Addressing recent docking challenges: A hybrid strategy to integrate template-based and free protein-protein docking

Multi-epitope peptide vaccines targeting dengue virus serotype 2 created via immunoinformatic analysis

The Middle East has witnessed a greater spread of infectious Dengue viruses, with serotype 2 (DENV-2) being the most prevalent form. Through this work, multi-epitope peptide vaccines against DENV-2 that target E and nonstructural (NS1) proteins were generated through an immunoinformatic approach. MHC class I and II and LBL epitopes among NS1 and envelope E proteins sequences were predicted and their antigenicity, toxicity, and allergenicity were investigated. Studies of the population coverage denoted the high prevalence of NS1 and envelope-E epitopes among different countries where DENV-2 endemic. Further, both the CTL and HTL epitopes retrieved from NS1 epitopes exhibited high conservancies' percentages with other DENV serotypes (1, 3, and 4). Three vaccine constructs were created and the expected immune responses for the constructs were estimated using C-IMMSIM and HADDOCK (against TLR 2,3,4,5, and 7). Molecular dynamics simulation for vaccine construct 2 with TLR4 denoted high binding affinity and stability of the construct with the receptor which might foretell favorable in vivo interaction and immune responses.

Development of a novel multi-epitope vaccine for brucellosis prevention

Brucellosis, a zoonotic disease caused by Brucella, presents a significant threat to both animal and human health. In animals, the disease can lead to infertility, miscarriage, and high fever, while in humans, symptoms may include recurrent fever, fatigue, sweating, hepatosplenomegaly, and joint and muscle pain following infection. Treatment often involves long-term antibiotic therapy, placing a substantial psychological and financial burden on patients. While vaccination is crucial for prevention, current animal vaccines have drawbacks such as residual virulence, and a safe and effective human vaccine is lacking. Hence, the development of a vaccine for brucellosis is imperative. In this study, we utilized bioinformatics methods to design a multi-epitope vaccine targeting Brucella. Targeting Heme transporter BhuA and polysaccharide export protein, we identified antigenic epitopes, including six cytotoxic T lymphocyte (CTL) dominant epitopes, six helper T lymphocyte (HTL) dominant epitopes, one conformation B cell dominant epitope, and three linear B cell dominant epitopes. By linking these epitopes with appropriate linkers and incorporating a Toll-like receptor (TLR) agonist (human beta-defensin-2) and an auxiliary peptide (Pan HLA-DR epitopes), we constructed the multi-epitope vaccine (MEV). The MEV demonstrated high antigenicity, non-toxicity, non-allergenicity, non-human homology, stability, and solubility. Molecular docking analysis and molecular dynamics simulations confirmed the interaction and stability of the MEV with receptors (MHCI, MHCII, TLR4). Codon optimization and in silico cloning validated the translation efficiency and successful expression of MEV in Escherichia coli. Immunological simulations further demonstrated the efficacy of MEV in inducing robust immune responses. In conclusion, our findings suggest that the engineered MEVs have the potential to stimulate both humoral and cellular immune responses, offering valuable insights for the future development of safe and efficient Brucella vaccines.

In silico discovery of potential PPI inhibitors for anti-lung cancer activity by targeting the CCND1-CDK4 complex via the P21 inhibition mechanism

Non-Small Cell Lung Cancer (NSCLC) is a prevalent and deadly form of lung cancer worldwide with a low 5-year survival rate. Current treatments have limitations, particularly for advanced-stage patients. P21, a protein that inhibits the CCND1-CDK4 complex, plays a crucial role in cell proliferation. Computer-Aided Drug Design (CADD) based on pharmacophores can screen and design PPI inhibitors targeting the CCND1-CDK4 complex. By analyzing known inhibitors, key pharmacophores are identified, and computational methods are used to screen potential PPI inhibitors. Molecular docking, pharmacophore matching, and structure-activity relationship studies optimize the inhibitors. This approach accelerates the discovery of CCND1-CDK4 PPI inhibitors for NSCLC treatment. Molecular dynamics simulations of CCND1-CDK4-P21 and CCND1-CDK4 complexes showed stable behavior, comprehensive sampling, and P21's impact on complex stability and hydrogen bond formation. A pharmacophore model facilitated virtual screening, identifying compounds with favorable binding affinities. Further simulations confirmed the stability and interactions of selected compounds, including 513457. This study demonstrates the potential of CADD in optimizing PPI inhibitors targeting the CCND1-CDK4 complex for NSCLC treatment. Extended simulations and experimental validations are necessary to assess their efficacy and safety.

Carbohydrate polymer degradation derivatives as possible natural mannanase inhibitors

The role of mannanases is diverse and they are used in many industrial applications, in animal feed, in the food industry and in healthcare. They are also applied in biomass processing, because they play an important role in the breakdown of hemicellulose. Among the mannanase inhibitors, heavy metal ions and general enzyme inhibitors are mainly mentioned. Unfortunately, almost no data are available on carbohydrate-based natural inhibitors of mannanases. According to the literature, carbohydrates do not play an important role in the inhibition of mannanases, so neither do oligosaccharides. This is in contrast to the action and inhibition of other O-glycosyl hydrolases. My hypothesis is that mannanases, like other polysaccharide-degrading enzymes, work in the same way and can be inhibited by oligosaccharides. Evidence from docking and modeling results supports and makes probable the hypothesis that oligosaccharides can inhibit the activity of mannanases, similar to the inhibition of other O-glycosyl hydrolases. Among natural carbohydrate oligomers, several potential mannanase inhibitors have been identified and characterized. In addition to expensive research, it is very important to use research based on cheaper modeling to explore the processes. The results obtained are novel and forward-looking, enabling in-depth and targeted research to be carried out.

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.

Balancing the Affinity and Tumor Cell Binding of a Two-in-One Antibody Simultaneously Targeting EGFR and PD-L1

The optimization of the affinity of monoclonal antibodies is crucial for the development of drug candidates, as it can impact the efficacy of the drug and, thus, the dose and dosing regimen, limit adverse effects, and reduce therapy costs. Here, we present the affinity maturation of an EGFR×PD-L1 Two-in-One antibody for EGFR binding utilizing site-directed mutagenesis and yeast surface display. The isolated antibody variants target EGFR with a 60-fold-improved affinity due to the replacement of a single amino acid in the CDR3 region of the light chain. The binding properties of the Two-in-One variants were confirmed using various methods, including BLI measurements, real-time antigen binding measurements on surfaces with a mixture of both recombinant proteins and cellular binding experiments using flow cytometry as well as real-time interaction cytometry. An AlphaFold-based model predicted that the amino acid exchange of tyrosine to glutamic acid enables the formation of a salt bridge to an arginine at EGFR position 165. This easily adaptable approach provides a strategy for the affinity maturation of bispecific antibodies with respect to the binding of one of the two antigens.

Borrelia burgdorferi PlzA is a cyclic-di-GMP dependent DNA and RNA binding protein

The PilZ domain-containing protein, PlzA, is the only known cyclic di-GMP binding protein encoded by all Lyme disease spirochetes. PlzA has been implicated in the regulation of many borrelial processes, but the effector mechanism of PlzA was not previously known. Here, we report that PlzA can bind DNA and RNA and that nucleic acid binding requires c-di-GMP, with the affinity of PlzA for nucleic acids increasing as concentrations of c-di-GMP were increased. A mutant PlzA that is incapable of binding c-di-GMP did not bind to any tested nucleic acids. We also determined that PlzA interacts predominantly with the major groove of DNA and that sequence length and G-C content play a role in DNA binding affinity. PlzA is a dual-domain protein with a PilZ-like N-terminal domain linked to a canonical C-terminal PilZ domain. Dissection of the domains demonstrated that the separated N-terminal domain bound nucleic acids independently of c-di-GMP. The C-terminal domain, which includes the c-di-GMP binding motifs, did not bind nucleic acids under any tested conditions. Our data are supported by computational docking, which predicts that c-di-GMP binding at the C-terminal domain stabilizes the overall protein structure and facilitates PlzA-DNA interactions via residues in the N-terminal domain. Based on our data, we propose that levels of c-di-GMP during the various stages of the enzootic life cycle direct PlzA binding to regulatory targets.

