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Showing papers in "ChemRxiv in 2020"


Posted ContentDOI
13 Apr 2020-ChemRxiv
TL;DR: The results showed the ORF8 and surface glycoprotein could bind to the porphyrin, respectively, and the mechanism also interfered with the normal heme anabolic pathway of the human body, which is expected to result in human disease.
Abstract: The novel coronavirus pneumonia (COVID-19) is an infectious acute respiratory infection caused by the novel coronavirus The virus is a positive-strand RNA virus with high homology to bat coronavirus In this study, conserved domain analysis, homology modeling, and molecular docking were used to compare the biological roles of certain proteins of the novel coronavirus The results showed the ORF8 and surface glycoprotein could bind to the porphyrin, respectively At the same time, orf1ab, ORF10, and ORF3a proteins could coordinate attack the heme on the 1-beta chain of hemoglobin to dissociate the iron to form the porphyrin The attack will cause less and less hemoglobin that can carry oxygen and carbon dioxide The lung cells have extremely intense poisoning and inflammatory due to the inability to exchange carbon dioxide and oxygen frequently, which eventually results in ground-glass-like lung images The mechanism also interfered with the normal heme anabolic pathway of the human body, is expected to result in human disease According to the validation analysis of these finds, chloroquine could prevent orf1ab, ORF3a, and ORF10 to attack the heme to form the porphyrin, and inhibit the binding of ORF8 and surface glycoproteins to porphyrins to a certain extent, effectively relieve the symptoms of respiratory distress Favipiravir could inhibit the envelope protein and ORF7a protein bind to porphyrin, prevent the virus from entering host cells, and catching free porphyrins Because the novel coronavirus is dependent on porphyrins, it may originate from an ancient virus Therefore, this research is of high value to contemporary biological experiments, disease prevention, and clinical treatment br

222 citations


Posted ContentDOI
14 Aug 2020-ChemRxiv
TL;DR: In this article, the authors show that including excess aluminum during synthesis of the Ti3AlC2 MAX phase precursor leads to the creation of Ti3C2 grains with improved stoichiometry and crystallinity.
Abstract: One of the primary factors limiting further research and the commercial use of the two-dimensional (2D) MXene titanium carbide (Ti3C2), as well as MXenes in general, is the rate at which freshly made samples oxidize and degrade when stored as aqueous suspensions. Here, we show that including excess aluminum during synthesis of the Ti3AlC2 MAX phase precursor leads to the creation of Ti3AlC2 grains with improved stoichiometry and crystallinity. Ti3C2 nanosheets produced from the improved Ti3AlC2 are of higher quality, as evidenced by their increased resistance to oxidation and an increase in their electrical conductivity to 20,000 S/cm. Our results indicate that defects created during the synthesis of Ti3C2 (and by inference, other MXenes) lead to the previously observed instability. We show that by eliminating those defects results in Ti3C2 that is highly stable in aqueous solutions and in air. Aqueous suspensions of single- to few-layer Ti3C2 flakes produced from the modified Ti3AlC2 have a shelf life of over ten months, compared to one to two weeks for Ti3C2 produced from conventional Ti3AlC2, even when stored in ambient conditions. Freestanding films made from Ti3C2 suspensions stored for ten months show minimal decreases in electrical conductivity and negligible oxidation. Oxidation of the improved Ti3C2 in air initiates at temperatures that are 100-150°C higher than conventional Ti3C2. The observed improvements in both the shelf life and properties of Ti3C2 will facilitate the widespread use of this material.

173 citations


Posted ContentDOI
22 Jul 2020-ChemRxiv
TL;DR: Preclinical experiments reveal 4 (PF-00835231) as a potent inhibitor of CoV-2 3CLpro with suitable pharmaceutical properties to warrant further development as an intravenous treatment for COVID-19.
Abstract: The novel coronavirus disease COVID-19 that emerged in 2019 is caused by the virus SARS CoV-2 and named for its close genetic similarity to SARS CoV-1 that caused severe acute respiratory syndrome (SARS) in 2002. Both SARS coronavirus genomes encode two overlapping large polyproteins which are cleaved at specific sites by a cysteine 3C-like protease (3CLpro) in a post-translational processing step that is critical for coronavirus replication. The 3CLpro sequences for CoV-1 and CoV-2 viruses are 100% identical in the catalytic domain that carries out protein cleavage. A research effort that focused on the discovery of reversible and irreversible ketone-based inhibitors of SARS CoV-1 3CLpro employing ligand-protease structures solved by X-ray crystallography led to the identification of 3 and 4. Preclinical experiments reveal 4 (PF-00835231) as a potent inhibitor of CoV-2 3CLpro with suitable pharmaceutical properties to warrant further development as an intravenous treatment for COVID-19.

