Atomic-level protein structure refinement using fragment-guided molecular dynamics conformation sampling

In silico mutation of aromatic with aliphatic amino acid residues in Clostridium perfringens epsilon toxin (ETX) reduces its binding efficiency to Caprine Myelin and lymphocyte (MAL) protein receptors

Enterotoxaemia (ET) is a severe disease that affects domestic ruminants, including sheep and goats, and is caused by Clostridium perfringens type B and D strains. The disease is characterized by the production of Epsilon toxin (ETX), which has a significant impact on the farming industry due to its high lethality. The binding of ETX to the host cell receptor is crucial, but still poorly understood. Therefore, the structural features of goat Myelin and lymphocytic (MAL) protein were investigated and defined in this study. We induced the mutations in aromatic amino acid residues of ETX and substituted them with aliphatic residues at domains I and II. Subsequently, protein-protein interactions (PPI) were performed between ETX (wild)-MAL and ETX (mutated)-MAL protein predicting the domain sites of ETX structure. Further, molecular dynamics (MD) simulation studies were performed for both complexes to investigate the dynamic behavior of the proteins. The binding efficiency between 'ETX (wild)-MAL protein' and 'ETX (mutated)-MAL protein complex' interactions were compared and showed that the former had stronger interactions and binding efficiency due to the higher stability of the complex. The MD analysis showed destabilization and higher fluctuations in the PPI of the mutated heterodimeric ETX-MAL complex which is otherwise essential for its functional conformation. Such kind of interactions with mutated functional domains of ligands provided much-needed clarity in understanding the pre-pore complex formation of epsilon toxin with the MAL protein receptor of goats. The findings from this study would provide an impetus for designing a novel vaccine for Enterotoxaemia in goats.Communicated by Ramaswamy H. Sarma.

TM-search: An Efficient and Effective Tool for Protein Structure Database Search

The quickly increasing size of the Protein Data Bank is challenging biologists to develop a more scalable protein structure alignment tool for fast structure database search. Although many protein structure search algorithms and programs have been designed and implemented for this purpose, most require a large amount of computational time. We propose a novel protein structure search approach, TM-search, which is based on the pairwise structure alignment program TM-align and a new iterative clustering algorithm. Benchmark tests demonstrate that TM-search is 27 times faster than a TM-align full database search while still being able to identify ∼90% of all high TM-score hits, which is 2-10 times more than other existing programs such as Foldseek, Dali, and PSI-BLAST.

PKD1L1 Is Involved in Congenital Chylothorax

Besides visceral heterotaxia, Pkd1l1 null mouse embryos exhibit general edema and perinatal lethality. In humans, congenital chylothorax (CCT) is a frequent cause of fetal hydrops. In 2021, Correa and colleagues reported ultrarare compound heterozygous variants in PKD1L1 exhibiting in two consecutive fetuses with severe hydrops, implicating a direct role of PKD1L1 in fetal hydrops formation. Here, we performed an exome survey and identified ultrarare compound heterozygous variants in PKD1L1 in two of the five case-parent trios with CCT. In one family, the affected carried the ultrarare missense variants c.1543G>A(p.Gly515Arg) and c.3845T>A(p.Val1282Glu). In the other family, the affected carried the ultrarare loss-of-function variant (LoF) c.863delA(p.Asn288Thrfs*3) and the ultrarare missense variant c.6549G>T(p.Gln2183His). Investigation of the variants' impact on PKD1L1 protein localization suggests the missense variants cause protein dysfunction and the LoF variant causes protein mislocalization. Further analysis of Pkd1l1 mutant mouse embryos revealed about 20% of Pkd1l1-/- embryos display general edema and pleural effusion at 14.5 dpc. Immunofluorescence staining at 14.5 dpc in Pkd1l1-/- embryos displayed both normal and massively altered lymphatic vessel morphologies. Together, our studies suggest the implication of PKD1L1 in congenital lymphatic anomalies, including CCTs.

Agonistic Bivalent Human scFvs-Fcγ Fusion Antibodies to OX40 Ectodomain Enhance T Cell Activities against Cancer

(1) Background: Understanding how advanced cancers evade host innate and adaptive immune opponents has led to cancer immunotherapy. Among several immunotherapeutic strategies, the reversal of immunosuppression mediated by regulatory T cells in the tumor microenvironment (TME) using blockers of immune-checkpoint signaling in effector T cells is the most successful treatment measure. Furthermore, agonists of T cell costimulatory molecules (CD40, 4-1BB, OX40) play an additional anti-cancer role to that of checkpoint blocking in combined therapy and serve also as adjuvant/neoadjuvant/induction therapy to conventional cancer treatments, such as tumor resection and radio- and chemo- therapies. (2) Methods and Results: In this study, novel agonistic antibodies to the OX40/CD134 ectodomain (EcOX40), i.e., fully human bivalent single-chain variable fragments (HuscFvs) linked to IgG Fc (bivalent HuscFv-Fcγ fusion antibodies) were generated by using phage-display technology and genetic engineering. The HuscFvs in the fusion antibodies bound to the cysteine-rich domain-2 of the EcOX40, which is known to be involved in OX40-OX40L signaling for NF-κB activation in T cells. The fusion antibodies caused proliferation, and increased the survival and cytokine production of CD3-CD28-activated human T cells. They showed enhancement trends for other effector T cell activities like granzyme B production and lysis of ovarian cancer cells when added to the activated T cells. (3) Conclusions: The novel OX40 agonistic fusion antibodies should be further tested step-by-step toward their safe use as an adjunctive non-immunogenic cancer immunotherapeutic agent.

A novel TWIK2 channel inhibitor binds at the bottom of the selectivity filter and protects against LPS-induced experimental endotoxemia in vivo

TWIK2 channel plays a critical role in NLRP3 inflammasome activation and mice deficient in TWIK2 channel are protected from sepsis and inflammatory lung injury. However, inhibitors of TWIK2 channel are currently in an early stage of development, and the molecular determinants underlying the chemical modulation of TWIK2 channel remain unexplored. In this study, we identified NPBA and the synthesized derivative NPBA-4 potently and selectively inhibited TWIK2 channel by using whole-cell patch clamp techniques. Furthermore, the mutation of the last residues of the selectivity filter in both P1 and P2 (i.e., T106A, T214A) of TWIK2 channel substantially abolished the effect of NPBA on TWIK2 channel. Our data suggest that NPBA blocked TWIK2 channel through binding at the bottom of the selectivity filter, which was also supported by molecular docking prediction. Moreover, we found that NPBA significantly suppressed NLRP3 inflammasome activation in macrophages and alleviated LPS-induced endotoxemia and organ injury in vivo. Notably, the protective effects of NPBA against LPS-induced endotoxemia were abolished in Kcnk6-/- mice. In summary, our study has uncovered a series of novel inhibitors of TWIK2 channel and revealed their distinct molecular determinants interacting TWIK2 channel. These findings provide new insights into the mechanisms of pharmacological action on TWIK2 channel and opportunities for the development of selective TWIK2 channel modulators to treat related inflammatory diseases.

DeepFold: enhancing protein structure prediction through optimized loss functions, improved template features, and re-optimized energy function

MOTIVATION

Predicting protein structures with high accuracy is a critical challenge for the broad community of life sciences and industry. Despite progress made by deep neural networks like AlphaFold2, there is a need for further improvements in the quality of detailed structures, such as side-chains, along with protein backbone structures.

RESULTS

Building upon the successes of AlphaFold2, the modifications we made include changing the losses of side-chain torsion angles and frame aligned point error, adding loss functions for side chain confidence and secondary structure prediction, and replacing template feature generation with a new alignment method based on conditional random fields. We also performed re-optimization by conformational space annealing using a molecular mechanics energy function which integrates the potential energies obtained from distogram and side-chain prediction. In the CASP15 blind test for single protein and domain modeling (109 domains), DeepFold ranked fourth among 132 groups with improvements in the details of the structure in terms of backbone, side-chain, and Molprobity. In terms of protein backbone accuracy, DeepFold achieved a median GDT-TS score of 88.64 compared with 85.88 of AlphaFold2. For TBM-easy/hard targets, DeepFold ranked at the top based on Z-scores for GDT-TS. This shows its practical value to the structural biology community, which demands highly accurate structures. In addition, a thorough analysis of 55 domains from 39 targets with publicly available structures indicates that DeepFold shows superior side-chain accuracy and Molprobity scores among the top-performing groups.

AVAILABILITY AND IMPLEMENTATION

DeepFold tools are open-source software available at https://github.com/newtonjoo/deepfold.