An Ensemble Docking Approach for Analyzing and Designing Aptamer Heterodimers Targeting VEGF165

Vascular endothelial growth factor 165 (VEGF165) is a prominent isoform of the VEGF-A protein that plays a crucial role in various angiogenesis-related diseases. It is homodimeric, and each of its monomers is composed of two domains connected by a flexible linker. DNA aptamers, which have emerged as potent therapeutic molecules for many proteins with high specificity and affinity, can also work for VEGF165. A DNA aptamer heterodimer composed of monomers of V7t1 and del5-1 connected by a flexible linker (V7t1:del5-1) exhibits a greater binding affinity with VEGF165 compared to either of the two monomers alone. Although the structure of the complex formed between the aptamer heterodimer and VEGF165 is unknown due to the highly flexible linkers, gaining structural information will still be valuable for future developments. Toward this end of accessing structural information, we adopt an ensemble docking approach here. We first obtain an ensemble of structures for both VEGF165 and the aptamer heterodimer by considering both small- and large-scale motions. We then proceed through an extraction process based on ensemble docking, molecular dynamics simulations, and binding free energy calculations to predict the structures of the VEGF165/V7t1:del5-1 complex. Through the same procedures, we reach a new aptamer heterodimer that bears a locked nucleic acid-modified counterpart of V7t1, namely RNV66:del5-1, which also binds well with VEGF165. We apply the same protocol to the monomeric units V7t1, RNV66, and del5-1 to target VEGF165. We observe that V7t1:del5-1 and RNV66:del5-1 show higher binding affinities with VEGF165 than any of the monomers, consistent with experiments that support the notion that aptamer heterodimers are more effective anti-VEGF165 aptamers than monomeric aptamers. Among the five different aptamers studied here, the newly designed RNV66:del5-1 shows the highest binding affinity with VEGF165. We expect that our ensemble docking approach can help in de novo designs of homo/heterodimeric anti-angiogenic drugs to target the homodimeric VEGF165.

OTUD4 promotes the progression of glioblastoma by deubiquitinating CDK1 and activating MAPK signaling pathway

Glioblastoma, IDH-Wild type (GBM, CNS WHO Grade 4) is a highly heterogeneous and aggressive primary malignant brain tumor with high morbidity, high mortality, and poor patient prognosis. The global burden of GBM is increasing notably due to limited treatment options, drug delivery problems, and the lack of characteristic molecular targets. OTU deubiquitinase 4 (OTUD4) is a potential predictive factor for several cancers such as breast cancer, liver cancer, and lung cancer. However, its function in GBM remains unknown. In this study, we found that high expression of OTUD4 is positively associated with poor prognosis in GBM patients. Moreover, we provided in vitro and in vivo evidence that OTUD4 promotes the proliferation and invasion of GBM cells. Mechanism studies showed that, on the one hand, OTUD4 directly interacts with cyclin-dependent kinase 1 (CDK1) and stabilizes CDK1 by removing its K11, K29, and K33-linked polyubiquitination. On the other hand, OTUD4 binds to fibroblast growth factor receptor 1 (FGFR1) and reduces FGFR1's K6 and K27-linked polyubiquitination, thereby indirectly stabilizing CDK1, ultimately influencing the activation of the downstream MAPK signaling pathway. Collectively, our results revealed that OTUD4 promotes GBM progression via OTUD4-CDK1-MAPK axis, and may be a prospective therapeutic target for GBM treatment.

Transcriptome Analysis Reveals the Molecular Mechanisms of BR Negative Regulatory Factor StBIN2 Maintaining Tuber Dormancy

Potato is an important food crop. After harvest, these tubers will undergo a period of dormancy. Brassinosteroids (BRs) are a new class of plant hormones that regulate plant growth and seed germination. In this study, 500 nM of BR was able to break the dormancy of tubers. Additionally, exogenous BR also upregulated BR signal transduction genes, except for StBIN2. StBIN2 is a negative regulator of BR, but its specific role in tuber dormancy remains unclear. Transgenic methods were used to regulate the expression level of StBIN2 in tubers. It was demonstrated that the overexpression of StBIN2 significantly prolonged tuber dormancy while silencing StBIN2 led to premature sprouting. To further investigate the effect of StBIN2 on tuber dormancy, RNA-Seq was used to analyze the differentially expressed genes in OE-StBIN2, RNAi-StBIN2, and WT tubers. The results showed that StBIN2 upregulated the expression of ABA signal transduction genes but inhibited the expression of lignin synthesis key genes. Meanwhile, it was also found that StBIN2 physically interacted with StSnRK2.2 and StCCJ9. These results indicate that StBIN2 maintains tuber dormancy by mediating ABA signal transduction and lignin synthesis. The findings of this study will help us better understand the molecular mechanisms underlying potato tuber dormancy and provide theoretical support for the development of new varieties using related genes.

Syringaresinol promotes the recovery of spinal cord injury by inhibiting neuron apoptosis via activating the ubiquitination factor E4B/AKT Serine/Threonine kinase signal pathway

Spinal cord injury (SCI) is a serious traumatic disease with no effective treatment. This study aimed to explore the therapeutic effect of syringaresinol on SCI. First, the potential targets and associated signaling pathways of syringaresinol were predicted by bioinformatics analysis and molecular docking. Second, MTT was employed to evaluate cell proliferation rate, Western blot was performed to detect protein expression, RT-qPCR was conducted to detect mRNA expression levels, flow cytometry and 5-ethynyl-2'-deoxyuridine (EDU) staining were used to determine cell apoptosis, and immunofluorescence and immunohistochemistry were used to estimate the expression of RNA binding fox-1 homolog 3 and clipped caspase 3. Basso-Beattie-Bresnahan scores and inclined plate tests were conducted to analyze hindlimb locomotor function. Results showed that syringaresinol could inhibit the apoptosis of glutamate-treated SHSY5Y cells by upregulating the expression of ubiquitination factor E4B (UBE4B) and activating the AKT serine/threonine kinase (AKT) signaling pathway. This effect can be rescued by UBE4B knockdown or AKT pathway inhibition. Syringaresinol remarkably improved locomotor function and increased neuronal survival in SCI rats. Our results suggested that syringaresinol could promote locomotor functional recovery by reducing neuronal apoptosis by activating the UBE4B/AKT signaling pathway.

Genomic Expedition: Deciphering Human Adenovirus Strains from the 2023 Outbreak in West Bengal, India: Insights into Viral Evolution and Molecular Epidemiology

Understanding the genetic dynamics of circulating Human Adenovirus (HAdV) types is pivotal for effectively managing outbreaks and devising targeted interventions. During the West Bengal outbreak of 2022-2023, an investigation into the genetic characteristics and outbreak potential of circulating HAdV types was conducted. Twenty-four randomly selected samples underwent whole-genome sequencing. Analysis revealed a prevalent recombinant strain, merging type 3 and type 7 of human mastadenovirus B1 (HAd-B1) species, indicating the emergence of recent strains of species B in India. Furthermore, distinctions in VA-RNAs and the E3 region suggested that current circulating strains of human mastadenovirus B1 (HAd-B1) possess the capacity to evade host immunity, endure longer within hosts, and cause severe respiratory infections. This study underscores the significance of evaluating the complete genome sequence of HAdV isolates to glean insights into their outbreak potential and the severity of associated illnesses.

Recent Advances and Challenges in Protein Structure Prediction

Artificial intelligence has made significant advances in the field of protein structure prediction in recent years. In particular, DeepMind's end-to-end model, AlphaFold2, has demonstrated the capability to predict three-dimensional structures of numerous unknown proteins with accuracy levels comparable to those of experimental methods. This breakthrough has opened up new possibilities for understanding protein structure and function as well as accelerating drug discovery and other applications in the field of biology and medicine. Despite the remarkable achievements of artificial intelligence in the field, there are still some challenges and limitations. In this Review, we discuss the recent progress and some of the challenges in protein structure prediction. These challenges include predicting multidomain protein structures, protein complex structures, multiple conformational states of proteins, and protein folding pathways. Furthermore, we highlight directions in which further improvements can be conducted.

