GalaxyTongDock: Symmetric and asymmetric ab initio protein-protein docking web server with improved energy parameters

Structural insights into rapamycin-induced oligomerization of a FRB-FKBP fusion protein

Inducible dimerization systems, such as rapamycin-induced dimerization of FK506 binding protein (FKBP) and FKBP-rapamycin binding (FRB) domain, are widely employed chemical biology tools to manipulate cellular functions. We previously advanced an inducible dimerization system into an inducible oligomerization system by developing a bivalent fusion protein, FRB-FKBP, which forms large oligomers upon rapamycin addition and can be used to manipulate cells. However, the oligomeric structure of FRB-FKBP remains unclear. Here, we report that FRB-FKBP forms a rotationally symmetric trimer in crystals, but a larger oligomer in solution, primarily tetramers and pentamers, which maintain similar inter-subunit contacts as in the crystal trimer. These findings expand the applications of the FRB-FKBP oligomerization system in diverse biological events.

Review and Comparative Analysis of Methods and Advancements in Predicting Protein Complex Structure

Protein complexes perform diverse biological functions, and obtaining their three-dimensional structure is critical to understanding and grasping their functions. In many cases, it's not just two proteins interacting to form a dimer; instead, multiple proteins interact to form a multimer. Experimentally resolving protein complex structures can be quite challenging. Recently, there have been efforts and methods that build upon prior predictions of dimer structures to attempt to predict multimer structures. However, in comparison to monomeric protein structure prediction, the accuracy of protein complex structure prediction remains relatively low. This paper provides an overview of recent advancements in efficient computational models for predicting protein complex structures. We introduce protein-protein docking methods in detail and summarize their main ideas, applicable modes, and related information. To enhance prediction accuracy, other critical protein-related information is also integrated, such as predicting interchain residue contact, utilizing experimental data like cryo-EM experiments, and considering protein interactions and non-interactions. In addition, we comprehensively review computational approaches for end-to-end prediction of protein complex structures based on artificial intelligence (AI) technology and describe commonly used datasets and representative evaluation metrics in protein complexes. Finally, we analyze the formidable challenges faced in current protein complex structure prediction tasks, including the structure prediction of heteromeric complex, disordered regions in complex, antibody-antigen complex, and RNA-related complex, as well as the evaluation metrics for complex assessment. We hope that this work will provide comprehensive knowledge of complex structure predictions to contribute to future advanced predictions.

Investigating D-Amino Acid Oxidase Expression and Interaction Network Analyses in Pathways Associated With Cellular Stress: Implications in the Biology of Aging

D-amino acid oxidase (DAO) is a flavoenzyme that metabolizes D-amino acids by oxidative deamination, producing hydrogen peroxide (H2O2) as a by-product. The generation of intracellular H2O2 may alter the redox-homeostasis mechanism of cells and increase the oxidative stress levels in tissues, associated with the pathogenesis of age-related diseases and organ decline. This study investigates the effect of DAO knockdown using clustered regularly interspaced short palindromic repeats (CRISPR) through an in silico approach on its protein-protein interactions (PPIs) and their potential roles in the process of aging. The target sequence and guide RNA of DAO were designed using the CCTop database, PPI analysis using the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) database, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses, Reactome biological pathway, protein docking using GalaxyTongDock database, and structure analysis. The translated target sequence of DAO lies between amino acids 43 to 50. The 10 proteins that were predicted to interact with DAO are involved in peroxisome pathways such as acyl-coenzyme A oxidase 1 (ACOX1), alanine-glyoxylate and serine-pyruvate aminotransferase (AGXT), catalase (CAT), carnitine O-acetyltransferase (CRAT), glyceronephosphate O-acyltransferase (GNPAT), hydroxyacid oxidase 1 (HAO1), hydroxyacid oxidase 2 (HAO2), trans-L-3-hydroxyproline dehydratase (L3HYPDH), polyamine oxidase (PAOX), and pipecolic acid and sarcosine oxidase (PIPOX). In summary, DAO mutation would most likely reduce activity with its interacting proteins that generate H2O2. However, DAO mutation may result in peroxisomal disorders, and thus, alternative techniques should be considered for an in vivo approach.

Multi-omic analysis characterizes molecular susceptibility of receptors to SARS-CoV-2 spike protein

In the post COVID-19 era, new SARS-CoV-2 variant strains may continue emerging and long COVID is poised to be another public health challenge. Deciphering the molecular susceptibility of receptors to SARS-CoV-2 spike protein is critical for understanding the immune responses in COVID-19 and the rationale of multi-organ injuries. Currently, such systematic exploration remains limited. Here, we conduct multi-omic analysis of protein binding affinities, transcriptomic expressions, and single-cell atlases to characterize the molecular susceptibility of receptors to SARS-CoV-2 spike protein. Initial affinity analysis explains the domination of delta and omicron variants and demonstrates the strongest affinities between BSG (CD147) receptor and most variants. Further transcriptomic data analysis on 4100 experimental samples and single-cell atlases of 1.4 million cells suggest the potential involvement of BSG in multi-organ injuries and long COVID, and explain the high prevalence of COVID-19 in elders as well as the different risks for patients with underlying diseases. Correlation analysis validated moderate associations between BSG and viral RNA abundance in multiple cell types. Moreover, similar patterns were observed in primates and validated in proteomic expressions. Overall, our findings implicate important therapeutic targets for the development of receptor-specific vaccines and drugs for COVID-19.

