Computational identification of self-inhibitory peptides from envelope proteins

Designing Self-Inhibitory fusion peptide analogous to viral spike protein against novel severe acute respiratory syndrome (SARS-CoV-2)

COVID-19 is a highly contagious viral infection caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which is declared pandemic by the World Health Organization (WHO). The spike protein of SARS-CoV-2 is a key component playing a pivotal role in facilitating viral fusion as well as release of genome into the host cell. Till date there is no clinically approved vaccine or drug available against Covid-19. We designed four hydrophobic inhibitory peptides (ITPs) based on WWIHS (Wimley and White interfacial hydrophobicity scale) score, targeting the HR1 domain of spike protein. Two inhibitory peptides out of four have a strong affinity to the hydrophobic surface of HR1 domain in pre-fusion spike protein. The MD simulation result showed the strong accommodation of ITPs with HR1 domain surface. These self-inhibitory peptides mimic the function of HR2 by binding to HR1 domain, thus inhibiting the formation of HR1-HR2 post-fusion complex, which is a key structure for virus-host tropism.Communicated by Ramaswamy H. Sarma.

Hit-to-Lead Short Peptides against Dengue Type 2 Envelope Protein: Computational and Experimental Investigations

Data from the World Health Organisation show that the global incidence of dengue infection has risen drastically, with an estimated 400 million cases of dengue infection occurring annually. Despite this worrying trend, there is still no therapeutic treatment available. Herein, we investigated short peptide fragments with a varying total number of amino acid residues (peptide fragments) from previously reported dengue virus type 2 (DENV2) peptide-based inhibitors, DN58wt (GDSYIIIGVEPGQLKENWFKKGSSIGQMF), DN58opt (TWWCFYFCRRHHPFWFFYRHN), DS36wt (LITVNPIVTEKDSPVNIEAE), and DS36opt (RHWEQFYFRRRERKFWLFFW), aided by in silico approaches: peptide–protein molecular docking and 100 ns of molecular dynamics (MD) simulation via molecular mechanics using Poisson–Boltzmann surface area (MMPBSA) and molecular mechanics generalised Born surface area (MMGBSA) methods. A library of 11,699 peptide fragments was generated, subjected to in silico calculation, and the candidates with the excellent binding affinity and shown to be stable in the DI-DIII binding pocket of DENV2 envelope (E) protein were determined. Selected peptides were synthesised using conventional Fmoc solid-phase peptide chemistry, purified by RP-HPLC, and characterised using LCMS. In vitro studies followed, to test for the peptides’ toxicity and efficacy in inhibiting the DENV2 growth cycle. Our studies identified the electrostatic interaction (from free energy calculation) to be the driving stabilising force for the E protein–peptide interactions. Five key E protein residues were also identified that had the most interactions with the peptides: (polar) LYS36, ASN37, and ARG350, and (nonpolar) LEU351 and VAL354; these residues might play crucial roles in the effective binding interactions. One of the peptide fragments, DN58opt_8-13 (PFWFFYRH), showed the best inhibitory activity, at about 63% DENV2 plague reduction, compared with no treatment. This correlates well with the in silico studies in which the peptide possessed the lowest binding energy (−9.0 kcal/mol) and was maintained steadily within the binding pocket of DENV2 E protein during the MD simulations. This study demonstrates the use of computational studies to expand research on lead optimisation of antiviral peptides, thus explaining the inhibitory potential of the designed peptides.

Computational-aided design: minimal peptide sequence to block dengue virus transmission into cells

Dengue virus (DV) infection is one of the main public health concerns, affecting approximately 390 million people worldwide, as reported by the World Health Organization. Yet, there is no antiviral treatment for DV infection. Therefore, the development of potent and nontoxic anti-DV, as a complement for the existing treatment strategies, is urgently needed. Herein, we investigate a series of small peptides inhibitors of DV antiviral activity targeting the entry process as the promising strategy to block DV infection. The peptides were designed based on our previously reported peptide sequence, DN58opt (TWWCFYFCRRHHPFWFFYRHN), to identify minimal effective inhibitory sequence through molecular docking and dynamics studies. The in silico designed peptides were synthesized using conventional Fmoc solid-phase peptide synthesis chemistry, purified by RP-HPLC and characterized using LCMS. Later, they were screened for their antiviral activity. One of the peptides, AC 001, was able to reduce about 40% of DV plaque formation. This observation correlates well with the molecular mechanics-Poisson-Boltzmann surface area (MM-PBSA) analysis - AC 001 showed the most favorable binding affinity through 60 ns simulations. Pairwise residue decomposition analysis has revealed four key residues that contributed to the binding of these peptides into the DV2 E protein pocket. This work identifies the minimal peptide sequence required to inhibit DV replication and explains the behavior observed on an atomic level using computational study.Communicated by Ramaswamy H. Sarma.

Orientation-dependent toxic effect of human papillomavirus type 33 long control region DNA in Escherichia coli cells

The functional analysis of human papillomavirus (HPV) sequence variation requires the molecular cloning of different genomic regions of virus variants. In this study, we report an unexpected difficulty experienced when trying to clone HPV33 long control region (LCR) variants in Escherichia coli. Standard cloning strategies proved to be inappropriate to clone HPV33 LCR variants in the forward orientation into a eukaryotic reporter vector (pGL2-Basic). However, by slight modification of culture conditions (incubation at 25 °C instead of 37 °C), constructs containing the HPV33 LCR variants in the forward orientation were obtained. Transformation experiments performed with different HPV33 LCR constructs indicated that there is a sequence element in the 5′ LCR of HPV33 causing temperature-dependent toxic effect in E. coli. Sequence analysis revealed the presence of an open reading frame (ORF) in the 5′ part of HPV33 LCR potentially encoding a 116-amino acid polypeptide. Protein structure prediction suggested that this putative protein might have a structural similarity to transmembrane proteins. Even a low-level expression of this protein may cause significant toxicity in the host bacteria. In silico analysis of the LCR of HPV33 and some other HPV types belonging to the species Alphapapillomavirus 9 (HPV31, 35 and 58) seemed to support the assumption that the ORFs found in the 5′ LCR of these HPVs are protein-coding sequences. Further studies should be performed to prove that these putative proteins are really expressed in the infected host cells and to identify their function.