148 citations


Posted ContentDOI
24 Feb 2020-ChemRxiv
TL;DR: It is hypothesize the identified small-molecules may be repurposed to limit viral recognition of host cells and/or disrupt host-virus interactions and a ranked list of compounds is given that can be tested experimentally.
Abstract: The novel Wuhan coronavirus (SARS-CoV-2) has been sequenced, and the virus shares substantial similarity with SARS-CoV Here, using a computational model of the spike protein (S-protein) of SARS-CoV-2 interacting with the human ACE2 receptor, we make use of the world's most powerful supercomputer, SUMMIT, to enact an ensemble docking virtual high-throughput screening campaign and identify small-molecules which bind to either the isolated Viral S-protein at its host receptor region or to the S protein-human ACE2 interface We hypothesize the identified small-molecules may be repurposed to limit viral recognition of host cells and/or disrupt host-virus interactions A ranked list of compounds is given that can be tested experimentally br

143 citations


Posted ContentDOI
11 Feb 2020-ChemRxiv
TL;DR: The emergence of the 2019 novel coronavirus (COVID-19), for which there is no vaccine or any known effective treatment created a sense of urgency for novel drug discovery approaches, and Insilico Medicine decided to utilize a part of its generative chemistry pipeline to design novel drug-like inhibitors of CO VID-19 and started generation on January 30th.
Abstract: The emergence of the 2019 novel coronavirus (2019-nCoV), for which there is no vaccine or any known effective treatment created a sense of urgency for novel drug discovery approaches One of the most important 2019-nCoV protein targets is the 3C-like protease for which the crystal structure is known Most of the immediate efforts are focused on drug repurposing of known clin -approved drugs and virtual screening for the mols available from chem libraries that may not work well For example, the IC50 of lopinavir, an HIV protease inhibitor, against the 3C-like protease is approx 50 micromolar In an attempt to address this challenge, on Jan 28th, 2020 Insilico Medicine decided to utilize a part of its generative chem pipeline to design novel drug-like inhibitors of 2019-nCoV and started generation on Jan 30th It utilized three of its previously validated generative chem approaches: crystal-derived pocked-based generator, homol modeling-based generation, and ligand-based generation Novel druglike compounds generated using these approaches are being published at www insilico com/ncov-sprint/ and will be continuously updated Several mols will be synthesized and tested using the internal resources;however, the team is seeking collaborations to synthesize, test, and, if needed, optimize the published mols

134 citations


Posted ContentDOI
19 Feb 2020-ChemRxiv
TL;DR: A rapid, highly sensitive, point-of-care, molecular test that has the potential to significantly reduce false negatives while being amenable to use with minimal instrumentation and training is described.
Abstract: The 2019 novel coronavirus (COVID-19) is a newly emerged strain that has never been found in humans before At present, the laboratory-based reverse transcription-polymerase chain reaction (RT-PCR) is the main method to confirm COVID-19 infection The intensification of the COVID-19 epidemic overwhelms limited clinical resources in particular, but not only, in developing countries, resulting in many patients not being tested for the infection and in large queues of potentially infected individuals waiting to be tested while providing a breeding ground for the disease We describe here a rapid, highly sensitive, point-of-care, molecular test amenable for use at home, in the clinic, and at points of entry by minimally trained individuals and with minimal instrumentation Our test is based on loomediated isothermal amplification (COVID-19 LAMP) and for higher sensitivity on nested nucleic acid, two stage isothermal amplification (COVID-19 Penn-RAMP) Both tests can be carried out in closed tubes with either fluorescence or colorimetric (e g , leuco crystal violet LCV) detection COVID-19 LAMperforms on par with COVID-19 RT-PCR COVID-19 RAMhas 10 fold better sensitivity than COVID-19 LAMand COVID-19 RT-PCR when testing purified targets and 100 times better sensitivity than COVID-19 LAMand COVID-19 RT-PCR when testing rapidly prepared sample mimics Due to fortunate scarcity of COVID-19 infections in the USA, we were not able to test our assays and methods with patient samples We hope that such tests will be carried out by colleagues in impacted countries Our Closed-Tube Penn-RAMhas the potential to significantly reduce false negatives while being amenable to use with minimal instrumentation and training