Integrating deep learning, threading alignments, and a multi-MSA strategy for high-quality protein monomer and complex structure prediction in CASP15

We report the results of the "UM-TBM" and "Zheng" groups in CASP15 for protein monomer and complex structure prediction. These prediction sets were obtained using the D-I-TASSER and DMFold-Multimer algorithms, respectively. For monomer structure prediction, D-I-TASSER introduced four new features during CASP15: (i) a multiple sequence alignment (MSA) generation protocol that combines multi-source MSA searching and a structural modeling-based MSA ranker; (ii) attention-network based spatial restraints; (iii) a multi-domain module containing domain partition and arrangement for domain-level templates and spatial restraints; (iv) an optimized I-TASSER-based folding simulation system for full-length model creation guided by a combination of deep learning restraints, threading alignments, and knowledge-based potentials. For 47 free modeling targets in CASP15, the final models predicted by D-I-TASSER showed average TM-score 19% higher than the standard AlphaFold2 program. We thus showed that traditional Monte Carlo-based folding simulations, when appropriately coupled with deep learning algorithms, can generate models with improved accuracy over end-to-end deep learning methods alone. For protein complex structure prediction, DMFold-Multimer generated models by integrating a new MSA generation algorithm (DeepMSA2) with the end-to-end modeling module from AlphaFold2-Multimer. For the 38 complex targets, DMFold-Multimer generated models with an average TM-score of 0.83 and Interface Contact Score of 0.60, both significantly higher than those of competing complex prediction tools. Our analyses on complexes highlighted the critical role played by MSA generating, ranking, and pairing in protein complex structure prediction. We also discuss future room for improvement in the areas of viral protein modeling and complex model ranking.

A single amino acid change led to structural and functional differentiation of PvHd1 to control flowering in switchgrass

Switchgrass, a forage and bioenergy crop, occurs as two main ecotypes with different but overlapping ranges of adaptation. The two ecotypes differ in a range of characteristics, including flowering time. Flowering time determines the duration of vegetative development and therefore biomass accumulation, a key trait in bioenergy crops. No causal variants for flowering time differences between switchgrass ecotypes have, as yet, been identified. In this study, we mapped a robust flowering time quantitative trait locus (QTL) on chromosome 4K in a biparental F2 population and characterized the flowering-associated transcription factor gene PvHd1, an ortholog of CONSTANS in Arabidopsis and Heading date 1 in rice, as the underlying causal gene. Protein modeling predicted that a serine to glycine substitution at position 35 (p.S35G) in B-Box domain 1 greatly altered the global structure of the PvHd1 protein. The predicted variation in protein compactness was supported in vitro by a 4 °C shift in denaturation temperature. Overexpressing the PvHd1-p.35S allele in a late-flowering CONSTANS-null Arabidopsis mutant rescued earlier flowering, whereas PvHd1-p.35G had a reduced ability to promote flowering, demonstrating that the structural variation led to functional divergence. Our findings provide us with a tool to manipulate the timing of floral transition in switchgrass cultivars and, potentially, expand their cultivation range.

Study on the Properties and Synergistic Antioxidant Effects of Novel Bifunctional Fusion Proteins Expressed Using the UTuT6 System

Important antioxidant enzymes, glutathione peroxidase (GPx) and superoxide dismutase (SOD), are involved in maintaining redox balance. They can protect each other and result in more efficiently removing excessive reactive oxygen species (ROS), protecting cells against injury, and maintaining the normal metabolism of ROS. In this study, human cytosolic GPx (hGPx1) and human phospholipid hydroperoxide GPx (hGPx4) genes were integrated into the same open reading frame with human extracellular SOD active site (SOD3-72P) genes, respectively, and several novel fusion proteins were obtained by using the UTuT6 expression system for the first time. Among them, Se-hGPx1UAG-L4-SOD3-72P is the bifunctional fusion protein with the highest GPx activity and the best anti-hydrogen peroxide inactivation ability thus far. The Se-hGPx4UAG-L3-SOD3-72P fusion protein exhibits the strongest alkali and high temperature resistance and a greater protective effect against lipoprotein peroxidation damage. Se-hGPx1UAG-L4-SOD3-72P and Se-hGPx4UAG-L3-SOD3-72P fusion proteins both have good synergistic and antioxidant abilities in H2O2-induced RBCs and liver damage models. We believe that this research will help with the development of novel bifunctional fusion proteins and the investigation of the synergistic and catalytic mechanisms of GPx and SOD, which are important in creating novel protein therapeutics.

Structural Insights into the Giardia lamblia Target of Rapamycin Homolog: A Bioinformatics Approach

TOR proteins, also known as targets of rapamycin, are serine/threonine kinases involved in various signaling pathways that regulate cell growth. The protozoan parasite Giardia lamblia is the causative agent of giardiasis, a neglected infectious disease in humans. In this study, we used a bioinformatics approach to examine the structural features of GTOR, a G. lamblia TOR-like protein, and predict functional associations. Our findings confirmed that it shares significant similarities with functional TOR kinases, including a binding domain for the FKBP-rapamycin complex and a kinase domain resembling that of phosphatidylinositol 3-kinase-related kinases. In addition, it can form multiprotein complexes such as TORC1 and TORC2. These results provide valuable insights into the structure-function relationship of GTOR, highlighting its potential as a molecular target for controlling G. lamblia cell proliferation. Furthermore, our study represents a step toward rational drug design for specific anti-giardiasis therapeutic agents.

Design, evaluation, and immune simulation of potentially universal multi-epitope mpox vaccine candidate: focus on DNA vaccine

Monkeypox (mpox) is a zoonotic infectious disease caused by the mpox virus. Mpox symptoms are similar to smallpox with less severity and lower mortality. As yet mpox virus is not characterized by as high transmissibility as some severe acute respiratory syndrome 2 (SARS-CoV-2) variants, still, it is spreading, especially among men who have sex with men (MSM). Thus, taking preventive measures, such as vaccination, is highly recommended. While the smallpox vaccine has demonstrated considerable efficacy against the mpox virus due to the antigenic similarities, the development of a universal anti-mpox vaccine remains a necessary pursuit. Recently, nucleic acid vaccines have garnered special attention owing to their numerous advantages compared to traditional vaccines. Importantly, DNA vaccines have certain advantages over mRNA vaccines. In this study, a potentially universal DNA vaccine candidate against mpox based on conserved epitopes was designed and its efficacy was evaluated via an immunoinformatics approach. The vaccine candidate demonstrated potent humoral and cellular immune responses in silico, indicating the potential efficacy in vivo and the need for further research.

Rapid Generation and Molecular Docking Analysis of Single-Chain Fragment Variable (scFv) Antibody Selected by Ribosome Display Targeting Cholecystokinin B Receptor (CCK-BR) for Reduction of Chronic Neuropathic Pain

A robust cell-free platform technology, ribosome display in combination with cloning, expression, and purification was utilized to develop single chain Fragment variable (scFv) antibody variants as pain therapy directed at the mouse cholecystokinin B (CCK-B) receptor. Three effective CCK-B peptide-specific scFvs were generated through ribosomal display technology. Soluble expression and ELISA analysis showed that one antibody, scFv77-2 had the highest binding and could be purified from bacterial cells in large quantities. Octet measurements further revealed that the CCK-B scFv77-2 antibody had binding kinetics of K_D = 1.794 × 10^-8 M. Molecular modeling and docking analyses suggested that the scFv77-2 antibody shaped a proper cavity to embed the whole CCK-B peptide molecule and that a steady-state complex was formed relying on intermolecular forces, including hydrogen bonding, electrostatic force, and hydrophobic interactions. Thus, the scFv antibody can be applied for mechanistic intermolecular interactions and functional in vivo studies of CCK-BR. The high affinity scFv77-2 antibody showed good efficacy with binding to CCK-BR tested in a chronic pain model. In vivo studies validated the efficacy of the CCK-B receptor (CCK-BR) scFv77-2 antibody as a potential therapy for chronic trigeminal nerve injury-induced pain. Mice were given a single dose of the CCK-B receptor (CCK-BR) scFv antibody 3 weeks after induction of a chronic trigeminal neuropathic pain model, during the transition from acute to chronic pain. The long-term effectiveness for the reduction of mechanical hypersensitivity was evident, persisting for months. The anxiety- and depression-related behaviors typically accompanying persisting hypersensitivity subsequently never developed in the mice given CCK-BR scFv. The effectiveness of the antibody is the basis for further development of the lead CCK-BR scFv as a promising non-opioid therapeutic for chronic pain and the long-term reduction of chronic pain- and anxiety-related behaviors.