Systematic and Comparative Evaluation of Software Programs for Template-Based Modeling of Protein Structures

Modeling protein structures is critical for understanding protein functions in various biological and biotechnological studies. Among representative protein structure modeling approaches, template-based modeling (TBM) is by far the most reliable and most widely used approach to model protein structures. However, it still remains as a challenge to select appropriate software programs for pairwise alignments and model building, two major steps of the TBM. In this paper, pairwise alignment methods for TBM are first compared with respect to the quality of structure models built using these methods. This comparative study is conducted using comprehensive datasets, which cover 6185 domain sequences from Structural Classification of Proteins extended for soluble proteins, and 259 Protein Data Bank entries (whole protein sequences) from Orientations of Proteins in Membranes database for membrane proteins. Overall, a profile-based method, especially PSI-BLAST, consistently shows high performance across the datasets and model evaluation metrics used. Next, use of two model building programs, MODELLER and SWISS-MODEL, does not seem to significantly affect the quality of protein structure models built except for the Hard group (a group of relatively less homologous proteins) of membrane proteins. The results presented in this study will be useful for more accurate implementation of TBM.

SEQUENCE SLIDER: expanding polyalanine fragments for phasing with multiple side-chain hypotheses

Fragment-based molecular-replacement methods can solve a macromolecular structure quasi-ab initio. ARCIMBOLDO, using a common secondary-structure or tertiary-structure template or a library of folds, locates these with Phaser and reveals the rest of the structure by density modification and autotracing in SHELXE. The latter stage is challenging when dealing with diffraction data at lower resolution, low solvent content, high β-sheet composition or situations in which the initial fragments represent a low fraction of the total scattering or where their accuracy is low. SEQUENCE SLIDER aims to overcome these complications by extending the initial polyalanine fragment with side chains in a multisolution framework. Its use is illustrated on test cases and previously unknown structures. The selection and order of fragments to be extended follows the decrease in log-likelihood gain (LLG) calculated with Phaser upon the omission of each single fragment. When the starting substructure is derived from a remote homolog, sequence assignment to fragments is restricted by the original alignment. Otherwise, the secondary-structure prediction is matched to that found in fragments and traces. Sequence hypotheses are trialled in a brute-force approach through side-chain building and refinement. Scoring the refined models through their LLG in Phaser may allow discrimination of the correct sequence or filter the best partial structures for further density modification and autotracing. The default limits for the number of models to pursue are hardware dependent. In its most economic implementation, suitable for a single laptop, the main-chain trace is extended as polyserine rather than trialling models with different sequence assignments, which requires a grid or multicore machine. SEQUENCE SLIDER has been instrumental in solving two novel structures: that of MltC from 2.7 Å resolution data and that of a pneumococcal lipoprotein with 638 residues and 35% solvent content.

Discovery of Dengue Virus Inhibitors

To date, there is still no approved anti-dengue agent to treat dengue infection in the market. Although the only licensed dengue vaccine, Dengvaxia is available, its protective efficacy against serotypes 1 and 2 of dengue virus was reported to be lower than serotypes 3 and 4. Moreover, according to WHO, the risk of being hospitalized and having severe dengue increased in seronegative individuals after they received Dengvaxia vaccination. Nevertheless, various studies had been carried out in search of dengue virus inhibitors. These studies focused on the structural (C, prM, E) and non-structural proteins (NS1, NS2A, NS2B, NS3, NS4A, NS4B and NS5) of dengue virus as well as host factors as drug targets. Hence, this article provides an overall up-to-date review of the discovery of dengue virus inhibitors that are only targeting the structural and non-structural viral proteins as drug targets.

Competitive ubiquitination activates the tumor suppressor p53

Blocking p53 ubiquitination through disrupting its interaction with MDM2 or inhibiting the MDM2 catalytic activity is the central mechanism by which the tumor suppressor p53 is activated in response to genotoxic challenges. Although MDM2 is first characterized as the major E3 ubiquitin ligase for p53, it can also catalyze the conjugation of ubiquitin moieties to other proteins (e.g., activating transcription factor 3, or ATF3). Here we report that ATF3 can act as an ubiquitin “trap” and competes with p53 for MDM2-mediated ubiquitination. While ATF3-mediated p53 stabilization required ATF3 binding to the MDM2 RING domain, we demonstrated that ATF3 ubiquitination catalyzed by MDM2 was indispensable for p53 activation in response to DNA damage. Moreover, a cancer-derived ATF3 mutant (R88G) devoid of ubiquitination failed to prevent p53 from MDM2-mediated degradation and thus was unable to activate the tumor suppressor. Therefore, we have identified a previously-unknown mechanism that can activate p53 in the genotoxic response.

Molecular replacement using structure predictions from databases

Molecular replacement (MR) is the predominant route to solution of the phase problem in macromolecular crystallography. Where the lack of a suitable homologue precludes conventional MR, one option is to predict the target structure using bioinformatics. Such modelling, in the absence of homologous templates, is called ab initio or de novo modelling. Recently, the accuracy of such models has improved significantly as a result of the availability, in many cases, of residue-contact predictions derived from evolutionary covariance analysis. Covariance-assisted ab initio models representing structurally uncharacterized Pfam families are now available on a large scale in databases, potentially representing a valuable and easily accessible supplement to the PDB as a source of search models. Here, the unconventional MR pipeline AMPLE is employed to explore the value of structure predictions in the GREMLIN and PconsFam databases. It was tested whether these deposited predictions, processed in various ways, could solve the structures of PDB entries that were subsequently deposited. The results were encouraging: nine of 27 GREMLIN cases were solved, covering target lengths of 109-355 residues and a resolution range of 1.4-2.9 Å, and with target-model shared sequence identity as low as 20%. The cluster-and-truncate approach in AMPLE proved to be essential for most successes. For the overall lower quality structure predictions in the PconsFam database, remodelling with Rosetta within the AMPLE pipeline proved to be the best approach, generating ensemble search models from single-structure deposits. Finally, it is shown that the AMPLE-obtained search models deriving from GREMLIN deposits are of sufficiently high quality to be selected by the sequence-independent MR pipeline SIMBAD. Overall, the results help to point the way towards the optimal use of the expanding databases of ab initio structure predictions.

