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Background. Paeoniae Radix Alba (PRA), the root of the plant Paeonia lactiflora Pall., has been suggested to play an important role for the treatment of asthma. A biochemical understanding of the clinical effects of Paeoniae Radix Alba is needed. Here, we explore the phytochemicals and therapeutic mechanisms via a systematic and comprehensive network pharmacology analysis. Methods. Through TCMSP, PubChem, GeneCards database, and SwissTargetPrediction online tools, potential targets of active ingredients from PRA for the treatment of asthma were obtained. Cytoscape 3.7.2 was used to determine the target of active ingredients of PRA. Target protein interaction (PPI) network was constructed through the STRING database. The Gene Ontology (GO) biological process and Kyoto Encyclopedia of Genes and Genes (KEGG) pathway enrichment analysis were analyzed through the biological information annotation database (DAVID). Results. Our results indicate that PRA contains 21 candidate active ingredients with the potential to treat asthma. The enrichment analysis of GO and KEGG pathways found that the treatment of asthma by PRA may be related to the process of TNF (tumor necrosis factor) release, which can regulate and inhibit multiple signaling pathways such as ceramide signaling. Conclusions. Our work provides a phytochemical basis and therapeutic mechanisms of PRA for the treatment of asthma, which provides new insights on further research on PRA.

BACKGROUND: Active proliferation is specific property of a tumor cells. However, the cost of the analysis is high due to commercial anti-Ki-67 mAbs used as the main immunoreagent for reliable identification of proliferating cells. In this study, recombinant protein was used to obtain specific mAbs for Ki-67 biomarker immunodetection. METHODS: Codon optimized fragment of ki-67 gene was cloned into the pET28c(+)vector. The recombinant protein was purified by immobilized metal affinity chromatography (IMAC) and confirmed by liquid chromatography–mass spectrometry (LC-MS)/MS. Hybridoma cells were obtained by fusing myeloma cells with mouse spleen cells immunized with recombinant antigen. The specificity and activity of mAbs was determined by enzyme-linked immunosorbent assay (ELISA), Western blot and immunocytochemistry. RESULTS: The pET-28c(+)/ ki-67 plasmid, which encodes 355 amino acid protein, was obtained. Analysis by LC-MS/MS of the recombinant antigen showed that 77.5% of the amino-acid sequence belonged to Ki-67 protein. Recombinant fragment of Ki-67 protein was used to obtain specific hybridoma strains. ELISA and Western blot demonstrated high affinity and the specificity of obtained mAbs against Ki-67 protein. Newly generated anti-Ki67 mAbs detected target protein in proliferating cells of MCF-7 cell line by immunocytochemistry. CONCLUSION: Newly developed mAbs are potentially useful as an immunodiagnostic tool for assessing the proliferative activity of breast tumor cells using immunocytochemistry. KEYWORDS: breast cancer, Ki-67, monoclonal antibodies, nuclear antigen, recombinant antigen, tumor cells

Amyloid-like aggregation of proteins is induced by short amyloidogenic sequence segments within a specific protein sequence resulting in self-assembly into β-sheets. We recently validated a technology platform in which synthetic amyloid peptides ("Pept-ins") containing a specific aggregation-prone region (APR) are used to induce specific functional knockdown of the target protein from which the APR was derived, including bacterial, viral, and mammalian cell proteins. In this work, we investigated if Pept-ins can be used as vector probes for in vivo Positron Emission Tomography (PET) imaging of intracellular targets. The radiolabeled Pept-ins [68Ga]Ga-NODAGA-PEG4-vascin (targeting VEGFR2) and [68Ga]Ga-NODAGA-PEG2-P2 (targeting E. coli) were evaluated as PET probes. The Pept-in based radiotracers were cross-validated in a murine tumor and muscle infection model, respectively, and were found to combine target specificity with favorable in vivo pharmacokinetics. When the amyloidogenicity of the interacting region of the peptide is suppressed by mutation, cellular uptake and in vivo accumulation are abolished, highlighting the importance of the specific design of synthetic Pept-ins. The ubiquity of target-specific amyloidogenic sequence segments in natural proteins, the straightforward sequence-based design of the Pept-in probes, and their spontaneous internalization by cells suggest that Pept-ins may constitute a generic platform for in vivo PET imaging of intracellular targets. ispartof: BIOCONJUGATE CHEMISTRY vol:32 issue:9 pages:2052-2064 ispartof: location:United States status: published

Cyclin dependent kinase 2 (CDK2) is an established target protein for therapeutic intervention in various diseases, including cancer. Reported inhibitors of CDK2 target the ATP-binding pocket to inhibit the kinase activity. Many small molecule CDK2 inhibitors have been discovered and their crystal structure with CDK2 or CDK2/Cyclin A complex have been published. NU6140 is a CDK2 inhibitor with moderate potency and selectivity. Herein we report the co-crystal structure determination of NU6140 in complex with CDK2 and confirmation of the binding using various biophysical methods. Our data shows that NU6140 bind to CDK2 with a Kd of 800 nM as determined by SPR and stabilizes the protein against thermal denaturation (ΔTm- 5 ℃). The co-crystal structure determined in our study shows that NU6140 binds in the ATP binding pocket as expected for this class of compounds and interacts with Leu83 and Glu81 with regular hydrogen bonds and with Asp145 via water mediated H-bond. Based on these data, we propose structural modifications of NU6140 to introduce new interactions with CDK2 that can improve its potency while retaining the selectivity.

A green synthetic protocol has been developed for the synthesis of imidazo[4,5-b]pyrazine-conjugated benzamides in 80–85% yield via one-pot three-component reaction of phthalic anhydride, substituted anilines, and pyrazine-2,3-diamine in the presence of phosphoric acid as catalyst in water at 95–100°C for 100–120 min. The proposed protocol has the advantages of mild reaction conditions, good yields, short reaction times, and environmental friendliness. The products have been isolated as clean compounds without using column chromatography. The synthesized imidazo[4,5-b]pyrazine-conjugated benzamides were tested for their anticancer activity against liver and ovarian cancer cell lines (HepG2 and HeLa) with IC50 values ranging from 9.8 to 100 µM. Molecular modeling studies revealed the crucial binding interactions of the target protein and the synthesized ligands. In addition, permeability and bioavailability properties have been predicted along with molecular descriptors such as shape index, molecular complexity, and molecular flexibility. The insights drawn from these studies, would help us to design better potent analogs in the future.