A morpheein equilibrium regulates catalysis in phosphoserine phosphatase SerB2 from Mycobacterium tuberculosis

Mycobacterium tuberculosis phosphoserine phosphatase MtSerB2 is of interest as a new antituberculosis target due to its essential metabolic role in L-serine biosynthesis and effector functions in infected cells. Previous works indicated that MtSerB2 is regulated through an oligomeric transition induced by L-Ser that could serve as a basis for the design of selective allosteric inhibitors. However, the mechanism underlying this transition remains highly elusive due to the lack of experimental structural data. Here we describe a structural, biophysical, and enzymological characterisation of MtSerB2 oligomerisation in the presence and absence of L-Ser. We show that MtSerB2 coexists in dimeric, trimeric, and tetrameric forms of different activity levels interconverting through a conformationally flexible monomeric state, which is not observed in two near-identical mycobacterial orthologs. This morpheein behaviour exhibited by MtSerB2 lays the foundation for future allosteric drug discovery and provides a starting point to the understanding of its peculiar multifunctional moonlighting properties.

Immunoinformatics for Novel Multi-Epitope Vaccine Development in Canine Parvovirus Infections

Canine parvovirus (CPV-2) is one of the most important pathogens of dogs of all ages, causing pandemic infections that are characterized by fatal hemorrhagic enteritis. The CPV-2 vaccine is recommended as a core vaccine for pet animals. Despite the intensive practice of active immunization, CPV-2 remains a global threat. In this study, a multi-epitope vaccine against CPV-2 was designed, targeting the highly conserved capsid protein (VP2) via in silico approaches. Several immunoinformatics methods, such as epitope screening, molecular docking, and simulation were used to design a potential vaccine construct. The partial protein sequences of the VP2 gene of CPV-2 and protein sequences retrieved from the NCBI were screened to predict highly antigenic proteins through antigenicity, trans-membrane-topology screening, an allergenicity assessment, and a toxicity analysis. Homologous VP2 protein sequences typically linked to the disease were identified using NCBI BLAST, in which four conserved regions were preferred. Overall, 10 epitopes, DPIGGKTGI, KEFDTDLKP, GTDPDDVQ, GGTNFGYIG, GTFYFDCKP, NRALGLPP, SGTPTN, LGLPPFLNSL, IGGKTG, and VPPVYPN, were selected from the conserved regions to design the vaccine construct. The molecular docking demonstrated the higher binding affinity of these epitopes with dog leukocyte antigen (DLA) molecules. The selected epitopes were linked with Salmonella enterica flagellin FliC adjuvants, along with the PADRE sequence, by GGS linkers to construct a vaccine candidate with 272 nucleotides. The codon adaptation and in silico cloning showed that the generated vaccine can be expressed by the E. coli strain, K12, and the sequence of the vaccine construct showed no similarities with dog protein. Our results suggest that the vaccine construct might be useful in preventing canine parvoviral enteritis (CPE) in dogs. Further in vitro and in vivo experiments are needed for the validation of the vaccine candidate.

ECPAS/Ecm29-mediated 26S proteasome disassembly is an adaptive response to glucose starvation

The 26S proteasome comprises 20S catalytic and 19S regulatory complexes. Approximately half of the proteasomes in cells exist as free 20S complexes; however, our mechanistic understanding of what determines the ratio of 26S to 20S species remains incomplete. Here, we show that glucose starvation uncouples 26S holoenzymes into 20S and 19S subcomplexes. Subcomplex affinity purification and quantitative mass spectrometry reveal that Ecm29 proteasome adaptor and scaffold (ECPAS) mediates this structural remodeling. The loss of ECPAS abrogates 26S dissociation, reducing degradation of 20S proteasome substrates, including puromycylated polypeptides. In silico modeling suggests that ECPAS conformational changes commence the disassembly process. ECPAS is also essential for endoplasmic reticulum stress response and cell survival during glucose starvation. In vivo xenograft model analysis reveals elevated 20S proteasome levels in glucose-deprived tumors. Our results demonstrate that the 20S-19S disassembly is a mechanism adapting global proteolysis to physiological needs and countering proteotoxic stress.

Fast and versatile sequence-independent protein docking for nanomaterials design using RPXDock

Computationally designed multi-subunit assemblies have shown considerable promise for a variety of applications, including a new generation of potent vaccines. One of the major routes to such materials is rigid body sequence-independent docking of cyclic oligomers into architectures with point group or lattice symmetries. Current methods for docking and designing such assemblies are tailored to specific classes of symmetry and are difficult to modify for novel applications. Here we describe RPXDock, a fast, flexible, and modular software package for sequence-independent rigid-body protein docking across a wide range of symmetric architectures that is easily customizable for further development. RPXDock uses an efficient hierarchical search and a residue-pair transform (RPX) scoring method to rapidly search through multidimensional docking space. We describe the structure of the software, provide practical guidelines for its use, and describe the available functionalities including a variety of score functions and filtering tools that can be used to guide and refine docking results towards desired configurations.