A new approach to biomining: Bioengineering surfaces for metal recovery from aqueous solutions

Electronics waste production has been fueled by economic growth and the demand for faster, more efficient consumer electronics. The glass and metals in end-of-life electronics components can be reused or recycled; however, conventional extraction methods rely on energy-intensive processes that are inefficient when applied to recycling e-waste that contains mixed materials and small amounts of metals. To make e-waste recycling economically viable and competitive with obtaining raw materials, recovery methods that lower the cost of metal reclamation and minimize environmental impact need to be developed. Microbial surface adsorption can aid in metal recovery with lower costs and energy requirements than traditional metal-extraction approaches. We introduce a novel method for metal recovery by utilizing metal-binding peptides to functionalize fungal mycelia and enhance metal recovery from aqueous solutions such as those found in bioremediation or biomining processes. Using copper-binding as a proof-of-concept, we compared binding parameters between natural motifs and those derived in silico, and found comparable binding affinity and specificity for Cu. We then combined metal-binding peptides with chitin-binding domains to functionalize a mycelium-based filter to enhance metal recovery from a Cu-rich solution. This finding suggests that engineered peptides could be used to functionalize biological surfaces to recover metals of economic interest and allow for metal recovery from metal-rich effluent with a low environmental footprint, at ambient temperatures, and under circumneutral pH.

Advances in protein structure prediction and design

The prediction of protein three-dimensional structure from amino acid sequence has been a grand challenge problem in computational biophysics for decades, owing to its intrinsic scientific interest and also to the many potential applications for robust protein structure prediction algorithms, from genome interpretation to protein function prediction. More recently, the inverse problem - designing an amino acid sequence that will fold into a specified three-dimensional structure - has attracted growing attention as a potential route to the rational engineering of proteins with functions useful in biotechnology and medicine. Methods for the prediction and design of protein structures have advanced dramatically in the past decade. Increases in computing power and the rapid growth in protein sequence and structure databases have fuelled the development of new data-intensive and computationally demanding approaches for structure prediction. New algorithms for designing protein folds and protein-protein interfaces have been used to engineer novel high-order assemblies and to design from scratch fluorescent proteins with novel or enhanced properties, as well as signalling proteins with therapeutic potential. In this Review, we describe current approaches for protein structure prediction and design and highlight a selection of the successful applications they have enabled.

Fueling ab initio folding with marine metagenomics enables structure and function predictions of new protein families

INTRODUCTION

The ocean microbiome represents one of the largest microbiomes and produces nearly half of the primary energy on the planet through photosynthesis or chemosynthesis. Using recent advances in marine genomics, we explore new applications of oceanic metagenomes for protein structure and function prediction.

RESULTS

By processing 1.3 TB of high-quality reads from the Tara Oceans data, we obtain 97 million non-redundant genes. Of the 5721 Pfam families that lack experimental structures, 2801 have at least one member associated with the oceanic metagenomics dataset. We apply C-QUARK, a deep-learning contact-guided ab initio structure prediction pipeline, to model 27 families, where 20 are predicted to have a reliable fold with estimated template modeling score (TM-score) at least 0.5. Detailed analyses reveal that the abundance of microbial genera in the ocean is highly correlated to the frequency of occurrence in the modeled Pfam families, suggesting the significant role of the Tara Oceans genomes in the contact-map prediction and subsequent ab initio folding simulations. Of interesting note, PF15461, which has a majority of members coming from ocean-related bacteria, is identified as an important photosynthetic protein by structure-based function annotations. The pipeline is extended to a set of 417 Pfam families, built on the combination of Tara with other metagenomics datasets, which results in 235 families with an estimated TM-score over 0.5.

CONCLUSIONS

These results demonstrate a new avenue to improve the capacity of protein structure and function modeling through marine metagenomics, especially for difficult proteins with few homologous sequences.

Redirecting the immune response towards immunoprotective domains of a DNABII protein resolves experimental otitis media

The chronicity and recurrence of many bacterial diseases is largely attributable to the presence of a biofilm, and eradication of these structures is confounded by an extracellular DNA-rich matrix. DNABII proteins, including integration host factor (IHF), are critical components of the matrix formed by all human pathogens tested to date. Whereas the natural adaptive immune response to IHF is against non-protective epitopes within the carboxyl-terminal region, antibodies against the DNA-binding “tips” induce biofilm collapse. We designed a “tip-chimer” immunogen to mimic the DNA-binding regions within the α-subunit and β-subunit of IHF from nontypeable Haemophilus influenzae (IHF_NTHi). Re-direction of the natural adaptive immune response toward immunoprotective domains disrupted NTHi biofilms in vitro and in an experimental model of otitis media. Our data support the rational design of a powerful therapeutic approach, and also that of a DNABII-directed vaccine antigen that would avoid augmentation of any pre-existing natural, but nonprotective, immune response.

Bacterial biofilms are characterized by the presence of a protective extracellular polymeric substance (EPS) that incorporates both eDNA and members of the DNABII family of bacterial DNA-binding proteins. Antibodies against the “tips” of these DNA binding-domains can cause biofilm collapse, but these epitopes are masked from the host adaptive immune system when bound to eDNA, making biofilm eradication difficult. Here, the team led by Lauren Bakaletz used a chimeric peptide to generate tip-specific antibodies against nontypeable Haemophilus influenzae to treat biofilms in vitro and in vivo. The “tip-chimer” contained the immunoprotective domains from the DNA-binding tips of a DNABII protein, integration host factor (IHF), expressed by nontypeable Haemophilus influenzae. The consequent antibodies disrupted H. influenzae biofilms in vitro and were used to treat a chinchilla model of experimental otitis media when inoculated directly into the middle ear, resulting in reduced bacterial load and clearance of already established mucosal biofilms. These findings suggest that redirecting the host adaptive immune response towards the immunoprotective tips of DNABII proteins could provide a strategy to eradicate biofilms caused by various pathogens that produce these proteins.

Structure-function relationship of an Urokinase Receptor-derived peptide which inhibits the Formyl Peptide Receptor type 1 activity

The interaction between the short 88Ser-Arg-Ser-Arg-Tyr92 sequence of the urokinase receptor (uPAR) and the formyl peptide receptor type 1 (FPR1) elicits cell migration. We generated the Ac-(D)-Tyr-(D)-Arg-Aib-(D)-Arg-NH2 (RI-3) peptide which inhibits the uPAR/FPR1 interaction, reducing migration of FPR1 expressing cells toward N-formyl-methionyl-leucyl-phenylalanine (fMLF) and Ser-Arg-Ser-Arg-Tyr (SRSRY) peptides. To understand the structural basis of the RI-3 inhibitory effects, the FPR1/fMLF, FPR1/SRSRY and FPR1/RI-3 complexes were modeled and analyzed, focusing on the binding pocket of FPR1 and the interaction between the amino acids that signal to the FPR1 C-terminal loop. We found that RI-3 shares the same binding site of fMLF and SRSRY on FPR1. However, while fMLF and SRSRY display the same agonist activation signature (i.e. the series of contacts that transmit the conformational transition throughout the complex), translating binding into signaling, RI-3 does not interact with the activation region of FPR1 and hence does not activate signaling. Indeed, fluorescein-conjugated RI-3 prevents either fMLF and SRSRY uptake on FPR1 without triggering FPR1 internalization and cell motility in the absence of any stimulus. Collectively, our data show that RI-3 is a true FPR1 antagonist and suggest a pharmacophore model useful for development of compounds that selectively inhibit the uPAR-triggered, FPR1-mediated cell migration.