Development of a Multi-Epitope Universal mRNA Vaccine Candidate for Monkeypox, Smallpox, and Vaccinia Viruses: Design and In Silico Analyses

Notwithstanding the presence of a smallpox vaccine that is effective against monkeypox (mpox), developing a universal vaccine candidate against monkeypox virus (MPXV) is highly required as the mpox multi-country outbreak has increased global concern. MPXV, along with variola virus (VARV) and vaccinia virus (VACV), belongs to the Orthopoxvirus genus. Due to the genetic similarity of antigens in this study, we have designed a potentially universal mRNA vaccine based on conserved epitopes that are specific to these three viruses. In order to design a potentially universal mRNA vaccine, antigens A29, A30, A35, B6, and M1 were selected. The conserved sequences among the three viral species-MPXV, VACV, and VARV-were detected, and B and T cell epitopes containing the conserved elements were used for the design of the multi-epitope mRNA construct. Immunoinformatics analyses demonstrated the stability of the vaccine construct and optimal binding to MHC molecules. Humoral and cellular immune responses were induced by immune simulation analyses. Eventually, based on in silico analysis, the universal mRNA multi-epitope vaccine candidate designed in this study may have a potential protection against MPXV, VARV, and VACV that will contribute to the advancement of prevention strategies for unpredictable pandemics.

Molecular Dynamics Simulations of Ion Permeation in Human Voltage-Gated Sodium Channels

The recent determination of cryo-EM structures of voltage-gated sodium (Na_v) channels has revealed many details of these proteins. However, knowledge of ionic permeation through the Na_v pore remains limited. In this work, we performed atomistic molecular dynamics (MD) simulations to study the structural features of various neuronal Na_v channels based on homology modeling of the cryo-EM structure of the human Na_v1.4 channel and, in addition, on the recently resolved configuration for Na_v1.2. In particular, single Na⁺ permeation events during standard MD runs suggest that the ion resides in the inner part of the Na_v selectivity filter (SF). On-the-fly free energy parametrization (OTFP) temperature-accelerated molecular dynamics (TAMD) was also used to calculate two-dimensional free energy surfaces (FESs) related to single/double Na⁺ translocation through the SF of the homology-based Na_v1.2 model and the cryo-EM Na_v1.2 structure, with different realizations of the DEKA filter domain. These additional simulations revealed distinct mechanisms for single and double Na⁺ permeation through the wild-type SF, which has a charged lysine in the DEKA ring. Moreover, the configurations of the ions in the SF corresponding to the metastable states of the FESs are specific for each SF motif. Overall, the description of these mechanisms gives us new insights into ion conduction in human Na_v cryo-EM-based and cryo-EM configurations that could advance understanding of these systems and how they differ from potassium and bacterial Na_v channels.

Enhanced compound-protein binding affinity prediction by representing protein multimodal information via a coevolutionary strategy

Due to the lack of a method to efficiently represent the multimodal information of a protein, including its structure and sequence information, predicting compound-protein binding affinity (CPA) still suffers from low accuracy when applying machine-learning methods. To overcome this limitation, in a novel end-to-end architecture (named FeatNN), we develop a coevolutionary strategy to jointly represent the structure and sequence features of proteins and ultimately optimize the mathematical models for predicting CPA. Furthermore, from the perspective of data-driven approach, we proposed a rational method that can utilize both high- and low-quality databases to optimize the accuracy and generalization ability of FeatNN in CPA prediction tasks. Notably, we visually interpret the feature interaction process between sequence and structure in the rationally designed architecture. As a result, FeatNN considerably outperforms the state-of-the-art (SOTA) baseline in virtual drug evaluation tasks, indicating the feasibility of this approach for practical use. FeatNN provides an outstanding method for higher CPA prediction accuracy and better generalization ability by efficiently representing multimodal information of proteins via a coevolutionary strategy.

Multiple-P450 Gene Co-Up-Regulation in the Development of Permethrin Resistance in the House Fly, Musca domestica

This paper reports a study conducted at the whole transcriptome level to characterize the P450 genes involved in the development of pyrethroid resistance, utilizing expression profile analyses of 86 cytochrome P450 genes in house fly strains with different levels of resistance to pyrethroids/permethrin. Interactions among the up-regulated P450 genes and possible regulatory factors in different autosomes were examined in house fly lines with different combinations of autosomes from a resistant house fly strain, ALHF. Eleven P450 genes that were significantly up-regulated, with levels > 2-fold those in the resistant ALHF house flies, were in CYP families 4 and 6 and located on autosomes 1, 3 and 5. The expression of these P450 genes was regulated by trans- and/or cis-acting factors, especially on autosomes 1 and 2. An in vivo functional study indicated that the up-regulated P450 genes also conferred permethrin resistance in Drosophila melanogaster transgenic lines. An in vitro functional study confirmed that the up-regulated P450 genes are able to metabolize not only cis- and trans-permethrin, but also two metabolites of permethrin, PBalc and PBald. In silico homology modeling and the molecular docking methodology further support the metabolic capacity of these P450s for permethrin and substrates. Taken together, the findings of this study highlight the important function of multi-up-regulated P450 genes in the development of insecticide resistance in house flies.

Designing multi-epitope mRNA construct as a universal influenza vaccine candidate for future epidemic/pandemic preparedness

Despite the availability of prevention and treatment strategies and advancing immunization approaches, the influenza virus remains a global threat that continues to plague humanity with unpredictable pandemics. Due to the unusual genetic variability and segmented genome, the reassortment between different strains of influenza is facilitated and the viruses continuously evolve and adapt to the host cell's immunity. This underlies the seasonal vaccine mismatches that decrease the vaccine efficacy and increase the risk of outbreaks. Thus, the development of a universal vaccine covering all the influenza A and B strains would reduce the pervasiveness of the influenza virus. In the current study, a potentially universal influenza multi-epitope vaccine was designed based on the experimentally tested conserved T cell and B cell epitopes of hemagglutinin (HA), neuraminidase (NA), nucleoprotein (NP), and matrix-2 proton channel (M2) of the virus. The immune simulation and molecular docking of the vaccine construct with TLR2, TLR3, and TLR4 elicited the favorable immunogenicity of the vaccine and the formation of stable complexes, respectively. Ultimately, based on the immunoinformatics analysis, the universal mRNA multi-epitope vaccine designed in this study might have a protection potential against the various subtypes of influenza A and B.

Using Local Protein Model Quality Estimates to Guide a Molecular Dynamics-Based Refinement Strategy

The refinement of predicted 3D models aims to bring them closer to the native structure by fixing errors including unusual bonds and torsion angles and irregular hydrogen bonding patterns. Refinement approaches based on molecular dynamics (MD) simulations using different types of restraints have performed well since CASP10. ReFOLD, developed by the McGuffin group, was one of the many MD-based refinement approaches, which were tested in CASP 12. When the performance of the ReFOLD method in CASP12 was evaluated, it was observed that ReFOLD suffered from the absence of a reliable guidance mechanism to reach consistent improvement for the quality of predicted 3D models, particularly in the case of template-based modelling (TBM) targets. Therefore, here we propose to utilize the local quality assessment score produced by ModFOLD6 to guide the MD-based refinement approach to further increase the accuracy of the predicted 3D models. The relative performance of the new local quality assessment guided MD-based refinement protocol and the original MD-based protocol ReFOLD are compared utilizing many different official scoring methods. By using the per-residue accuracy (or local quality) score to guide the refinement process, we are able to prevent the refined models from undesired structural deviations, thereby leading to more consistent improvements. This chapter will include a detailed analysis of the performance of the local quality assessment guided MD-based protocol versus that deployed in the original ReFOLD method.