Demand has arisen for developing new azole antifungal agents with the growth of the resistant rate of infective fungal species to current azole antifungals in recent years. Accordingly, the present study reports the synthesis of novel fluconazole (FLC) analogues bearing urea functionality that led to discovering new azole agents with promising antifungal activities. In particular, compounds 8b and 8c displayed broad-spectrum activity and superior in vitro antifungal capabilities compared to the standard drug FLC against sensitive and resistant Candida albicans (C. albicans). The highly active compounds 8b and 8c had potent antibiofilm properties against FLC-resistant C. albicans species. Additionally, these compounds exhibited very low toxicity for three mammalian cell lines and human red blood cells. Time-kill studies revealed that our synthesized compounds displayed a fungicidal mechanism toward fungal growth. Furthermore, a density functional theory (DFT) calculation, additional docking, and independent gradient model (IGM) studies were performed to analyze their structure-activity relationship (SAR) and to assess the molecular interactions in the related target protein. Finally, in vivo results represented a significant reduction in the tissue fungal burden and improvements in the survival rate in a mice model of systemic candidiasis along with in vitro and in silico studies, demonstrating the therapeutic efficiency of compounds 8b and 8c as novel leads for candidiasis drug discovery.

Doxorubicin (DOX)-induced cardiotoxicity has been one of the major limitations for its clinical use. Although extensive studies have been conducted to decipher the molecular mechanisms underlying DOX cardiotoxicity, no effective preventive or therapeutic measures have yet been identified. Microarray analysis showed that multiple long non-coding RNAs (lncRNAs) are differentially expressed between control- and DOX-treated cardiomyocytes. Functional enrichment analysis indicated that the differentially expressed genes are annotated to cardiac hypertrophic pathways. Among differentially expressed lncRNAs, cardiomyocyte mitochondrial dynamic-related lncRNA 1 (CMDL-1) is the most significantly downregulated lncRNA in cardiomyocytes after DOX exposure. The protein-RNA interaction analysis showed that CMDL-1 may target dynamin-related protein 1 (Drp1). Mechanistic analysis shows that lentiviral overexpression of CMDL-1 prevents DOX-induced mitochondrial fission and apoptosis in cardiomyocytes. However, overexpression of CMDL-1 cannot effectively reduce mitochondrial fission when Drp1 is minimally expressed by small interfering RNA Drp1 (siDrp1). Overexpression of CMDL-1 promotes the association between CMDL-1 and Drp1, as well as with phosphorylated (p-)Drp1, as evidenced by RNA immunoprecipitation analysis. These data indicate the role of CMDL-1 in posttranslational modification of a target protein via regulating its phosphorylation. Collectively, our data indicate that CMDL-1 may play an anti-apoptotic role in DOX cardiotoxicity by regulating Drp1 S637 phosphorylation. Thus, CMDL-1 may serve as a potential therapeutic target in DOX cardiotoxicity., Graphical abstract, Under physiological conditions, CMDL-1 may bind to Drp1 and enhance its phosphorylation at S637, and prevent mitochondrial fission. During DOX exposure, a reduced CMDL-1 expression decreases its binding to Drp1 and prevents Drp1 phosphorylation, thereby activating mitochondrial fission and apoptosis, suggesting that CMDL-1 may serve as a novel therapeutic target.

Single-molecule counting is the most accurate and precise method for determining the concentration of a biomarker in solution and is leading to the emergence of digital diagnostic platforms enabling precision medicine. In principle, solid-state nanopores—fully electronic sensors with single-molecule sensitivity—are well suited to the task. Here we present a digital immunoassay scheme capable of reliably quantifying the concentration of a target protein in complex biofluids that overcomes specificity, sensitivity, and consistency challenges associated with the use of solid-state nanopores for protein sensing. This is achieved by employing easily-identifiable DNA nanostructures as proxies for the presence (“1”) or absence (“0”) of the target protein captured via a magnetic bead-based sandwich immunoassay. As a proof-of-concept, we demonstrate quantification of the concentration of thyroid-stimulating hormone from human serum samples down to the high femtomolar range. Further optimization to the method will push sensitivity and dynamic range, allowing for development of precision diagnostic tools compatible with point-of-care format.

The ability to detect and characterize drug binding to a target protein is of high priority in drug discovery research. However, there are inherent challenges when the target of interest is an integral membrane protein (IMP). Assuming successful purification of the IMP, traditional approaches for measuring binding such as surface plasmon resonance (SPR) and fluorescence resonance energy transfer (FRET) have been proven valuable. However, the mass dependence of SPR signals may preclude the detection of binding events when the ligand has a significantly smaller mass than the target protein. In FRET-based experiments, protein labeling through modification may inadvertently alter protein dynamics. Graphene Bio-Electronic Sensing Technology (GBEST) aims to overcome these challenges. Label-free characterization takes place in a microfluidic chamber wherein a fluid lipid membrane is reconstituted directly above the GBEST sensor surface. By leveraging the high conductivity, sensitivity, and electrical properties of monolayer graphene, minute changes in electrostatic charges arising from the binding and unbinding of a ligand to a native IMP target can be detected in real time and in a mass-independent manner. Using crude membrane fractions prepared from cells overexpressing monocarboxylate transporter 1 (MCT1), we demonstrate the ability to (1) form a fluid lipid bilayer enriched with MCT1 directly on top of the GBEST sensor and (2) obtain kinetic binding data for an anti-MCT1 antibody. Further development of this novel technology will enable characterization of target engagement by both low- and high-molecular-weight drug candidates to native IMP targets in a physiologically relevant membrane environment.

RNA hydrolysis presents problems in manufacturing, long-term storage, world-wide delivery, and in vivo stability of messenger RNA (mRNA)-based vaccines and therapeutics. A largely unexplored strategy to reduce mRNA hydrolysis is to redesign RNAs to form double-stranded regions, which are protected from in-line cleavage and enzymatic degradation, while coding for the same proteins. The amount of stabilization that this strategy can deliver and the most effective algorithmic approach to achieve stabilization remain poorly understood. Here, we present simple calculations for estimating RNA stability against hydrolysis, and a model that links the average unpaired probability of an mRNA, or AUP, to its overall hydrolysis rate. To characterize the stabilization achievable through structure design, we compare AUP optimization by conventional mRNA design methods to results from more computationally sophisticated algorithms and crowdsourcing through the OpenVaccine challenge on the Eterna platform. These computational tests were carried out on both model mRNAs and COVID-19 mRNA vaccine candidates. We find that rational design on Eterna and the more sophisticated algorithms lead to constructs with low AUP, which we term ‘superfolder’ mRNAs. These designs exhibit wide diversity of sequence and structure features that may be desirable for translation, biophysical size, and immunogenicity, and their folding is robust to temperature, choice of flanking untranslated regions, and changes in target protein sequence, as illustrated by rapid redesign of superfolder mRNAs for B.1.351, P.1, and B.1.1.7 variants of the prefusion-stabilized SARS-CoV-2 spike protein. Increases in in vitro mRNA half-life by at least two-fold appear immediately achievable.Significance statementMessenger RNA (mRNA) medicines that encode and promote translation of a target protein have shown promising use as vaccines in the current SARS-CoV-2 pandemic as well as infectious diseases due to their speed of design and manufacturing. However, these molecules are intrinsically prone to hydrolysis, leading to poor stability in aqueous buffer and major challenges in distribution. Here, we present a principled biophysical model for predicting RNA degradation, and demonstrate that the stability of any mRNA can be increased at least two-fold over conventional design techniques. Furthermore, the predicted stabilization is robust to post-design modifications. This conceptual framework and accompanying algorithm can be immediately deployed to guide re-design of mRNA vaccines and therapeutics to increase in vitro stability.