Mutations in RABL3 alter KRAS prenylation and are associated with hereditary pancreatic cancer

Pancreatic ductal adenocarcinoma is an aggressive cancer with limited treatment options¹. Approximately 10% of cases exhibit familial predisposition, but causative genes are not known in most families². We perform whole-genome sequence analysis in a family with multiple cases of pancreatic ductal adenocarcinoma and identify a germline truncating mutation in the member of the RAS oncogene family-like 3 (RABL3) gene. Heterozygous rabl3 mutant zebrafish show increased susceptibility to cancer formation. Transcriptomic and mass spectrometry approaches implicate RABL3 in RAS pathway regulation and identify an interaction with RAP1GDS1 (SmgGDS), a chaperone regulating prenylation of RAS GTPases³. Indeed, the truncated mutant RABL3 protein accelerates KRAS prenylation and requires RAS proteins to promote cell proliferation. Finally, evidence in patient cohorts with developmental disorders implicates germline RABL3 mutations in RASopathy syndromes. Our studies identify RABL3 mutations as a target for genetic testing in cancer families and uncover a mechanism for dysregulated RAS activity in development and cancer.

Structure determination of the CAMP factor of Streptococcus agalactiae with the aid of an MBP tag and insights into membrane-surface attachment

CAMP factor is a unique α-helical bacterial toxin that is known for its co-hemolytic activity in combination with staphylococcal sphingomyelinase. It was first discovered in the human pathogen Streptococcus agalactiae (also known as group B streptococcus), but homologous genes have been found in many other Gram-positive pathogens. In this study, the efforts that led to the determination of the first structure of a CAMP-family toxin are reported. Initially, it was possible to produce crystals of the native protein which diffracted to near 2.45 Å resolution. However, a series of technical obstacles were encountered on the way to structure determination. Over a period of more than five years, many methods, including selenomethionine labeling, mutations, crystallization chaperones and heavy-atom soaking, were attempted, but these attempts resulted in limited progress. The structure was finally solved using a combination of iodine soaking and molecular replacement using the crystallization chaperone maltose-binding protein (MBP) as a search model. Analysis of native and MBP-tagged CAMP-factor structures identified a conserved interaction interface in the C-terminal domain (CTD). The positively charged surface may be critical for binding to acidic ligands. Furthermore, mutations on the interaction interface at the CTD completely abolished its co-hemolytic activities. This study provides novel insights into the mechanism of the membrane-permeabilizing activity of CAMP factor.

[Mullerian inhibiting substance type II receptor as a potential target for antineoplastic therapy]

The review considers properties of the type II anti-Mullerian hormone receptor (mullerian inhibiting substance receptor type II, MISRII), a transmembrane sensor with its own serine/threonine protein kinase activity, triggering apoptosis of the Mullerian ducts in mammalian embryogenesis and providing formation of the male type reproductive system. According to recent data, MISRII overexpression in the postnatal period is found in cells of a number of ovarian, mammary gland, and prostate tumors, and anti-Mullerian hormone (AMH) has a pro-apoptotic effect on MISRII-positive tumor cells. This fact makes MISRII a potential target for targeted anti-cancer therapy. Treatment based on targeting MISRII seems to be a much more effective alternative to the traditional one and will significantly reduce the drug dose. However, the mechanism of MISRII-AMH interaction is still poorly understood, so the development of new anticancer drugs is complicated. The review analyzes MISRII molecular structure and expression levels in various tissues and cell lines, as well as current understanding of the AMH binding mechanisms and data on the possibility of using MISRII as a target for the action of AMH-based antineoplastic drugs.

Computational identification of self-inhibitory peptides from white spot syndrome virus envelope protein VP28

Since effective chemotherapeutics or preventive measures are still unavailable, finding feasible approaches against white spot syndrome virus (WSSV) has always been the vital subject in shrimp farming field. Envelope proteins are the ideal targets for antiviral strategies development due to their indispensable roles in virus entry, and inhibitory peptides targeting them have been proved to be promising in blocking virus infection. In this study, the Wimley-White interfacial hydrophobicity scale (WWIHS) in combination with known structural data was applied to identify potential inhibitory peptides that targeted the envelope protein VP28 of WSSV. Results showed that two potential inhibitory peptides were identified, one of which exhibited not only obvious antiviral activity, but also broad-spectrum antimicrobial activity. The inhibitory peptide identified here can serve as a lead compound for anti-WSSV strategies development.

Molecular architecture, polar targeting and biogenesis of the Legionella Dot/Icm T4SS

Legionella pneumophila survives and replicates inside host cells by secreting ~300 effectors through the defective in organelle trafficking (Dot)/intracellular multiplication (Icm) type IVB secretion system (T4BSS). Here, we used complementary electron cryotomography and immunofluorescence microscopy to investigate the molecular architecture and biogenesis of the Dot/Icm secretion apparatus. Electron cryotomography mapped the location of the core and accessory components of the Legionella core transmembrane subcomplex, revealing a well-ordered central channel that opens into a large, windowed secretion chamber with an unusual 13-fold symmetry. Immunofluorescence microscopy deciphered an early-stage assembly process that begins with the targeting of Dot/Icm components to the bacterial poles. Polar targeting of this T4BSS is mediated by two Dot/Icm proteins, DotU and IcmF, that, interestingly, are homologues of the T6SS membrane complex components TssL and TssM, suggesting that the Dot/Icm T4BSS is a hybrid system. Together, these results revealed that the Dot/Icm complex assembles in an 'axial-to-peripheral' pattern.

