Computational Design of 25-mer Peptide Binders of SARS-CoV-2

Identification of a broad-spectrum high-affinity peptide ligand for the purification of spike proteins

Since the outbreak of coronavirus disease 2019, the global demand for vaccines has increased rapidly to prevent infection and protect high-risk populations. However, identifying viral mutations poses an additional challenge for chromatographic purification of vaccines and subunit vaccines. In this study, a new affinity peptide model, X1VX2GLNX3WX4RYSK, was established, and a library of 612 peptides was generated for ligand screening. Based on a multistep strategy of ligand screening, 18 candidate peptides were obtained. The top ranking peptide, LP14 (YVYGLNIWLRYSK), and two other representative peptides, LP02 and LP06, with lower rankings were compared via molecular dynamics simulation. The results revealed that peptide binding to the receptor binding domain (RBD) was driven by hydrophobic interactions and the key residues involved in the binding were identified. Surface plasmon resonance analysis further confirmed that LP14 had the highest affinity for the wild RBD (Kd=0.520 μmol/L), and viral mutation had little influence on the affinity of LP14, demonstrating its great potential as a broad-spectrum ligand for RBD purification. Finally, chromatographic performance of LP14-coupled gel-packed column verified that both wild and omicron RBDs could be purified and were eluted by 0.1 mol/L Gly-HCl buffer (pH 3.0). This research identified a broad-spectrum peptide for RBD purification based on rational design and demonstrated its potential application in the purification of RBDs from complex feedstock.

In silico study identifies peptide inhibitors that negate the effect of non-synonymous mutations in major drug targets of SARS-CoV-2 variants

Since its advent in December 2019, SARS-CoV-2 has diverged into multiple variants with differing levels of virulence owing to the accumulation of mutations in its genome. The structural changes induced by non-synonymous mutations in major drug targets of the virus are known to alter the binding of potential antagonistic inhibitors. Here, we analyzed the effects of non-synonymous mutations in major targets of SARS-CoV-2 in response to potential peptide inhibitors. We screened 12 peptides reported to have anti-viral properties against RBD and 5 peptides against Mpro of SARS-CoV-2 variants using molecular docking and simulation approaches. The mutational landscape of RBD among SARS-CoV-2 variants had 21 non-synonymous mutations across 18 distinct sites. Among these, 14 mutations were present in the RBM region directly interacting with the hACE2 receptor. However, Only 3 non-synonymous mutations were observed in Mpro. We found that LCB1 - a de novo-synthesized peptide has the highest binding affinity to RBD despite non-synonymous mutations in variants and engages key residues of RBD-hACE2 interaction such as K417, E484, N487, and N501. Similarly, an antimicrobial peptide; 2JOS, was identified against Mpro with high binding affinity as it interacts with key residues in dimerization sites such as E166 and F140 crucial for viral replication. MD simulations affirm the stability of RBD-LCB1 and Mpro-2JOS complexes with an average RMSD of 1.902 and 2.476 respectively. We ascertain that LCB1 and 2JOS peptides are promising inhibitors to combat emerging variants of SARS-CoV-2 and thus warrant further investigations using in-vitro and in-vivo analysis.Communicated by Ramaswamy H. Sarma.

From De Novo Design to Redesign: Harnessing Computational Protein Design for Understanding SARS-CoV-2 Molecular Mechanisms and Developing Therapeutics

The continuous emergence of novel SARS-CoV-2 variants and subvariants serves as compelling evidence that COVID-19 is an ongoing concern. The swift, well-coordinated response to the pandemic highlights how technological advancements can accelerate the detection, monitoring, and treatment of the disease. Robust surveillance systems have been established to understand the clinical characteristics of new variants, although the unpredictable nature of these variants presents significant challenges. Some variants have shown resistance to current treatments, but innovative technologies like computational protein design (CPD) offer promising solutions and versatile therapeutics against SARS-CoV-2. Advances in computing power, coupled with open-source platforms like AlphaFold and RFdiffusion (employing deep neural network and diffusion generative models), among many others, have accelerated the design of protein therapeutics with precise structures and intended functions. CPD has played a pivotal role in developing peptide inhibitors, mini proteins, protein mimics, decoy receptors, nanobodies, monoclonal antibodies, identifying drug-resistance mutations, and even redesigning native SARS-CoV-2 proteins. Pending regulatory approval, these designed therapies hold the potential for a lasting impact on human health and sustainability. As SARS-CoV-2 continues to evolve, use of such technologies enables the ongoing development of alternative strategies, thus equipping us for the "New Normal".