COVID-19 disease caused by the SARS-CoV-2 virus has shaken our health and wealth foundations. Although COVID-19 vaccines will become available allowing for attenuation of disease progression rates, distribution of vaccines can create other challenges and delays. Hence repurposed drugs against SARS-CoV-2 can be an attractive parallel strategy that can be integrated into routine clinical practice even in poorly-resourced countries. The present study was designed using knowledge of viral pathogenesis and pharmacodynamics of broad-spectrum antiviral agents (BSAAs). We carried out the virtual screening of BSAAs against the SARS-CoV-2 spike glycoprotein, RNA dependent RNA polymerase (RdRp), the main protease (Mpro) and the helicase enzyme of SARS-CoV-2. Imatinib (a tyrosine kinase inhibitor), Suramin (an anti-parasitic), Glycyrrhizin (an anti-inflammatory) and Bromocriptine (a dopamine agonist) showed higher binding affinity to multiple targets. Further through molecular dynamics simulation, critical conformational changes in the target protein molecules were revealed upon drug binding which illustrates the favorable binding conformations of antiviral drugs against SARS-CoV-2 target proteins. The resulting drugs from the present study in combination and in cocktails from the arsenal of existing drugs could reduce the translational distance and could offer substantial clinical benefit to decrease the burden of COVID-19 illness. This also creates a roadmap for subsequent viral diseases that emerge. Communicated by Ramaswamy H. Sarma

Protein-ligand interaction is one of the highlights of molecular recognition. The most popular application of this type of interaction is drug development which requires a high throughput screening of a ligand that binds to the target protein. Our goal was to find a binding ligand with a simple detection, and once this type of ligand was found, other methods could then be used to measure the detailed kinetic or thermodynamic parameters. We started with the idea that the ligand NMR signal would disappear if it was bound to the non-tumbling mass. In order to create the non-tumbling mass, we tried the aggregates of a target protein, which was fused to the elastin-like polypeptide. We chose the maltose binding proteinas a test case, and we tried it with several sugars, which included maltose, glucose, sucrose, lactose, galactose, maltotriose, and β-cyclodextrin. The maltose signal in the H-1 NMR spectrum disappeared completely as hoped around the protein to ligand ratio of 1:3 at 298 K where the proteins aggregated. The protein signals also disappeared upon aggregation except for the fast-moving part, which resulted in a cleaner background than the monomeric form. Since we only needed to look for a disappearing signal amongst those from the mixture, it should be useful in high throughput screening. Other types of sugars except for the maltotriose and β-cyclodextrin, which are siblings of the maltose, did not seem to bind at all. We believe that our system would be especially more effective when dealing with a smaller target protein, so both the protein and the bound ligand would lose their signals only when the aggregates formed. We hope that our proposed method would contribute to accelerating the development of the potent drug candidates by simultaneously identifying several binders directly from a mixture. Supplementary Information The online version contains supplementary material available at 10.1007/s10858-021-00381-x.

Main protease (Mpro) and Spike (S) proteins are said potential drug targets of COVID-19. Pneumonia like respiratory illness caused by SARS-CoV-2 is spreading rapidly due to its replication and transmission rate. Protease is the protein that is involved in both replication and transcription. Since CoV-2 shares, genomic similarity with CoV and MERS-CoV, drugs from previous outbreaks are used as primary treatment of the disease. In-silico drug development strategies are said to be faster and effective than in-vitro with a lesser amount of risk factors. Fragment Based Drug Designing (FBDD), also known as rational drug design in which a potential target protein is selected and docked with a lead-like molecule that eventually leads to drug development. Nine (9) drugs that are currently being used to treat patients of coronavirus were selected in this study from the latest literature review and fragmented as per rules followed by crosslinking of drug fragments using editor tools. These native drugs and synthesized drugs were then docked against the main protease. Results of the study revealed that one of the crosslinked lead-like compounds showed a higher binding affinity (∆G) more than any of the native compounds. Further, the results of this study suggested that the combination of potential drugs can be an effective way to develop new drugs to treat a deadly disease. © 2021, Editorial board of Journal of Experimental Biology and Agricultural Sciences. All rights reserved.

[Image: see text] Peptide-based drugs are an attractive new modality of therapeutics, and in vitro selection from a large-scale library is a powerful way to identify new lead sequences. In conventional screenings, peptide specificity and stability in physiological heterogenous environments are not evaluated, which sometimes makes subsequent optimization difficult. Here we show that selection using a cDNA display system can be performed in a high percentage of serum and that this might be an option to select molecules with high potency and stability in a biological context. Specifically, we chose interleukin-17A as a target protein and performed in vitro selection of cyclic peptide aptamers from a library of approximately 10(12) members in the presence of serum. The selected molecules had nanomolar affinity to the target and were stable in serum. Interestingly, we found that a component of the DNA linker that connected the peptide and cDNA may play a pivotal role in target binding.

Antimicrobial resistance (AMR) threatens millions of people around the world and has been declared a global risk by the World Economic Forum. One of the important AMR mechanisms in Enterobacteriaceae is the production of extended-spectrum β-lactamases. The most common ESBL, CTX-M β-lactamases, is spread to the world by CTX-M-15 and CTX-M-14. Sulbactam, clavulanic acid, and tazobactam are first-generation β-lactamase inhibitors and avibactam is a new non-β-lactam β-lactamase inhibitor. We studied that avibactam, sulbactam, clavulanic acid, tazobactam, and quercetin natural flavonoids were docked to target protein CTXM-15. Subsequently, the complexes were simulated using the molecular dynamics simulations method during 100 ns for determining the final binding positions of ligands. Clavulanic acid left CTX-M-15 and other ligands remained in the binding site after the simulation. The estimated binding energies were calculated during 100 ns simulation by the MMGBSA-MMPBSA method. The estimated free binding energies of avibactam, sulbactam, quercetin, tazobactam, and clavulanic acid were sorted as –33.61 kcal/mol, –16.04 kcal/mol, –14 kcal/mol, –12.68 kcal/mol, and –2.95 kcal/mol. As a result of both final binding positions and free binding energy calculations, Quercetin may be evaluated an alternative candidate and a more potent β-lactamases inhibitor for new antimicrobial combinations to CTX-M-15. The results obtained in silico studies are predicted to be a preliminary study for in vitro studies for quercetin and similar bioactive natural compounds. These studies are notable for the discovery of natural compounds that can be used in the treatment of infections caused by β-lactamase-producing pathogens.