Variants in DOCK3 cause developmental delay and hypotonia

The DOCK3 gene encodes the Dedicator of cytokinesis 3 (DOCK3) protein, which belongs to the family of guanine nucleotide exchange factors and is expressed almost exclusively in the brain and spinal cord. We used whole exome sequencing (WES) to investigate the molecular cause of developmental delay and hypotonia in three unrelated probands. WES identified truncating and splice site variants in Patient 1 and compound heterozygous and homozygous missense variants in Patients 2 and 3, respectively. We studied the effect of the three missense variants in vitro by using site-directed mutagenesis and pull-down assay and show that the induction of Rac1 activation was significantly lower in DOCK3 mutant cells compared with wild type human DOCK3 (P < 0.05). We generated a protein model to further examine the effect of the two missense variants within or adjacent to the DHR-2 domain in DOCK3 and this model supports pathogenicity. Our results support a loss of function mechanism but the data on the patients with missense variants should be cautiously interpreted because of the variability of the phenotypes and limited number of cases. Prior studies have described DOCK3 bi-allelic loss of function variants in two families with ataxia, hypotonia, and developmental delay. Here, we report on three patients with DOCK3-related developmental delay, wide-based or uncoordinated gait, and hypotonia, further supporting DOCK3's role in a neurodevelopmental syndrome and expanding the spectrum of phenotypic and genotypic variability.

Dynamics and binding interactions of peptide inhibitors of dengue virus entry

In this study, we investigate the binding interactions of two synthetic antiviral peptides (DET2 and DET4) on type II dengue virus (DENV2) envelope protein domain III. These two antiviral peptides are designed based on the domain III of the DENV2 envelope protein, which has shown significant inhibition activity in previous studies and can be potentially modified further to be active against all dengue strains. Molecular docking was performed using AutoDock Vina and the best-ranked peptide-domain III complex was further explored using molecular dynamics simulations. Molecular mechanics-Poisson-Boltzmann surface area (MM-PBSA) was used to calculate the relative binding free energies and to locate the key residues of peptide-protein interactions. The predicted binding affinity correlated well with the previous experimental studies. DET4 outperformed DET2 and is oriented within the binding site through favorable vdW and electrostatic interactions. Pairwise residue decomposition analysis has revealed several key residues that contribute to the binding of these peptides. Residues in DET2 interact relatively lesser with the domain III compared to DET4. Dynamic cross-correlation analysis showed that both the DET2 and DET4 trigger different dynamic patterns on the domain III. Correlated motions were seen between the residue pairs of DET4 and the binding site while binding of DET2 results in anti-correlated motion on the binding site. This work showcases the use of computational study in elucidating and explaining the experiment observation on an atomic level.

Advances in Protein Super-Secondary Structure Prediction and Application to Protein Structure Prediction

Due to the advancement in various sequencing technologies, the gap between the number of protein sequences and the number of experimental protein structures is ever increasing. Community-wide initiatives like CASP have resulted in considerable efforts in the development of computational methods to accurately model protein structures from sequences. Sequence-based prediction of super-secondary structure has direct application in protein structure prediction, and there have been significant efforts in the prediction of super-secondary structure in the last decade. In this chapter, we first introduce the protein structure prediction problem and highlight some of the important progress in the field of protein structure prediction. Next, we discuss recent methods for the prediction of super-secondary structures. Finally, we discuss applications of super-secondary structure prediction in structure prediction/analysis of proteins. We also discuss prediction of protein structures that are composed of simple super-secondary structure repeats and protein structures that are composed of complex super-secondary structure repeats. Finally, we also discuss the recent trends in the field.

Computational Opportunities and Challenges in Finding Cyclic Peptide Modulators of Protein-Protein Interactions

Peptide cyclization can improve stability, conformational constraint, and compactness. However, apart from beta-turn structures, which are well incorporated into cyclic peptides (CPs), many primary peptide structures and functions are markedly altered by cyclization. Accordingly, to mimic linear peptide interfaces with cyclic peptides, it can be beneficial to screen combinatorial cyclic peptide libraries. Computational methods have been developed to screen CPs, but face a number of challenges. Here, we review methods to develop in silico computational libraries, and the potential for screening naturally occurring libraries of CPs. The simplest and most rapid computational pharmacophore methods that estimate peptide three-dimensional structures to be screened versus targets are relatively easy to implement, and while the constraint on structure imposed by cyclization makes them more effective than the same approaches with linear peptides, there are a large number of limiting assumptions. In contrast, full molecular dynamics simulations of cyclic peptide structures not only are costly to implement, but also require careful attention to interpretation, so that not only is the computation time rate limiting, but the interpretation time is also rate limiting due to the analysis of the typically complex underlying conformational space of CPs. A challenge for the field of computational cyclic peptide screening is to bridge this gap effectively. Natural compound libraries of short cyclic peptides, and short cyclized regions of proteins, encoded in the genomes of many organisms present a potential treasure trove of novel functionality which may be screened via combined computational and experimental screening approaches.

Third generation antibody discovery methods: in silico rational design

Owing to their outstanding performances in molecular recognition, antibodies are extensively used in research and applications in molecular biology, biotechnology and medicine. Recent advances in experimental and computational methods are making it possible to complement well-established in vivo (first generation) and in vitro (second generation) methods of antibody discovery with novel in silico (third generation) approaches. Here we describe the principles of computational antibody design and review the state of the art in this field. We then present Modular, a method that implements the rational design of antibodies in a modular manner, and describe the opportunities offered by this approach.

The translation of non-canonical open reading frames controls mucosal immunity

The annotation of the mammalian protein-coding genome is incomplete. Arbitrary size restriction of open reading frames (ORFs) and the absolute requirement for a methionine codon as the sole initiator of translation have constrained the identification of potentially important transcripts with non-canonical protein-coding potential1,2. Here, using unbiased transcriptomic approaches in macrophages that respond to bacterial infection, we show that ribosomes associate with a large number of RNAs that were previously annotated as 'non-protein coding'. Although the idea that such non-canonical ORFs can encode functional proteins is controversial3,4, we identify a range of short and non-ATG-initiated ORFs that can generate stable and spatially distinct proteins. Notably, we show that the translation of a new ORF 'hidden' within the long non-coding RNA Aw112010 is essential for the orchestration of mucosal immunity during both bacterial infection and colitis. This work expands our interpretation of the protein-coding genome and demonstrates that proteinaceous products generated from non-canonical ORFs are crucial for the immune response in vivo. We therefore propose that the misannotation of non-canonical ORF-containing genes as non-coding RNAs may obscure the essential role of a multitude of previously undiscovered protein-coding genes in immunity and disease.