Designing peptides predicted to bind to the omicron variant better than ACE2 via computational protein design and molecular dynamics

Brought about by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), coronavirus disease (COVID-19) pandemic has resulted in large numbers of worldwide deaths and cases. Several SARS-CoV-2 variants have evolved, and Omicron (B.1.1.529) was one of the important variants of concern. It gets inside human cells by using its S1 subunit's receptor-binding domain (SARS-CoV-2-RBD) to bind to Angiotensin-converting enzyme 2 receptor's peptidase domain (ACE2-PD). Using peptides to inhibit binding interactions (BIs) between ACE2-PD and SARS-CoV-2-RBD is one of promising COVID-19 therapies. Employing computational protein design (CPD) as well as molecular dynamics (MD), this study used ACE2-PD's α1 helix to generate novel 25-mer peptide binders (SPB25) of Omicron RBD that have predicted binding affinities (ΔGbind (MM‑GBSA)) better than ACE2 by increasing favorable BIs between SPB25 and the conserved residues of RBD. Results from MD and the MM-GBSA method identified two best designed peptides (SPB25T7L/K11A and SPB25T7L/K11L with ΔGbind (MM‑GBSA) of -92.4 ± 0.4 and -95.7 ± 0.5 kcal/mol, respectively) that have better ΔGbind (MM‑GBSA) to Omicron RBD than ACE2 (-87.9 ± 0.5 kcal/mol) and SPB25 (-71.6 ± 0.5 kcal/mol). Additionally, they were predicted to have slightly higher stabilities, based on their percent helicities in water, than SBP1 (the experimentally proven inhibitor of SARS-CoV-2-RBD). Our two best designed SPB25s are promising candidates as omicron variant inhibitors.

Computational redesign of Beta-27 Fab with substantially better predicted binding affinity to the SARS-CoV-2 Omicron variant than human ACE2 receptor

During the COVID-19 pandemic, SARS-CoV-2 has caused large numbers of morbidity and mortality, and the Omicron variant (B.1.1.529) was an important variant of concern. To enter human cells, the receptor-binding domain (RBD) of the S1 subunit of SARS-CoV-2 (SARS-CoV-2-RBD) binds to the peptidase domain (PD) of Angiotensin-converting enzyme 2 (ACE2) receptor. Disrupting the binding interactions between SARS-CoV-2-RBD and ACE2-PD using neutralizing antibodies is an effective COVID-19 therapeutic solution. Previous study found that Beta-27 Fab, which was obtained by digesting the full IgG antibodies that were isolated from a patient infected with SARS-CoV-2 Beta variant, can neutralize Victoria, Alpha (B.1.1.7), Beta (B.1.351), Gamma (P.1), and Delta (B.1.617.2) variants. This study employed computational protein design and molecular dynamics (MD) to investigate and enhance the binding affinity of Beta-27 Fab to SARS-CoV-2-RBD Omicron variant. MD results show that five best designed Beta-27 Fabs (Beta-27-D01 Fab, Beta-27-D03 Fab, Beta-27-D06 Fab, Beta-27-D09 Fab and Beta-27-D10 Fab) were predicted to bind to Omicron RBD in the area, where ACE2 binds, with significantly better binding affinities than Beta-27 Fab and ACE2. Their enhanced binding affinities are mostly caused by increased binding interactions of CDR L2 and L3. They are promising candidates that could potentially be employed to disrupt the binding between ACE2 and Omicron RBD.

Computational Protein Design for COVID-19 Research and Emerging Therapeutics

As the world struggles with the ongoing COVID-19 pandemic, unprecedented obstacles have continuously been traversed as new SARS-CoV-2 variants continually emerge. Infectious disease outbreaks are unavoidable, but the knowledge gained from the successes and failures will help create a robust health management system to deal with such pandemics. Previously, scientists required years to develop diagnostics, therapeutics, or vaccines; however, we have seen that, with the rapid deployment of high-throughput technologies and unprecedented scientific collaboration worldwide, breakthrough discoveries can be accelerated and insights broadened. Computational protein design (CPD) is a game-changing new technology that has provided alternative therapeutic strategies for pandemic management. In addition to the development of peptide-based inhibitors, miniprotein binders, decoys, biosensors, nanobodies, and monoclonal antibodies, CPD has also been used to redesign native SARS-CoV-2 proteins and human ACE2 receptors. We discuss how novel CPD strategies have been exploited to develop rationally designed and robust COVID-19 treatment strategies.

Discovery of Highly Potent Small Molecule Pan-Coronavirus Fusion Inhibitors

The unprecedented pandemic of COVID-19, caused by a novel coronavirus, SARS-CoV-2, and its highly transmissible variants, led to massive human suffering, death, and economic devastation worldwide. Recently, antibody-evasive SARS-CoV-2 subvariants, BQ and XBB, have been reported. Therefore, the continued development of novel drugs with pan-coronavirus inhibition is critical to treat and prevent infection of COVID-19 and any new pandemics that may emerge. We report the discovery of several highly potent small-molecule inhibitors. One of which, NBCoV63, showed low nM potency against SARS-CoV-2 (IC₅₀: 55 nM), SARS-CoV-1 (IC₅₀: 59 nM), and MERS-CoV (IC₅₀: 75 nM) in pseudovirus-based assays with excellent selectivity indices (SI > 900), suggesting its pan-coronavirus inhibition. NBCoV63 showed equally effective antiviral potency against SARS-CoV-2 mutant (D614G) and several variants of concerns (VOCs) such as B.1.617.2 (Delta), B.1.1.529/BA.1 and BA.4/BA.5 (Omicron), and K417T/E484K/N501Y (Gamma). NBCoV63 also showed similar efficacy profiles to Remdesivir against authentic SARS-CoV-2 (Hong Kong strain) and two of its variants (Delta and Omicron), SARS-CoV-1, and MERS-CoV by plaque reduction in Calu-3 cells. Additionally, we show that NBCoV63 inhibits virus-mediated cell-to-cell fusion in a dose-dependent manner. Furthermore, the absorption, distribution, metabolism, and excretion (ADME) data of NBCoV63 demonstrated drug-like properties.

