation: immunoinformatics in fish disease control

The spread of infectious illnesses has been a significant factor restricting aquaculture production. To maximise aquatic animal health, vaccination tactics are very successful and cost-efficient for protecting fish and aquaculture animals against many disease pathogens. However, due to the increasing number of immunological cases and their complexity, it is impossible to manage, analyse, visualise, and interpret such data without the assistance of advanced computational techniques. Hence, the use of immunoinformatics tools is crucial, as they not only facilitate the management of massive amounts of data but also greatly contribute to the creation of fresh hypotheses regarding immune responses. In recent years, advances in biotechnology and immunoinformatics have opened up new research avenues for generating novel vaccines and enhancing existing vaccinations against outbreaks of infectious illnesses, thereby reducing aquaculture losses. This review focuses on understanding in silico epitope-based vaccine design, the creation of multi-epitope vaccines, the molecular interaction of immunogenic vaccines, and the application of immunoinformatics in fish disease based on the frequency of their application and reliable results. It is believed that it can bridge the gap between experimental and computational approaches and reduce the need for experimental research, so that only wet laboratory testing integrated with in silico techniques may yield highly promising results and be useful for the development of vaccines for fish.

In-silico modeling of the interplay between APOE4, NLRP3, and ACE2-SPIKE complex in neurodegeneration between Alzheimer and SARS-CoV: implications for understanding pathogenesis and developing therapeutic strategies

The multifaceted interplay between neurodegenerative pathologies, including Alzheimer's disease (AD), and the highly virulent severe acute respiratory syndrome coronavirus (SARS-CoV), is implicated in various conditions. AD and SARS-CoV pathogenesis involve the APOE4 allele, NLRP3 inflammasome, and ACE2-SPIKE complex. APOE4, a genetic polymorphism of the APOE gene, is associated with an increased susceptibility to AD. NLRP3, an inflammatory protein of the innate immune system, plays a pivotal role in immune response cascades. In SARS-CoV, the ACE2 receptor serves as the principal portal for cellular entry, while APOE4 intricately interacts with the ACE2-spike protein complex, enhancing viral internalization process. The interaction of NLRP3 with the ACE2-spike protein complex leads to increased inflammatory signaling. The convergence of APOE4/NLRP3 and ACE2-spike protein complex interactions suggests a possible link between SARS and AD. Therefore, the current research centralizes the association between by utilizing SARS-CoV datasets to explore possible mechanisms that account for the pathogenesis of SARS-CoV and AD. The work is further extended to unveil the molecular interactions of APOE4 and NLRP3 with the ACE2-Spike protein complex at the molecular level by employing molecular dynamics simulation techniques. The therapeutic efficacy of Chyawanprash nutraceuticals is evaluated as their inhibitory potential towards APOE4-ACE2-Spike protein and NLRP3-ACE2-Spike protein complexes. Notably, our simulations unequivocally demonstrate the robust and enduring binding capability of the compound Phyllantidine with the target complexes throughout the simulation period. The findings of the studies further corroborate the primary hypothesis of APOE4 and NLRP3 as driver factors in the pathogenesis of both SARS-CoV and AD. Therefore, this research establishes a paradigm for comprehending the complex interaction between AD and SARS-CoV and lays the groundwork for further study in this domain.Communicated by Ramaswamy H. Sarma.

Molecular docking in organic, inorganic, and hybrid systems: a tutorial review

Molecular docking simulation is a very popular and well-established computational approach and has been extensively used to understand molecular interactions between a natural organic molecule (ideally taken as a receptor) such as an enzyme, protein, DNA, RNA and a natural or synthetic organic/inorganic molecule (considered as a ligand). But the implementation of docking ideas to synthetic organic, inorganic, or hybrid systems is very limited with respect to their use as a receptor despite their huge popularity in different experimental systems. In this context, molecular docking can be an efficient computational tool for understanding the role of intermolecular interactions in hybrid systems that can help in designing materials on mesoscale for different applications. The current review focuses on the implementation of the docking method in organic, inorganic, and hybrid systems along with examples from different case studies. We describe different resources, including databases and tools required in the docking study and applications. The concept of docking techniques, types of docking models, and the role of different intermolecular interactions involved in the docking process to understand the binding mechanisms are explained. Finally, the challenges and limitations of dockings are also discussed in this review.