The interplay between MMP-12 and t-PA in the brain after ischemic stroke

Tissue-type plasminogen activator (t-PA) expression is known to increase following transient focal cerebral ischemia and reperfusion. Previously, we reported downregulation of t-PA upon suppression of matrix metalloproteinase-12 (MMP-12), following transient focal cerebral ischemia and reperfusion. We now present data on the temporal expression of t-PA in the brain after transient ischemia, as well as the interaction between MMP-12 and t-PA, two proteases associated with the breakdown of the blood-brain barrier (BBB) and ischemic brain damage. We hypothesized that there might be reciprocal interactions between MMP-12 and t-PA in the brain after ischemic stroke. This hypothesis was tested using shRNA-mediated gene silencing and computational modeling. Suppression of t-PA following transient ischemia and reperfusion in rats attenuated MMP-12 expression in the brain. The overall effect of t-PA shRNA administration was to attenuate the degradation of BBB tight junction protein claudin-5, diminish BBB disruption, and reduce neuroinflammation by decreasing the expression of the microglia/macrophage pro-inflammatory M1 phenotype (CD68, iNOS, IL-1β, and TNFα). Reduced BBB disruption and subsequent lack of infiltration of macrophages (the main source of MMP-12 in the ischemic brain) could account for the decrease in MMP-12 expression after t-PA suppression. Computational modeling of in silico protein-protein interactions indicated that MMP-12 and t-PA may interact physically. Overall, our findings demonstrate that MMP-12 and t-PA interact directly or indirectly at multiple levels in the brain following an ischemic stroke. The present findings could be useful in the development of new pharmacotherapies for the treatment of stroke.

Holo Protein Conformation Generation from Apo Structures by Ligand Binding Site Refinement

An important part in structure-based drug design is the selection of an appropriate protein structure. It has been revealed that a holo protein structure that contains a well-defined binding site is a much better choice than an apo structure in structure-based drug discovery. Therefore, it is valuable to obtain a holo-like protein conformation from apo structures in the case where no holo structure is available. Meeting the need, we present a robust approach to generate reliable holo-like structures from apo structures by ligand binding site refinement with restraints derived from holo templates with low homology. Our method was tested on a test set of 32 proteins from the DUD-E data set and compared with other approaches. It was shown that our method successfully refined the apo structures toward the corresponding holo conformations for 23 of 32 proteins, reducing the average all-heavy-atom RMSD of binding site residues by 0.48 Å. In addition, when evaluated against all the holo structures in the protein data bank, our method can improve the binding site RMSD for 14 of 19 cases that experience significant conformational changes. Furthermore, our refined structures also demonstrate their advantages over the apo structures in ligand binding mode predictions by both rigid docking and flexible docking and in virtual screening on the database of active and decoy ligands from the DUD-E. These results indicate that our method is effective in recovering holo-like conformations and will be valuable in structure-based drug discovery.

Effect of the Type VI Secretion System Secreted Protein Hcp on the Virulence of Aeromonas salmonicida

Aeromonas salmonicida, a psychrophilic bacterial pathogen, is widely distributed in marine freshwater, causing serious economic losses to major salmon farming areas in the world. At present, it is still one of the most important pathogens threatening salmon farming. Hcp (haemolysin-coregulated protein) is an effector protein in the type-VI secretion system (T6SS), which is secreted by T6SS and functions as its structural component. The results of our previous genomic sequencing showed that hcp existed in the mesophilic A. salmonicida SRW-OG1 isolated from naturally infected Epinephelus coioides. To further explore the role of Hcp in A. salmonicida SRW-OG1, we constructed an hcp-RNAi strain and verified its effect on the virulence of A. salmonicida. The results showed that compared with the wild strain, the hcp-RNAi strain suffered from different degrees of decreased adhesion, growth, biofilm formation, extracellular product secretion, and virulence. It was suggested that hcp may be an important virulence gene of A. salmonicida SRW-OG1.

Structure-based virtual screening and molecular dynamics of potential inhibitors targeting sodium-bile acid co-transporter of carcinogenic liver fluke Clonorchis sinensis

Background

Clonorchis sinensis requires bile acid transporters as this fluke inhabits bile juice-filled biliary ducts, which provide an extreme environment. Clonorchis sinensis sodium-bile acid co-transporter (CsSBAT) is indispensable for the fluke’s survival in the final host, as it circulates taurocholate and prevents bile toxicity in the fluke; hence, it is recognized as a useful drug target.

Methodology and principal findings

In the present study, using structure-based virtual screening approach, we presented inhibitor candidates targeting a bile acid-binding pocket of CsSBAT. CsSBAT models were built using tertiary structure modeling based on a bile acid transporter template (PDB ID: 3zuy and 4n7x) and were applied into AutoDock Vina for competitive docking simulation. First, potential compounds were identified from PubChem (holding more than 100,000 compounds) by applying three criteria: i) interacting more favorably with CsSBAT than with a human homolog, ii) intimate interaction to the inward- and outward-facing conformational states, iii) binding with CsSBAT preferably to natural bile acids. Second, two compounds were identified following the Lipinski’s rule of five. Third, other two compounds of molecular weight higher than 500 Da (Mr > 500 Da) were presumed to efficiently block the transporter via a feasible rational screening strategy. Of these candidates, compound 9806452 exhibited the least hepatotoxicity that may enhance drug-likeness properties.

Conclusions

It is proposed that compound 9806452 act as a potential inhibitor toward CsSBAT and further studies are warranted for drug development process against clonorchiasis.

Strategy of developing nucleic acid-based universal monkeypox vaccine candidates

Until May 2022, zoonotic infectious disease monkeypox (MPX) caused by the monkeypox virus (MPXV) was one of the forgotten viruses considered to be geographically limited in African countries even though few cases outside of Africa were identified. Central and West African countries are known to be endemic for MPXV. However, since the number of human MPX cases has rapidly increased outside of Africa the global interest in this virus has markedly grown. The majority of infected people with MPXV have never been vaccinated against smallpox virus. Noteworthily, the MPXV spreads fast in men who have sex with men (MSM). Preventive measures against MPXV are essential to be taken, indeed, vaccination is the key. Due to the antigenic similarities, the smallpox vaccine is efficient against MPXV. Nevertheless, there is no specific MPXV vaccine until now. Nucleic acid vaccines deserve special attention since the emergency approval of two messenger RNA (mRNA)-based coronavirus disease 2019 (COVID-19) vaccines in 2020. This milestone in vaccinology has opened a new platform for developing more mRNA- or DNA-based vaccines. Certainly, this type of vaccine has a number of advantages including time- and cost-effectiveness over conventional vaccines. The platform of nucleic acid-based vaccines gives humankind a huge opportunity. Ultimately, there is a strong need for developing a universal vaccine against MPXV. This review will shed the light on the strategies for developing nucleic acid vaccines against MPXV in a timely manner. Consequently, developing nucleic acid-based vaccines may alleviate the global threat against MPXV.

Promising strategy for developing mRNA-based universal influenza virus vaccine for human population, poultry, and pigs- focus on the bigger picture

Since the first outbreak in the 19th century influenza virus has remained emergent owing to the huge pandemic potential. Only the pandemic of 1918 caused more deaths than any war in world history. Although two types of influenza- A (IAV) and B (IBV) cause epidemics annually, influenza A deserves more attention as its nature is much wilier. IAVs have a large animal reservoir and cause the infection manifestation not only in the human population but in poultry and domestic pigs as well. This many-sided characteristic of IAV along with the segmented genome gives rise to the antigenic drift and shift that allows evolving the new strains and new subtypes, respectively. As a result, the immune system of the body is unable to recognize them. Importantly, several highly pathogenic avian IAVs have already caused sporadic human infections with a high fatality rate (~60%). The current review discusses the promising strategy of using a potentially universal IAV mRNA vaccine based on conserved elements for humans, poultry, and pigs. This will better aid in averting the outbreaks in different susceptible species, thus, reduce the adverse impact on agriculture, and economics, and ultimately, prevent deadly pandemics in the human population.

Characterization of Treponema denticola Major Surface Protein (Msp) by Deletion Analysis and Advanced Molecular Modeling

Treponema denticola, a keystone pathogen in periodontitis, is a model organism for studying Treponema physiology and host-microbe interactions. Its major surface protein Msp forms an oligomeric outer membrane complex that binds fibronectin, has cytotoxic pore-forming activity, and disrupts several intracellular processes in host cells. T. denticola msp is an ortholog of the Treponema pallidum tprA to -K gene family that includes tprK, whose remarkable in vivo hypervariability is proposed to contribute to T. pallidum immune evasion. We recently identified the primary Msp surface-exposed epitope and proposed a model of the Msp protein as a β-barrel protein similar to Gram-negative bacterial porins. Here, we report fine-scale Msp mutagenesis demonstrating that both the N and C termini as well as the centrally located Msp surface epitope are required for native Msp oligomer expression. Removal of as few as three C-terminal amino acids abrogated Msp detection on the T. denticola cell surface, and deletion of four residues resulted in complete loss of detectable Msp. Substitution of a FLAG tag for either residues 6 to 13 of mature Msp or an 8-residue portion of the central Msp surface epitope resulted in expression of full-length Msp but absence of the oligomer, suggesting roles for both domains in oligomer formation. Consistent with previously reported Msp N-glycosylation, proteinase K treatment of intact cells released a 25 kDa polypeptide containing the Msp surface epitope into culture supernatants. Molecular modeling of Msp using novel metagenome-derived multiple sequence alignment (MSA) algorithms supports the hypothesis that Msp is a large-diameter, trimeric outer membrane porin-like protein whose potential transport substrate remains to be identified. IMPORTANCE The Treponema denticola gene encoding its major surface protein (Msp) is an ortholog of the T. pallidum tprA to -K gene family that includes tprK, whose remarkable in vivo hypervariability is proposed to contribute to T. pallidum immune evasion. Using a combined strategy of fine-scale mutagenesis and advanced predictive molecular modeling, we characterized the Msp protein and present a high-confidence model of its structure as an oligomer embedded in the outer membrane. This work adds to knowledge of Msp-like proteins in oral treponemes and may contribute to understanding the evolutionary and potential functional relationships between T. denticola Msp and the orthologous T. pallidum Tpr proteins.