Advances in developing ACE2 derivatives against SARS-CoV-2

Extensive immune evasion of SARS-CoV-2 rendered therapeutic antibodies ineffective in the COVID-19 pandemic. Propagating SARS-CoV-2 variants are characterised by immune evasion capacity through key amino acid mutations, but can still bind human angiotensin-converting enzyme 2 (ACE2) through the spike protein and are, thus, sensitive to ACE2-mimicking decoys as inhibitors. In this Review, we examine advances in the development of ACE2 derivatives from the past 3 years, including the recombinant ACE2 proteins, ACE2-loaded extracellular vesicles, ACE2-mimicking antibodies, and peptide or mini-protein mimetics of ACE2. Several ACE2 derivatives are granted potent neutralisation efficacy against SARS-CoV-2 variants that rival or surpass endogenous antibodies by various auxiliary techniques such as chemical modification and practical recombinant design. The derivatives also represent enhanced production efficiency and improved bioavailability. In addition to these derivatives of ACE2, new effective therapeutics against SARS-CoV-2 variants are expected to be developed.

Chemoenzymatic Synthesis of SARS-CoV-2 Homogeneous O-Linked Glycopeptides for Exploring Their Inhibition Functions

Harnessing highly conserved peptides derived from the receptor binding domain (RBD) of spike (S) protein to construct peptide-based inhibitors is one of the most effective strategies to fight against the ever-mutating coronavirus SARS-CoV-2. But how the O-glycosylation affects their inhibition abilities has not been intensively explored. Herein, an intrinsic O-glycosylated peptide P_320-334 derived from RBD was screened and homogeneous O-linked glycopeptides containing Tn (GalNAcα1-O-Ser/Thr), T (Galβ1-3GalNAcα1-O-Ser/Thr), sialyl-Tn (sTn, Siaα2-6GalNAcα1-O-Ser/Thr), and sialyl-T (sT, Siaα2-3Galβ1-3GalNAcα1-O-Ser/Thr) structures were first synthesized via chemoenzymatic strategies. Compared with the unglycosylated peptide, the binding of sT-P_320-334 to hACE2 was enhanced to 133% and the inhibition capacity against RBD-hACE2 binding of sTn- and sT-P_320-334 was significantly increased up to 150-410%. Thus, our results suggest the sialic acid residue on the terminal of short O-glycan structures might strengthen the inhibition capacities of these peptide-based inhibitors, which might provide novel optimization directions for the inhibitor design.

Improvement of native structure-based peptides as efficient inhibitors of protein-protein interactions of SARS-CoV-2 spike protein and human ACE2

New pathogens responsible for novel human disease outbreaks in the last two decades are mainly the respiratory system viruses. Not different was the last pandemic episode, caused by infection of a severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). One of the extensively explored targets, in the recent scientific literature, as a possible way for rapid development of COVID-19 specific drug(s) is the interaction between the receptor-binding domain of the virus’ spike (S) glycoprotein and human receptor angiotensin-converting enzyme 2 (hACE2). This protein-protein recognition process is involved in the early stages of the SARS-CoV-2 life cycle leading to the host cell membrane penetration. Thus, disrupting this interaction may block or significantly reduce the infection caused by the novel pathogen. Previously we have designed (by in silico structure-based analysis) three very short peptides having sequences inspirited by hACE2 native fragments, which effectively bind to the SARS-CoV-2 S protein and block its interaction with the human receptor. In continuation of the above mentioned studies, here we presented an application of molecular modeling approach resulting in improved binding affinity of the previously proposed ligand and its enhanced ability to inhibit meaningful host-virus protein-protein interaction. The new optimized hexapeptide binds to the virus protein with affinity one magnitude higher than the initial ligand and, as a very short peptide, has also great potential for further drug development. The peptide-based strategy is rapid and cost-effective for developing and optimizing efficient protein-protein interactions disruptors and may be successfully applied to discover antiviral candidates against other future emerging human viral infections.

Biochemical and ligand binding properties of recombinant Xenopus laevis cortical granule lectin-1

Intelectins are putative innate immune lectins that are found throughout chordates. The first intelectin reported was Xenopus laevis cortical granule lectin-1 (XCGL-1 or XL-35). XCGL-1 is critical in fertilization membrane development in Xenopus. Here, we explored the biochemical properties of XCGL-1. The cysteines responsible for forming intermolecular disulfide bonds were identified. XCGL-1 adopted a four-lobed structure as observed by electron microscopy. The full-length XCGL-1 and the carbohydrate recognition domain (CRD) bind galactose-containing carbohydrates at nanomolar to micromolar affinities. Molecular modeling suggested that galactoside ligands coordinated the binding site calcium ion and interacted with residues around the groove made available by the non-conserved substitution compared to human intelectin-1. Folding conditions for production of recombinant XCGL-1 CRD were also investigated. Our results not only provide new biochemical insights into the function of XCGL-1, but may also provide foundation for further applications of XCGL-1 as glycobiology tools.