Repurposing immune boosting and anti-viral efficacy of Parkia bioactive entities as multi-target directed therapeutic approach for SARS-CoV-2: exploration of lead drugs by drug likeness, molecular docking and molecular dynamics simulation methods

The COVID-19 pandemic has caused adverse health (severe respiratory, enteric and systemic infections) and environmental impacts that have threatened public health and the economy worldwide. Drug repurposing and small molecule multi-target directed herbal medicine therapeutic approaches are the most appropriate exploration strategies for SARS-CoV-2 drug discovery. This study identified potential multi-target-directed Parkia bioactive entities against SARS-CoV-2 receptors (S-protein, ACE2, TMPRSS2, RBD/ACE2, RdRp, MPro, and PLPro) using ADMET, drug-likeness, molecular docking (AutoDock, FireDock and HDOCK), molecular dynamics simulation and MM-PBSA tools. One thousand Parkia bioactive entities were screened out by virtual screening and forty-five bioactive phytomolecules were selected based on favorable binding affinity and acceptable pharmacokinetic and pharmacodynamics properties. The binding affinity values of Parkia phyto-ligands (AutoDock: -6.00--10.40 kcal/mol; FireDock: -31.00--62.02 kcal/mol; and HDOCK: -150.0--294.93 kcal/mol) were observed to be higher than the reference antiviral drugs (AutoDock: -5.90--9.10 kcal/mol; FireDock: -35.64--59.35 kcal/mol; and HDOCK: -132.82--211.87 kcal/mol), suggesting a potent modulatory action of Parkia bioactive entities against the SARS-CoV-2. Didymin, rutin, epigallocatechin gallate, epicatechin-3-0-gallate, hyperin, ursolic acid, lupeol, stigmasta-5,24(28)-diene-3-ol, ellagic acid, apigenin, stigmasterol, and campesterol strongly bound with the multiple targets of the SARS-CoV-2 receptors, inhibiting viral entry, attachment, binding, replication, transcription, maturation, packaging and spread. Furthermore, ACE2, TMPRSS2, and MPro receptors possess significant molecular dynamic properties, including stability, compactness, flexibility and total binding energy. Residues GLU-589, and LEU-95 of ACE2, GLN-350, HIS-186, and ASP-257 of TMPRSS2, and GLU-14, MET-49, and GLN-189 of MPro receptors contributed to the formation of hydrogen bonds and binding interactions, playing vital roles in inhibiting the activity of the receptors. Promising results were achieved by developing multi-targeted antiviral Parkia bioactive entities as lead and prospective candidates under a small molecule strategy against SARS-CoV-2 pathogenesis. The antiviral activity of Parkia bioactive entities needs to be further validated by pre-clinical and clinical trials.

Assessing toxicity mechanism of silver nanoparticles by using brine shrimp (Artemia salina) as model

The acute toxicity of silver nanoparticles (AgNPs) in Artemia salina is primarily attributed to the interaction between silver ions (Ag+) and chitin, which constitutes the main structural component of the organism's cuticle. To investigate this interaction and gain a deeper understanding of its nature, geometric optimization calculations and symmetry-adapted perturbation theory (SAPT0) analysis were performed. These calculations aimed to determine the most favorable conformation based on the binding energies of silver ions with chitin and to elucidate the underlying mechanisms of their interaction. The results indicate an ionic effect dependent on the ion state, with simulations revealing that Ag3+ ions have the potential to cause significant deformation of the chitin structure. Furthermore, this study evaluated the behavior of AgNPs using nauplii of A. salina instar I, assessing both mortality rates and cell damage. Toxicity of AgNPs was observed in A. salina at concentrations of 50 and 100 ppm within a timeframe of 24-48 h. The toxicity of AgNPs can be attributed to their interaction with the cuticle and subsequent modification of the chitin structure through the binding of ionic silver. Light microscopy (LM) analysis confirmed the presence of AgNPs in the cuticle, while confocal laser scanning microscopy (CLSM) revealed cellular damage. In addition, this research offers new perspectives on the toxicity mechanism of AgNPs by introducing a novel model that explores the interaction of silver ions with the cuticle of A. salina. These insights are derived from a combination of atomistic models and ecotoxicology assays.

Immunoinformatics Prediction and Protective Efficacy of Vaccine Candidate PiuA-PlyD4 Against Streptococcus Pneumoniae

Purpose

This study was designed to evaluate the immune protective efficacy of the novel Streptococcus pneumoniae (S. pneumoniae) protein vaccine PiuA-PlyD4 through immunoinformatics prediction and in vitro and in vivo experiments.

Methods

In this study, we conducted immunoinformatics prediction and protection analysis on the fusion protein PiuA-PlyD4. The epitope composition of the vaccine was analyzed based on the prediction of B-cell and helper T-cell epitopes. Meanwhile, the molecular docking of PiuA and TLR2/4 was simulated. After immunizing C57BL/6 mice with the prepared vaccine, the biological safety, immunogenicity and conservation were evaluated. By constructing different infection models and from the aspects of adhesion inhibition and cytokines, the protective effect of the fusion protein vaccine PiuA-PlyD4 on S. pneumoniae infection was explored.

Results

PiuA-PlyD4 has abundant B-cell and helper T-cell epitopes and shows a high antigenicity score and structural stability. Molecular docking analysis suggested the potential interaction between PiuA and TLR2/4. The specific antibody titer of fusion protein antiserum was as high as (7.81±2.32) ×105. The protective effect of the immunized mice on nasal and lung colonization was significantly better than that of the control group, and the survival rate against S. pneumoniae infection of serotype 3 reached 50%. Cytokine detection showed that the humoral immune response, Th1, Th2 and Th17 cellular immune pathways were all involved in the process.

Conclusion

The study indicates that PiuA-PlyD4, whether the results are predicted by immunoinformatics or experimentally validated in vivo and in vitro, has good immunogenicity and immunoreactivity and can provide effective protection against S. pneumoniae infection. Therefore, it can be considered a promising prophylactic vaccine candidate for S. pneumoniae.

Phylogenetic and ecophysiological novelty of subsurface mercury methylators in mangrove sediments

Mangrove sediment is a crucial component in the global mercury (Hg) cycling and acts as a hotspot for methylmercury (MeHg) production. Early evidence has documented the ubiquity of well-studied Hg methylators in mangrove superficial sediments; however, their diversity and metabolic adaptation in the more anoxic and highly reduced subsurface sediments are lacking. Through MeHg biogeochemical assay and metagenomic sequencing, we found that mangrove subsurface sediments (20-100 cm) showed a less hgcA gene abundance but higher diversity of Hg methylators than superficial sediments (0-20 cm). Regional-scale investigation of mangrove subsurface sediments spanning over 1500 km demonstrated a prevalence and family-level novelty of Hg-methylating microbial lineages (i.e., those affiliated to Anaerolineae, Phycisphaerae, and Desulfobacterales). We proposed the candidate phylum Zixibacteria lineage with sulfate-reducing capacity as a currently understudied Hg methylator across anoxic environments. Unlike other Hg methylators, the Zixibacteria lineage does not use the Wood-Ljungdahl pathway but has unique capabilities of performing methionine synthesis to donate methyl groups. The absence of cobalamin biosynthesis pathway suggests that this Hg-methylating lineage may depend on its syntrophic partners (i.e., Syntrophobacterales members) for energy in subsurface sediments. Our results expand the diversity of subsurface Hg methylators and uncover their unique ecophysiological adaptations in mangrove sediments.

ComDock: A novel approach for protein-protein docking with an efficient fusing strategy

Protein-protein interaction plays an important role in studying the mechanism of protein functions from the structural perspective. Molecular docking is a powerful approach to detect protein-protein complexes using computational tools, due to the high cost and time-consuming of the traditional experimental methods. Among existing technologies, the template-based method utilizes the structural information of known homologous 3D complexes as available and reliable templates to achieve high accuracy and low computational complexity. However, the performance of the template-based method depends on the quality and quantity of templates. When insufficient or even no templates, the ab initio docking method is necessary and largely enriches the docking conformations. Therefore, it's a feasible strategy to fuse the effectivity of the template-based model and the universality of ab initio model to improve the docking performance. In this study, we construct a new, diverse, comprehensive template library derived from PDB, containing 77,685 complexes. We propose a template-based method (named TemDock), which retrieves the evolutionary relationship between the target sequence and samples in the template library and transfers similar structural information. Then, the target structure is built by superposing on the homologous template complex with TM-align. Moreover, we develop a consensus-based method (named ComDock) to integrate our TemDock and an existing ab initio method (ZDOCK). On 105 targets with templates from Benchmark 5.0, the TemDock and ComDock achieve a success rate of 68.57 % and 71.43 % in the top 10 conformations, respectively. Compared with the HDOCK, ComDock obtains better I-RMSD of hit configurations on 9 targets and more hit models in the top 100 conformations. As an efficient method for protein-protein docking, the ComDock is expected to study protein-protein recognition and reveal the various biological passways that are critical for developing drug discovery. The final results are stored at https://github.com/guofei-tju/mqz_ComDock_docking.