Evolution of a chordate-specific mechanism for myoblast fusion

Vertebrate myoblast fusion allows for multinucleated muscle fibers to compound the size and strength of mononucleated cells, but the evolution of this important process is unknown. We investigated the evolutionary origins and function of membrane-coalescing agents Myomaker and Myomixer in various groups of chordates. Here, we report that Myomaker likely arose through gene duplication in the last common ancestor of tunicates and vertebrates, while Myomixer appears to have evolved de novo in early vertebrates. Functional tests revealed a complex evolutionary history of myoblast fusion. A prevertebrate phase of muscle multinucleation driven by Myomaker was followed by the later emergence of Myomixer that enables the highly efficient fusion system of vertebrates. Evolutionary comparisons between vertebrate and nonvertebrate Myomaker revealed key structural and mechanistic insights into myoblast fusion. Thus, our findings suggest an evolutionary model of chordate fusogens and illustrate how new genes shape the emergence of novel morphogenetic traits and mechanisms.

I-TASSER-MTD: a deep-learning-based platform for multi-domain protein structure and function prediction

Most proteins in cells are composed of multiple folding units (or domains) to perform complex functions in a cooperative manner. Relative to the rapid progress in single-domain structure prediction, there are few effective tools available for multi-domain protein structure assembly, mainly due to the complexity of modeling multi-domain proteins, which involves higher degrees of freedom in domain-orientation space and various levels of continuous and discontinuous domain assembly and linker refinement. To meet the challenge and the high demand of the community, we developed I-TASSER-MTD to model the structures and functions of multi-domain proteins through a progressive protocol that combines sequence-based domain parsing, single-domain structure folding, inter-domain structure assembly and structure-based function annotation in a fully automated pipeline. Advanced deep-learning models have been incorporated into each of the steps to enhance both the domain modeling and inter-domain assembly accuracy. The protocol allows for the incorporation of experimental cross-linking data and cryo-electron microscopy density maps to guide the multi-domain structure assembly simulations. I-TASSER-MTD is built on I-TASSER but substantially extends its ability and accuracy in modeling large multi-domain protein structures and provides meaningful functional insights for the targets at both the domain- and full-chain levels from the amino acid sequence alone.

Proteome Exploration of Legionella pneumophila To Identify Novel Therapeutics: a Hierarchical Subtractive Genomics and Reverse Vaccinology Approach

Legionella pneumophila is a human pathogen distributed worldwide, causing Legionnaires’ disease (LD), a severe form of pneumonia and respiratory tract infection. L. pneumophila is emerging as an antibiotic-resistant strain, and controlling LD is now difficult. Hence, developing novel drugs and vaccines against L. pneumophila is a major research priority.

DEMO2: Assemble multi-domain protein structures by coupling analogous template alignments with deep-learning inter-domain restraint prediction

Most proteins in nature contain multiple folding units (or domains). The revolutionary success of AlphaFold2 in single-domain structure prediction showed potential to extend deep-learning techniques for multi-domain structure modeling. This work presents a significantly improved method, DEMO2, which integrates analogous template structural alignments with deep-learning techniques for high-accuracy domain structure assembly. Starting from individual domain models, inter-domain spatial restraints are first predicted with deep residual convolutional networks, where full-length structure models are assembled using L-BFGS simulations under the guidance of a hybrid energy function combining deep-learning restraints and analogous multi-domain template alignments searched from the PDB. The output of DEMO2 contains deep-learning inter-domain restraints, top-ranked multi-domain structure templates, and up to five full-length structure models. DEMO2 was tested on a large-scale benchmark and the blind CASP14 experiment, where DEMO2 was shown to significantly outperform its predecessor and the state-of-the-art protein structure prediction methods. By integrating with new deep-learning techniques, DEMO2 should help fill the rapidly increasing gap between the improved ability of tertiary structure determination and the high demand for the high-quality multi-domain protein structures. The DEMO2 server is available at https://zhanggroup.org/DEMO/.

Kunitz-Type Peptides from Sea Anemones Protect Neuronal Cells against Parkinson's Disease Inductors via Inhibition of ROS Production and ATP-Induced P2X7 Receptor Activation

Parkinson’s disease (PD) is a socially significant disease, during the development of which oxidative stress and inflammation play a significant role. Here, we studied the neuroprotective effects of four Kunitz-type peptides from Heteractis crispa and Heteractis magnifica sea anemones against PD inductors. The peptide HCIQ1c9, which was obtained for the first time, inhibited trypsin less than other peptides due to unfavorable interactions of Arg17 with Lys43 in the enzyme. Its activity was reduced by up to 70% over the temperature range of 60–100 °C, while HCIQ2c1, HCIQ4c7, and HMIQ3c1 retained their conformation and stayed active up to 90–100 °C. All studied peptides inhibited paraquat- and rotenone-induced intracellular ROS formation, in particular NO, and scavenged free radicals outside the cells. The peptides did not modulate the TRPV1 channels but they affected the P2X7R, both of which are considered therapeutic targets in Parkinson’s disease. HMIQ3c1 and HCIQ4c7 almost completely inhibited the ATP-induced uptake of YO-PRO-1 dye in Neuro-2a cells through P2X7 ion channels and significantly reduced the stable calcium response in these cells. The complex formation of the peptides with the P2X7R extracellular domain was determined via SPR analysis. Thus, these peptides may be considered promising compounds to protect neuronal cells against PD inductors, which act as ROS production inhibitors and partially act as ATP-induced P2X7R activation inhibitors.

LOMETS3: integrating deep learning and profile alignment for advanced protein template recognition and function annotation

Deep learning techniques have significantly advanced the field of protein structure prediction. LOMETS3 (https://zhanglab.ccmb.med.umich.edu/LOMETS/) is a new generation meta-server approach to template-based protein structure prediction and function annotation, which integrates newly developed deep learning threading methods. For the first time, we have extended LOMETS3 to handle multi-domain proteins and to construct full-length models with gradient-based optimizations. Starting from a FASTA-formatted sequence, LOMETS3 performs four steps of domain boundary prediction, domain-level template identification, full-length template/model assembly and structure-based function prediction. The output of LOMETS3 contains (i) top-ranked templates from LOMETS3 and its component threading programs, (ii) up to 5 full-length structure models constructed by L-BFGS (limited-memory Broyden–Fletcher–Goldfarb–Shanno algorithm) optimization, (iii) the 10 closest Protein Data Bank (PDB) structures to the target, (iv) structure-based functional predictions, (v) domain partition and assembly results, and (vi) the domain-level threading results, including items (i)–(iii) for each identified domain. LOMETS3 was tested in large-scale benchmarks and the blind CASP14 (14th Critical Assessment of Structure Prediction) experiment, where the overall template recognition and function prediction accuracy is significantly beyond its predecessors and other state-of-the-art threading approaches, especially for hard targets without homologous templates in the PDB. Based on the improved developments, LOMETS3 should help significantly advance the capability of broader biomedical community for template-based protein structure and function modelling.

Progressive assembly of multi-domain protein structures from cryo-EM density maps

Progress in cryo-electron microscopy has provided the potential for large-size protein structure determination. However, the success rate for solving multi-domain proteins remains low because of the difficulty in modelling inter-domain orientations. Here we developed domain enhanced modeling using cryo-electron microscopy (DEMO-EM), an automatic method to assemble multi-domain structures from cryo-electron microscopy maps through a progressive structural refinement procedure combining rigid-body domain fitting and flexible assembly simulations with deep-neural-network inter-domain distance profiles. The method was tested on a large-scale benchmark set of proteins containing up to 12 continuous and discontinuous domains with medium- to low-resolution density maps, where DEMO-EM produced models with correct inter-domain orientations (template modeling score (TM-score) >0.5) for 97% of cases and outperformed state-of-the-art methods. DEMO-EM was applied to the severe acute respiratory syndrome coronavirus 2 genome and generated models with average TM-score and root-mean-square deviation of 0.97 and 1.3 Å, respectively, with respect to the deposited structures. These results demonstrate an efficient pipeline that enables automated and reliable large-scale multi-domain protein structure modelling from cryo-electron microscopy maps.