Graphical abstract

Bacterial Lectin FimH and Its Aggregation Hot-Spots: An Alternative Strategy against Uropathogenic Escherichia coli

Type I fimbriae are the main adhesive organelles of uropathogenic Escherichia coli (UPEC), consisting of four different subunits. Their component with the most important role in establishing bacterial infections is the FimH adhesin located at the fimbrial tip. This two-domain protein mediates adhesion to host epithelial cells through interaction with terminal mannoses on epithelial glycoproteins. Here, we propose that the amyloidogenic potential of FimH can be exploited for the development of therapeutic agents against Urinary Tract Infections (UTIs). Aggregation-prone regions (APRs) were identified via computational methods, and peptide-analogues corresponding to FimH lectin domain APRs were chemically synthesized and studied with the aid of both biophysical experimental techniques and molecular dynamic simulations. Our findings indicate that these peptide-analogues offer a promising set of antimicrobial candidate molecules since they can either interfere with the folding process of FimH or compete for the mannose-binding pocket.

Structure based Drug Designing Approaches in SARS-CoV-2 Spike Inhibitor Design

The COVID-19 outbreak and the pandemic situation have hastened the research community to design a novel drug and vaccine against its causative organism, the SARS-CoV-2. The spike glycoprotein present on the surface of this pathogenic organism plays an immense role in viral entry and antigenicity. Hence, it is considered an important drug target in COVID-19 drug design. Several three-dimensional crystal structures of this SARS-CoV-2 spike protein have been identified and deposited in the Protein DataBank during the pandemic period. This accelerated the research in computer- aided drug designing, especially in the field of structure-based drug designing. This review summarizes various structure-based drug design approaches applied to this SARS-CoV-2 spike protein and its findings. Specifically, it is focused on different structure-based approaches such as molecular docking, high-throughput virtual screening, molecular dynamics simulation, drug repurposing, and target-based pharmacophore modelling and screening. These structural approaches have been applied to different ligands and datasets such as FDA-approved drugs, small molecular chemical compounds, chemical libraries, chemical databases, structural analogs, and natural compounds, which resulted in the prediction of spike inhibitors, spike-ACE-2 interface inhibitors, and allosteric inhibitors.

NINJ2 deficiency inhibits preadipocyte differentiation and promotes insulin resistance through regulating insulin signaling

OBJECTIVE

Genetic variants in ninjurin-2 (NINJ2; nerve injury-induced protein 2) confer risk of ischemic strokes and coronary artery disease as well as endothelial activation and inflammation. However, little is known about NINJ2's in vivo functions and underlying mechanisms.

METHODS

The phenotypes of NINJ2 knockout mice were analyzed, and mechanisms of NINJ2 that regulate body weight, insulin resistance, and glucose homeostasis and lipogenesis were investigated in vivo and in vitro.

RESULTS

This study found that mice lacking NINJ2 showed impaired adipogenesis, increased insulin resistance, and abnormal glucose homeostasis, all of which are risk factors for strokes and coronary artery disease. Mechanistically, NINJ2 directly interacts with insulin receptor/insulin-like growth factor 1 receptor (INSR/IGF1R), and NINJ2 knockdown can block insulin-induced mitotic clonal expansion during preadipocyte differentiation by inhibiting protein kinase B/extracellular signal-regulated kinase (AKT/ERK) signaling and by decreasing the expression of key adipocyte transcriptional regulators CCAAT/enhancer-binding protein β (C/EBP-β), C/EBP-α, and peroxisome proliferator-activated receptor γ (PPAR-γ). Furthermore, the interaction between NINJ2 and INSR/IGF1R is needed for maintaining insulin sensitivity in adipocytes and muscle via AKT and glucose transporter type 4. Notably, adenovirus-mediated NINJ2 overexpression can ameliorate diet-induced insulin resistance in mice.

CONCLUSIONS

In conclusion, these findings reveal NINJ2 as an important new facilitator of insulin receptors, and the authors propose a unique regulatory mechanism between insulin signaling, adipogenesis, and insulin resistance.