Bioinformatics analysis of multi-epitope peptide vaccines against Hepatitis C virus: a molecular docking study

BACKGROUND

Hepatitis C Virus (HCV) infection is one of the causal agents of liver disease burden. Six multiple antigenic peptides were synthesized including (P315, P412, and P517) plus (P1771, P2121, and P2941) to induce humoral and cellular responses, respectively against HCV infection.

AIM

This paper aimed to employ computational tools to evaluate the efficacy of each peptide individually and to determine the most effective one for better vaccine development and/or immunotherapy.

METHODS

VaxiJen web and AllerTOP servers were used for antigenicity and allergenicity prediction, respectively. The ToxinPred web server was used to investigate the peptide toxicity. Each peptide was docked with its corresponding receptors.

RESULTS

No peptides were expected to be toxic. P315 and P2941 are predicted to have robust antigenic properties, lowest allergenicity, and minimal sOPEP energies. In turn, P315 (derived from gpE1) formed the highest hydrophobic bonds with the BCR and CD81 receptors that will elicit B cell function. P2941 (derived from NS5B) was shown to strongly bind to both CD4 and CD8 receptors that will elicit T cell function.

CONCLUSION

P315 successfully bound to B cell (BCR and CD81) receptors. Also, P2941 is strongly bound to T cell (CD4 and CD8) receptors.

Computational design of novel nanobodies targeting the receptor binding domain of variants of concern of SARS-CoV-2

The COVID-19 pandemic has created an urgent need for effective therapeutic and diagnostic strategies to manage the disease caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). However, the emergence of numerous variants of concern (VOCs) has made it challenging to develop targeted therapies that are broadly specific in neutralizing the virus. In this study, we aimed to develop neutralizing nanobodies (Nbs) using computational techniques that can effectively neutralize the receptor-binding domain (RBD) of SARS-CoV-2 VOCs. We evaluated the performance of different protein-protein docking programs and identified HDOCK as the most suitable program for Nb/RBD docking with high accuracy. Using this approach, we designed 14 novel Nbs with high binding affinity to the VOC RBDs. The Nbs were engineered with mutated amino acids that interacted with key amino acids of the RBDs, resulting in higher binding affinity than human angiotensin-converting enzyme 2 (ACE2) and other viral RBDs or haemagglutinins (HAs). The successful development of these Nbs demonstrates the potential of molecular modeling as a low-cost and time-efficient method for engineering effective Nbs against SARS-CoV-2. The engineered Nbs have the potential to be employed in RBD-neutralizing assays, facilitating the identification of novel treatment, prevention, and diagnostic strategies against SARS-CoV-2.

Developing a peptide to disrupt cohesin head domain interactions

Cohesin mediates the 3-D structure of chromatin and is involved in maintaining genome stability and function. The cohesin core comprises Smc1 and Smc3, elongated-shaped proteins that dimerize through globular domains at their edges, called head and hinge. ATP binding to the Smc heads induces their dimerization and the formation of two active sites, while ATP hydrolysis results in head disengagement. This ATPase cycle is essential for driving cohesin activity. We report on the development of the first cohesin-inhibiting peptide (CIP). The CIP binds Smc3 in vitro and inhibits the ATPase activity of the holocomplex. Treating yeast cells with the CIP prevents cohesin's tethering activity and, interestingly, leads to the accumulation of cohesin on chromatin. CIP3 also affects cohesin activity in human cells. Altogether, we demonstrate the power of peptides to inhibit cohesin in cells and discuss the potential application of CIPs as a therapeutic approach.

Tryptophan-PNA gc Conjugates Self-Assemble to Form Fibers

Peptide nucleic acids and their conjugates to peptides can self-assemble and generate complex architectures. In this work, we explored the self-assembly of PNA dimers conjugated to the dipeptide WW. Our studies suggest that the indole ring of tryptophan promotes aggregation of the conjugates. The onset of fluorescence is observed upon self-assembly. The structure of self-assembled WWgc is concentration-dependent, being spherical at low concentrations and fibrous at high concentrations. As suggested by molecular modeling studies, fibers are stabilized by stacking interactions between tryptophans and Watson-Crick hydrogen bonds between nucleobases.

Isolation and Characterization of scFv Antibody against Internal Ribosomal Entry Site of Enterovirus A71

Enterovirus A71 (EV-A71) is one of the causative agents of hand-foot-mouth disease, which can be associated with neurocomplications of the central nervous system. A limited understanding of the virus's biology and pathogenesis has led to the unavailability of effective anti-viral treatments. The EV-A71 RNA genome carries type I internal ribosomal entry site (IRES) at 5' UTR that plays an essential role in the viral genomic translation. However, the detailed mechanism of IRES-mediated translation has not been elucidated. In this study, sequence analysis revealed that the domains IV, V, and VI of EV-A71 IRES contained the structurally conserved regions. The selected region was transcribed in vitro and labeled with biotin to use as an antigen for selecting the single-chain variable fragment (scFv) antibody from the naïve phage display library. The so-obtained scFv, namely, scFv #16-3, binds specifically to EV-A71 IRES. The molecular docking showed that the interaction between scFv #16-3 and EV-A71 IRES was mediated by the preferences of amino acid residues, including serine, tyrosine, glycine, lysine, and arginine on the antigen-binding sites contacted the nucleotides on the IRES domains IV and V. The so-produced scFv has the potential to develop as a structural biology tool to study the biology of the EV-A71 RNA genome.

Critical Assessment of Methods for Predicting the 3D Structure of Proteins and Protein Complexes

Advances in a scientific discipline are often measured by small, incremental steps. In this review, we report on two intertwined disciplines in the protein structure prediction field, modeling of single chains and modeling of complexes, that have over decades emulated this pattern, as monitored by the community-wide blind prediction experiments CASP and CAPRI. However, over the past few years, dramatic advances were observed for the accurate prediction of single protein chains, driven by a surge of deep learning methodologies entering the prediction field. We review the mainscientific developments that enabled these recent breakthroughs and feature the important role of blind prediction experiments in building up and nurturing the structure prediction field. We discuss how the new wave of artificial intelligence-based methods is impacting the fields of computational and experimental structural biology and highlight areas in which deep learning methods are likely to lead to future developments, provided that major challenges are overcome.

Human IL-32θA94V mutant attenuates monocyte-endothelial adhesion by suppressing the expression of ICAM-1 and VCAM-1 via binding to cell surface receptor integrin αVβ3 and αVβ6 in TNF-α-stimulated HUVECs

Interleukin-32 (IL-32), first reported in 2005, and its isoforms have been the subject of numerous studies investigating their functions in virus infection, cancer, and inflammation. IL-32θ, one of the IL-32 isoforms, has been shown to modulate cancer development and inflammatory responses. A recent study identified an IL-32θ mutant with a cytosine to thymine replacement at position 281 in breast cancer tissues. It means that alanine was also replaced to valine at position 94 in amino acid sequence (A94V). In this study, we investigated the cell surface receptors of IL-32θA94V and evaluated their effect on human umbilical vein endothelial cells (HUVECs). Recombinant human IL-32θA94V was expressed, isolated, and purified using Ni-NTA and IL-32 mAb (KU32-52)-coupled agarose columns. We observed that IL-32θA94V could bind to the integrins αVβ3 and αVβ6, suggesting that integrins act as cell surface receptors for IL-32θA94V. IL-32θA94V significantly attenuated monocyte-endothelial adhesion by inhibiting the expression of Intercellular adhesion molecule-1 (ICAM-1) and vascular cell adhesion molecule-1 (VCAM-1) in tumor necrosis factor (TNF)-α-stimulated HUVECs. IL-32θA94V also reduced the TNF-α-induced phosphorylation of protein kinase B (AKT) and c-jun N-terminal kinases (JNK) by inhibiting phosphorylation of focal adhesion kinase (FAK). Additionally, IL-32θA94V regulated the nuclear translocation of nuclear factor kappa B (NF-κB) and activator protein 1 (AP-1), which are involved in ICAM-1 and VCAM-1 expression. Monocyte-endothelial adhesion mediated by ICAM-1 and VCAM-1 is an important early step in atherosclerosis, which is a major cause of cardiovascular disease. Our findings suggest that IL-32θA94V binds to the cell surface receptors, integrins αVβ3 and αVβ6, and attenuates monocyte-endothelial adhesion by suppressing the expression of ICAM-1 and VCAM-1 in TNF-α-stimulated HUVECs. These results demonstrate that IL-32θA94V can act as an anti-inflammatory cytokine in a chronic inflammatory disease such as atherosclerosis.