Membranotropic peptides mediating viral entry

The means used by enveloped viruses to bypass cellular membranes are well characterized; however, the mechanisms used by non-enveloped viruses to deliver their genome inside the cell remain unresolved and poorly defined. The discovery of short, membrane interacting, amphipathic or hydrophobic sequences (known as membranotropic peptides) in both enveloped and non-enveloped viruses suggests that these small peptides are strongly involved in breaching the host membrane and in the delivery of the viral genome into the host cell. Thus, in spite of noticeable differences in entry, this short stretches of membranotropic peptides are probably associated with similar entry-related events. This review will uncover the intrinsic features of viral membranotropic peptides involved in viral entry of both naked viruses and the ones encircled with a biological membrane with the objective to better elucidate their different functional properties and possible applications in the biomedical field.

Evolutionary Analysis of the Lysine-Rich N-terminal Cytoplasmic Domains of the Gastric H+,K+-ATPase and the Na+,K+-ATPase

The catalytic α-subunits of both the Na⁺,K⁺-ATPase and the gastric H⁺,K⁺-ATPase possess lysine-rich N-termini which project into the cytoplasm. Due to conflicting experimental results, it is currently unclear whether the N-termini play a role in ion pump function or regulation, and, if they do, by what mechanism. Comparison of the lysine frequencies of the N-termini of both proteins with those of all of their extramembrane domains showed that the N-terminal lysine frequencies are far higher than one would expect simply from exposure to the aqueous solvent. The lysine frequency was found to vary significantly between different vertebrate classes, but this is due predominantly to a change in N-terminal length. As evidenced by a comparison between fish and mammals, an evolutionary trend towards an increase of the length of the N-terminus of the H⁺,K⁺-ATPase on going from an ancestral fish to mammals could be identified. This evolutionary trend supports the hypothesis that the N-terminus is important in ion pump function or regulation. In placental mammals, one of the lysines is replaced by serine (Ser-27), which is a target for protein kinase C. In most other animal species, a lysine occupies this position and hence no protein kinase C target is present. Interaction with protein kinase C is thus not the primary role of the lysine-rich N-terminus. The disordered structure of the N-terminus may, via increased flexibility, facilitate interaction with another binding partner, e.g. the surrounding membrane, or help to stabilise particular enzyme conformations via the increased entropy it produces.

Protein structure prediction

Predicting 3D structure of protein from its amino acid sequence is one of the most important unsolved problems in biophysics and computational biology. This paper attempts to give a comprehensive introduction of the most recent effort and progress on protein structure prediction. Following the general flowchart of structure prediction, related concepts and methods are presented and discussed. Moreover, brief introductions are made to several widely-used prediction methods and the community-wide critical assessment of protein structure prediction (CASP) experiments.

New insights into the structural dynamics of the kinase JNK3

In this work, we study the dynamics and the energetics of the all-atom structure of a neuronal-specific serine/threonine kinase c-Jun N-terminal kinase 3 (JNK3) in three states: unphosphorylated, phosphorylated, and ATP-bound phosphorylated. A series of 2 µs atomistic simulations followed by a conformational landscape mapping and a principal component analysis supports the mechanistic understanding of the JNK3 inactivation/activation process and also indicates key structural intermediates. Our analysis reveals that the unphosphorylated JNK3 undergoes the ‘open-to-closed’ movement via a two-step mechanism. Furthermore, the phosphorylation and ATP-binding allow the JNK3 kinase to attain a fully active conformation. JNK3 is a widely studied target for small-drugs used to treat a variety of neurological disorders. We believe that the mechanistic understanding of the large-conformational changes upon the activation of JNK3 will aid the development of novel targeted therapeutics.

Structural basis of meiotic chromosome synapsis through SYCP1 self-assembly

Meiotic chromosomes adopt unique structures in which linear arrays of chromatin loops are bound together in homologous chromosome pairs by a supramolecular protein assembly, the synaptonemal complex. This three-dimensional scaffold provides the essential structural framework for genetic exchange by crossing over and subsequent homolog segregation. The core architecture of the synaptonemal complex is provided by SYCP1. Here we report the structure and self-assembly mechanism of human SYCP1 through X-ray crystallographic and biophysical studies. SYCP1 has an obligate tetrameric structure in which an N-terminal four-helical bundle bifurcates into two elongated C-terminal dimeric coiled-coils. This building block assembles into a zipper-like lattice through two self-assembly sites. N-terminal sites undergo cooperative head-to-head assembly in the midline, while C-terminal sites interact back to back on the chromosome axis. Our work reveals the underlying molecular structure of the synaptonemal complex in which SYCP1 self-assembly generates a supramolecular lattice that mediates meiotic chromosome synapsis.

Antimicrobial and structural insights of a new snakin-like peptide isolated from Peltophorum dubium (Fabaceae)

Snakins are antimicrobial peptides (AMPs) found, so far, exclusively in plants, and known to be important in the defense against a wide range of pathogens. Like other plant AMPs, they contain several positively charged amino acids, and an even number of cysteine residues forming disulfide bridges which are considered important for their usual function. Despite its importance, studies on snakin tertiary structure and mode of action are still scarce. In this study, a new snakin-like gene was isolated from the native plant Peltophorum dubium, and its expression was verified in seedlings and adult leaves. The deduced peptide (PdSN1) shows 84% sequence identity with potato snakin-1 mature peptide, with the 12 cysteines characteristic from this peptide family at the GASA domain. The mature PdSN1 coding sequence was successfully expressed in Escherichia coli. The purified recombinant peptide inhibits the growth of important plant and human pathogens, like the economically relevant potato pathogen Streptomyces scabies and the opportunistic fungi Candida albicans and Aspergillus niger. Finally, homology and ab initio modeling techniques coupled to extensive molecular dynamics simulations were used to gain insight on the 3D structure of PdSN1, which exhibited a helix-turn-helix motif conserved in both native and recombinant peptides. We found this motif to be strongly coded in the sequence of PdSN1, as it is stable under different patterns of disulfide bonds connectivity, and even when the 12 cysteines are considered in their reduced form, explaining the previous experimental evidences.

Structural basis of the bacteriophage TP901-1 CI repressor dimerization and interaction with DNA

Temperate bacteriophages are known for their bistability, which in TP901-1 is controlled by two proteins, CI and MOR. Clear 1 repressor (CI) is hexameric and binds three palindromic operator sites via an N-terminal helix-turn-helix domain (NTD). A dimeric form, such as the truncated CI∆58 investigated here, is necessary for high-affinity binding to DNA. The crystal structure of the dimerization region (CTD₁ ) is determined here, showing that it forms a pair of helical hooks. This newly determined structure is used together with the known crystal structure of the CI-NTD and small angle X-ray scattering data, to determine the solution structure of CI∆58 in complex with a palindromic operator site, showing that the two NTDs bind on opposing sides of the DNA helix.