Modeling of Protein Complexes

The recent advances in structural biology, combined with continuously increasing computational capabilities and development of advanced softwares, have drastically simplified the workflow for protein homology modeling. Modeling of individual proteins is nowadays quick and straightforward for a large variety of protein targets, thanks to guided pipelines relying on advanced computational tools and user-friendly interfaces, which have extended and promoted the use of modeling also to scientists not focusing on molecular structures of proteins. Nevertheless, construction of models of multi-protein complexes remains quite challenging for the non-experts, often due to the usage of specific procedures depending on the system under investigation and the need for experimental validation approaches to strengthen the generated output.In this chapter, we provide a brief overview of the approaches enabling generation of multi-protein complex models starting from homology models of individual protein components. Using real-life examples, we include two examples to guide the reader in the generation of homomeric and heteromeric protein models.

ADGRL3 genomic variation implicated in neurogenesis and ADHD links functional effects to the incretin polypeptide GIP

Attention deficit/hyperactivity disorder (ADHD) is the most common childhood neurodevelopmental disorder. Single nucleotide polymorphisms (SNPs) in the Adhesion G Protein-Coupled Receptor L3 (ADGRL3) gene are associated with increased susceptibility to developing ADHD worldwide. However, the effect of ADGRL3 non-synonymous SNPs (nsSNPs) on the ADGRL3 protein function is vastly unknown. Using several bioinformatics tools to evaluate the impact of mutations, we found that nsSNPs rs35106420, rs61747658, and rs734644, previously reported to be associated and in linkage with ADHD in disparate populations from the world over, are predicted as pathogenic variants. Docking analysis of rs35106420, harbored in the ADGLR3-hormone receptor domain (HRM, a common extracellular domain of the secretin-like GPCRs family), showed that HRM interacts with the Glucose-dependent insulinotropic polypeptide (GIP), part of the incretin hormones family. GIP has been linked to the pathogenesis of diabetes mellitus, and our analyses suggest a potential link to ADHD. Overall, the comprehensive application of bioinformatics tools showed that functional mutations in the ADGLR3 gene disrupt the standard and wild ADGRL3 structure, most likely affecting its metabolic regulation. Further in vitro experiments are granted to evaluate these in silico predictions of the ADGRL3-GIP interaction and dissect the complexity underlying the development of ADHD.

The AIRE G228W mutation disturbs the interaction of AIRE with its partner molecule SIRT1

The autoimmune regulator (AIRE) protein functions as a tetramer, interacting with partner proteins to form the “AIRE complex,” which relieves RNA Pol II stalling in the chromatin of medullary thymic epithelial cells (mTECs). AIRE is the primary mTEC transcriptional controller, promoting the expression of a large set of peripheral tissue antigen genes implicated in the negative selection of self-reactive thymocytes. Under normal conditions, the SIRT1 protein temporarily interacts with AIRE and deacetylates K residues of the AIRE SAND domain. Once the AIRE SAND domain is deacetylated, the binding with SIRT1 is undone, allowing the AIRE complex to proceed downstream with the RNA Pol II to the elongation phase of transcription. Considering that the in silico and in vitro binding of the AIRE SAND domain with SIRT1 provides a powerful model system for studying the dominant SAND G228W mutation mechanism, which causes the autoimmune polyglandular syndrome-1, we integrated computational molecular modeling, docking, dynamics between the whole SAND domain with SIRT1, and surface plasmon resonance using a peptide harboring the 211 to 230 residues of the SAND domain, to compare the structure and energetics of binding/release between AIRE G228 (wild-type) and W228 (mutant) SAND domain to SIRT1. We observed that the G228W mutation in the SAND domain negatively influences the AIRE-SIRT1 interaction. The disturbed interaction might cause a disruption in the binding of the AIRE SAND domain with the SIRT1 catalytic site, impairing the AIRE complex to proceed downstream with RNA Pol II.

Protein-protein interaction networks as miners of biological discovery

Protein-protein interactions (PPIs) form the basis of a myriad of biological pathways and mechanism, such as the formation of protein-complexes or the components of signaling cascades. Here, we reviewed experimental methods for identifying PPI pairs, including yeast two-hybrid, mass spectrometry, co-localization, and co-immunoprecipitation. Furthermore, a range of computational methods leveraging biochemical properties, evolution history, protein structures and more have enabled identification of additional PPIs. Given the wealth of known PPIs, we reviewed important network methods to construct and analyze networks of PPIs. These methods aid biological discovery through identifying hub genes and dynamic changes in the network, and have been thoroughly applied in various fields of biological research. Lastly, we discussed the challenges and future direction of research utilizing the power of PPI networks. This article is protected by copyright. All rights reserved.