Abstract The goal of this work was to identify the target protein and epitope of a previously reported Escherichia coli O157:H7 (ECO157)–specific monoclonal antibody (mAb) 2G12. mAb 2G12 has shown high specificity for the recovery and detection of ECO157. To achieve this goal, the target protein was first separated by two-dimensional gel electrophoresis (2-DE) and located by Western blot (WB). The protein spots were identified to be the outer membrane protein (Omp) C by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF–MS). After that, the target protein was purified by immunoaffinity chromatography (IAC) and subjected to in situ enzymatic cleavage of the vulnerable peptides. Eight eluted peptides of OmpC identified by liquid chromatography–tandem mass spectrometry (LC–MS/MS) were further mapped onto the homologous protein structure of E. coli OmpC (2IXX). The topology of OmpC showed that three peptides had extracellular loops. Epitope mapping with overlapping peptide library and sequence homology analysis revealed that the epitope consisted of a specific peptide, “LGVING,” and an adjacent conservative peptide, “TQTYNATRVGSLG.” Both peptides loop around the overall structure of the epitope. To test the availability of the epitope when ECO157 was grown under different osmolarity, pH, and nutrition levels, the binding efficacy of mAb 2G12 with ECO157 grown in these conditions was evaluated. Results further demonstrated the good stability of this epitope under potential stressful environmental conditions. In summary, this study revealed that mAb 2G12 targeted one specific and one conservative extracellular loop (peptide) of the OmpC present on ECO157, and the epitope was stable and accessible on ECO157 cells grown in different environment. Key points • OmpC is the target of a recently identified ECO157-specific mAb 2G12. • Eight peptides were identified from the OmpC by using LC–MS/MS. • The specificity of mAb 2G12 is mainly determined by the “LGVING” peptide.

In the past two decades, a DNA-encoded chemical library (DEL or DECL) has emerged and has become a major technology platform for ligand discovery in drug discovery as well as in chemical biology research. Although based on a simple concept, i.e., encoding each compound with a unique DNA tag in a combinatorial chemical library, DEL has been proven to be a powerful tool for interrogating biological targets by accessing vast chemical space at a fraction of the cost of traditional high-throughput screening (HTS). Moreover, the recent technological advances and rapid developments of DEL-compatible reactions have greatly enhanced the chemical diversity of DELs. Today, DELs have been adopted by nearly all major pharmaceutical companies and are also gaining momentum in academia. However, this field is heavily biased toward library encoding and synthesis, and an underexplored aspect of DEL research is the selection methods. Generally, DEL selection is considered to be a massive binding assay conducted over an immobilized protein to identify the physical binders using the typical bind-wash-elute procedure. In recent years, we and other research groups have developed new approaches that can perform DEL selections in the solution phase, which has enabled the selection against complex biological targets beyond purified proteins. On the one hand, these methods have significantly widened the target scope of DELs; on the other hand, they have enabled the functional and potentially phenotypic assays of DELs beyond simple binding. An overview of these methods is provided in this Account.Our laboratory has been using DNA-programmed affinity labeling (DPAL) as the main strategy to develop new DEL selection methods. DPAL is based on DNA-templated synthesis; by using a known ligand to guide the target binding, DPAL is able to specifically establish a stable linkage between the target protein and the ligand. The DNA tag of the target-ligand conjugates serves as a programmable handle for protein characterization or hit compound decoding in the case of DEL selections. DPAL also takes advantage of the fast reaction kinetics of photo-cross-linking to achieve high labeling specificity and fidelity, especially in the selection of DNA-encoded dynamic libraries (DEDLs). DPAL has enabled DEL selections not only in buffer and cell lysates but also with complex biological systems, such as large protein complexes and live cells. Moreover, this strategy has also been employed in other biological applications, such as site-specific protein labeling, protein detection, protein profiling, and target identification. In the Account, we describe these methods, highlight their underlying principles, and conclude with perspectives of the development of the DEL technology.

Targeted protein degradation (TPD) has emerged as a promising therapeutic strategy. Most TPD technologies use the ubiquitin-proteasome system, and are therefore limited to targeting intracellular proteins. To address this limitation, we developed a class of modular, bifunctional synthetic molecules called MoDE-As (molecular degraders of extracellular proteins through the asialoglycoprotein receptor (ASGPR)), which mediate the degradation of extracellular proteins. MoDE-A molecules mediate the formation of a ternary complex between a target protein and ASGPR on hepatocytes. The target protein is then endocytosed and degraded by lysosomal proteases. We demonstrated the modularity of the MoDE-A technology by synthesizing molecules that induce depletion of both antibody and proinflammatory cytokine proteins. These data show experimental evidence that nonproteinogenic, synthetic molecules can enable TPD of extracellular proteins in vitro and in vivo. We believe that TPD mediated by the MoDE-A technology will have widespread applications for disease treatment.

Site-specific protein labeling methods are highly valuable tools for research and applications. We present a new protein labeling method that allows covalent attachment of a chromo-and fluorogenic flavin (FMN) to any targeted protein using a short flavinylation peptide-Tag. We show that this peptide can be as short as 7 residues and can be located at the N-Terminus, C-Terminus, or in internal regions of the target protein. Analogous to kinase-catalyzed phosphorylation, the flavin is covalently attached via a stable phosphothreonyl linkage. The site-specific covalent tethering of FMN is accomplished by using a bacterial flavin transferase. The covalent coupling of FMN was shown to work in Escherichia coli and Saccharomyces cerevisiae cells and could be performed in vitro, rendering the "Flavin-Tag"method a powerful tool for the selective decoration of proteins with a biocompatible redox-Active fluorescent chromophore.

Transition-metal-based approaches to selectively modify proteins hold promise in addressing challenges in chemical biology. Unique bioorthogonal chemistry can be achieved with preformed metal-based compounds; however, their utility in native protein sites within cells remain underdeveloped. Here, we tune the ancillary ligands of cyclometalated gold(III) as a reactive group, and the gold scaffold allows for rapid modification of a desired cysteine residue proximal to the ligand binding site of a target protein. Moreover, evidence for a ligand association mechanism toward C-S bond formation by X-crystallography is established. The observed reactivity of cyclometalated gold(III) enables the rational design of a cysteine-targeted covalent inhibitor of mutant KRAS. This work illustrates the potential of structure-activity relationship studies to tune kinetics of cysteine arylation and rational design of metal-mediated ligand affinity chemistry (MLAC) of native proteins.