Quantitative comparison of protein-protein interaction interface using physicochemical feature-based descriptors of surface patches

Driving mechanisms of many biological functions in a cell include physical interactions of proteins. As protein-protein interactions (PPIs) are also important in disease development, protein-protein interactions are highlighted in the pharmaceutical industry as possible therapeutic targets in recent years. To understand the variety of protein-protein interactions in a proteome, it is essential to establish a method that can identify similarity and dissimilarity between protein-protein interactions for inferring the binding of similar molecules, including drugs and other proteins. In this study, we developed a novel method, protein-protein interaction-Surfer, which compares and quantifies similarity of local surface regions of protein-protein interactions. protein-protein interaction-Surfer represents a protein-protein interaction surface with overlapping surface patches, each of which is described with a three-dimensional Zernike descriptor (3DZD), a compact mathematical representation of 3D function. 3DZD captures both the 3D shape and physicochemical properties of the protein surface. The performance of protein-protein interaction-Surfer was benchmarked on datasets of protein-protein interactions, where we were able to show that protein-protein interaction-Surfer finds similar potential drug binding regions that do not share sequence and structure similarity. protein-protein interaction-Surfer is available at https://kiharalab.org/ppi-surfer.

The formation of HuR/YB1 complex is required for the stabilization of target mRNA to promote myogenesis

mRNA stability is the mechanism by which cells protect transcripts allowing their expression to execute various functions that affect cell metabolism and fate. It is well-established that RNA binding proteins (RBPs) such as HuR use their ability to stabilize mRNA targets to modulate vital processes such as muscle fiber formation (myogenesis). However, the machinery and the mechanisms regulating mRNA stabilization are still elusive. Here, we identified Y-Box binding protein 1 (YB1) as an indispensable HuR binding partner for mRNA stabilization and promotion of myogenesis. Both HuR and YB1 bind to 409 common mRNA targets, 147 of which contain a U-rich consensus motif in their 3' untranslated region (3'UTR) that can also be found in mRNA targets in other cell systems. YB1 and HuR form a heterodimer that associates with the U-rich consensus motif to stabilize key promyogenic mRNAs. The formation of this complex involves a small domain in HuR (227-234) that if mutated prevents HuR from reestablishing myogenesis in siHuR-treated muscle cells. Together our data uncover that YB1 is a key player in HuR-mediated stabilization of pro-myogenic mRNAs and provide the first indication that the mRNA stability mechanism is as complex as other key cellular processes such as mRNA decay and translation.

Identification of a peptide ligand for human ALDH3A1 through peptide phage display: Prediction and characterization of protein interaction sites and inhibition of ALDH3A1 enzymatic activity

Aldehyde dehydrogenase 3A1 (ALDH3A1) by oxidizing medium chain aldehydes to their corresponding carboxylic acids, is involved in the detoxification of toxic byproducts and is considered to play an important role in antioxidant cellular defense. ALDH3A1 has been implicated in various other functions such as cell proliferation, cell cycle regulation, and DNA damage response. Recently, it has been identified as a putative biomarker of prostate, gastric, and lung cancer stem cell phenotype. Although ALDH3A1 has multifaceted functions in both normal and cancer homeostasis, its modes of action are currently unknown. To this end, we utilized a random 12-mer peptide phage display library to identify efficiently human ALDH3A1-interacting peptides. One prevailing peptide (P1) was systematically demonstrated to interact with the protein of interest, which was further validated in vitro by peptide ELISA. Bioinformatic analysis indicated two putative P1 binding sites on the protein surface implying biomedical potential and potent inhibitory activity of the P1 peptide on hALDH3A1 activity was demonstrated by enzymatic studies. Furthermore, in search of potential hALDH3A1 interacting players, a BLASTp search demonstrated that no protein in the database includes the full-length amino acid sequence of P1, but identified a list of proteins containing parts of the P1 sequence, which may prove potential hALDH3A1 interacting partners. Among them, Protein Kinase C Binding Protein 1 and General Transcription Factor II-I are candidates of high interest due to their cellular localization and function. To conclude, this study identifies a novel peptide with potential biomedical applications and further suggests a list of protein candidates be explored as possible hALDH3A1-interacting partners in future studies.