Investigation of Plant Antimicrobial Peptides against Selected Pathogenic Bacterial Species Using a Peptide-Protein Docking Approach

Antimicrobial resistance is the key threat to global health due to high morbidity and mortality. The alteration of bacterial proteins, enzymatic degradation, and change of membrane permeability towards antimicrobial agents are the key mechanisms of antimicrobial resistance. Based on the current condition, there is an urgent clinical need to develop new drugs to treat these bacterial infections. In the current study, the binding patterns of selected antimicrobial peptides (AMPs) with different multidrug-resistant bacterial strains have been analyzed. Among ten selected AMPs in this study, napin and snakin-1 exhibited the best scores and binding patterns. Napin exhibited strong interactions with penicillin-binding protein 1a of Acinetobacter baumannii (with a binding score of -158.7 kcal/mol and ten hydrogen bonds), with glucose-1-phosphate thymidylyltransferase of Mycobacterium tuberculosis H37Rv (with a binding score of -107.8 kcal/mol and twelve hydrogen bonds), and with streptomycin 3^″-adenylyltransferase protein of Salmonella enterica (with a binding score of -84.2 kcal/mol and four hydrogen bonds). Similarly, snakin-1 showed strong interactions with oxygen-insensitive NADPH nitroreductase of Helicobacter pylori (with a binding score of -105.0 kcal/mol and thirteen hydrogen bonds) and with penicillin-binding protein 2a of methicillin-resistant Staphylococcus aureus (with a binding score of -103.8 kcal/mol and twenty-three hydrogen bonds). The docking results were further validated by molecular dynamics simulations. The results of this computational approach support the evidence of efficiency of these AMPs as potent inhibitors of these specific proteins of bacterial strains. However, further validations are required to fully evaluate the potential of selected AMPs as drug candidates against these resistant bacterial strains.

Identification of novel inhibitors targeting TIRAP interactions with BTK and PKCδ in inflammation through an in silico approach

Advanced computational tools focusing on protein-protein interaction (PPI) based drug development is a powerful platform to accelerate the therapeutic development of small lead molecules and repurposed drugs. Toll/interleukin-1 receptor (TIR) domain-containing adapter protein (TIRAP) and its interactions with other proteins in macrophages signalling are crucial components of severe or persistent inflammation. TIRAP activation through Bruton's tyrosine kinase (BTK) and Protein Kinase C delta (PKCδ) is essential for downstream inflammatory signalling. We created homology-based structural models of BTK and PKCδ in MODELLER 9.24. TIRAP interactions with BTK and PKCδ in its non-phosphorylated and phosphorylated states were determined by multiple docking tools including HADDOCK 2.4, pyDockWEB and ClusPro 2.0. Food and Drug Administration (FDA)-approved drugs were virtually screened through Discovery Studio LibDock and Autodock Vina tools to target the common TIR domain residues of TIRAP, which interact with both BTK and PKC at the identified interfacial sites of the complexes. Four FDA-approved drugs were identified and found to have stable interactions over a range of 100 ns MD simulation timescales. These drugs block the interactions of both kinases with TIRAP in silico. Hence, these drugs have the potential to dampen downstream inflammatory signalling and inflammation-mediated disease.

p21-Activated Kinase 1 Promotes Breast Tumorigenesis via Phosphorylation and Activation of the Calcium/Calmodulin-Dependent Protein Kinase II

p21-Activated kinase-1 (Pak1) is frequently overexpressed and/or amplified in human breast cancer and is necessary for transformation of mammary epithelial cells. Here, we show that Pak1 interacts with and phosphorylates the Calcium/Calmodulin-dependent Protein Kinase II (CaMKII), and that pharmacological inhibition or depletion of Pak1 leads to diminished activity of CaMKII. We found a strong correlation between Pak1 and CaMKII expression in human breast cancer samples, and combined inhibition of Pak1 and CaMKII with small-molecule inhibitors was synergistic and induced apoptosis more potently in Her2 positive and triple negative breast cancer (TNBC) cells. Co-adminstration of Pak and CaMKII small-molecule inhibitors resulted in a dramatic reduction of proliferation and an increase in apoptosis in a 3D cell culture setting, as well as an impairment in migration and invasion of TNBC cells. Finally, mice bearing xenografts of TNBC cells showed a significant delay in tumor growth when treated with small-molecule inhibitors of Pak and CaMKII. These data delineate a signaling pathway from Pak1 to CaMKII that is required for efficient proliferation, migration and invasion of mammary epithelial cells, and suggest new therapeutic strategies in breast cancer.