Background: The rapid spread of SARS-CoV-2 has caused havoc and panic among individuals, which has further worsened due to the unavailability of a proven drug(s) regime. Objective: The current work involves drug repurposing from the pool of USFDA approved drugs involving in silico virtual screening technique against COVID-19. Materials and Methods: Methodology involves virtual screening of 8548 FDA approved drugs against target protein endoribonuclease NendoU (Nsp15) (PDB ID: 6VWW). Results: Virtual screening-based analysis enabled us to identify four drugs, Eprosartan, Inarigivir soproxil, Foretinib, and DB01813 that could plausibly target Nsp15 against COVID-19 disease. Conclusion: The work offers the scope to corroborate the findings via in vitro and in vivo techniques to identify the potential of selected leads against COVID-19. The outcome may also help in tracing their molecular mechanism(s) in addition to their development at the clinical level in the future.

Background: Essential proteins play a crucial role in most of the living organisms. The computer-based task of predicting essential proteins is important for target protein identification, disease treatment and suitable drug development. Objective: Traditionally many experimental and centrality measures have been proposed by researchers to predict protein essentiality. Methods: The prediction accuracy, sensitivity, specificity identified by the traditional methods is very low. Results and Discussion: In this research work, a novel computational based approach such as NCKNN model has been proposed to identify the essential proteins. The proposed work uses a combination of network topology measure and machine learning model to predict the essential proteins. Conclusion: The proposed work shows a remarkable improvement than seven traditional centrality based measures such as DC, BC, CC, EC, NC, ECC and SC in terms of the metrics such as accuracy(A1), precision(P1), recall(R1), sensitivity(SE) and specificity(SP).

The Virus BioResistor (VBR) is a biosensor capable of the rapid and sensitive detection of small protein disease markers using a simple dip-and-read modality. For example, the bladder cancer-associated protein DJ-1 (22 kDa) can be detected in human urine within 1.0 min. with a limit-of-detection (LOD) of 10 pM. The VBR uses engineered virus particles as receptors to recognize and selectively bind the protein of interest. These virus particles are entrained in a conductive poly(3,4 ethylenedioxythiophene) or PEDOT channel. The electrical impedance of the channel increases when the target protein is bound by the virus particles. But VBRs exhibit a sensitivity that is inversely related to the molecular weight of the protein target. Thus, large proteins, such as IgG antibodies (150 kDa), can be undetectable even at high concentrations. We demonstrate that the electrochemical over-oxidation of the VBR’s PEDOT channel increases its electrical impedance, conferring enhanced sensitivity for both small and large proteins. Over-oxidation makes possible the detection of two an antibody, undetectable at a normal VBR, with a limit-of-detection of 40 ng/mL (250 pM), and a dynamic range for quantitation extending to 600 ng/mL.

Baculiferins are a group of marine sponge-derived polycyclic alkaloids with anti-HIV (human immunodeficiency virus) activities. To identify additional baculiferin-based congeners for SAR analysis and to investigate the mode of action, a total of 18 new baculiferin-type derivatives were synthesized. The inhibitory activities of the congeners against the HIV-1 virus were evaluated in vitro, and the relevant SAR was discussed. Compound 18 exerted the most potent activity toward VSV-G-pseudotyped HIV-1 (IC50 of 3.44 μM) and HIV-1 strain SF33 (IC50 of 2.80 μM) in vitro. To identify the cellular targets, three photoaffinity baculiferin probes were simultaneously synthesized. Photoaffinity labeling experiments together with LC-MS/MS data identified aspartate-tRNA ligase (DARS) as a putative target protein of 18. The overexpression and knockdown of DARS in HEK293T cells provided additional data to demonstrate that DARS is a potential target protein in the regulation of HIV virus infection. The modes of antiviral baculiferins 13 and 18 binding to DARS were determined by a molecular docking simulation. Thus, baculiferin 18 is considered a promising lead as a new molecular target for the development of anti-HIV agents.

Proximity biotinylation workflows typically require CRISPR-based genetic manipulation of target cells. To overcome this bottleneck, we fused the TurboID proximity biotinylation enzyme to Protein A. Upon target cell permeabilization, the ProtA-Turbo enzyme can be targeted to proteins or post-translational modifications of interest using bait-specific antibodies. Addition of biotin then triggers bait-proximal protein biotinylation. Biotinylated proteins can subsequently be enriched from crude lysates and identified by mass spectrometry. We demonstrate this workflow by targeting Emerin, H3K9me3 and BRG1. Amongst the main findings, our experiments reveal that the essential protein FLYWCH1 interacts with a subset of H3K9me3-marked (peri)centromeres in human cells. The ProtA-Turbo enzyme represents an off-the-shelf proximity biotinylation enzyme that facilitates proximity biotinylation experiments in primary cells and can be used to understand how proteins cooperate in vivo and how this contributes to cellular homeostasis and disease., Proximity biotinylation is a powerful tool to profile interactomes, but it requires genetic engineering of the target protein. Here, the authors develop a proximity biotinylation enzyme that can be directed to the target using antibodies, enabling interactome profiling of endogenous proteins or PTMs.

We developed a photoreactive molecular glue, BPGlue-N3, which can provide a universal strategy to enhance the efficacy of DNA aptamers by temporary-to-permanent stepwise stabilization of their conjugates with target proteins. As a proof-of-concept study, we applied BPGlue-N3 to the SL1 (DNA aptamer)/c-Met (target protein) conjugate system. BPGlue-N3 can adhere to and temporarily stabilize this aptamer/protein conjugate multivalently using its guanidinium ion (Gu+) pendants that form a salt bridge with oxyanionic moieties (e.g., carboxylate and phosphate) and benzophenone (BP) group that is highly affinitive to DNA duplexes. BPGlue-N3 is designed to carry a dual-mode photoreactivity; upon exposure to UV light, the temporarily stabilized aptamer/protein conjugate reacts with the photoexcited BP unit of adhering BPGlue-N3 and also a nitrene species, possibly generated by the BP-to-N3 energy transfer in BPGlue-N3. We confirmed that SL1, covalently conjugated with c-Met, hampered the binding of hepatocyte growth factor (HGF) onto c-Met, even when the SL1/c-Met conjugate was rinsed prior to the treatment with HGF, and suppressed cell migration caused by HGF-induced c-Met phosphorylation.