A novel variant in the FBP1 gene causes fructose-1,6-bisphosphatase deficiency through increased ubiquitination

Fructose-1,6-bisphosphatase (FBPase) deficiency is an autosomal recessive disorder characterized by impaired gluconeogenesis caused by mutations in the fructose-1,6-bisphosphatase 1 (FBP1) gene. The molecular mechanisms underlying FBPase deficiency caused by FBP1 mutations require investigation. Herein, we report the case of a Chinese boy with FBPase deficiency who presented with hypoglycemia, ketonuria, metabolic acidosis, and repeated episodes of generalized seizures that progressed to epileptic encephalopathy. Whole-exome sequencing revealed compound heterozygous variants, c.761A  >  G (H254R) and c.962C  >  T (S321F), in FBP1. The variants, especially the novel H254R, reduced protein stability and enzymatic activity in patient-derived leukocytes and transfected HepG2 and U251 cells. Mutant FBP1 undergoes enhanced ubiquitination and proteasomal degradation. NEDD4-2 was identified as an E3 ligase for FBP1 ubiquitination in transfected cells and the liver and brain of Nedd4-2 knockout mice. The H254R mutant FBP1 interacted with NEDD4-2 at significantly higher levels than the wild-type control. Our study identified a novel H254R variant of FBP1 underlying FBPase deficiency and elucidated the molecular mechanism underlying the enhanced NEDD4-2-mediated ubiquitination and proteasomal degradation of mutant FBP1.

Dual-Mechanism Glycolipidpeptide with High Antimicrobial Activity, Immunomodulatory Activity, and Potential Application for Combined Antibacterial Therapy

Bacterial drug resistance is becoming increasingly serious, and it is urgent to develop effective antibacterial drugs. Antimicrobial peptides (AMPs), as potential candidates against bacteria, have a broad prospect for development. Herein, a series of AMPs with biological characteristics (net positive charge, amphiphilicity, and α-helix), an AXA motif recognized by membrane bound serine protease type I signal peptidases (SPase I), an FLPII motif to reduce hemolysis, and a monosaccharide motif to improve the stability and activity were designed and synthesized, and among which, the glycolipidpeptide GLP6 (glycosylated LP6 lipopeptide) had excellent antibacterial and immunomodulatory activity, good stability and biocompatibility, and excellent biofilm eradication and membrane penetrating activity. The positively charged spherical aggregates formed by self-assembly of GLP6 could encapsulate tetracycline (TC) to form GLP6@TC with a sustained-release effect, which could enhance the sensitivity of bacteria to the antibiotic and realize combined sterilization. The results of acute peritonitis and bacterial keratitis showed that GLP6@TC had a good combined antibacterial effect and the ability to inhibit interleukin-2 (IL-2), which could significantly reduce the inflammatory response while treating bacterial infection, and it had great potential for application. The results of computer molecular docking showed the AXA motif could effectively bind to SPase I, which was consistent with the results of biological experiments. In general, the study could provide a perspective for the design of AMPs and combined antibacterial therapy.

Validation of HIV-1 MA Shell Structural Arrangements and Env Protein Interactions Predict a Role of the MA Shell in Viral Maturation

The molecular structure of the type 1 human immunodeficiency virus (HIV-1) is tightly linked to the mechanism of viral entry. The spike envelope (Env) glycoproteins and their interaction with the underlying matrix (MA) shell have emerged as key components of the entry mechanism. Microscopy evidence suggests that the MA shell does not span the entire inner lipid surface of the virus, producing a region of the virus that completely lacks an MA shell. Interestingly, evidence also suggests that Env proteins cluster during viral maturation and, thus, it is likely that this event takes place in the region of the virus that lacks an MA shell. We have previously called this part of the virus a fusion hub to highlight its importance during viral entry. While the structure of the MA shell is in contention due to the unaddressed inconsistencies between its reported hexagonal arrangement and the physical plausibility of such a structure, it is possible that a limited number of MA hexagons could form. In this study, we measured the size of the fusion hub by analysing the cryo-EM maps of eight HIV-1 particles and measured the size of the MA shell gap to be 66.3 nm ± 15.0 nm. We also validated the feasibility of the hexagonal MA shell arrangement in six reported structures and determined the plausible components of these structures that do not violate geometrical limitations. We also examined the cytosolic domain of Env proteins and discovered a possible interaction between adjacent Env proteins that could explain the stability of cluster formation. We present an updated HIV-1 model and postulate novel roles of the MA shell and Env structure.

Development of KLA-RGD integrated lipopeptide with the effect of penetrating membrane which target the αvβ3 receptor and the application of combined antitumor

Herein, an amphiphilic cationic anticancer lipopeptide P17 with α-helical structure was synthesized based on the integration of KLA and RGD peptide which could bind with the receptor of integrin α_vβ₃. P17 could self assemble into stable spherical aggregates in aqueous solution, and which could encapsulate the anticancer drugs (Such as Dox) to form P17 @ Anticancer drug nanomedicine (P17 @ Dox nanomedicine) which could play the combined therapy of P17 and anticancer drugs (Dox). The encapsulation efficiency of P17 aggregates to Dox was 80.4 ± 3.2 %, and the release behavior of P17 @ Dox nanomedicine in vitro had the characteristics of slow-release and pH responsiveness. The experiments in vitro showed that P17 lipopeptide had low cytotoxicity, high serum stability, low hemolysis and strong penetrating membrane ability. The release of Dox from P17 @ Dox in cells was time-dependment, and the P17 @ Dox nanomedicine had a good anticancer effect. The experiments in vivo showed that P17 and P17 @ Dox nanomedicine both had low hemolysis, and P17 @ Dox nanomedicine could effectively inhibit tumor growth and significantly reduce the toxic and side effects of Dox. Molecular docking experiments showed that P17 could effectively interact with the receptor of integrin α_vβ₃. In conclusion, P17 lipopeptide could be used as an excellent drug carrier and play the combined anticancer effect of P17 and anticancer drugs.

Structural evolution of an amphibian-specific globin: A computational evolutionary biochemistry approach

Studies on the globin family are continuously revealing insights into the mechanisms of gene and protein evolution. The rise of a new globin gene type in Pelobatoidea and Neobatrachia (Amphibia:Anura) from an α-globin precursor provides the opportunity to investigate the genetic and physical mechanisms underlying the origin of new protein structural and functional properties. This amphibian-specific globin (globin A/GbA) discovered in the heart of Rana catesbeiana is a monomer. As the ancestral oligomeric state of α-globins is a homodimer, we inferred that the ancestral state was lost somewhere in the GbA lineage. Here, we combined computational molecular evolution with structural bioinformatics to determine the extent to which the loss of the homodimeric state is pervasive in the GbA clade. We also characterized the loci of GbA genes in Bufo bufo. We found two GbA clades in Neobatrachia. One was deleted in Ranidae, but retained and expanded to yield a new globin cluster in Bufonidae species. Loss of the ancestral oligomeric state seems to be pervasive in the GbA clade. However, a taxonomic sampling that includes more Pelobatoidea, as well as early Neobatrachia, lineages would be necessary to determine the oligomeric state of the last common ancestor of all GbA. The evidence presented here points out a possible loss of oligomerization in Pelobatoidea GbA as a result of amino acid substitutions that weaken the homodimeric state. In contrast, the loss of oligomerization in both Neobatrachia GbA clades was linked to independent deletions that disrupted many packing contacts at the homodimer interface.