A Model for the Signal Initiation Complex Between Arrestin-3 and the Src Family Kinase Fgr

Arrestins regulate a wide range of signaling events, most notably when bound to active G protein-coupled receptors (GPCRs). Among the known effectors recruited by GPCR-bound arrestins are Src family kinases, which regulate cellular growth and proliferation. Here, we focus on arrestin-3 interactions with Fgr kinase, a member of the Src family. Previous reports demonstrated that Fgr exhibits high constitutive activity, but can be further activated by both arrestin-dependent and arrestin-independent pathways. We report that arrestin-3 modulates Fgr activity with a hallmark bell-shaped concentration-dependence, consistent with a role as a signaling scaffold. We further demonstrate using NMR spectroscopy that a polyproline motif within arrestin-3 interacts directly with the SH3 domain of Fgr. To provide a framework for this interaction, we determined the crystal structure of the Fgr SH3 domain at 1.9 Å resolution and developed a model for the GPCR-arrestin-3-Fgr complex that is supported by mutagenesis. This model suggests that Fgr interacts with arrestin-3 at multiple sites and is consistent with the locations of disease-associated Fgr mutations. Collectively, these studies provide a structural framework for arrestin-dependent activation of Fgr.

Understanding COVID-19 Pathogenesis: A Drug-Repurposing Effort to Disrupt Nsp-1 Binding to Export Machinery Receptor Complex

Non-structural protein 1 (Nsp1) is a virulence factor found in all beta coronaviruses (b-CoVs). Recent studies have shown that Nsp1 of SARS-CoV-2 virus interacts with the nuclear export receptor complex, which includes nuclear RNA export factor 1 (NXF1) and nuclear transport factor 2-like export factor 1 (NXT1). The NXF1-NXT1 complex plays a crucial role in the transport of host messenger RNA (mRNA). Nsp1 interferes with the proper binding of NXF1 to mRNA export adaptors and its docking to the nuclear pore complex. We propose that drugs targeting the binding surface between Nsp1 and NXF1-NXT1 may be a useful strategy to restore host antiviral gene expression. Exploring this strategy forms the main goals of this paper. Crystal structures of Nsp1 and the heterodimer of NXF1-NXT1 have been determined. We modeled the docking of Nsp1 to the NXF1-NXT1 complex, and discovered repurposed drugs that may interfere with this binding. To our knowledge, this is the first attempt at drug-repurposing of this complex. We used structural analysis to screen 1993 FDA-approved drugs for docking to the NXF1-NXT1 complex. The top hit was ganirelix, with a docking score of -14.49. Ganirelix competitively antagonizes the gonadotropin releasing hormone receptor (GNRHR) on pituitary gonadotrophs, and induces rapid, reversible suppression of gonadotropin secretion. The conformations of Nsp1 and GNRHR make it unlikely that they interact with each other. Additional drug leads were inferred from the structural analysis of this complex, which are discussed in the paper. These drugs offer several options for therapeutically blocking Nsp1 binding to NFX1-NXT1, which may normalize nuclear export in COVID-19 infection.

Protein oligomer modeling guided by predicted interchain contacts in CASP14

For CASP14, we developed deep learning‐based methods for predicting homo‐oligomeric and hetero‐oligomeric contacts and used them for oligomer modeling. To build structure models, we developed an oligomer structure generation method that utilizes predicted interchain contacts to guide iterative restrained minimization from random backbone structures. We supplemented this gradient‐based fold‐and‐dock method with template‐based and ab initio docking approaches using deep learning‐based subunit predictions on 29 assembly targets. These methods produced oligomer models with summed Z‐scores 5.5 units higher than the next best group, with the fold‐and‐dock method having the best relative performance. Over the eight targets for which this method was used, the best of the five submitted models had average oligomer TM‐score of 0.71 (average oligomer TM‐score of the next best group: 0.64), and explicit modeling of inter‐subunit interactions improved modeling of six out of 40 individual domains (ΔGDT‐TS > 2.0).