The present work describes the synthesis of 4-amino-6-(2-benzylidenehydrazinyl)-pyrimidine-5-carbonitrile derivatives, 4-amino-6-[(2-phenylethyl)amino]pyrimidine-5-carbonitrile, and 4-amino-6-(piperidin-1-yl)pyrimidine-5-carbonitrile. The compounds were characterized by FT-IR and 1H and 13C NMR spectroscopy and mass spectrometry. All the compounds were evaluated for in vitro antimicrobial activity against different bacterial and fungal strains. The minimum inhibitory concentrations (MICs) of all the compounds were validated. 4-Amino-6-[2-(3,4-dimethoxybenzylidene)hydrazinyl]pyrimidine-5-carbonitrile and 4-amino-6-(piperidin-1-yl)pyrimidine-5-carbonitrile, which have the lowest MIC values were selected for cell leakage analysis and bacterial growth curve study. It was found that both the compounds have potential to induce bacterial cell membrane rupture and disintegration. Field emission scanning electron microscopic analysis confirmed the effect of the selected compounds on the morphology of both Gram-positive (S. aureus) and Gram-negative (E. coli) bacteria. The mechanism of interaction between the drug and the target protein of S. aureus and E. coli was studied by molecular docking.

A workflow to expand crystallographic fragment hits to higher affinity compounds using readily available analogs is described and successfully applied., In recent years, crystallographic fragment screening has matured into an almost routine experiment at several modern synchrotron sites. The hits of the screening experiment, i.e. small molecules or fragments binding to the target protein, are revealed along with their 3D structural information. Therefore, they can serve as useful starting points for further structure-based hit-to-lead development. However, the progression of fragment hits to tool compounds or even leads is often hampered by a lack of chemical feasibility. As an attractive alternative, compound analogs that embed the fragment hit structurally may be obtained from commercial catalogs. Here, a workflow is reported based on filtering and assessing such potential follow-up compounds by template docking. This means that the crystallographic binding pose was integrated into the docking calculations as a central starting parameter. Subsequently, the candidates are scored on their interactions within the binding pocket. In an initial proof-of-concept study using five starting fragments known to bind to the aspartic protease endothiapepsin, 28 follow-up compounds were selected using the designed workflow and their binding was assessed by crystallography. Ten of these compounds bound to the active site and five of them showed significantly increased affinity in isothermal titration calorimetry of up to single-digit micromolar affinity. Taken together, this strategy is capable of efficiently evolving the initial fragment hits without major synthesis efforts and with full control by X-ray crystallography.

Proper targeting of the βPAK-interacting exchange factor (βPIX)/G protein-coupled receptor kinase-interacting target protein (GIT) complex into distinct cellular compartments is essential for its diverse functions including neurite extension and synaptogenesis. However, the mechanism for translocation of this complex is still unknown. In the present study, we reported that the conventional kinesin, called kinesin-1, can transport the βPIX/GIT complex. Additionally, βPIX bind to KIF5A, a neuronal isoform of kinesin-1 heavy chain, but not KIF1 and KIF3. Mapping analysis revealed that the tail of KIF5s and LZ domain of βPIX were the respective binding domains. Silencing KIF5A or the expression of a variety of mutant forms of KIF5A inhibited βPIX targeting the neurite tips in PC12 cells. Furthermore, truncated mutants of βPIX without LZ domain did not interact with KIF5A, and were unable to target the neurite tips in PC12 cells. These results defined kinesin-1 as a motor protein of βPIX, and may provide new insights into βPIX/GIT complex-dependent neuronal pathophysiology. [BMB Reports 2021; 54(7): 380-385].

Heat shock protein 90 (HSP90) has been recognized as a crucial target in cancer cells. However, various toxic reactions targeting the ATP binding site of HSP90 may not be the best choice for HSP90 inhibitors. In this paper, an ellagic acid derivative, namely, okicamelliaside (OCS), with antitumor effects was found. To identify potential anti-cancer mechanisms, an OCS photosensitive probe was applied to target fishing and tracing. Chemical proteomics and protein-drug interaction experiments have shown that HSP90 is a key target for OCS, with a strong binding affinity (K(D) = 6.45 μM). Mutation analysis of the target protein and molecular dynamics simulation revealed that OCS could competitively act on the key Glu-47 site at the N-terminal chaperone pocket of HSP90, where the co-chaperone CDC37 binds to HSP90, affect its stability and reduce the ∆G(bind) of HSP90-CDC37. It was demonstrated that OCS destroys the protein–protein interactions of HSP90-CDC37; selectively affects downstream kinase client proteins of HSP90, including CDK4, P-AKT(473), and P-ERK1/2; and exerts antitumor effects on A549 cells. Furthermore, tumor xenograft experiments demonstrated high antitumor activity and low toxicity of OCS in the same way. Our findings identified a novel N-terminal chaperone pocket natural inhibitor of HSP90, that is, OCS, which selectively inhibits the formation of the HSP90-CDC37 protein complex, and provided further insight into HSP90 inhibitors for anti-cancer candidate drugs. [Image: see text]

Coronavirus disease 2019 (COVID-19), resulting from infection by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), can cause severe and fatal pneumonia along with other life-threatening complications. The COVID-19 pandemic has taken a heavy toll on the healthcare system globally and has hit the economy hard in all affected countries. As a result, there is an unmet medical need for both the prevention and treatment of COVID-19 infection. Several herbal remedies have claimed to show promising clinical results, but the mechanisms of action are not clear. We set out to identify the anti-viral natural products of these herbal remedies that presumably inhibit the life cycle of SARS-CoV-2. Particularly we chose four key SARS-CoV-2 viral enzymes as targets: Papain-like protease, Main protease, RNA dependent RNA polymerase, and 2’-O-ribose methyltransferase, which were subjected to an unbiased in silico screening against a small molecule library of 33,765 compounds originating from herbs and medicinal plants. The small molecules were then ranked based on their free energy of fitting into the “druggable” pockets on the surface of each target protein. We have analyzed the best “fit” molecules and annotated them according to their plant sources and pharmacokinetic properties. Here we present a list of potential anti-viral ingredients of herbal remedies targeting SARS-CoV-2 and explore the potential mechanisms of action of these compounds as a framework for further development of chemoprophylaxis agents against COVID-19. Graphic abstract Supplementary Information The online version contains supplementary material available at 10.1007/s12539-021-00461-4.