Repurposing Lansoprazole and Posaconazole to treat leishmaniasis: Integration of in vitro testing, pharmacological corroboration, and mechanisms of action

Leishmaniasis remains a serious public health problem in many tropical regions of the world. Among neglected tropical diseases, the mortality rate of leishmaniasis is second only to malaria. All currently approved therapeutics have toxic side effects and face rapidly increasing resistance. To identify existing drugs with antileishmanial activity and predict the mechanism of action, we designed a drug-discovery pipeline utilizing both in-silico and in-vitro methods. First, we screened compounds from the Selleckchem Bio-Active Compound Library containing ~1622 FDA-approved drugs and narrowed these down to 96 candidates based on data mining for possible anti-parasitic properties. Next, we completed preliminary in-vitro testing of compounds against Leishmania amastigotes and selected the most promising active compounds, Lansoprazole and Posaconazole. We identified possible Leishmania drug targets of Lansoprazole and Posaconazole using several available servers. Our in-silico screen identified likely Lansoprazole targets as the closely related calcium-transporting ATPases (LdBPK_352080.1, LdBPK_040010.1, and LdBPK_170660.1), and the Posaconazole target as lanosterol 14-alpha-demethylase (LdBPK_111100.1). Further validation showed LdBPK_352080.1 to be the most plausible target based on induced-fit docking followed by long (100ns) MD simulations to confirm the stability of the docked complexes. We present a likely ion channel-based mechanism of action of Lansoprazole against Leishmania calcium-transporting ATPases, which are essential for parasite metabolism and infectivity. The LdBPK_111100.1 interaction with Posaconazole is very similar to the known fungal orthologue. Herein, we present two novel anti-leishmanial agents, Posaconazole and Lansoprazole, already approved by the FDA for different indications and propose plausible mechanisms of action for their antileishmanial activity.

Iron dysregulation in COVID-19 and reciprocal evolution of SARS-CoV-2: Natura nihil frustra facit

After more than a year of the COVID-19 pandemic, SARS-CoV-2 infection rates with newer variants continue to devastate much of the world. Global healthcare systems are overwhelmed with high positive patient numbers. Silent hypoxia accompanied by rapid deterioration and some cases with septic shock is responsible for COVID-19 mortality in many hospitalized patients. There is an urgent need to further understand the relationships and interplay with human host components during pathogenesis and immune evasion strategies. Currently, acquired immunity through vaccination or prior infection usually provides sufficient protection against the emerging variants of SARS-CoV-2 except Omicron variant requiring recent booster. New strains have shown higher viral loads and greater transmissibility with more severe disease presentations. Notably, COVID-19 has a peculiar prognosis in severe patients with iron dysregulation and hypoxia which is still poorly understood. Studies have shown abnormally low serum iron levels in severe infection but a high iron overload in lung fibrotic tissue. Data from our in-silico structural analysis of the spike protein sequence along with host proteolysis processing suggests that the viral spike protein fragment mimics Hepcidin and is resistant to the major human proteases. This functional spike-derived peptide dubbed "Covidin" thus may be intricately involved with host ferroportin binding and internalization leading to dysregulated host iron metabolism. Here, we propose the possible role of this potentially allogenic mimetic hormone corresponding to severe COVID-19 immunopathology and illustrate that this molecular mimicry is responsible for a major pathway associated with severe disease status. Furthermore, through 3D molecular modeling and docking followed by MD simulation validation, we have unraveled the likely role of Covidin in iron dysregulation in COVID-19 patients. Our meta-analysis suggests the Hepcidin mimetic mechanism is highly conserved among its host range as well as among all new variants to date including Omicron. Extensive analysis of current mutations revealed that new variants are becoming alarmingly more resistant to selective human proteases associated with host defense.

CR-I-TASSER: assemble protein structures from cryo-EM density maps using deep convolutional neural networks

Cryo-electron microscopy (cryo-EM) has become a leading approach for protein structure determination, but it remains challenging to accurately model atomic structures with cryo-EM density maps. We propose a hybrid method, CR-I-TASSER, which integrates deep neural-network learning with I-TASSER assembly simulations for automated cryo-EM structure determination. The method is benchmarked on 778 proteins with simulated and experimental density maps, where CR-I-TASSER constructs models with a correct fold (TM-score>0.5) for 643 targets that is 64% higher than the best of other de novo and refinement-based approaches on high-resolution data samples. Detailed data analyses showed that the major advantage of CR-I-TASSER lies in the deep-learning based Cα position prediction, which significantly improves the threading template quality and therefore boosts the accuracy of final models through optimized fragment assembly simulations. These results demonstrate a new avenue to determine cryo-EM protein structures with high accuracy and robustness covering various target types and density-map resolutions.

Docking-guided rational engineering of a macrolide glycosyltransferase glycodiversifies epothilone B

Glycosyltransferases typically display acceptor substrate flexibility but more stringent donor specificity. BsGT-1 is a highly effective glycosyltransferase to glycosylate macrolides, including epothilones, promising antitumor compounds. Here, we show that BsGT-1 has three major regions significantly influencing the glycodiversification of epothilone B based on structural molecular docking, "hot spots" alanine scanning, and site saturation mutagenesis. Mutations in the PSPG-like motif region and the C2 loop region are more likely to expand donor preference; mutations of the flexible N3 loop region located at the mouth of the substrate-binding cavity produce novel epothilone oligosaccharides. These "hot spots" also functioned in homologues of BsGT-1. The glycosides showed significantly enhanced water solubility and decreased cytotoxicity, although the glycosyl appendages of epothilone B also reduced drug permeability and attenuated antitumor efficacy. This study laid a foundation for the rational engineering of other GTs to synthesize valuable small molecules.

Molecular Detection of Colistin Resistance mcr-1 Gene in Multidrug-Resistant Escherichia coli Isolated from Chicken

Zoonotic and antimicrobial-resistant Escherichia coli (hereafter, E. coli) is a global public health threat which can lead to detrimental effects on human health. Here, we aim to investigate the antimicrobial resistance and the presence of mcr-1 gene in E. coli isolated from chicken feces. Ninety-four E. coli isolates were obtained from samples collected from different locations in Bangladesh, and the isolates were identified using conventional microbiological tests. Phenotypic disk diffusion tests using 20 antimicrobial agents were performed according to CLSI-EUCAST guidelines, and minimum inhibitory concentrations (MICs) were determined for a subset of samples. E. coli isolates showed high resistance to colistin (88.30%), ciprofloxacin (77.66%), trimethoprim/sulfamethoxazole (76.60%), tigecycline (75.53%), and enrofloxacin (71.28%). Additionally, the pathotype eaeA gene was confirmed in ten randomly selected E. coli isolates using primer-specific polymerase chain reaction (PCR). The presence of mcr-1 gene was confirmed using PCR and sequencing analysis in six out of ten E. coli isolates. Furthermore, sequencing and phylogenetic analyses revealed a similarity between the catalytic domain of Neisseria meningitidis lipooligosaccharide phosphoethanolamine transferase A (LptA) and MCR proteins, indicating that the six tested isolates were colistin resistant. Finally, the findings of the present study showed that E. coli isolated from chicken harbored mcr-1 gene, and multidrug and colistin resistance. These findings accentuate the need to implement strict measures to limit the imprudent use of antibiotics, particularly colistin, in agriculture and poultry farms.

finDr: A web server for in silico D-peptide ligand identification

In the rapidly expanding field of peptide therapeutics, the short in vivo half-life of peptides represents a considerable limitation for drug action. D-peptides, consisting entirely of the dextrorotatory enantiomers of naturally occurring levorotatory amino acids (AAs), do not suffer from these shortcomings as they are intrinsically resistant to proteolytic degradation, resulting in a favourable pharmacokinetic profile. To experimentally identify D-peptide binders to interesting therapeutic targets, so-called mirror-image phage display is typically performed, whereby the target is synthesized in D-form and L-peptide binders are screened as in conventional phage display. This technique is extremely powerful, but it requires the synthesis of the target in D-form, which is challenging for large proteins. Here we present finDr, a novel web server for the computational identification and optimization of D-peptide ligands to any protein structure (https://findr.biologie.uni-freiburg.de/). finDr performs molecular docking to virtually screen a library of helical 12-mer peptides extracted from the RCSB Protein Data Bank (PDB) for their ability to bind to the target. In a separate, heuristic approach to search the chemical space of 12-mer peptides, finDr executes a customizable evolutionary algorithm (EA) for the de novo identification or optimization of D-peptide ligands. As a proof of principle, we demonstrate the validity of our approach to predict optimal binders to the pharmacologically relevant target phenol soluble modulin alpha 3 (PSMα3), a toxin of methicillin-resistant Staphylococcus aureus (MRSA). We validate the predictions using in vitro binding assays, supporting the success of this approach. Compared to conventional methods, finDr provides a low cost and easy-to-use alternative for the identification of D-peptide ligands against protein targets of choice without size limitation. We believe finDr will facilitate D-peptide discovery with implications in biotechnology and biomedicine.