114 citations


Journal ArticleDOI
01 Aug 2020-ChemRxiv
TL;DR: The substrate scope and reproducibility of this method are improved by avoiding catalyst deactivation and strategies to achieve the latter are reported.
Abstract: Dual photoredox/nickel-catalysed C–N cross-couplings suffer from low yields for electron-rich aryl halides. The formation of catalytically inactive nickel-black is responsible for this limitation and causes severe reproducibility issues. Here, we demonstrate that catalyst deactivation can be avoided by using a carbon nitride photocatalyst. The broad absorption of the heterogeneous photocatalyst enables wavelength-dependent control of the rate of reductive elimination to prevent nickel-black formation during the coupling of cyclic, secondary amines and aryl halides. A second approach, which is applicable to a broader set of electron-rich aryl halides, is to run the reactions at high concentrations to increase the rate of oxidative addition. Less nucleophilic, primary amines can be coupled with electron-rich aryl halides by stabilizing low-valent nickel intermediates with a suitable additive. The developed protocols enable reproducible, selective C–N cross-couplings of electron-rich aryl bromides and can also be applied for electron-poor aryl chlorides. Dual nickel/photoredox catalysis is a promising alternative for palladium-catalysed cross-couplings, but suffers from limitations. Now, the substrate scope and reproducibility of this method are improved by avoiding catalyst deactivation and strategies to achieve the latter are reported.

112 citations


Posted ContentDOI
07 May 2020-ChemRxiv
TL;DR: This work shows how machine learning can be used to quantify similarities of MOFs, and shows that this diversity analysis can identify biases in the databases, and how such bias can lead to incorrect conclusions.
Abstract: By combining metal nodes and organic linkers one can make millions of different metal-organic frameworks (MOFs). At present over 90,000 MOFs have been synthesized and there are databases with over 500,000 predicted structures. This raises the question whether a new experimental or predicted structure adds new information. For MOF-chemists the chemical design space is a combination of pore geometry, metal nodes, organic linkers, and functional groups, but at present we do not have a formalism to quantify optimal coverage of chemical design space. In this work, we show how machine learning can be used to quantify similarities of MOFs. This quantification allows us to use techniques from ecology to analyse the chemical diversity of these materials in terms of diversity metrics. In particular, we show that this diversity analysis can identify biases in the databases, and how such bias can lead to incorrect conclusions. This formalism provides us with a simple and powerful practical guideline to see whether a set of new structures will have the potential for new insights, or constitute a relatively small variation of existing structures.

108 citations


Posted ContentDOI
20 Feb 2020-ChemRxiv
TL;DR: In this article, a homology model of the Papain-like protease (PLpro) was built based on the SARS-coronavirus PLpro structure, and sixteen FDA approved drugs, including chloroquine and formoterol, were found to bind the target enzyme with significant affinity and good geometry.
Abstract: The cases of 2019 novel coronavirus (SARS-CoV-2) infection have been continuously increasing ever since its outbreak in China last December Currently, there are no approved drugs to treat the infection In this scenario, there is a need to utilize the existing repertoire of FDA approved drugs to treat the disease The rational selection of these drugs could be made by testing their ability to inhibit any SARS-CoV-2 proteins essential for viral life-cycle We chose one such crucial viral protein, the papain-like protease (PLpro), to screen the FDA approved drugs in silico The homology model of the protease was built based on the SARS-coronavirus PLpro structure, and the drugs were docked in S3/S4 pockets of the active site of the enzyme In our docking studies, sixteen FDA approved drugs, including chloroquine and formoterol, was found to bind the target enzyme with significant affinity and good geometry, suggesting their potential to be utilized against the virus