Computational design of Lactobacillus Acidophilus α-L-rhamnosidase to increase its structural stability

α-L-rhamnosidase catalyzes hydrolysis of the terminal α-L-rhamnose from various natural rhamnoglycosides, including naringin and hesperidin, and has various applications such as debittering of citrus juices in the food industry and flavonoid derhamnosylation in the pharmaceutical industry. However, its activity is lost at high temperatures, limiting its usage. To improve Lactobacillus acidophilus α-L-rhamnosidase stability, we employed molecular dynamics (MD) to identify a highly flexible region, as evaluated by its root mean square fluctuation (RMSF) value, and computational protein design (Rosetta) to increase rigidity and favorable interactions of residues in highly flexible regions. MD results show that five regions have the highest flexibilities and were selected for design by Rosetta. Twenty-one designed mutants with the best ΔΔG at each position and ΔΔG < 0 REU were simulated at high temperature. Eight designed mutants with ΔRMSF of highly flexible regions lower than -10.0% were further simulated at the optimum temperature of the wild type. N88Q, N202V, G207D, Q209M, N211T and Y213K mutants were predicted to be more stable and could maintain their native structures better than the wild type due to increased hydrogen bond interactions of designed residues and their neighboring residues. These designed mutants are promising enzymes with high potential for stability improvement.

Computational design of stapled peptide inhibitor against SARS‐CoV ‐2 receptor binding domain

Since its first detection in 2019, the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS‐CoV‐2) has been the cause of millions of deaths worldwide. Despite the development and administration of different vaccines, the situation is still worrisome as the virus is constantly mutating to produce newer variants some of which are highly infectious. This raises an urgent requirement to understand the infection mechanism and thereby design therapeutic‐based treatment for COVID‐19. The gateway of the virus to the host cell is mediated by the binding of the receptor binding domain (RBD) of the virus spike protein to the angiotensin‐converting enzyme 2 (ACE2) of the human cell. Therefore, the RBD of SARS‐CoV‐2 can be used as a target to design therapeutics. The α1 helix of ACE2, which forms direct contact with the RBD surface, has been used as a template in the current study to design stapled peptide therapeutics. Using computer simulation, the mechanism and thermodynamics of the binding of six stapled peptides with RBD have been estimated. Among these, the one with two lactam stapling agents has shown binding affinity, sufficient to overcome RBD‐ACE2 binding. Analyses of the mechanistic detail reveal that a reorganization of amino acids at the RBD‐ACE2 interface produces favorable enthalpy of binding whereas conformational restriction of the free peptide reduces the loss in entropy to result higher binding affinity. The understanding of the relation of the nature of the stapling agent with their binding affinity opens up the avenue to explore stapled peptides as therapeutic against SARS‐CoV‐2.

Computational Site Saturation Mutagenesis of Canonical and Non-Canonical Amino Acids to Probe Protein-Peptide Interactions

Technologies for discovering peptides as potential therapeutics have rapidly advanced in recent years with significant interest from both academic and pharmaceutical labs. These advancements in turn drive the need for new computational tools to design peptides for purposes of advancing lead molecules into the clinic. Here we report the development and application of a new automated tool, AutoRotLib, for parameterizing a diverse set of non-canonical amino acids (NCAAs), N-methyl, or peptoid residues for use with the computational design program Rosetta. In addition, we developed a protocol for designing thioether-cyclized macrocycles within Rosetta, due to their common application in mRNA display using the RaPID platform. To evaluate the utility of these new computational tools, we screened a library of canonical and NCAAs on both a linear peptide and a thioether macrocycle, allowing us to quickly identify mutations that affect peptide binding and subsequently measure our results against previously published data. We anticipate in silico screening of peptides against a diverse chemical space will be a fundamental component for peptide design and optimization, as more amino acids can be explored in a single in silico screen than an in vitro screen. As such, these tools will enable maturation of peptide affinity for protein targets of interest and optimization of peptide pharmacokinetics for therapeutic applications.

Unbinding of hACE2 and inhibitors from the receptor binding domain of SARS-CoV-2 spike protein

The first direful biomolecular event leading to COVID-19 disease is the SARS-CoV-2 virus surface spike (S) protein-mediated interaction with the human transmembrane protein, angiotensin-converting enzyme 2 (hACE2). Prevention of this interaction presents an attractive alternative to thwart SARS-CoV-2 replications. The development of monoclonal antibodies (mAbs) in the convalescent plasma treatment, nanobody, and designer peptides, which recognizes epitopes that overlap with hACE2 binding sites in the receptor-binding domain (RBD) of S protein (S/RBD) and thereby blocking the infection has been the center stage of therapeutic research. Here we report atomistic and reliable in silico structure-energetic features of the S/RBD interactions with hACE2 and its two inhibitors (convalescent mAb, B38, and an alpaca nanobody, Ty1). The discovered potential of mean forces exhibits free energy basin and barriers along the interaction pathways, providing sufficient molecular insights to design a B38 mutant and a Ty1-based peptide with higher binding capacity. While the mutated B38 forms a 60-fold deeper free energy minimum, the designer peptide (Ty1-based) constitutes 38 amino acids and is found to form a 100-fold deeper free energy minimum in the first binding basin than their wild-type variants in complex with S/RBD. Our strategy may help to design more efficacious biologics towards therapeutic intervention against the current raging pandemic.Communicated by Ramaswamy H. Sarma.