In silico optimization of a guava antimicrobial peptide enables combinatorial exploration for peptide design

Plants are extensively used in traditional medicine, and several plant antimicrobial peptides have been described as potential alternatives to conventional antibiotics. However, after more than four decades of research no plant antimicrobial peptide is currently used for treating bacterial infections, due to their length, post-translational modifications or  high dose requirement for a therapeutic effect . Here we report the design of antimicrobial peptides derived from a guava glycine-rich peptide using a genetic algorithm. This approach yields guavanin peptides, arginine-rich α-helical peptides that possess an unusual hydrophobic counterpart mainly composed of tyrosine residues. Guavanin 2 is characterized as a prototype peptide in terms of structure and activity. Nuclear magnetic resonance analysis indicates that the peptide adopts an α-helical structure in hydrophobic environments. Guavanin 2 is bactericidal at low concentrations, causing membrane disruption and triggering hyperpolarization. This computational approach for the exploration of natural products could be used to design effective peptide antibiotics.

Antimicrobial peptides are considered promising alternatives to antibiotics. Here the authors developed a computational algorithm that starts with peptides naturally occurring in plants and optimizes this starting material to yield new variants which are highly distinct from the parent peptide.

Exploiting distant homologues for phasing through the generation of compact fragments, local fold refinement and partial solution combination

Macromolecular structures can be solved by molecular replacement provided that suitable search models are available. Models from distant homologues may deviate too much from the target structure to succeed, notwithstanding an overall similar fold or even their featuring areas of very close geometry. Successful methods to make the most of such templates usually rely on the degree of conservation to select and improve search models. ARCIMBOLDO_SHREDDER uses fragments derived from distant homologues in a brute-force approach driven by the experimental data, instead of by sequence similarity. The new algorithms implemented in ARCIMBOLDO_SHREDDER are described in detail, illustrating its characteristic aspects in the solution of new and test structures. In an advance from the previously published algorithm, which was based on omitting or extracting contiguous polypeptide spans, model generation now uses three-dimensional volumes respecting structural units. The optimal fragment size is estimated from the expected log-likelihood gain (LLG) values computed assuming that a substructure can be found with a level of accuracy near that required for successful extension of the structure, typically below 0.6 Å root-mean-square deviation (r.m.s.d.) from the target. Better sampling is attempted through model trimming or decomposition into rigid groups and optimization through Phaser's gyre refinement. Also, after model translation, packing filtering and refinement, models are either disassembled into predetermined rigid groups and refined (gimble refinement) or Phaser's LLG-guided pruning is used to trim the model of residues that are not contributing signal to the LLG at the target r.m.s.d. value. Phase combination among consistent partial solutions is performed in reciprocal space with ALIXE. Finally, density modification and main-chain autotracing in SHELXE serve to expand to the full structure and identify successful solutions. The performance on test data and the solution of new structures are described.

ARCIMBOLDO on coiled coils

ARCIMBOLDO solves the phase problem by combining the location of small model fragments using Phaser with density modification and autotracing using SHELXE. Mainly helical structures constitute favourable cases, which can be solved using polyalanine helical fragments as search models. Nevertheless, the solution of coiled-coil structures is often complicated by their anisotropic diffraction and apparent translational noncrystallographic symmetry. Long, straight helices have internal translational symmetry and their alignment in preferential directions gives rise to systematic overlap of Patterson vectors. This situation has to be differentiated from the translational symmetry relating different monomers. ARCIMBOLDO_LITE has been run on single workstations on a test pool of 150 coiled-coil structures with 15-635 amino acids per asymmetric unit and with diffraction data resolutions of between 0.9 and 3.0 Å. The results have been used to identify and address specific issues when solving this class of structures using ARCIMBOLDO. Features from Phaser v.2.7 onwards are essential to correct anisotropy and produce translation solutions that will pass the packing filters. As the resolution becomes worse than 2.3 Å, the helix direction may be reversed in the placed fragments. Differentiation between true solutions and pseudo-solutions, in which helix fragments were correctly positioned but in a reverse orientation, was found to be problematic at resolutions worse than 2.3 Å. Therefore, after every new fragment-placement round, complete or sparse combinations of helices in alternative directions are generated and evaluated. The final solution is once again probed by helix reversal, refinement and extension. To conclude, density modification and SHELXE autotracing incorporating helical constraints is also exploited to extend the resolution limit in the case of coiled coils and to enhance the identification of correct solutions. This study resulted in a specialized mode within ARCIMBOLDO for the solution of coiled-coil structures, which overrides the resolution limit and can be invoked from the command line (keyword coiled_coil) or ARCIMBOLDO_LITE task interface in CCP4i.

Recent developments in MrBUMP: better search-model preparation, graphical interaction with search models, and solution improvement and assessment

Increasing sophistication in molecular-replacement (MR) software and the rapid expansion of the PDB in recent years have allowed the technique to become the dominant method for determining the phases of a target structure in macromolecular X-ray crystallography. In addition, improvements in bioinformatic techniques for finding suitable homologous structures for use as MR search models, combined with developments in refinement and model-building techniques, have pushed the applicability of MR to lower sequence identities and made weak MR solutions more amenable to refinement and improvement. MrBUMP is a CCP4 pipeline which automates all stages of the MR procedure. Its scope covers everything from the sourcing and preparation of suitable search models right through to rebuilding of the positioned search model. Recent improvements to the pipeline include the adoption of more sensitive bioinformatic tools for sourcing search models, enhanced model-preparation techniques including better ensembling of homologues, and the use of phase improvement and model building on the resulting solution. The pipeline has also been deployed as an online service through CCP4 online, which allows its users to exploit large bioinformatic databases and coarse-grained parallelism to speed up the determination of a possible solution. Finally, the molecular-graphics application CCP4mg has been combined with MrBUMP to provide an interactive visual aid to the user during the process of selecting and manipulating search models for use in MR. Here, these developments in MrBUMP are described with a case study to explore how some of the enhancements to the pipeline and to CCP4mg can help to solve a difficult case.