Characterization of phi112, a Molecular Marker Tightly Linked to the o2 Gene of Maize, and Its Utilization in Multiplex PCR for Differentiating Normal Maize from QPM

Quality Protein Maize (QPM) contains higher amounts of essential amino acids lysine and tryptophan. The QPM phenotype is based on regulating zein protein synthesis by opaque2 transcription factor. Many gene modifiers act to optimize the amino acid content and agronomic performance. An SSR marker, phi112, is present upstream of the opaque2 DNA gene. Its analysis has shown the presence of transcription factor activity. The functional associations of opaque2 have been determined. The putative transcription factor binding at phi112 marked DNA was identified through computational analysis. The present study is a step towards understanding the intricate network of molecular interactions that fine-tune the QPM genotype to influence maize protein quality. In addition, a multiplex PCR assay for differentiation of QPM from normal maize is shown, which can be used for Quality Control at various stages of the QPM value chain.

A Putative New Role of Tv-PSP1 Recognizes IRE and ERE Hairpin Structures from Trichomonas vaginalis

To understand whether protein Tv-PSP1 from Trichomonas vaginalis recognizes mRNA parasite stem-loop structures, we conducted REMSA and intrinsic fluorescence assays. We found the recombinant Tv-PSP1 structure, determined with X-ray crystallography, showed unusual thermal stability of the quaternary structure, associated with a disulfide bridge CYS76-CYS104. To gain deeper insight into the Tv-PSP1 interaction with mRNA stem-loops (mRNAsl) and its relationship with thermal stability, we also used an integrated computational protocol that combined molecular dynamics simulations, docking assays, and binding energy calculations. Docking models allowed us to determine a putative contact surface interaction region between Tv-PSP1 and mRNAsl. We determined the contributions of these complexes to the binding free energy (ΔG_b) in the electrostatic (ΔG_elec) and nonelectrostatic (ΔG_non-elec) components using the Adaptive Poisson-Boltzmann Solver (APBS) program. We are the first, to the best of our knowledge, to show the interaction between Tv-PSP1 and the stem-loop structures of mRNA.

DNA Aptamer Selected against Esophageal Squamous Cell Carcinoma for Tissue Imaging and Targeted Therapy with Integrin β1 as a Molecular Target

Esophageal cancer, especially esophageal squamous cell carcinoma (ESCC), poses a serious threat to human health. It is urgently needed to develop recognition tools and discover molecular targets for early diagnosis and targeted therapy of esophageal cancer. Here, we developed several DNA aptamers that can bind to ESCC KYSE410 cells with a nanomolar range of dissociation constants by using cell-based systematic evolution of ligands by exponential enrichment (cell-SELEX). The selected A2 aptamer is found to strongly bind with multiple cancer cells, including several ESCC cell lines. Tissue imaging displayed that the A2 aptamer can specifically recognize clinical ESCC tissues but not the adjacent tissues. Moreover, we identified integrin β1 as the binding target of A2 through pull-down and RNA interference assays. Meanwhile, molecular docking and mutation assays suggested that A2 probably binds to integrin β1 through the nucleotides of DA16-DG21, and competitive binding and structural alignment assays indicated that A2 shares the overlapped binding sites with laminin and arginine-glycine-aspartate ligands. Furthermore, we engineered A2-induced targeted therapy for ESCC. By constructing A2-tethered DNA nanoassemblies carrying multiple doxorubicin (Dox) molecules as antitumor agents, inhibition of tumor cell growth in vitro and in vivo was achieved. This work provides a useful targeting tool and a potential molecular target for cancer diagnosis and targeted therapy and is helpful for understanding the integrin mechanism and developing integrin inhibitors.

HDOCK update for modeling protein-RNA/DNA complex structures

Protein-nucleic acid interactions are involved in various cellular processes. Therefore, determining the structures of protein-nucleic acid complexes can provide insights into the mechanisms of the interactions and thus guide the rational drug design to modulate these interactions. Due to the high cost and technical difficulties of solving complex structures experimentally, computational modeling such as molecular docking has been playing an important role in the study of molecular interactions. In order to make it easier for researchers to obtain biomolecular complex structures through molecular docking, we developed the HDOCK server for protein-protein and protein-RNA/DNA docking (accessed at http://hdock.phys.hust.edu.cn/). Since its first release in 2017, HDOCK has been widely used in the scientific community. As nucleic acids may include single-stranded (ss) RNA/DNA and double-stranded (ds) RNA/DNA, we now present an updated version of HDOCK, which offers new options for structural modeling of ssRNA, ssDNA, dsRNA, and dsDNA. We hope this update will better help the scientific community solve important biological problems, thereby advancing the field. In this article, we describe the general protocol of HDOCK with emphasis on the new functions on RNA/DNA modeling. Several application examples are also given to illustrate the usage of the new functions.

Protein-protein interaction prediction with deep learning: A comprehensive review

Most proteins perform their biological function by interacting with themselves or other molecules. Thus, one may obtain biological insights into protein functions, disease prevalence, and therapy development by identifying protein-protein interactions (PPI). However, finding the interacting and non-interacting protein pairs through experimental approaches is labour-intensive and time-consuming, owing to the variety of proteins. Hence, protein-protein interaction and protein-ligand binding problems have drawn attention in the fields of bioinformatics and computer-aided drug discovery. Deep learning methods paved the way for scientists to predict the 3-D structure of proteins from genomes, predict the functions and attributes of a protein, and modify and design new proteins to provide desired functions. This review focuses on recent deep learning methods applied to problems including predicting protein functions, protein-protein interaction and their sites, protein-ligand binding, and protein design.

Identification of antiviral peptide inhibitors for receptor binding domain of SARS-CoV-2 omicron and its sub-variants: an in-silico approach

Omicron, a variant of concern (VOC) of SARS-CoV-2, emerged in South Africa in November 2021. Omicron has been continuously acquiring a series of new mutations, especially in the spike (S) protein that led to high infectivity and transmissibility. Peptides targeting the receptor-binding domain (RBD) of the spike protein by which omicron and its variants attach to the host receptor, angiotensin-converting enzyme (ACE2) can block the viral infection at the first step. This study aims to identify antiviral peptides from the Antiviral peptide database (AVPdb) and HIV-inhibitory peptide database (HIPdb) against the RBD of omicron by using a molecular docking approach. The lead RBD binder peptides obtained through molecular docking were screened for allergenicity and physicochemical criteria (isoelectric point (pI) and net charge) required for peptide-based drugs. The binding affinity of the best five peptide inhibitors with the RBD of omicron was validated further by molecular dynamics (MD) simulation. Our result introduces five antiviral peptides, including AVP1056, AVP1059, AVP1225, AVP1801, and HIP755, that may effectively hinder omicron-host interactions. It is worth mentioning that all the three major sub-variants of omicron, BA.1 (B.1.1.529.1), BA.2 (B.1.1.529.2), and BA.3 (B.1.1.529.3), exhibits conserved ACE-2 interacting residues. Hence, the screened antiviral peptides with similar affinity can also interrupt the RBD-mediated invasion of different major sub-variants of omicron. Altogether, these peptides can be considered in the peptide-based therapeutics development for omicron treatment after further experimentation.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13205-022-03258-4.

Identification of a HTT-specific binding motif in DNAJB1 essential for suppression and disaggregation of HTT

Huntington’s disease is a neurodegenerative disease caused by an expanded polyQ stretch within Huntingtin (HTT) that renders the protein aggregation-prone, ultimately resulting in the formation of amyloid fibrils. A trimeric chaperone complex composed of Hsc70, DNAJB1 and Apg2 can suppress and reverse the aggregation of HTTExon1Q₄₈. DNAJB1 is the rate-limiting chaperone and we have here identified and characterized the binding interface between DNAJB1 and HTTExon1Q₄₈. DNAJB1 exhibits a HTT binding motif (HBM) in the hinge region between C-terminal domains (CTD) I and II and binds to the polyQ-adjacent proline rich domain (PRD) of soluble as well as aggregated HTT. The PRD of HTT represents an additional binding site for chaperones. Mutation of the highly conserved H244 of the HBM of DNAJB1 completely abrogates the suppression and disaggregation of HTT fibrils by the trimeric chaperone complex. Notably, this mutation does not affect the binding and remodeling of any other protein substrate, suggesting that the HBM of DNAJB1 is a specific interaction site for HTT. Overexpression of wt DNAJB1, but not of DNAJB1^H244A can prevent the accumulation of HTTExon1Q₉₇ aggregates in HEK293 cells, thus validating the biological significance of the HBM within DNAJB1.