Accelerating the discovery of the beyond rule of five compounds that have high affinities toward SARS-CoV-2 spike RBD

The battle against SARS-CoV-2 coronavirus is the focal point for the global pandemic that has affected millions of lives worldwide. The need for effective and selective therapeutics for the treatment of the disease caused by SARS-CoV-2 is critical. Herein, we performed a hierarchical computational approach incorporating molecular docking studies, molecular dynamics simulations, absolute binding energy calculations, and steered molecular dynamics simulations for the discovery of potential compounds with high affinity towards SARS-CoV-2 spike RBD. By leveraging ZINC15 database, a total of 1282 in-clinical and FDA approved drugs were filtered out from nearly 0.5 million protomers of relatively large compounds (MW > 500, and LogP ≤ 5). Our results depict plausible mechanistic aspects related to the blockage of SARS-CoV-2 spike RBD by the top hits discovered. We found that the most promising candidates, namely, ZINC95628821, ZINC95617623, ZINC3979524, and ZINC261494658, strongly bind to the spike RBD and interfere with the human ACE2 receptor. These findings accelerate the rational design of selective inhibitors targeting the spike RBD protein of SARS-CoV-2.Communicated by Ramaswamy H. Sarma.

Optimizing peptide inhibitors of SARS-Cov-2 nsp10/nsp16 methyltransferase predicted through molecular simulation and machine learning

Coronaviruses, including the recent pandemic strain SARS-Cov-2, use a multifunctional 2′-O-methyltransferase (2′-O-MTase) to restrict the host defense mechanism and to methylate RNA. The nonstructural protein 16 2′-O-MTase (nsp16) becomes active when nonstructural protein 10 (nsp10) and nsp16 interact. Novel peptide drugs have shown promise in the treatment of numerous diseases and new research has established that nsp10 derived peptides can disrupt viral methyltransferase activity via interaction of nsp16. This study had the goal of optimizing new analogous nsp10 peptides that have the ability to bind nsp16 with equal to or higher affinity than those naturally occurring. The following research demonstrates that in silico molecular simulations can shed light on peptide structures and predict the potential of new peptides to interrupt methyltransferase activity via the nsp10/nsp16 interface. The simulations suggest that misalignments at residues F68, H80, I81, D94, and Y96 or rotation at H80 abrogate MTase function. We develop a new set of peptides based on conserved regions of the nsp10 protein in the Coronaviridae species and test these to known MTase variant values. This results in the prediction that the H80R variant is a solid new candidate for potential new testing. We envision that this new lead is the beginning of a reputable foundation of a new computational method that combats coronaviruses and that is beneficial for new peptide drug development.

Peptides and peptidomimetics as therapeutic agents for Covid-19

The severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) Covid-19 pandemic has caused high morbidity and mortality rates worldwide. Virus entry into cells can be blocked using several strategies, including inhibition of protein-protein interactions (PPIs) between the viral spike glycoprotein and cellular receptors, as well as blocking of spike protein conformational changes that are required for cleavage/activation and fusogenicity. The spike-mediated viral attachment and entry into cells via fusion of the viral envelope with cellular membranes involve PPIs mediated by short peptide fragments exhibiting particular secondary structures. Thus, peptides that can inhibit these PPIs may be used as potential antiviral agents preventing virus entry and spread. This review is focused on peptides and peptidomimetics as PPI modulators and protease inhibitors against SARS-CoV-2.

Discovery of Highly Potent Fusion Inhibitors with Potential Pan-Coronavirus Activity That Effectively Inhibit Major COVID-19 Variants of Concern (VOCs) in Pseudovirus-Based Assays

We report the discovery of several highly potent small molecules with low-nM potency against severe acute respiratory syndrome coronavirus (SARS-CoV; lowest half-maximal inhibitory concentration (IC₅₀: 13 nM), SARS-CoV-2 (IC₅₀: 23 nM), and Middle East respiratory syndrome coronavirus (MERS-CoV; IC₅₀: 76 nM) in pseudovirus-based assays with excellent selectivity index (SI) values (>5000), demonstrating potential pan-coronavirus inhibitory activities. Some compounds showed 100% inhibition against the cytopathic effects (CPE; IC₁₀₀) of an authentic SARS-CoV-2 (US_WA-1/2020) variant at 1.25 µM. The most active inhibitors also potently inhibited variants of concern (VOCs), including the UK (B.1.1.7) and South African (B.1.351) variants and the Delta variant (B.1.617.2) originally identified in India in pseudovirus-based assay. Surface plasmon resonance (SPR) analysis with one potent inhibitor confirmed that it binds to the prefusion SARS-CoV-2 spike protein trimer. These small-molecule inhibitors prevented virus-mediated cell-cell fusion. The absorption, distribution, metabolism, and excretion (ADME) data for one of the most active inhibitors, NBCoV1, demonstrated drug-like properties. An in vivo pharmacokinetics (PK) study of NBCoV1 in rats demonstrated an excellent half-life (t_1/2) of 11.3 h, a mean resident time (MRT) of 14.2 h, and oral bioavailability. We expect these lead inhibitors to facilitate the further development of preclinical and clinical candidates.