Structural and functional modeling of viral protein 5 of Infectious Bursal Disease Virus

Infectious Bursal Disease (IBD) is an acute, highly contagious and immunosuppressive disease of young chicken. The causative virus (IBDV) is a bi-segmented, double-stranded RNA virus. The virus encodes five major proteins, viral protein (VP) 1-5. VPs 1-3 have been characterized crystallographically. Albeit a rise in the number of studies reporting successful heterologous expression of VP5 in recent times, challenging the notion that rapid death of host cells overexpressing VP5 disallows obtaining sufficiently pure preparations of the protein for crystallographic studies, the structure of VP5 remains unknown and its function controversial. Our study describes the first 3D model of IBD VP5 obtained through an elaborate computational workflow. Based on the results of the study, IBD VP5 can be predicted to be a structural analog of the leucine-rich repeat (LRR) family of proteins. Functional implications arising from structural similarity of VP5 with host Toll-like receptor (Tlr) 3 also satisfy the previously reported opposing roles of the protein in first abolishing and later inducing host-cell apoptosis.

Finding the needle in the haystack: towards solving the protein-folding problem computationally

Prediction of protein tertiary structures from amino acid sequence and understanding the mechanisms of how proteins fold, collectively known as "the protein folding problem," has been a grand challenge in molecular biology for over half a century. Theories have been developed that provide us with an unprecedented understanding of protein folding mechanisms. However, computational simulation of protein folding is still difficult, and prediction of protein tertiary structure from amino acid sequence is an unsolved problem. Progress toward a satisfying solution has been slow due to challenges in sampling the vast conformational space and deriving sufficiently accurate energy functions. Nevertheless, several techniques and algorithms have been adopted to overcome these challenges, and the last two decades have seen exciting advances in enhanced sampling algorithms, computational power and tertiary structure prediction methodologies. This review aims at summarizing these computational techniques, specifically conformational sampling algorithms and energy approximations that have been frequently used to study protein-folding mechanisms or to de novo predict protein tertiary structures. We hope that this review can serve as an overview on how the protein-folding problem can be studied computationally and, in cases where experimental approaches are prohibitive, help the researcher choose the most relevant computational approach for the problem at hand. We conclude with a summary of current challenges faced and an outlook on potential future directions.

Distributed computing for macromolecular crystallography

Modern crystallographic computing is characterized by the growing role of automated structure-solution pipelines, which represent complex expert systems utilizing a number of program components, decision makers and databases. They also require considerable computational resources and regular database maintenance, which is increasingly more difficult to provide at the level of individual desktop-based CCP4 setups. On the other hand, there is a significant growth in data processed in the field, which brings up the issue of centralized facilities for keeping both the data collected and structure-solution projects. The paradigm of distributed computing and data management offers a convenient approach to tackling these problems, which has become more attractive in recent years owing to the popularity of mobile devices such as tablets and ultra-portable laptops. In this article, an overview is given of developments by CCP4 aimed at bringing distributed crystallographic computations to a wide crystallographic community.

Structure optimisation to improve the delivery efficiency and cell selectivity of a tumour-targeting cell-penetrating peptide

Cell-penetrating peptide (CPP) is used for the delivery of biomacromolecules across the cell membrane and is limited in cancer therapy due to the lack of cell selectivity. Epidermal growth factor receptor (EGFR) has been widely used in clinical targeted therapy for tumours. Here, we reported a novel tumour targeting cell-penetrating peptide (TCPP), EHB (ELBD-C6H) with 20-fold and 3000-fold greater transmembrane ability and tumour cell selectivity than our previously reported S3-HBD and classic CPP TAT, respectively. In this new TCPP, a specific alpha helix structure was inserted into a repeated amino acid (AA) sequence formed by tandem multiple selected key AA residues of vaccinia growth factor (VGF), and this sequence was then fused to a tailored heparin binding domain sequence (C6H) derived from heparin-binding epidermal growth factor-like growth factor to intensify its targeting delivery ability. EHB could carry anticancer proteins such as MAP30 (Momordica Antiviral Protein 30 kDa) into EGFR-overexpressing cancer cell and inhibit cell growth, but it had a greatly reduced interaction with normal cells. These results indicated that EHB, as a novel efficient TCPP for the selective delivery of drug molecules into cancer cells, would help to improve the efficacy and safety of anti-tumour drugs.

Approaches to ab initio molecular replacement of α-helical transmembrane proteins

α-Helical transmembrane proteins are a ubiquitous and important class of proteins, but present difficulties for crystallographic structure solution. Here, the effectiveness of the AMPLE molecular replacement pipeline in solving α-helical transmembrane-protein structures is assessed using a small library of eight ideal helices, as well as search models derived from ab initio models generated both with and without evolutionary contact information. The ideal helices prove to be surprisingly effective at solving higher resolution structures, but ab initio-derived search models are able to solve structures that could not be solved with the ideal helices. The addition of evolutionary contact information results in a marked improvement in the modelling and makes additional solutions possible.

Structural model of the full-length Ser/Thr protein kinase StkP from S. pneumoniae and its recognition of peptidoglycan fragments

The unique eukaryotic-like Ser/Thr protein kinases of Streptococcus pneumoniae, StkP, plays a primary role in the cell division process. It is composed of an intracellular kinase domain, a transmembrane helix and four extracellular PASTA subunits. PASTA domains were shown to interact with cell wall fragments but the key questions related to the molecular mechanism governing ligand recognition remain unclear. To address this issue, the full-length structural model of StkP was generated by combining small-angle X-ray scattering data with the results of computer simulations. Docking and molecular dynamics studies on the generated three-dimensional model structure reveal the possibility of peptidoglycan fragment binding at the hinge regions between PASTA subunits with a preference for a bent hinge between PASTA3 and PASTA4.

Peptides as Therapeutic Agents for Dengue Virus

Dengue is an important global threat caused by dengue virus (DENV) that records an estimated 390 million infections annually. Despite the availability of CYD-TDV as a commercial vaccine, its long-term efficacy against all four dengue virus serotypes remains unsatisfactory. There is therefore an urgent need for the development of antiviral drugs for the treatment of dengue. Peptide was once a neglected choice of medical treatment but it has lately regained interest from the pharmaceutical industry following pioneering advancements in technology. In this review, the design of peptide drugs, antiviral activities and mechanisms of peptides and peptidomimetics (modified peptides) action against dengue virus are discussed. The development of peptides as inhibitors for viral entry, replication and translation is also described, with a focus on the three main targets, namely, the host cell receptors, viral structural proteins and viral non-structural proteins. The antiviral peptides designed based on these approaches may lead to the discovery of novel anti-DENV therapeutics that can treat dengue patients.