Ayala Mariscal et al have identified and characterized the interface of pathogenic Huntingtin and the molecular chaperone DNAJB1. Histidine-244 of the C-terminal domain of DNAJB1 is a key residues for binding to the poly-proline region of HTT. This binding site is specific for the interaction with Huntingtin.

Methylphenidate Analogues as a New Class of Potential Disease-Modifying Agents for Parkinson's Disease: Evidence from Cell Models and Alpha-Synuclein Transgenic Mice

Parkinson's disease (PD) is characterized by dopaminergic nigrostriatal neurons degeneration and Lewy body pathology, mainly composed of α-synuclein (αSyn) fibrillary aggregates. We recently described that the neuronal phosphoprotein Synapsin III (Syn III) participates in αSyn pathology in PD brains and is a permissive factor for αSyn aggregation. Moreover, we reported that the gene silencing of Syn III in a human αSyn transgenic (tg) mouse model of PD at a pathological stage, manifesting marked insoluble αSyn deposits and dopaminergic striatal synaptic dysfunction, could reduce αSyn aggregates, restore synaptic functions and motor activities and exert neuroprotective effects. Interestingly, we also described that the monoamine reuptake inhibitor methylphenidate (MPH) can recover the motor activity of human αSyn tg mice through a dopamine (DA) transporter-independent mechanism, which relies on the re-establishment of the functional interaction between Syn III and α-helical αSyn. These findings support that the pathological αSyn/Syn III interaction may constitute a therapeutic target for PD. Here, we studied MPH and some of its analogues as modulators of the pathological αSyn/Syn III interaction. We identified 4-methyl derivative I-threo as a lead candidate modulating αSyn/Syn III interaction and having the ability to reduce αSyn aggregation in vitro and to restore the motility of αSyn tg mice in vivo more efficiently than MPH. Our results support that MPH derivatives may represent a novel class of αSyn clearing agents for PD therapy.

Novel Design of RNA Aptamers as Cancer Inhibitors and Diagnosis Targeting the Tyrosine Kinase Domain of the NT-3 Growth Factor Receptor Using a Computational Sequence-Based Approach

Aptamers, the nucleic acid analogs of antibodies, bind to their target molecules with remarkable specificity and sensitivity, making them promising diagnostic and therapeutic tools. The systematic evolution of ligands by exponential enrichment (SELEX) is time-consuming and expensive. However, regardless of those issues, it is the most used in vitro method for selecting aptamers. Therefore, recent studies have used computational approaches to reduce the time and cost associated with the synthesis and selection of aptamers. In an effort to present the potential of computational techniques in aptamer selection, a simple sequence-based method was used to design a 69-nucleotide long aptamer (mod_09) with a relatively stable structure (with a minimum free energy of -32.2 kcal/mol) and investigate its binding properties to the tyrosine kinase domain of the NT-3 growth factor receptor, for the first time, by employing computational modeling and docking tools.

Sigma-1 receptor attenuates osteoclastogenesis by promoting ER-associated degradation of SERCA2

Sigma-1 receptor (Sigmar1) is a specific chaperone located in the mitochondria-associated endoplasmic reticulum membrane (MAM) and plays a role in several physiological processes. However, the role of Sigmar1 in bone homeostasis remains unknown. Here, we show that mice lacking Sigmar1 exhibited severe osteoporosis in an ovariectomized model. In contrast, overexpression of Sigmar1 locally alleviated the osteoporosis phenotype. Treatment with Sigmar1 agonists impaired both human and mice osteoclast formation in vitro. Mechanistically, SERCA2 was identified to interact with Sigmar1 based on the immunoprecipitation-mass spectrum (IP-MS) and co-immunoprecipitation (co-IP) assays, and Q615 of SERCA2 was confirmed to be the critical residue for their binding. Furthermore, Sigmar1 promoted SERCA2 degradation through Hrd1/Sel1L-dependent ER-associated degradation (ERAD). Ubiquitination of SERCA2 at K460 and K541 was responsible for its proteasomal degradation. Consequently, inhibition of SERCA2 impeded Sigmar1 deficiency enhanced osteoclastogenesis. Moreover, we found that dimemorfan, an FDA-approved Sigmar1 agonist, effectively rescued bone mass in various established bone-loss models. In conclusion, Sigmar1 is a negative regulator of osteoclastogenesis, and activation of Sigmar1 by dimemorfan may be a potential treatment for osteoporosis in clinical practice.

Fibronectin containing alternatively spliced extra domain A interacts at the central and c-terminal domain of Toll-like receptor-4

Extra domain A of cellular fibronectin (FN-EDA) is known to cause insulin resistance, atherosclerosis, tissue fibrosis, ischemic stroke and exaggerated myocardial reperfusion injury through Toll-like receptor 4 (TLR4). However, the FN-EDA-TLR4 interacting site is not well established. Therefore, in-silico approaches have been used to study FN-EDA and TLR4 interactions at the interface. In the present study, molecular docking studies of FN-EDA with TLR4-myeloid differentiation factor 2 (MD2) heterodimer have been performed to unravel the FN-EDA-TLR4 interacting sequence. Furthermore, the modulatory role of FN-EDA adjacent domains FNIII(11) and FNIII(12) on its interaction with TLR4-MD2 was investigated. The results show that FN-EDA interacting sequence “SPEDGIRELF” selectively interacts with TLR4 directly near its central and C-terminal domain region. The regulatory domains, FN type III 11 facilitate and 12 impede the FN-EDA-TLR4 interaction. Furthermore, the molecular dynamic simulation studies confirmed that FN-EDA forms a stable complex with TLR4-MD2 heterodimer. In conclusion, FN-EDA interacts and forms a stable complex through its “SPEDGIRELF” sequence at the central and C-terminal domain region of TLR4. The revelation of FN-EDA and TLR4 interacting sites may help design novel therapeutics for drug discovery research.

In silico design and analyses of a multi-epitope vaccine against Crimean-Congo hemorrhagic fever virus through reverse vaccinology and immunoinformatics approaches

Crimean Congo Hemorrhagic Fever virus (CCHFV) is a deadly human pathogen that causes an emerging zoonotic disease with a broad geographic spread, especially in Africa, Asia, and Europe, and the second most common viral hemorrhagic fever and widely transmitted tick-borne viral disease. Following infection, the patients are presented with a variety of clinical manifestations and a fatality rate of 40%. Despite the high fatality rate, there are unmet clinical interventions, as no antiviral drugs or vaccines for CCHF have been approved. Immunoinformatics pipeline and reverse vaccinology were used in this study to design a multi-epitope vaccine that may elicit a protective humoral and cellular immune response against Crimean-Congo hemorrhagic fever virus infection. Three essential virulent and antigenic proteins (S, M, and L) were used to predict seven CTL and 18 HTL epitopes that were non-allergenic, antigenic, IFN-γ inducing, and non-toxic. The epitopes were connected using linkers and 50S ribosomal protein L7/L12 was used as an adjuvant and raised a multi-epitope vaccine (MEV) that is 567 amino acids long. Molecular docking and simulation of the predicted 3D structure of the MEV with the toll-like (TLR2, TLR3, and TLR4) receptors and major histocompatibility complex (MCH-I and MCH-II) indicate high interactions and stability of the complexes, MM-GBSA free binding energy calculation revealed a favourable protein-protein complex. Maximum MEV expression was achieved with a CAI value of 0.98 through in silico cloning in the Drosophila melanogaster host. According to the immune simulation, IgG1, T-helper cells, T-cytotoxic cells, INF-γ, and IL-2 were predicted to be significantly elevated. These robust computational analyses demonstrated that the proposed MEV is effective in preventing CCHFV infections. However, it is still necessary to conduct both in vitro and in vivo experiments to validate the potential of the vaccine.