Computational redesign of Fab CC12.3 with substantially better predicted binding affinity to SARS-CoV-2 than human ACE2 receptor

SARS-CoV-2 is responsible for COVID-19 pandemic, causing large numbers of cases and deaths. It initiates entry into human cells by binding to the peptidase domain of angiotensin-converting enzyme 2 (ACE2) receptor via its receptor binding domain of S1 subunit of spike protein (SARS-CoV-2-RBD). Employing neutralizing antibodies to prevent binding between SARS-CoV-2-RBD and ACE2 is an effective COVID-19 therapeutic solution. Previous studies found that CC12.3 is a highly potent neutralizing antibody that was isolated from a SARS-CoV-2 infected patient, and its Fab fragment (Fab CC12.3) bound to SARS-CoV-2-RBD with comparable binding affinity to ACE2. To enhance its binding affinity, we employed computational protein design to redesign all CDRs of Fab CC12.3 and molecular dynamics (MD) to validate their predicted binding affinities by the MM-GBSA method. MD results show that the predicted binding affinities of the three best designed Fabs CC12.3 (CC12.3-D02, CC12.3-D05, and CC12.3-D08) are better than those of Fab CC12.3 and ACE2. Additionally, our results suggest that enhanced binding affinities of CC12.3-D02, CC12.3-D05, and CC12.3-D08 are caused by increased SARS-CoV-2-RBD binding interactions of CDRs L1 and L3. This study redesigned neutralizing antibodies with better predicted binding affinities to SARS-CoV-2-RBD than Fab CC12.3 and ACE2. They are promising candidates as neutralizing antibodies against SARS-CoV-2.

Global diversity of the gene encoding the Pfs25 protein-a Plasmodium falciparum transmission-blocking vaccine candidate

Background

Vaccines against the sexual stages of the malarial parasite Plasmodium falciparum are indispensable for controlling malaria and abrogating the spread of drug-resistant parasites. Pfs25, a surface antigen of the sexual stage of P. falciparum, is a leading candidate for transmission-blocking vaccine development. While clinical trials have reported that Pfs25-based vaccines are safe and effective in inducing transmission-blocking antibodies, the extent of the genetic diversity of Pfs25 in malaria endemic populations has rarely been studied. Thus, this study aimed to investigate the global diversity of Pfs25 in P. falciparum populations.

Methods

A database of 307 Pfs25 sequences of P. falciparum was established. Population genetic analyses were performed to evaluate haplotype and nucleotide diversity, analyze haplotypic distribution patterns of Pfs25 in different geographical populations, and construct a haplotype network. Neutrality tests were conducted to determine evidence of natural selection. Homology models of the Pfs25 haplotypes were constructed, subjected to molecular dynamics (MD), and analyzed in terms of flexibility and percentages of secondary structures.

Results

The Pfs25 gene of P. falciparum was found to have 11 unique haplotypes. Of these, haplotype 1 (H1) and H2, the major haplotypes, represented 70% and 22% of the population, respectively, and were dominant in Asia, whereas only H1 was dominant in Africa, Central America, and South America. Other haplotypes were rare and region-specific, resulting in unique distribution patterns in different geographical populations. The diversity in Pfs25 originated from ten single-nucleotide polymorphism (SNP) loci located in the epidermal growth factor (EGF)-like domains and anchor domain. Of these, an SNP at position 392 (GGA/GCA), resulting in amino acid substitution 131 (Gly/Ala), defined the two major haplotypes. The MD results showed that the structures of H1 and H2 variants were relatively similar. Limited polymorphism in Pfs25 could likely be due to negative selection.

Conclusions

The study successfully established a Pfs25 sequence database that can become an essential tool for monitoring vaccine efficacy, designing assays for detecting malaria carriers, and conducting epidemiological studies of P. falciparum. The discovery of the two major haplotypes, H1 and H2, and their conserved structures suggests that the current Pfs25-based vaccines could be used globally for malaria control.

Graphical Abstract

Supplementary Information

The online version contains supplementary material available at 10.1186/s13071-021-05078-6.

A high-throughput pipeline for design and selection of peptides targeting the SARS-Cov-2 Spike protein

Rapid design, screening, and characterization of biorecognition elements (BREs) is essential for the development of diagnostic tests and antiviral therapeutics needed to combat the spread of viruses such as severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). To address this need, we developed a high-throughput pipeline combining in silico design of a peptide library specific for SARS-CoV-2 spike (S) protein and microarray screening to identify binding sequences. Our optimized microarray platform allowed the simultaneous screening of ~ 2.5 k peptides and rapid identification of binding sequences resulting in selection of four peptides with nanomolar affinity to the SARS-CoV-2 S protein. Finally, we demonstrated the successful integration of one of the top peptides into an electrochemical sensor with a clinically relevant limit of detection for S protein in spiked saliva. Our results demonstrate the utility of this novel pipeline for the selection of peptide BREs in response to the SARS-CoV-2 pandemic, and the broader application of such a platform in response to future viral threats.