108 citations


Posted ContentDOI
09 Apr 2020-ChemRxiv
TL;DR: These flavonoid and non-flavonoid moieties have significantly high binding affinity for the two main important domains of the spike protein which is responsible for the attachment and internalization of the virus in the host cell and their binding affinities are much higher compared to that of HCQ.
Abstract: Spike glycoprotein found on the surface of SARS-CoV-2 (SARS-CoV-2S) is a class I fusion protein which helps the virus in its initial attachment with human Angiotensin converting enzyme 2 (ACE2) receptor and its consecutive fusion with the host cells. The attachment is mediated by the S1 subunit of the protein via its receptor binding domain. Upon binding with the receptor the protein changes its conformation from a pre-fusion to a post-fusion form. The membrane fusion and internalization of the virus is brought about by the S2 domain of the spike protein. From ancient times people have relied on naturally occurring substances like phytochemicals to fight against diseases and infection. Among these phytochemicals, flavonoids and non-flavonoids have been found to be the active source of different anti-microbial agents. Recently, studies have shown that these phytochemicals have essential anti-viral activities. We performed a molecular docking study using 10 potential naturally occurring flavonoids/non-flavonoids against the SARS-CoV-2 spike protein and compared their affinity with the FDA approved drug hydroxychloroquine (HCQ). Interestingly, the docking analysis suggested that C-terminal of S1 domain and S2 domain of the spike protein are important for binding with these compounds. Kamferol, curcumin, pterostilbene, and HCQ interact with the C-terminal of S1 domain with binding energies of -7.4, -7.1, -6.7 and -5.6 Kcal/mol, respectively. Fisetin, quercetin, isorhamnetin, genistein, luteolin, resveratrol and apigenin on the other hand, interact with the S2 domain of spike protein with the binding energies of -8.5, -8.5, -8.3, -8.2, -8.2, -7.9, -7.7 Kcal/mol, respectively. Our study suggested that, these flavonoid and non-flavonoid moieties have significantly high binding affinity for the two main important domains of the spike protein which is responsible for the attachment and internalization of the virus in the host cell and their binding affinities are much higher compared to that of HCQ. In addition, ADME (absorption, distribution, metabolism and excretion) analysis also suggested that these compounds consist of drug likeness property which may help for further explore as anti-SARS-CoV-2 agents. Further, in vitro and in vivo study of these compounds will provide a clear path for the development of novel compounds that would most likely prevent the receptor binding or internalization of the SARS-CoV-2 spike protein and therefore could be used as drugs for COVID-19 therapy.

94 citations


Posted ContentDOI
26 Aug 2020-ChemRxiv
TL;DR: This application note aims to offer the community a production-ready tool for de novo design that can be effectively applied on drug discovery projects that are striving to resolve either exploration or exploitation problems while navigating the chemical space.
Abstract: With this application note we aim to offer the community a production-ready tool for de novo design. It can be effectively applied on drug discovery projects that are striving to resolve either exploration or exploitation problems while navigating the chemical space. By releasing the code we are aiming to facilitate the research on using generative methods on drug discovery problems and to promote the collaborative efforts in this area so that it can be used as an interaction point for future scientific collaborations.

Posted ContentDOI
29 Oct 2020-ChemRxiv
TL;DR: The first publicly available quantum-chemical database for MOFs is developed (the “QMOF database”), which consists of properties derived from density functional theory (DFT) for over 14,000 experimentally synthesized MOFs, and it is demonstrated how this new database can be used to identify MOFs with targeted electronic structure properties.
Abstract: Metal–organic frameworks (MOFs) are a widely investigated class of crystalline solids with tunable structures that make it possible to impart specific chemical functionality tailored for a given application However, the enormous number of possible MOFs that can be synthesized makes it difficult to determine which materials would be the most promising candidates, especially for applications governed by electronic structure properties that are often computationally demanding to simulate and time-consuming to probe experimentally Here, we have developed the first publicly available quantum-chemical database for MOFs (the “QMOF database”), which consists of properties derived from density functional theory (DFT) for over 14,000 experimentally synthesized MOFs Throughout this study, we demonstrate how this new database can be used to identify MOFs with targeted electronic structure properties As a proof-of-concept, we use the QMOF database to evaluate the performance of several machine learning models for the prediction of DFT-computed band gaps and find that crystal graph convolutional neural networks are capable of achieving superior predictive performance, making it possible to circumvent computationally expensive quantum-chemical calculations We also show how unsupervised learning methods can aid the discovery of otherwise subtle structure–property relationships using the computational findings in this work We conclude by highlighting several MOFs with low band gaps, a challenging task given the electronically insulating nature of most MOF structures The data and predictive models generated in this work, as well as the database of MOF structures, should be highly useful to other researchers interested in the predictive design and discovery of MOFs for the many applications dictated by quantum-chemical phenomena