HIF-1-Dependent Induction of β3 Adrenoceptor: Evidence from the Mouse Retina

A major player in the homeostatic response to hypoxia is the hypoxia-inducible factor (HIF)-1 that transactivates a number of genes involved in neovessel proliferation in response to low oxygen tension. In the retina, hypoxia overstimulates β-adrenoceptors (β-ARs) which play a key role in the formation of pathogenic blood vessels. Among β-ARs, β3-AR expression is increased in proliferating vessels in concomitance with increased levels of HIF-1α and vascular endothelial growth factor (VEGF). Whether, similarly to VEGF, hypoxia-induced β3-AR upregulation is driven by HIF-1 is still unknown. We used the mouse model of oxygen-induced retinopathy (OIR), an acknowledged model of retinal angiogenesis, to verify the hypothesis of β3-AR transcriptional regulation by HIF-1. Investigation of β3-AR regulation over OIR progression revealed that the expression profile of β3-AR depends on oxygen tension, similar to VEGF. The additional evidence that HIF-1α stabilization decouples β3-AR expression from oxygen levels further indicates that HIF-1 regulates the expression of the β3-AR gene in the retina. Bioinformatics predicted the presence of six HIF-1 binding sites (HBS #1-6) upstream and inside the mouse β3-AR gene. Among these, HBS #1 has been identified as the most suitable HBS for HIF-1 binding. Chromatin immunoprecipitation-qPCR demonstrated an effective binding of HIF-1 to HBS #1 indicating the existence of a physical interaction between HIF-1 and the β3-AR gene. The additional finding that β3-AR gene expression is concomitantly activated indicates the possibility that HIF-1 transactivates the β3-AR gene. Our results are indicative of β3-AR involvement in HIF-1-mediated response to hypoxia.

Computational Tools and Strategies to Develop Peptide-Based Inhibitors of Protein-Protein Interactions

Protein-protein interactions play crucial and subtle roles in many biological processes and modifications of their fine mechanisms generally result in severe diseases. Peptide derivatives are very promising therapeutic agents for modulating protein-protein associations with sizes and specificities between those of small compounds and antibodies. For the same reasons, rational design of peptide-based inhibitors naturally borrows and combines computational methods from both protein-ligand and protein-protein research fields. In this chapter, we aim to provide an overview of computational tools and approaches used for identifying and optimizing peptides that target protein-protein interfaces with high affinity and specificity. We hope that this review will help to implement appropriate in silico strategies for peptide-based drug design that builds on available information for the systems of interest.

How much metagenome data is needed for protein structure prediction: The advantages of targeted approach from the ecological and evolutionary perspectives

It has been proven that three-dimensional protein structures could be modeled by supplementing homologous sequences with metagenome sequences. Even though a large volume of metagenome data is utilized for such purposes, a significant proportion of proteins remain unsolved. In this review, we focus on identifying ecological and evolutionary patterns in metagenome data, decoding the complicated relationships of these patterns with protein structures, and investigating how these patterns can be effectively used to improve protein structure prediction. First, we proposed the metagenome utilization efficiency and marginal effect model to quantify the divergent distribution of homologous sequences for the protein family. Second, we proposed that the targeted approach effectively identifies homologous sequences from specified biomes compared with the untargeted approach's blind search. Finally, we determined the lower bound for metagenome data required for predicting all the protein structures in the Pfam database and showed that the present metagenome data is insufficient for this purpose. In summary, we discovered ecological and evolutionary patterns in the metagenome data that may be used to predict protein structures effectively. The targeted approach is promising in terms of effectively extracting homologous sequences and predicting protein structures using these patterns.

The Healing Power of Clean Rivers: In Silico Evaluation of the Antipsoriatic Potential of Apiin and Hyperoside Plant Metabolites Contained in River Waters

Humanity may benefit greatly from intact riverine ecosystems not only because they supply water to be used in the most common human activities, but also for the effects that clean rivers can have on human health. Herein, we used a computational approach to show that some phytochemicals produced by riparian plants as secondary metabolites, which are naturally released into river waters, can have therapeutic properties. These include antipsoriatic activities which we demonstrated in silico by modelling the interaction of apiin, guanosine and hyperoside, a few main river plant metabolites, with NF-kB, IL-17 and IL-36, which are recognized targets involved in psoriasis disease. In particular, we found that apiin and hyperoside are endowed with docking energies and binding affinities which are more favorable than the known reference inhibitors of the three protein targets whilst, in silico, guanosine shows comparable activity with respect to the inhibitors of IL-36 and NF-kB. The low skin permeation (logKp < −8) we predicted for apiin and hyperoside led us to hypothesize their possible utilization as topic antipsoriatic therapeutics, and in particular after PAINS (pan-assay interference compounds) score evaluation, we reached the conclusion that apiin, with no predicted tendency to react nonspecifically with the numerous targets involved in the biological cellular pathways, is particularly interesting for the desired therapeutic application.

Destabilization of macrophage migration inhibitory factor by 4-IPP reduces NF-κB/P-TEFb complex-mediated c-Myb transcription to suppress osteosarcoma tumourigenesis

BACKGROUND

As an inflammatory factor and oncogenic driver protein, the pleiotropic cytokine macrophage migration inhibitory factor (MIF) plays a crucial role in the osteosarcoma microenvironment. Although 4-iodo-6-phenylpyrimidine (4-IPP) can inactivate MIF biological functions, its anti-osteosarcoma effect and molecular mechanisms have not been investigated. In this study, we identified the MIF inhibitor 4-IPP as a specific double-effector drug for osteosarcoma with both anti-tumour and anti-osteoclastogenic functions.

METHODS

The anti-cancer effects of 4-IPP were evaluated by wound healing assay, cell cycle analysis, colony formation assay, CCK-8 assay, apoptosis analysis, and Transwell migration/invasion assays. Through the application of a luciferase reporter, chromatin immunoprecipitation assays, and immunofluorescence and coimmunoprecipitation analyses, the transcriptional regulation of the NF-κB/P-TEFb complex on c-Myb- and STUB1-mediated proteasome-dependent MIF protein degradation was confirmed. The effect of 4-IPP on tumour growth and metastasis was assessed using an HOS-derived tail vein metastasis model and subcutaneous and orthotopic xenograft tumour models.

RESULTS

In vitro, 4-IPP significantly reduced the proliferation and metastasis of osteosarcoma cells by suppressing the NF-κB pathway. 4-IPP hindered the binding between MIF and CD74 as well as p65. Moreover, 4-IPP inhibited MIF to interrupt the formation of downstream NF-κB/P-TEFb complexes, leading to the down-regulation of c-Myb transcription. Interestingly, the implementation of 4-IPP can mediate small molecule-induced MIF protein proteasomal degradation via the STUB1 E3 ligand. However, 4-IPP still interrupted MIF-mediated communication between osteosarcoma cells and osteoclasts, thus promoting osteoclastogenesis. Remarkably, 4-IPP strongly reduced HOS-derived xenograft osteosarcoma tumourigenesis and metastasis in an in vivo mouse model.

CONCLUSIONS

Our findings demonstrate that the small molecule 4-IPP targeting the MIF protein exerts an anti-osteosarcoma effect by simultaneously inactivating the biological functions of MIF and promoting its proteasomal degradation. Direct destabilization of the MIF protein with 4-IPP may be a promising therapeutic strategy for treating osteosarcoma.

Limits and potential of combined folding and docking

MOTIVATION

In the last decade, de novo protein structure prediction accuracy for individual proteins has improved significantly by utilising deep learning (DL) methods for harvesting the co-evolution information from large multiple sequence alignments (MSAs). The same approach can, in principle, also be used to extract information about evolutionary-based contacts across protein-protein interfaces. However, most earlier studies have not used the latest DL methods for inter-chain contact distance prediction. This article introduces a fold-and-dock method based on predicted residue-residue distances with trRosetta.

RESULTS

The method can simultaneously predict the tertiary and quaternary structure of a protein pair, even when the structures of the monomers are not known. The straightforward application of this method to a standard dataset for protein-protein docking yielded limited success. However, using alternative methods for generating MSAs allowed us to dock accurately significantly more proteins. We also introduced a novel scoring function, PconsDock, that accurately separates 98% of correctly and incorrectly folded and docked proteins. The average performance of the method is comparable to the use of traditional, template-based or ab initio shape-complementarity-only docking methods. Moreover, the results of conventional and fold-and-dock approaches are complementary, and thus a combined docking pipeline could increase overall docking success significantly. This methodology contributed to the best model for one of the CASP14 oligomeric targets, H1065.

AVAILABILITY AND IMPLEMENTATION

All scripts for predictions and analysis are available from https://github.com/ElofssonLab/bioinfo-toolbox/ and https://gitlab.com/ElofssonLab/benchmark5/. All models joined alignments, and evaluation results are available from the following figshare repository https://doi.org/10.6084/m9.figshare.14654886.v2.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

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.