Staphylococcus aureus Exfoliative Toxin E, Oligomeric State and Flip of P186: Implications for Its Action Mechanism

Staphylococcal exfoliative toxins (ETs) are glutamyl endopeptidases that specifically cleave the Glu381-Gly382 bond in the ectodomains of desmoglein 1 (Dsg1) via complex action mechanisms. To date, four ETs have been identified in different Staphylococcus aureus strains and ETE is the most recently characterized. The unusual properties of ETs have been attributed to a unique structural feature, i.e., the 180° flip of the carbonyl oxygen (O) of the nonconserved residue 192/186 (ETA/ETE numbering), not conducive to the oxyanion hole formation. We report the crystal structure of ETE determined at 1.61 Å resolution, in which P186(O) adopts two conformations displaying a 180° rotation. This finding, together with free energy calculations, supports the existence of a dynamic transition between the conformations under the tested conditions. Moreover, enzymatic assays showed no significant differences in the esterolytic efficiency of ETE and ETE/P186G, a mutant predicted to possess a functional oxyanion hole, thus downplaying the influence of the flip on the activity. Finally, we observed the formation of ETE homodimers in solution and the predicted homodimeric structure revealed the participation of a characteristic nonconserved loop in the interface and the partial occlusion of the protein active site, suggesting that monomerization is required for enzymatic activity.

Antimicrobial Activity of Cathelicidin-Derived Peptide from the Iberian Mole Talpa occidentalis

The immune systems of all vertebrates contain cathelicidins, a family of antimicrobial peptides. Cathelicidins are a type of innate immune effector that have a number of biological functions, including a well-known direct antibacterial action and immunomodulatory function. In search of new templates for antimicrobial peptide discovery, we have identified and characterized the cathelicidin of the small mammal Talpa occidentalis. We describe the heterogeneity of cathelicidin in the order Eulipotyphla in relation to the Iberian mole and predict its antibacterial activity using bioinformatics tools. In an effort to correlate these findings, we derived the putative active peptide and performed in vitro hemolysis and antimicrobial activity assays, confirming that Iberian mole cathelicidins are antimicrobial. Our results showed that the Iberian mole putative peptide, named To-KL37 (KLFGKVGNLLQKGWQKIKNIGRRIKDFFRNIRPMQEA) has antibacterial and antifungal activity. Understanding the antimicrobial defense of insectivores may help scientists prevent the spread of pathogens to humans. We hope that this study can also provide new, effective antibacterial peptides for future drug development.

The chemistry of snake venom and its medicinal potential

The fascination and fear of snakes dates back to time immemorial, with the first scientific treatise on snakebite envenoming, the Brooklyn Medical Papyrus, dating from ancient Egypt. Owing to their lethality, snakes have often been associated with images of perfidy, treachery and death. However, snakes did not always have such negative connotations. The curative capacity of venom has been known since antiquity, also making the snake a symbol of pharmacy and medicine. Today, there is renewed interest in pursuing snake-venom-based therapies. This Review focuses on the chemistry of snake venom and the potential for venom to be exploited for medicinal purposes in the development of drugs. The mixture of toxins that constitute snake venom is examined, focusing on the molecular structure, chemical reactivity and target recognition of the most bioactive toxins, from which bioactive drugs might be developed. The design and working mechanisms of snake-venom-derived drugs are illustrated, and the strategies by which toxins are transformed into therapeutics are analysed. Finally, the challenges in realizing the immense curative potential of snake venom are discussed, and chemical strategies by which a plethora of new drugs could be derived from snake venom are proposed.

Dynamic Interactions of Fully Glycosylated SARS-CoV-2 Spike Protein with Various Antibodies

The spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) presents a public health crisis, and the vaccines that can induce highly potent neutralizing antibodies are essential for ending the pandemic. The spike (S) protein on the viral envelope mediates human angiotensin-converting enzyme 2 binding and thus is the target of a variety of neutralizing antibodies. In this work, we built various S trimer-antibody complex structures on the basis of the fully glycosylated S protein models described in our previous work and performed all-atom molecular dynamics simulations to gain insight into the structural dynamics and interactions between S protein and antibodies. Investigation of the residues critical for S-antibody binding allows us to predict the potential influence of mutations in SARS-CoV-2 variants. Comparison of the glycan conformations between S-only and S-antibody systems reveals the roles of glycans in S-antibody binding. In addition, we explored the antibody binding modes and the influences of antibody on the motion of S protein receptor binding domains. Overall, our analyses provide a better understanding of S-antibody interactions, and the simulation-based S-antibody interaction maps could be used to predict the influences of S mutation on S-antibody interactions, which will be useful for the development of vaccine and antibody-based therapy.

Discovery of a transdermally deliverable pentapeptide for activating AdipoR1 to promote hair growth

Alopecia induced by aging or side effects of medications affects millions of people worldwide and impairs the quality of life; however, there is a limit to the current medications. Here, we identify a small transdermally deliverable 5-mer peptide (GLYYF; P5) that activates adiponectin receptor 1 (AdipoR1) and promotes hair growth. P5 sufficiently reproduces the biological effect of adiponectin protein via AMPK signaling pathway, increasing the expression of hair growth factors in the dermal papilla cells of human hair follicle. P5 accelerates hair growth ex vivo and induces anagen hair cycle in mice in vivo. Furthermore, we elucidate a key spot for the binding between AdipoR1 and adiponectin protein using docking simulation and mutagenesis studies. This study suggests that P5 could be used as a topical peptide drug for alleviating pathological conditions, which can be improved by adiponectin protein, such as alopecia.