Decoding the link of microbiome niches with homologous sequences enables accurately targeted protein structure prediction

Information derived from metagenome sequences through deep-learning techniques has significantly improved the accuracy of template free protein structure modeling. However, most of the deep learning-based modeling studies are based on blind sequence database searches and suffer from low efficiency in computational resource utilization and model construction, especially when the sequence library becomes prohibitively large. We proposed a MetaSource model built on 4.25 billion microbiome sequences from four major biomes (Gut, Lake, Soil, and Fermentor) to decode the inherent linkage of microbial niches with protein homologous families. Large-scale protein family folding experiments on 8,700 unknown Pfam families showed that a microbiome targeted approach with multiple sequence alignment constructed from individual MetaSource biomes requires more than threefold less computer memory and CPU (central processing unit) time but generates contact-map and three-dimensional structure models with a significantly higher accuracy, compared with that using combined metagenome datasets. These results demonstrate an avenue to bridge the gap between the rapidly increasing metagenome databases and the limited computing resources for efficient genome-wide database mining, which provides a useful bluebook to guide future microbiome sequence database and modeling development for high-accuracy protein structure and function prediction.

Structural Predictive Model of Presenilin-2 Protein and Analysis of Structural Effects of Familial Alzheimer's Disease Mutations

Alzheimer's disease manifests itself in brain tissue by neuronal death, due to aggregation of β-amyloid, produced by senile plaques, and hyperphosphorylation of the tau protein, which produces neurofibrillary tangles. One of the genetic markers of the disease is the gene that translates the presenilin-2 protein, which has mutations that favor the appearance of the disease and has no reported crystallographic structure. In view of this, protein modeling is performed using prediction and structural refinement tools followed by an energetic and stereochemical characterization for its validation. For the simulation, four reported mutations are chosen, which are Met239Ile, Met239Val, Ser130Leu, and Thr122Arg, all associated with various functional responses. From a theoretical analysis, a preliminary bioinformatic study is made to find the phosphorylation patterns in the protein and the hydropathic index according to the polarity and chemical environment. Molecular visualization was carried out with the Chimera 1.14 software, and the theoretical calculation with the hybrid quantum mechanics/molecular mechanics system from the semi-empirical method, with Spartan18 software and an AustinModel1 basis. These relationships allow for studying the system from a structural approach with the determination of small distance changes, potential surfaces, electrostatic maps, and angle changes, which favor the comparison between wild-type and mutant systems. With the results obtained, it is expected to complement experimental data reported in the literature from models that would allow us to understand the effects of the selected mutations.

Engineered Fully Human Single-Chain Monoclonal Antibodies to PIM2 Kinase

Proviral integration site of Moloney virus-2 (PIM2) is overexpressed in multiple human cancer cells and high level is related to poor prognosis; thus, PIM2 kinase is a rational target of anti-cancer therapeutics. Several chemical inhibitors targeting PIMs/PIM2 or their downstream signaling molecules have been developed for treatment of different cancers. However, their off-target toxicity is common in clinical trials, so they could not be advanced to official approval for clinical application. Here, we produced human single-chain antibody fragments (HuscFvs) to PIM2 by using phage display library, which was constructed in a way that a portion of phages in the library carried HuscFvs against human own proteins on their surface with the respective antibody genes in the phage genome. Bacterial derived-recombinant PIM2 (rPIM2) was used as an antigenic bait to fish out the rPIM2-bound phages from the library. Three E. coli clones transfected with the HuscFv genes derived from the rPIM2-bound phages expressed HuscFvs that bound also to native PIM2 from cancer cells. The HuscFvs presumptively interact with the PIM2 at the ATP binding pocket and kinase active loop. They were as effective as small chemical drug inhibitor (AZD1208, which is an ATP competitive inhibitor of all PIM isoforms for ex vivo use) in inhibiting PIM kinase activity. The HuscFvs should be engineered into a cell-penetrating format and tested further towards clinical application as a novel and safe pan-anti-cancer therapeutics.

Improving fragment-based ab initio protein structure assembly using low-accuracy contact-map predictions

Sequence-based contact prediction has shown considerable promise in assisting non-homologous structure modeling, but it often requires many homologous sequences and a sufficient number of correct contacts to achieve correct folds. Here, we developed a method, C-QUARK, that integrates multiple deep-learning and coevolution-based contact-maps to guide the replica-exchange Monte Carlo fragment assembly simulations. The method was tested on 247 non-redundant proteins, where C-QUARK could fold 75% of the cases with TM-scores (template-modeling scores) ≥0.5, which was 2.6 times more than that achieved by QUARK. For the 59 cases that had either low contact accuracy or few homologous sequences, C-QUARK correctly folded 6 times more proteins than other contact-based folding methods. C-QUARK was also tested on 64 free-modeling targets from the 13th CASP (critical assessment of protein structure prediction) experiment and had an average GDT_TS (global distance test) score that was 5% higher than the best CASP predictors. These data demonstrate, in a robust manner, the progress in modeling non-homologous protein structures using low-accuracy and sparse contact-map predictions.

Human Transbodies to Reverse Transcriptase Connection Subdomain of HIV-1 Gag-Pol Polyprotein Reduce Infectiousness of the Virus Progeny

HIV-1 progeny are released from infected cells as immature particles that are unable to infect new cells. Gag-Pol polyprotein dimerization via the reverse transcriptase connection domain (RTCDs) is pivotal for proper activation of the virus protease (PR protein) in an early event of the progeny virus maturation process. Thus, the RTCD is a potential therapeutic target for a broadly effective anti-HIV agent through impediment of virus maturation. In this study, human single-chain antibodies (HuscFvs) that bound to HIV-1 RTCD were generated using phage display technology. Computerized simulation guided the selection of the transformed Escherichia coli-derived HuscFvs that bound to the RTCD dimer interface. The selected HuscFvs were linked molecularly to human-derived-cell-penetrating peptide (CPP) to make them cell-penetrable (i.e., become transbodies). The CPP-HuscFvs/transbodies produced by a selected transformed E. coli clone were tested for anti-HIV-1 activity. CPP-HuscFvs of transformed E. coli clone 11 (CPP-HuscFv11) that presumptively bound at the RTCD dimer interface effectively reduced reverse transcriptase activity in the newly released virus progeny. Infectiousness of the progeny viruses obtained from CPP-HuscFv11-treated cells were reduced by a similar magnitude to those obtained from protease/reverse transcriptase inhibitor-treated cells, indicating anti-HIV-1 activity of the transbodies. The CPP-HuscFv11/transbodies to HIV-1 RTCD could be an alternative, anti-retroviral agent for long-term HIV-1 treatment.

Protein structure prediction using deep learning distance and hydrogen-bonding restraints in CASP14

In this article, we report 3D structure prediction results by two of our best server groups ("Zhang-Server" and "QUARK") in CASP14. These two servers were built based on the D-I-TASSER and D-QUARK algorithms, which integrated four newly developed components into the classical protein folding pipelines, I-TASSER and QUARK, respectively. The new components include: (a) a new multiple sequence alignment (MSA) collection tool, DeepMSA2, which is extended from the DeepMSA program; (b) a contact-based domain boundary prediction algorithm, FUpred, to detect protein domain boundaries; (c) a residual convolutional neural network-based method, DeepPotential, to predict multiple spatial restraints by co-evolutionary features derived from the MSA; and (d) optimized spatial restraint energy potentials to guide the structure assembly simulations. For 37 FM targets, the average TM-scores of the first models produced by D-I-TASSER and D-QUARK were 96% and 112% higher than those constructed by I-TASSER and QUARK, respectively. The data analysis indicates noticeable improvements produced by each of the four new components, especially for the newly added spatial restraints from DeepPotential and the well-tuned force field that combines spatial restraints, threading templates, and generic knowledge-based potentials. However, challenges still exist in the current pipelines. These include difficulties in modeling multi-domain proteins due to low accuracy in inter-domain distance prediction and modeling protein domains from oligomer complexes, as the co-evolutionary analysis cannot distinguish inter-chain and intra-chain distances. Specifically tuning the deep learning-based predictors for multi-domain targets and protein complexes may be helpful to address these issues.