The novel SARS-CoV-2 (severe acute respiratory syndrome coronavirus-2) is spreading, as the causative pathogen of coronavirus disease-19 (COVID-19). It has infected more than 1.65 billion people all over the world since it was discovered and reported 3.43 million deaths by mid of May 2021. SARS-CoV-2 enters the host cell by binding to viral surface glycoprotein (S protein) with human ACE2 (angiotensin-converting enzyme2). Spike protein (contains S1 and S2 sub-domains) molecular interaction with the host cells is considered as a major step in the viral entry and disease initiation and progression and this identifies spike protein as a promising therapeutic target against antiviral drugs. Currently, there are no efficient antiviral drugs for the prevention of COVID-19 infection. In this study, we have analyzed global 8719 spike protein sequences from patients infected with SAR-CoV-2. These SAR-CoV-2 genome sequences were downloaded from the GISAID database. By using an open reading frame (ORF) tool we have identified the spike protein sequence. With these, all spike protein amino acid sequences are subjected to multiple sequence alignment (MSA) with Wuhan strain spike protein sequence as a query sequence, and it shows all SAR-CoV strain spike proteins are 99.8% identical. In the mutational analysis, we found 639 mutations in the spike protein sequence of SARS-CoV-2 and identified/highlighted 20 common mutations L5F, T22I, T29I, H49Y, L54F, V90F, S98F, S221L, S254F, V367F, A520S, T572I, D614G, H655Y, P809S, A879S, D936Y, A1020S, A1078S, and H1101Y. Further, we have analyzed the crystal structure of the 2019-nCoV chimeric receptor-binding complex with ACE2 (PDB ID: 6VW1) as a major target protein. The spike receptor binding protein (RBD) used as target region for our studies with FDA-approved drugs for repurposing, and identified few anti-SARS-CoV2 potential drugs (Silmitasertib, AC-55541, Merimepodib, XL413, AZ3451) based on their docking score and binding mode calculations expected to strongly bind to motifs of ACE2 receptor and may show impart relief in COVID-19 patients.

Consensus design (CD) is a representative sequence-based protein design method that enables the design of highly functional proteins by analyzing vast amounts of protein sequence data. This study proposes a partial consensus design (PCD) of a protein as a derivative approach of CD. The method replaces the target protein sequence with a consensus sequence in a secondary-structure-dependent manner (i.e., regionally dependent and divided into α-helix, β-sheet, and loop regions). In this study, we generated several artificial partial consensus l-threonine 3-dehydrogenases (PcTDHs) by PCD using the TDH from Cupriavidus necator (CnTDH) as a target protein. Structural and functional analysis of PcTDHs suggested that thermostability would be independently improved when consensus mutations are introduced into the loop region of TDHs. On the other hand, enzyme kinetic parameters (kcat/Km) and average productivity would be synergistically enhanced by changing the combination of the mutations-replacement of one region of CnTDH with a consensus sequence provided only negative effects, but the negative effects were nullified when the two regions were replaced simultaneously. Taken together, we propose the hypothesis that there are protein regions that encode individual protein properties, such as thermostability and activity, and that the introduction of consensus mutations into these regions could additively or synergistically modify their functions.

Objectives To explore Saccharomyces cerevisiae as an expression platform for dengue oral immune complex vaccine development. Results Molecular engineering was applied to create a fusion gene construct (scEDIII-PIGS) consisting of a yeast codon optimized sequence encoding for a synthetic consensus dengue envelope domain III (scEDIII) followed by a modified IgG Fc domain (PIGS). Northern blot showed transcription of the target gene, with a temporal expression pattern similar to those from previous work. Western blot showed assembly of various immune complexes from monomer to hexamer. Partial purification of scEDIII-PIGS was also attempted to demonstrate the feasibility of yeast system for immune complex vaccine development. Approximately 1 mg of scEDIII-PIGS can be produced from 1 l culture. Conclusion This work demonstrated for the first time that various immunocomplex structures of our target protein could be efficiently produced in S. cerevisiae for future application in developing oral and injectable vaccines against various pathogens.

Recently, molecular generation models based on deep learning have attracted significant attention in drug discovery. However, most existing molecular generation models have serious limitations in the context of drug design wherein they do not sufficiently consider the effect of the three-dimensional (3D) structure of the target protein in the generation process. In this study, we developed a new deep learning-based molecular generator, SBMolGen, that integrates a recurrent neural network, a Monte Carlo tree search, and docking simulations. The results of an evaluation using four target proteins (two kinases and two G protein-coupled receptors) showed that the generated molecules had a better binding affinity score (docking score) than the known active compounds, and the generated molecules possessed a broader chemical space distribution. SBMolGen not only generates novel binding active molecules but also presents 3D docking poses with target proteins, which will be useful in subsequent drug design. The code is available at https://github.com/clinfo/SBMolGen.

Acquired immune deficiency syndrome (AIDS) is a fatal disease caused by human immunodeficiency virus (HIV). Although 23 different drugs have been available, the treatment of AIDS remains challenging because the virus mutates very quickly which can lead to drug resistance. Therefore, predicting drug resistance before treatment is crucial for individual treatments. Here, based on HIV target protein sequence information, we analyzed 21-drug resistance caused by mutated residues using machine learning (ML) methods. To transform target sequences into numeric vectors, seven physicochemical properties were used, which can well represent the interacting characteristics of target proteins. Then, principal component analysis (PCA) method was adopted to reduce the feature dimensionality. Random forest (RF) and support vector machine (SVM) based on three different kernel functions, including linear, polynomial and radial basis function (RBF), were all employed. By comparisons, we found that RBF-based SVM method gives a comparative performance with RF model. Further, we added the weight information to RBF-based SVM method by four different weight evaluation methods of RF, eXtreme Gradient Boosting (XGB), CfsSubsetEval and ReliefFAttributeEval, respectively. Results show that the RF-weighted RBF-based SVM yield the superior performance and 13 out of 21 drug models provide the correlation coefficients (R2) over 0.8 and 3 of them are higher than 0.9. Finally, position-specific importance analysis indicates that most of the mutation residues with high RF weight scores are proved to be closely related with drug resistance, which has been revealed in previous reports. Overall, we can expect that this method can be a supplementary tool for predicting HIV drug resistance for newly discovered mutations. Here, based on HIV target protein sequence information, we analyzed 21-drug resistance caused by mutated residues using machine learning (ML) methods by fusing the weight information of different mutation positions.

Purpose: To investigate by in silico screening the anti-inflammatory constituents of Cinnamomum cassia twigs. Methods: Information on the constituents of C. cassia twigs was retrieved from the online Traditional Chinese Medicines (TCM) database and literature. Inflammation-related target proteins were identified from DrugBank, Online Mendelian Inheritance in Man (OMIM), Therapeutic Target Database (TTD), Genetic Association Database (GAD), and PharmGKB. The identified compounds were filtered by Lipinski’s rules with Discovery Studio software. The “Libdock” module was used to perform molecular docking; LibdockScores and default cutoff values for hydrogen bonds and van der Waals interactions were recorded. LibdockScores between the prototype ligand and target protein were set as the threshold; compounds with higher LibdockScores than threshold were regarded as active compounds. Cytoscape software was used to construct active constituent-target protein interaction networks. Results: Sixty-nine potential inflammatory constituents with good drug-like properties in C. cassia twigs were screened in silico based on molecular docking and network pharmacology analysis. JAK2, mPEGS-1, COX-2, IL-1β, and PPARγ were considered the five most important target proteins. Compounds such as methyl dihydromelilotoside, hierochin B, dihydromelilotoside, dehydrodiconiferyl alcohol, balanophonin, phenethyl (E)-3-[4-methoxyphenyl]-2-propenoate, quercetin, and luteolin each interacted with more than six of the selected target proteins. Conclusion: C. cassia twigs possess active compounds with good drug-like properties that can potentially be developed to treat inflammation with multi-components on multi-targets.