Wave-wise comparative genomic study for revealing the complete scenario and dynamic nature of COVID-19 pandemic in Bangladesh

As the COVID-19 pandemic continues to ravage across the globe and take millions of lives and like many parts of the world, the second wave of the pandemic hit Bangladesh, this study aimed at understanding its causative agent, SARS-CoV-2 at the genomic and proteomic level and provide precious insights about the pathogenesis, evolution, strengths and weaknesses of the virus. As of Mid-June 2021, over 1500 SARS-CoV-2 genomesequences have been deposited in the GISAID database from Bangladesh which were extracted and categorized into two waves. By analyzing these genome sequences, it was discovered that the wave-2 samples had a significantly greater average rate of mutation/sample (30.79%) than the wave-1 samples (12.32%). Wave-2 samples also had a higher frequency of deletion, and transversion events. During the first wave, the GR clade was the most predominant but it was replaced by the GH clade in the latter wave. The B.1.1.25 variant showed the highest frequency in wave-1 while in case of wave-2, the B.1.351.3 variant, was the most common one. A notable presence of the delta variant, which is currently at the center of concern, was also observed. Comparison of the Spike protein found in the reference and the 3 most common lineages found in Bangladesh namely, B.1.1.7, B.1.351, B.1.617 in terms of their ability to form stable complexes with ACE2 receptor revealed that B.1.617 had the potential to be more transmissible than others. Importantly, no indigenous variants have been detected so far which implies that the successful prevention of import of foreign variants can diminish the outbreak in the country.

Modeling and Structure Determination of Homo-Oligomeric Proteins: An Overview of Challenges and Current Approaches

Protein homo-oligomerization is a very common phenomenon, and approximately half of proteins form homo-oligomeric assemblies composed of identical subunits. The vast majority of such assemblies possess internal symmetry which can be either exploited to help or poses challenges during structure determination. Moreover, aspects of symmetry are critical in the modeling of protein homo-oligomers either by docking or by homology-based approaches. Here, we first provide a brief overview of the nature of protein homo-oligomerization. Next, we describe how the symmetry of homo-oligomers is addressed by crystallographic and non-crystallographic symmetry operations, and how biologically relevant intermolecular interactions can be deciphered from the ordered array of molecules within protein crystals. Additionally, we describe the most important aspects of protein homo-oligomerization in structure determination by NMR. Finally, we give an overview of approaches aimed at modeling homo-oligomers using computational methods that specifically address their internal symmetry and allow the incorporation of other experimental data as spatial restraints to achieve higher model reliability.

Protein oligomer structure prediction using GALAXY in CASP14

Proteins perform their functions by interacting with other biomolecules. For these interactions, proteins often form homo- or hetero-oligomers as well. Thus, oligomer protein structures provide important clues regarding the biological roles of proteins. To this end, computational prediction of oligomer structures may be a useful tool in the absence of experimentally resolved structures. Here, we describe our server and human-expert methods used to predict oligomer structures in the CASP14 experiment. Examples are provided for cases in which manual domain-splitting led to improved oligomeric domain structures by ab initio docking, automated oligomer structure refinement led to improved subunit orientation and terminal structure, and manual oligomer modeling utilizing literature information generated a reasonable oligomer model. We also discussed the results of post-prediction docking calculations with AlphaFold2 monomers as input in comparison to our blind prediction results. Overall, ab initio docking of AlphaFold2 models did not lead to better oligomer structure prediction, which may be attributed to the interfacial structural difference between the AlphaFold2 monomer structures and the crystal oligomer structures. This result poses a next-stage challenge in oligomer structure prediction after the success of AlphaFold2. For successful protein assembly structure prediction, a different approach that exploits further evolutionary information on the interface and/or flexible docking taking the interfacial conformational flexibilities of subunit structures into account is needed.

GalaxyHeteromer: protein heterodimer structure prediction by template-based and ab initio docking

Protein–protein interactions play crucial roles in diverse biological processes, including various disease progressions. Atomistic structural details of protein–protein interactions may provide important information that can facilitate the design of therapeutic agents. GalaxyHeteromer is a freely available automatic web server (http://galaxy.seoklab.org/heteromer) that predicts protein heterodimer complex structures from two subunit protein sequences or structures. When subunit structures are unavailable, they are predicted by template- or distance-prediction-based modelling methods. Heterodimer complex structures can be predicted by both template-based and ab initio docking, depending on the template's availability. Structural templates are detected from the protein structure database based on both the sequence and structure similarities. The templates for heterodimers may be selected from monomer and homo-oligomer structures, as well as from hetero-oligomers, owing to the evolutionary relationships of heterodimers with domains of monomers or subunits of homo-oligomers. In addition, the server employs one of the best ab initio docking methods when heterodimer templates are unavailable. The multiple heterodimer structure models and the associated scores, which are provided by the web server, may be further examined by user to test or develop functional hypotheses or to design new functional molecules.