Bioinformatic Analysis of Two TOR (Target of Rapamycin)-Like Proteins Encoded by Entamoeba histolytica Revealed Structural Similarities with Functional Homologs

The target of rapamycin (TOR), also known as FKBP-rapamycin associated protein (FRAP), is a protein kinase belonging to the PIKK (phosphatidylinositol 3-kinase (PI3K)-related kinases) family. TOR kinases are involved in several signaling pathways that control cell growth and proliferation. Entamoeba histolytica, the protozoan parasite that causes human amoebiasis, contains two genes encoding TOR-like proteins: EhFRAP and EhTOR2. To assess their potential as drug targets to control the cell proliferation of E. histolytica, we studied the structural features of EhFRAP and EhTOR2 using a biocomputational approach. The overall results confirmed that both TOR amoebic homologs share structural similarities with functional TOR kinases, and show inherent abilities to form TORC complexes and participate in protein-protein interaction networks. To our knowledge, this study represents the first in silico characterization of the structure-function relationships of EhFRAP and EhTOR2.

Folding non-homologous proteins by coupling deep-learning contact maps with I-TASSER assembly simulations

Structure prediction for proteins lacking homologous templates in the Protein Data Bank (PDB) remains a significant unsolved problem. We developed a protocol, C-I-TASSER, to integrate interresidue contact maps from deep neural-network learning with the cutting-edge I-TASSER fragment assembly simulations. Large-scale benchmark tests showed that C-I-TASSER can fold more than twice the number of non-homologous proteins than the I-TASSER, which does not use contacts. When applied to a folding experiment on 8,266 unsolved Pfam families, C-I-TASSER successfully folded 4,162 domain families, including 504 folds that are not found in the PDB. Furthermore, it created correct folds for 85% of proteins in the SARS-CoV-2 genome, despite the quick mutation rate of the virus and sparse sequence profiles. The results demonstrated the critical importance of coupling whole-genome and metagenome-based evolutionary information with optimal structure assembly simulations for solving the problem of non-homologous protein structure prediction.

Alternative splicing of the metalloprotease ADAMTS17 spacer regulates secretion and modulates autoproteolytic activity

ADAMTS proteases mediate biosynthesis and breakdown of secreted extracellular matrix (ECM) molecules in numerous physiological and disease processes. In addition to their catalytic domains, ADAMTS proteases contain ancillary domains, which mediate substrate recognition and ECM binding and confer distinctive properties and roles to individual ADAMTS proteases. Although alternative splicing can greatly expand the structural and functional diversity of ADAMTS proteases, it has been infrequently reported and functional consequences have been rarely investigated. Here, we characterize the structural and functional impact of alternative splicing of ADAMTS17, mutations in which cause Weill-Marchesani syndrome 4. Two novel ADAMTS17 splice variants, ADAMTS17A and ADAMTS17B, were investigated by structural modeling, mass spectrometry, and biochemical approaches. Our results identify a novel disulfide-bridged insertion in the ADAMTS17A spacer that originates from inclusion of a novel exon. This insertion results in differential autoproteolysis of ADAMTS17, and thus, predicts altered proteolytic activity against other substrates. The second variant, ADAMTS17B, results from an in-frame exon deletion and prevents ADAMTS17B secretion. Thus, alternative splicing of the ADAMTS spacer significantly regulates the physiologically relevant proteolytic activity of ADAMTS17, either by altering proteolytic specificity (ADAMTS17A) or by altering cellular localization (ADAMTS17B).

Co-existence of Alport syndrome and C3 glomerulonephritis in a proband with family history

Background

Alport syndrome and C3 glomerulonephritis (C3GN) are rare kidney diseases, frequently responsible for familial haematuria, proteinuria, and renal impairment. With the rapid development of molecular genetic testing, Alport syndrome causes have been restricted mostly to variants in the COL4A5 or COL4A3/COL4A4 genes. Moreover, a broad range of genetic contributors in the complement and complement-regulating proteins are definitely implicated in the pathogenesis of C3GN.

Methods

We sought a family with persistent microscopic haematuria associated with renal failure. Clinicopathologic and follow-up data were obtained, and molecular genetic testing was used to screen for pathogenic variants.

Results

We describe a three-generation family with Alport syndrome showing a dominant maternal inheritance. Notably, renal biopsy showed the concurrent histological evidence of C3GN in the proband harbouring an uncommon heterozygous variation in CFHR5, c.508G > A. The alteration leads to replacement of a highly conserved residue at position 170 of the β-strand subunit of CFHR5 (p.Val170Met). In silico analysis showed that the variation was predicted to deregulate complement activation by altering the structural properties and enhancing C3b binding capacity to compete with Complement Factor H (CFH), which was in line with experimental data previously published.

Conclusions

The comorbidity findings between Alport syndrome and C3GN indicate an underlying overlap and require further study.

Supplementary Information

The online version contains supplementary material available at 10.1186/s40001-021-00543-5.

Toward the solution of the protein structure prediction problem

Since Anfinsen demonstrated that the information encoded in a protein's amino acid sequence determines its structure in 1973, solving the protein structure prediction problem has been the Holy Grail of structural biology. The goal of protein structure prediction approaches is to utilize computational modeling to determine the spatial location of every atom in a protein molecule starting from only its amino acid sequence. Depending on whether homologous structures can be found in the Protein Data Bank (PDB), structure prediction methods have been historically categorized as template-based modeling (TBM) or template-free modeling (FM) approaches. Until recently, TBM has been the most reliable approach to predicting protein structures, and in the absence of reliable templates, the modeling accuracy sharply declines. Nevertheless, the results of the most recent community-wide assessment of protein structure prediction experiment (CASP14) have demonstrated that the protein structure prediction problem can be largely solved through the use of end-to-end deep machine learning techniques, where correct folds could be built for nearly all single-domain proteins without using the PDB templates. Critically, the model quality exhibited little correlation with the quality of available template structures, as well as the number of sequence homologs detected for a given target protein. Thus, the implementation of deep-learning techniques has essentially broken through the 50-year-old modeling border between TBM and FM approaches and has made the success of high-resolution structure prediction significantly less dependent on template availability in the PDB library.

Glutaredoxins and thioredoxin peroxidase involved in defense of emamectin benzoate induced oxidative stress in Grapholita molesta

Glutaredoxins (Grxs) and thioredoxin peroxidases (Tpxs) are major antioxidant enzyme families involved in regulating cellular redox homeostasis and in defense of enhanced oxidative stress through scavenging reactive oxygen species (ROS). However, the functions of these enzymes have not been reported in the oriental fruit moth, Grapholita molesta (Busck), a worldwide pest of stone and pome fruits. Here, we identified four new antioxidant genes, GmGrx, GmGrx3, GmGrx5, and GmTpx which were induced by exposure with emamectin benzoate, a commonly used biopesticide for G. molesta control. Other environmental factors (low and high temperatures, Escherichia coli and Metarhizium anisopliae) also significantly induced the expression of these genes. After GmGrx or GmTpx silenced by RNA interference (RNAi), the percentage of larval survival to emamectin benzoate were significantly decreased, demonstrating that GmGrx and GmTpx are involved in protecting G. molesta from stresses induced by emamectin benzoate. Furthermore, silenced GmGrx, GmGrx3, GmGrx5, or GmTpx significantly enhanced the enzymatic activities of superoxide dismutase (SOD) (except GmTpx) and peroxidase (POD), as well as the contents of hydrogen peroxide and metabolites ascorbate. Taken together, our results suggest that GmGrx, GmGrx3, GmGrx5, and GmTpx may play critical roles in antioxidant defense. Specially, GmGrx and GmTpx contribute to the defense of oxidative damage induced by exposure to emamectin benzoate through scavenging excessive ROS in G. molesta. Our findings provided a theoretical basis for understanding functions of insect glutaredoxin and peroxidase systems.