SARS-CoV-2 spike protein: pathogenesis, vaccines, and potential therapies

PURPOSE

COVID-19 pandemic has emerged as a result of infection by the deadly pathogenic severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), causing enormous threats to humans. Coronaviruses are distinguished by a clove-like spike (S) protein, which plays a key role in viral pathogenesis, evolutions, and transmission. The objectives of this study are to investigate the distinctive structural features of SARS-CoV-2 S protein, its essential role in pathogenesis, and its use in the development of potential therapies and vaccines.

METHODOLOGY

A literature review was conducted to summarize, analyze, and interpret the available scientific data related to SARS-CoV-2 S protein in terms of characteristics, vaccines development and potential therapies.

RESULTS

The data indicate that S protein subunits and their variable conformational states significantly affect the virus pathogenesis, infectivity, and evolutionary mutation. A considerable number of potential natural and synthetic therapies were proposed based on S protein. Additionally, neutralizing antibodies were recently approved for emergency use. Furthermore, several vaccines utilizing the S protein were developed.

CONCLUSION

A better understanding of S protein features, structure and mutations facilitate the recognition of the importance of SARS-CoV-2 S protein in viral infection, as well as the development of therapies and vaccines. The efficacy and safety of these therapeutic compounds and vaccines are still controversial. However, they may potentially reduce or prevent SARS-CoV-2 infection, leading to a significant reduction of the global health burden of this pandemic.

How much can physics do for protein design?

Physics and physical chemistry are an important thread in computational protein design, complementary to knowledge-based tools. They provide molecular mechanics scoring functions that need little or no ad hoc parameter readjustment, methods to thoroughly sample equilibrium ensembles, and different levels of approximation for conformational flexibility. They led recently to the successful redesign of a small protein using a physics-based folded state energy. Adaptive Monte Carlo or molecular dynamics schemes were discovered where protein variants are populated as per their ligand-binding free energy or catalytic efficiency. Molecular dynamics have been used for backbone flexibility. Implicit solvent models have been refined, polarizable force fields applied, and many physical insights obtained.

Peptide-Based Inhibitors for SARS-CoV-2 and SARS-CoV

The COVID‐19 (coronavirus disease) global pandemic, caused by the spread of the SARS‐CoV‐2 (severe acute respiratory syndrome coronavirus 2) virus, currently has limited treatment options which include vaccines, anti‐virals, and repurposed therapeutics. With their high specificity, tunability, and biocompatibility, small molecules like peptides are positioned to act as key players in combating SARS‐CoV‐2, and can be readily modified to match viral mutation rate. A recent expansion of the understanding of the viral structure and entry mechanisms has led to the proliferation of therapeutic viral entry inhibitors. In this comprehensive review, inhibitors of SARS and SARS‐CoV‐2 are investigated and discussed based on therapeutic design, inhibitory mechanistic approaches, and common targets. Peptide therapeutics are highlighted, which have demonstrated in vitro or in vivo efficacy, discuss advantages of peptide therapeutics, and common strategies in identifying targets for viral inhibition.

Computational design of SARS-CoV-2 peptide binders with better predicted binding affinities than human ACE2 receptor

SARS-CoV-2 is coronavirus causing COVID-19 pandemic. To enter human cells, receptor binding domain of S1 subunit of SARS-CoV-2 (SARS-CoV-2-RBD) binds to peptidase domain (PD) of angiotensin-converting enzyme 2 (ACE2) receptor. Employing peptides to inhibit binding between SARS-CoV-2-RBD and ACE2-PD is a therapeutic solution for COVID-19. Previous experimental study found that 23-mer peptide (SBP1) bound to SARS-CoV-2-RBD with lower affinity than ACE2. To increase SBP1 affinity, our previous study used residues 21–45 of α1 helix of ACE2-PD (SPB25) to design peptides with predicted affinity better than SBP1 and SPB25 by increasing interactions of residues that do not form favorable interactions with SARS-CoV-2-RBD. To design SPB25 with better affinity than ACE2, we employed computational protein design to increase interactions of residues reported to form favorable interactions with SARS-CoV-2-RBD and combine newly designed mutations with the best single mutations from our previous study. Molecular dynamics show that predicted binding affinities of three peptides (SPB25_Q22R, SPB25_{F8R/K11W/L25R} and SPB25_{F8R/K11F/Q22R/L25R}) are better than ACE2. Moreover, their predicted stabilities may be slightly higher than SBP1 as suggested by their helicities. This study developed an approach to design SARS-CoV-2 peptide binders with predicted binding affinities better than ACE2. These designed peptides are promising candidates as SARS-CoV-2 inhibitors.

Effective ACE2 peptide-nanoparticle conjugation and its binding with the SARS-Cov-2 RBD quantified by dynamic light scattering

The infection of coronavirus initiates with the binding between its spike protein receptor binding domain (RBD) and a human cellular receptor called angiotensin-converting enzyme 2 (ACE2). Here, we construct truncated ACE2 peptide-conjugated gold nanoparticles as antiviral scaffolds and study their binding with the SARS-CoV-2 RBD using dynamic light scattering (DLS). Systematic DLS analysis identifies the effective peptide-nanoparticle conjugation and its efficient, specific, and long-lasting multivalent binding towards the RBD with a binding affinity of 41 nM, indicating the potential of this antiviral platform to compete with natural ACE2-RBD interactions for viral blocking and showcasing an accessible approach to measure the binding constants and kinetics.