Dynamic Interactions of Fully Glycosylated SARS-CoV-2 Spike Protein with Various Antibodies

The spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) presents a public health crisis, and the vaccines that can induce highly potent neutralizing antibodies are essential for ending the pandemic. The spike (S) protein on the viral envelope mediates human angiotensin-converting enzyme 2 (ACE2) binding and thus is the target of a variety of neutralizing antibodies. In this work, we built various S trimer-antibody complex structures on the basis of the fully glycosylated S protein models described in our previous work, and performed all-atom molecular dynamics simulations to get insight into the structural dynamics and interactions between S protein and antibodies. Investigation of the residues critical for S-antibody binding allows us to predict the potential influence of mutations in SARS-CoV-2 variants. Comparison of the glycan conformations between S-only and S-antibody systems reveals the roles of glycans in S-antibody binding. In addition, we explored the antibody binding modes, and the influences of antibody on the motion of S protein receptor binding domains. Overall, our analyses provide a better understanding of S-antibody interactions, and the simulation-based S-antibody interaction maps could be used to predict the influences of S mutation on S-antibody interactions, which will be useful for the development of vaccine and antibody-based therapy.

Novel mutations in NSP-1 and PLPro of SARS-CoV-2 NIB-1 genome mount for effective therapeutics

BACKGROUND

Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), the etiologic agent of coronavirus disease 2019 (COVID-19), is rapidly acquiring new mutations. Analysis of these mutations is necessary for gaining knowledge regarding different aspects of therapeutic development. Previously, we have reported a Sanger method-based genome sequence of a viral isolate named SARS-CoV-2 NIB-1, circulating in Bangladesh. The genome has four novel non-synonymous mutations in V121D, V843F, A889V, and G1691C positions.

RESULTS

Using different computational tools, we have found V121D substitution has the potential to destabilize the non-structural protein-1 (NSP-1). NSP-1 inactivates the type-1 interferon-induced antiviral system. Hence, this mutant could be a basis of attenuated vaccines against SARS-CoV-2. V843F, A889V, and G1691C are all located in nonstructural protein-3 (NSP-3). G1691C can decrease the flexibility of the protein. V843F and A889V might change the binding pattern and efficacy of SARS-CoV-2 papain-like protease (PLPro) inhibitor GRL0617. V843F substitution in PLPro was the most prevalent mutation in the clinical samples. This mutation showed a reduced affinity for interferon-stimulated gene-15 protein (ISG-15) and might have an impact on innate immunity and viral spread. However, V843F+A889V double mutant exhibited the same binding affinity as wild type PLPro. A possible reason behind this phenomenon can be that V843F is a conserved residue of PLPro which damaged the protease structure, but A889V, a less conserved residue, presumably neutralized that damage.

CONCLUSIONS

Mutants of NSP-1 could provide attenuated vaccines against coronavirus. Also, these mutations of PLPro might be targeted to develop better anti-SARS therapeutics. We hope our study will help to get better insides during the development of attenuated vaccine and PLPro inhibitors.

Structure, Dynamics, Receptor Binding, and Antibody Binding of the Fully Glycosylated Full-Length SARS-CoV-2 Spike Protein in a Viral Membrane

The spike (S) protein of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) mediates host cell entry by binding to angiotensin-converting enzyme 2 (ACE2) and is considered the major target for drug and vaccine development. We previously built fully glycosylated full-length SARS-CoV-2 S protein models in a viral membrane including both open and closed conformations of the receptor-binding domain (RBD) and different templates for the stalk region. In this work, multiple μs-long all-atom molecular dynamics simulations were performed to provide deeper insights into the structure and dynamics of S protein and glycan functions. Our simulations reveal that the highly flexible stalk is composed of two independent joints and most probable S protein orientations are competent for ACE2 binding. We identify multiple glycans stabilizing the open and/or closed states of the RBD and demonstrate that the exposure of antibody epitopes can be captured by detailed antibody–glycan clash analysis instead of commonly used accessible surface area analysis that tends to overestimate the impact of glycan shielding and neglect possible detailed interactions between glycan and antibodies. Overall, our observations offer structural and dynamic insights into the SARS-CoV-2 S protein and potentialize for guiding the design of effective antiviral therapeutics.

Receptor-like role for PQLC2 amino acid transporter in the lysosomal sensing of cationic amino acids

PQLC2, a lysosomal cationic amino acid transporter, also serves as a sensor that responds to scarcity of its substrates by recruiting a protein complex composed of C9orf72, SMCR8, and WDR41 to the surface of lysosomes. This protein complex controls multiple aspects of lysosome function. Although it is known that this response to changes in cationic amino acid availability depends on an interaction between PQLC2 and WDR41, the underlying mechanism for the regulated interaction is not known. In this study, we present evidence that the WDR41-PQLC2 interaction is mediated by a short peptide motif in a flexible loop that extends from the WDR41 β-propeller and inserts into a cavity presented by the inward-facing conformation of PQLC2. The data support a transceptor model wherein conformational changes in PQLC2 related to substrate transport regulate the availability of the WDR41-binding site on PQLC2 and mediate recruitment of the WDR41-SMCR8-C9orf72 complex to the surface of lysosomes.