Nitric oxide (NO) and hydrogen sulfide (H2S) were previously only known for their toxic properties. Now they are regarded as potent gaseous messenger molecules (gasotransmitters) that rapidly transverse cell membranes and transduce cellular signals through their chemical reactions and modifications to protein targets. Both are known to regulate numerous physiological functions including angiogenesis, vascular tone, and immune response, to name a few. NO and H2S often work synergistically and in competition to regulate each other's synthesis, target protein activity via posttranslational modifications (PTMs), and chemical interactions. In addition to their canonical modes of action, increasing evidence has demonstrated that NO and H2S share another signaling mechanism: epigenetic regulation. This review will compare and contrast biosynthesis and metabolism of NO and H2S, their individual and shared interactions, and the growing body of evidence for their roles as endogenous epigenetic regulatory molecules.

After paraquat (PQ) poisoning, it is difficult to accurately diagnose patients' condition by only measuring their blood PQ concentration. Therefore, it is important to establish an accurate method to assist in the diagnosis of PQ poisoning, especially in the early stages. In this study, a gas chromatography-mass spectrometry (GC-MS) metabonomics strategy was established to obtain metabolite information. A random forest algorithm was used to search for potential biomarkers of PQ poisoning, and data mining and network pharmacological analysis were used to evaluate the active components, drug-disease targets, and key pathways of Xuebijing (XBJ) injection in the treatment of PQ-induced pulmonary fibrosis. Targets from the network pharmacology analysis and metabolites from plasma metabolomics were jointly analyzed to select crucial metabolic pathways. Finally, molecular docking technology and in vitro experiments were used to verify the pathway targets to further reveal the potential mechanisms underlying the antipulmonary fibrosis effect of XBJ. Metabonomics studies showed that l-valine, glycine, citric acid, d-mannose, d-galactose, maltose, l-tryptophan, and arachidonic acid contributed more to the differentiation of different groups than other metabolites. Compared with the control group, the PQ poisoning group had higher levels of l-valine, glycine, citric acid, l-tryptophan, and arachidonic acid, and lower levels of d-mannose, d-galactose, and maltose. After treatment with XBJ injection, the relative levels of these metabolites were reversed. The network pharmacological analysis screened a total of 180 targets, mainly involving multiple signaling pathways and metabolic pathways, which jointly played an antipulmonary fibrosis effect. Based on the combined analysis of 180 targets and 8 different metabolites, arachidonic acid metabolism was selected as the key metabolic pathway. Molecular docking analysis showed that the XBJ compound had strong binding activity with the target protein. Western blot results showed that XBJ injection could reduce the inflammatory response by downregulating the expressions of p-p65, p-IKBα, and p-IKKβ, thus inhibiting the development of PQ-induced pulmonary fibrosis. In summary, the combined results from metabolomics and network pharmacology studies showed that Xuebijing has the characteristics of multitarget, multichannel, and multicomponent action in the treatment of pulmonary fibrosis caused by PQ.

Background: COVID-19 is a pandemic respiratory contagious viral (SARS-CoV-2) disease associated with high morbidity and mortality worldwide. Currently, there are no effective preventive or treatment strategies for COVID-19 and it has been declared as a global health emergency by WHO. In silico molecular docking studies can be useful to predict the binding affinity between the phytocompound and the target protein and play a vital role in finding an inhibitor through structure-based drug design. Objective: In this aspect, our objective was to screen essential flavonoids against possible protein targets such as SARS-CoV-2 spike glycoprotein receptor binding domain (RBD-S) and host Angiotensin Converting Enzyme-2 protease domain (PD-ACE-2) using in silico molecular docking studies. Methods: Approximately 49 flavonoids were identified and were evaluated for their drug-likeness based on Lipinski rule, bioactivity scores, antiviral and toxicity profiles using SwissADME, Molinspiration, PASS and GUSAR online tools. The flavonoids that passed Lipinski rule were subjected to in silico analysis through molecular docking on RBD-S and PD-ACE-2 using Molegro Virtual Docker v6.0. Results: The bioactive flavonoids that showed NIL violations and were found in compliance with Lipinski rule were selected for docking studies. In silico analysis reported that biochanin A and silymarin bind significantly at the active sites of RBD-S and PD-ACE-2 with a MolDock score of -78.41and -121.28 kcal/mol respectively. Bioactivity scores, antiviral potential and toxicity profiles were predicted for the top interacting phytocompounds and substantial relevant data was reported. Conclusion: The current outcomes created a new paradigm for understanding biochanin A and silymarin bioflavonoids as potent inhibitors of RBD-S and PD-ACE-2 targets respectively. Further work can be extended to confirm their therapeutic potential for COVID-19.

Proteolysis-targeting chimeras (PROTACs) that degrade disease-causing proteins by hijacking the endogenous ubiquitin-proteasome system have emerged as an exciting and transformative technology in both chemical biology and drug discovery. Currently, the majority of PROTACs use reversible non-covalent ligands for both the target protein of interest (POI) and E3 ligase. In this review, we explore the burgeoning role of reversible and irreversible covalent chemistry in targeted protein degradation. We highlight the key advantages of targeted covalent inhibitors, whether as the target POI or E3 ligase ligand, such as their ability to enhance the selectivity of PROTACs, enable access to more of the "undruggable" proteome and expand the repertoire of recruited E3 ligases.

The novel coronavirus (COVID-19) infections have adopted the shape of a global pandemic now, demanding an urgent vaccine design. The current work reports contriving an anti-coronavirus peptide scanner tool to discern anti-coronavirus targets in the embodiment of peptides. The proffered CoronaPep tool features the fast fingerprinting of the anti-coronavirus target serving supreme prominence in the current bioinformatics research. The anti-coronavirus target protein sequences reported from the current outbreak are scanned against the anti-coronavirus target data-sets via CORONAPEP which provides precision-based anti-coronavirus peptides. This tool is specifically for the coronavirus data, which can predict peptides from the whole genome, or a gene or protein's list. Besides it is relatively fast, accurate, userfriendly and can generate maximum output from the limited information. The availability of tools like CORONAPEP will immeasurably perquisite researchers in the discipline of oncology and structure-based drug design.