Targeting SARS-CoV-2 Receptor Binding Domain with Stapled Peptides: An In Silico Study

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has evolved into a pandemic of unprecedented scale. This coronavirus enters cells by the interaction of the receptor binding domain (RBD) with the human angiotensin-converting enzyme 2 receptor (hACE2). In this study, we employed a rational structure-based design to propose 22-mer stapled peptides using the structure of the hACE2 α1 helix as a template. These peptides were designed to retain the α-helical character of the natural structure, to enhance binding affinity, and to display a better solubility profile compared to other designed peptides available in the literature. We employed different docking strategies (PATCHDOCK and ZDOCK) followed by a double-step refinement process (FIBERDOCK) to rank our peptides, followed by stability analysis/evaluation of the interaction profile of the best docking predictions using a 500 ns molecular dynamics (MD) simulation, and a further binding affinity analysis by molecular mechanics with generalized Born and surface area (MM/GBSA) method. Our most promising stapled peptides presented a stable profile and could retain important interactions with the RBD in the presence of the E484K RBD mutation. We predict that these peptides can bind to the viral RBD with similar potency to the control NYBSP-4 (a 30-mer experimentally proven peptide inhibitor). Furthermore, our study provides valuable information for the rational design of double-stapled peptide as inhibitors of SARS-CoV-2 infection.

Computational Design of Oligosaccharide-Producing Levansucrase from Bacillus licheniformis RN-01 to Increase Its Stability at High Temperature

Levan-type fructooligosaccharides (LFOs) and levan can potentially be used as ingredients in prebiotics, skincare products, and antitumor agents. The Y246S mutant of Bacillus licheniformis RN-01 levansucrase (oligosaccharide-producing levansucrase, OPL) was reported to productively synthesize LFOs; however, OPL's thermostability is low at high temperatures. To enhance OPL structural stability, this study employed molecular dynamics (AMBER) to identify a highly flexible region, as measured by its average root-mean-square fluctuation (RMSF) value, on the OPL surface and computational protein design (Rosetta) to rigidify and increase favorable interactions to increase its structural stability. AMBER identified region nine (residues 277-317) as a highly flexible region that was selected for design because it has the highest number of residues and the second-highest average RMSF, and it is farthest from the active site. Rosetta designed 14 mutants with the best ΔΔG value in each position, where three mutants have better ΔG than OPL. To determine whether their flexibilities and stabilities are lower than those of OPL, all 14 designed mutants were simulated at high temperature (500 K), and we found that K296E, G309S, and A310W mutants were predicted to be more stable and could retain their native structures better than OPL. Our results suggest that enhanced structural stabilities of these mutants are caused by increased hydrogen bond strengths of the designed residues and their neighboring residues. This study designed K296E, G309S, and A310W mutants of OPL with high potential for stability improvement, and they could potentially be used for the effective production of LFOs.

Native Structure-Based Peptides as Potential Protein-Protein Interaction Inhibitors of SARS-CoV-2 Spike Protein and Human ACE2 Receptor

Severe acute respiratory syndrome-coronavirus 2 (SARS-CoV-2) is a positive-strand RNA virus that causes severe respiratory syndrome in humans, which is now referred to as coronavirus disease 2019 (COVID-19). Since December 2019, the new pathogen has rapidly spread globally, with over 65 million cases reported to the beginning of December 2020, including over 1.5 million deaths. Unfortunately, currently, there is no specific and effective treatment for COVID-19. As SARS-CoV-2 relies on its spike proteins (S) to bind to a host cell-surface receptor angiotensin-converting enzyme-2(ACE2), and this interaction is proved to be responsible for entering a virus into host cells, it makes an ideal target for antiviral drug development. In this work, we design three very short peptides based on the ACE2 sequence/structure fragments, which may effectively bind to the receptor-binding domain (RBD) of S protein and may, in turn, disrupt the important virus-host protein-protein interactions, blocking early steps of SARS-CoV-2 infection. Two of our peptides bind to virus protein with affinity in nanomolar range, and as very short peptides have great potential for drug development.

Interaction analyses of SARS-CoV-2 spike protein based on fragment molecular orbital calculations

At the stage of SARS-CoV-2 infection in human cells, the spike protein consisting of three chains, A, B, and C, with a total of 3300 residues plays a key role, and thus its structural properties and the binding nature of receptor proteins to host human cells or neutralizing antibodies has attracted considerable interest. Here, we report on interaction analyses of the spike protein in both closed (PDB-ID: 6VXX) and open (6VYB) structures, based on large-scale fragment molecular orbital (FMO) calculations at the level of up to the fourth-order Møller–Plesset perturbation with singles, doubles, and quadruples (MP4(SDQ)). Inter-chain interaction energies were evaluated for both structures, and a mutual comparison indicated considerable losses of stabilization energies in the open structure, especially in the receptor binding domain (RBD) of chain-B. The role of charged residues in inter-chain interactions was illuminated as well. By two separate calculations for the RBD complexes with angiotensin-converting enzyme 2 (ACE2) (6M0J) and B38 Fab antibody (7BZ5), it was found that the binding with ACE2 or antibody partially compensated for this stabilization loss of RBD.

Visualized IFIE results seen from chain-B of spike protein.