Identification of Amino Acid Residues in Human IgM Fc Receptor (FcµR) Critical for IgM Binding

Both non-immune “natural” and antigen-induced “immune” IgM are important for protection against infections and for regulation of immune responses to self-antigens. The roles of its Fc receptor (FcµR) in these IgM effector functions have begun to be explored. In the present study, by taking advantage of the difference in IgM-ligand binding of FcµRs of human (constitutive binding) and mouse (transient binding), we replaced non-conserved amino acid residues of human FcµR with mouse equivalents before establishment of cell lines stably expressing mutant or wild-type (WT) receptors. The resultant eight-different mutant FcµR-bearing cells were compared with WT receptor-bearing cells for cell-surface expression and IgM-binding by flow cytometric assessments using receptor-specific mAbs and IgM paraproteins as ligands. Three sites Asn66, Lys79-Arg83, and Asn109, which are likely in the CDR2, DE loop and CDR3 of the human FcµR Ig-like domain, respectively, were responsible for constitutive IgM binding. Intriguingly, substitution of Glu41 and Met42 in the presumed CDR1 with the corresponding mouse residues Gln and Leu, either single or more prominently in combination, enhanced both the receptor expression and IgM binding. A four-aa stretch of Lys24-Gly27 in the predicted A ß-strand of human FcµR appeared to be essential for maintenance of its proper receptor conformation on plasma membranes because of reduction of both receptor expression and IgM-binding potential when these were mutated. Results from a computational structural modeling analysis were consistent with these mutational data and identified a possible mode of binding of FcµR with IgM involving the loops including Asn66, Arg83 and Asn109 of FcµR interacting principally with the Cµ4 domain including Gln510 and to a lesser extent Cµ3 domain including Glu398, of human IgM. To our knowledge, this is the first experimental report describing the identification of amino acid residues of human FcµR critical for binding to IgM Fc.

Further confirmation of the association of SLC12A2 with non-syndromic autosomal-dominant hearing impairment

Congenital hearing impairment (HI) is genetically heterogeneous making its genetic diagnosis challenging. Investigation of novel HI genes and variants will enhance our understanding of the molecular mechanisms and to aid genetic diagnosis. We performed exome sequencing and analysis using DNA samples from affected members of two large families from Ghana and Pakistan, segregating autosomal-dominant (AD) non-syndromic HI (NSHI). Using in silico approaches, we modeled and evaluated the effect of the likely pathogenic variants on protein structure and function. We identified two likely pathogenic variants in SLC12A2, c.2935G>A:p.(E979K) and c.2939A>T:p.(E980V), which segregate with NSHI in a Ghanaian and Pakistani family, respectively. SLC12A2 encodes an ion transporter crucial in the homeostasis of the inner ear endolymph and has recently been reported to be implicated in syndromic and non-syndromic HI. Both variants were mapped to alternatively spliced exon 21 of the SLC12A2 gene. Exon 21 encodes for 17 residues in the cytoplasmatic tail of SLC12A2, is highly conserved between species, and preferentially expressed in cochlear tissues. A review of previous studies and our current data showed that out of ten families with either AD non-syndromic or syndromic HI, eight (80%) had variants within the 17 amino acid residue region of exon 21 (48 bp), suggesting that this alternate domain is critical to the transporter activity in the inner ear. The genotypic spectrum of SLC12A2 was expanded and the involvement of SLC12A2 in ADNSHI was confirmed. These results also demonstrate the role that SLC12A2 plays in ADNSHI in diverse populations including sub-Saharan Africans.

Developing a Fully Glycosylated Full-Length SARS-CoV-2 Spike Protein Model in a Viral Membrane

This technical study describes all-atom modeling and simulation of a fully glycosylated full-length SARS-CoV-2 spike (S) protein in a viral membrane. First, starting from PDB: 6VSB and 6VXX, full-length S protein structures were modeled using template-based modeling, de-novo protein structure prediction, and loop modeling techniques in GALAXY modeling suite. Then, using the recently determined most occupied glycoforms, 22 N-glycans and 1 O-glycan of each monomer were modeled using Glycan Reader & Modeler in CHARMM-GUI. These fully glycosylated full-length S protein model structures were assessed and further refined against the low-resolution data in their respective experimental maps using ISOLDE. We then used CHARMM-GUI Membrane Builder to place the S proteins in a viral membrane and performed all-atom molecular dynamics simulations. All structures are available in CHARMM-GUI COVID-19 Archive (http://www.charmm-gui.org/docs/archive/covid19) so that researchers can use these models to carry out innovative and novel modeling and simulation research for the prevention and treatment of COVID-19.

Refinement of pairwise potentials via logistic regression to score protein-protein interactions

Protein-protein interactions (PPIs) are ubiquitous and functionally of great importance in biological systems. Hence, the accurate prediction of PPIs by protein-protein docking and scoring tools is highly desirable in order to characterize their structure and biological function. Ab initio docking protocols are divided into the sampling of docking poses to produce at least one near-native structure, and then to evaluate the vast candidate structures by scoring. Concurrent development in both sampling and scoring is crucial for the deployment of protein-protein docking software. In the present work, we apply a machine learning model on pairwise potentials to refine the task of protein quaternary structure native structure detection among decoys. A decoy set was featurized using the Knowledge and Empirical Combined Scoring Algorithm 2 (KECSA2) pairwise potential. The highly unbalanced decoy set was then balanced using a comparison concept between native and decoy structures. The resultant comparison descriptors were used to train a logistic regression (LR) classifier. The LR model yielded the optimal performance for native detection among decoys compared with conventional scoring functions, while exhibiting lesser performance for the detection of low root mean square deviation decoy structures. Its deployment on an independent benchmark set confirms that the scoring function performs competitively relative to other scoring functions. The scripts used are available at https://github.com/TanemuraKiyoto/PPI-native-detection-via-LR.