Neuropilin-1 assists SARS-CoV-2 infection by stimulating the separation of Spike protein S1 and S2

The cell surface receptor Neuropilin-1 (Nrp1) was recently identified as a host factor for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) entry. The Spike protein of SARS-CoV-2 is cleaved into two segments, the S1 (residues (res.) 1-685) and the S2 (res. 686-1273) domains by furin protease. Nrp1 predominantly binds to the C-terminal RRAR amino acid motif (res. 682-685) of the S1 domain. In this study, we firstly modeled the association of an Nrp1 protein (consisting of domains a2-b1-b2) with the Spike protein. Next, we studied the separation of S2 from the S1 domain, with and without Nrp1 bound, by utilizing molecular dynamics pulling simulations. During the separation, Nrp1 stabilizes the S1 C-terminal region (res. 640-685) and thereby assists the detachment of S2 N-terminal region (res. 686-700). Without Nrp1 bound, S1 tends to become stretched, whereas the bound Nrp1 stimulates an earlier separation of S2 from the S1 domain. The liberated S2 domain is known to mediate the fusion of virus and host membranes; thus, Nrp1 likely increases virus infectivity by facilitating the S1 and S2 separation. We further analyzed the possible topological structure of the SARS-CoV-2 Spike protein when bound with Nrp1 and angiotensin-converting enzyme 2 (ACE2). Understanding of such an Nrp1-assisted viral infection opens the gate for the generation of protein-protein inhibitors, such as antibodies, which could attenuate the infection mechanism and protect certain cells in a future Nrp1-ACE2 targeted combination therapy.

Protein Interaction Network Biology in Neuroscience

Mapping the intricate networks of cellular proteins in the human brain has the potential to address unsolved questions in molecular neuroscience, including the molecular basis of cognition, synaptic plasticity, long-term potentiation, learning, and memory. Perturbations to the protein-protein interaction networks (PPIN) present in neurons, glia, and other cell-types have been linked to multifactorial neurological disorders. Yet while knowledge of brain PPINs is steadily improving, the complexity and dynamic nature of the heterogeneous central nervous system in normal and disease contexts poses a formidable experimental challenge. In this review, the recent applications of functional proteomics and systems biology approaches to study PPINs central to normal neuronal function, during neurodevelopment, and in neurodegenerative disorders are summarized. How systematic PPIN analysis offers a unique mechanistic framework to explore intra- and inter-cellular functional modules governing neuronal activity and brain function is also discussed. Finally, future technological advancements needed to address outstanding questions facing neuroscience are outlined.

Neuropilin-1 Assists SARS-CoV-2 Infection by Stimulating the Separation of Spike Protein Domains S1 and S2

The cell surface receptor Neuropilin-1 (Nrp1) was recently identified as a host factor for SARS-CoV-2 entry. As the Spike protein of SARS-CoV-2 is cleaved into the S1 and the S2 domain by furin protease, Nrp1 binds to the newly created C-terminal RRAR amino acid sequence of the S1 domain. In this study, we model the association of a Nrp1 (a2-b1-b2) protein with the Spike protein computationally and analyze the topological constraints in the SARS-CoV-2 Spike protein for binding with Nrp1 and ACE2. Importantly, we study the exit mechanism of S2 from the S1 domain with the assistance of ACE2 as well as Nrp1 by molecular dynamics pulling simulations. In the presence of Nrp1, by binding the S1 more strongly to the host membrane, there is a high probability of S2 being pulled out, rather than S1 being stretched. Thus, Nrp1 binding could stimulate the exit of S2 from the S1 domain, which will likely increase virus infectivity as the liberated S2 domain mediates the fusion of virus and host membranes. Understanding of such a Nrp1-assisted viral infection opens the gate for the generation of protein-protein inhibitors, such as antibodies, which could attenuate the infection mechanism and protect certain cells in a future combination therapy.

Guardians of the Cell: State-of-the-Art of Membrane Proteins from a Computational Point-of-View

Membrane proteins (MPs) encompass a large family of proteins with distinct cellular functions, and although representing over 50% of existing pharmaceutical drug targets, their structural and functional information is still very scarce. Over the last years, in silico analysis and algorithm development were essential to characterize MPs and overcome some limitations of experimental approaches. The optimization and improvement of these methods remain an ongoing process, with key advances in MPs' structure, folding, and interface prediction being continuously tackled. Herein, we discuss the latest trends in computational methods toward a deeper understanding of the atomistic and mechanistic details of MPs.