Developing a Fully-glycosylated Full-length SARS-CoV-2 Spike Protein Model in a Viral Membrane

This technical study describes all-atom modeling and simulation of a fully-glycosylated full-length SARS-CoV-2 spike (S) protein in a viral membrane. First, starting from PDB:6VSB and 6VXX, full-length S protein structures were modeled using template-based modeling, de-novo protein structure prediction, and loop modeling techniques in GALAXY modeling suite. Then, using the recently-determined most occupied glycoforms, 22 N-glycans and 1 O-glycan of each monomer were modeled using Glycan Reader & Modeler in CHARMM-GUI. These fully-glycosylated full-length S protein model structures were assessed and further refined against the low-resolution data in their respective experimental maps using ISOLDE. We then used CHARMM-GUI Membrane Builder to place the S proteins in a viral membrane and performed all-atom molecular dynamics simulations. All structures are available in CHARMM-GUI COVID-19 Archive (http://www.charmm-gui.org/docs/archive/covid19), so researchers can use these models to carry out innovative and novel modeling and simulation research for the prevention and treatment of COVID-19.

Structure prediction of biological assemblies using GALAXY in CAPRI rounds 38-45

We participated in CARPI rounds 38-45 both as a server predictor and a human predictor. These CAPRI rounds provided excellent opportunities for testing prediction methods for three classes of protein interactions, that is, protein-protein, protein-peptide, and protein-oligosaccharide interactions. Both template-based methods (GalaxyTBM for monomer protein, GalaxyHomomer for homo-oligomer protein, GalaxyPepDock for protein-peptide complex) and ab initio docking methods (GalaxyTongDock and GalaxyPPDock for protein oligomer, GalaxyPepDock-ab-initio for protein-peptide complex, GalaxyDock2 and Galaxy7TM for protein-oligosaccharide complex) have been tested. Template-based methods depend heavily on the availability of proper templates and template-target similarity, and template-target difference is responsible for inaccuracy of template-based models. Inaccurate template-based models could be improved by our structure refinement and loop modeling methods based on physics-based energy optimization (GalaxyRefineComplex and GalaxyLoop) for several CAPRI targets. Current ab initio docking methods require accurate protein structures as input. Small conformational changes from input structure could be accounted for by our docking methods, producing one of the best models for several CAPRI targets. However, predicting large conformational changes involving protein backbone is still challenging, and full exploration of physics-based methods for such problems is still to come.

Performance and enhancement of the LZerD protein assembly pipeline in CAPRI 38-46

We report the performance of the protein docking prediction pipeline of our group and the results for Critical Assessment of Prediction of Interactions (CAPRI) rounds 38-46. The pipeline integrates programs developed in our group as well as other existing scoring functions. The core of the pipeline is the LZerD protein-protein docking algorithm. If templates of the target complex are not found in PDB, the first step of our docking prediction pipeline is to run LZerD for a query protein pair. Meanwhile, in the case of human group prediction, we survey the literature to find information that can guide the modeling, such as protein-protein interface information. In addition to any literature information and binding residue prediction, generated docking decoys were selected by a rank aggregation of statistical scoring functions. The top 10 decoys were relaxed by a short molecular dynamics simulation before submission to remove atom clashes and improve side-chain conformations. In these CAPRI rounds, our group, particularly the LZerD server, showed robust performance. On the other hand, there are failed cases where some other groups were successful. To understand weaknesses of our pipeline, we analyzed sources of errors for failed targets. Since we noted that structure refinement is a step that needs improvement, we newly performed a comparative study of several refinement approaches. Finally, we show several examples that illustrate successful and unsuccessful cases by our group.

Prediction of protein oligomer structures using GALAXY in CASP13

Many proteins need to form oligomers to be functional, so oligomer structures provide important clues to biological roles of proteins. Prediction of oligomer structures therefore can be a useful tool in the absence of experimentally resolved structures. In this article, we describe the server and human methods that we used to predict oligomer structures in the CASP13 experiment. Performances of the methods on the 42 CASP13 oligomer targets consisting of 30 homo-oligomers and 12 hetero-oligomers are discussed. Our server method, Seok-assembly, generated models with interface contact similarity measure greater than 0.2 as model 1 for 11 homo-oligomer targets when proper templates existed in the database. Model refinement methods such as loop modeling and molecular dynamics (MD)-based overall refinement failed to improve model qualities when target proteins have domains not covered by templates or when chains have very small interfaces. In human predictions, additional experimental data such as low-resolution electron microscopy (EM) map were utilized. EM data could assist oligomer structure prediction by providing a global shape of the complex structure.