Posted ContentDOI
19 Oct 2020-ChemRxiv
TL;DR: Using an electrochemical readout method that requires no external reagents, the SARS-CoV-2 virus in the saliva of infected patients is detected using a molecular sensor tethered to the surface of a gold electrode that contains an antibody, specific to the target of interest.
Abstract: This manuscript describes a new method that enables direct analysis of viral particles in unprocessed samples.Using an electrochemical readout method that requires no external reagents, we detect the SARS-CoV-2 virus in the saliva of infected patients.The approach relies on a molecular sensor tethered to the surface of a gold electrode that contains an antibody, specific to the targetof interest, which here is the SARS-CoV-2 S1 spike protein that is displayed on the viral capsule. The antibody is attached to the electrode using a negatively charged linker that is composed of DNA. When a positive potential is applied to the electrode, the sensor complex is attracted to the electrode surface. The kinetics of transport is measured using chronoamperometry and readout is possible based on the absense or precense of virus and its effect on the complex movevment on electrode surface.

Posted ContentDOI
04 May 2020-ChemRxiv
TL;DR: TorchANI is able to use PyTorch’s autograd engine to automatically compute analytical forces and Hessian matrices, as well as do force training without additional codes required.
Abstract: This paper presents TorchANI, a PyTorch based software for training/inferenceof ANI (ANAKIN-ME) deep learning models to obtain potential energy surfaces andother physical properties of molecular systems. ANI is an accurate neural networkpotential originally implemented using C++/CUDA in a program called NeuroChem.Compared with NeuroChem, TorchANI has a design emphasis on being light weight,user friendly, cross platform, and easy to read and modify for fast prototyping, whileallowing acceptable sacrifice on running performance. Because the computation ofatomic environmental vectors (AEVs) and atomic neural networks are all implementedusing PyTorch operators, TorchANI is able to use PyTorch’s autograd engine to automatically compute analytical forces and Hessian matrices, as well as do force trainingwithout additional codes required.

Posted ContentDOI
14 May 2020-ChemRxiv
TL;DR: The current brief report adopted a repositioning approach using insilico molecular modeling screening using FDA approved drugs with established safety profiles for potential inhibitory effects on Covid-19 virus to identify potential hits.
Abstract: The new strain of Coronaviruses (SARS-CoV-2), and the resulting Covid-19 disease has spread swiftly across the globe after its initial detection in late December 2019 in Wuhan, China, resulting in a pandemic status declaration by WHO within 3 months Given the heavy toll of this pandemic, researchers are actively testing various strategies including new and repurposed drugs as well as vaccines In the current brief report, we adopted a repositioning approach using insilico molecular modeling screening using FDA approved drugs with established safety profiles for potential inhibitory effects on Covid-19 virus We started with structure based drug design by screening more than 2000 FDA approved drugs /against Covid-19 virus main protease enzyme (Mpro) substrate-binding pocket to identify potential hits based on their binding energies, binding modes, interacting amino acids, and therapeutic indications In addition, we elucidate preliminary pharmacophore features for candidates bound to Covid-19 virus Mpro substratebinding pocket The tohits include anti-viral drugs such as Darunavir, Nelfinavirand Saquinavir, some of which are already being tested in Covid-19 patients Interestingly, one of the most promising hits in our screen is the hypercholesterolemia drug Rosuvastatin These results certainly do not confirm or indicate antiviral activity, but can rather be used as a starting point for further in vitro and in vivo testing, either individually or in combination /div

Journal ArticleDOI
01 Jul 2020-ChemRxiv
TL;DR: In this article, the authors used tip-enhanced Raman spectroscopy (TERS) to study the catalytic hydrogenation of chloronitrobenzenethiol on a well-defined Pd(submonolayer)/Au(111) bimetallic catalyst, where the surface topography and chemical fingerprint information were simultaneously mapped with nanoscale resolution.
Abstract: Understanding the mechanism of catalytic hydrogenation at the local environment requires chemical and topographic information involving catalytic sites, active hydrogen species, and their spatial distribution. Here we used tip-enhanced Raman spectroscopy (TERS) to study the catalytic hydrogenation of chloronitrobenzenethiol on a well-defined Pd(submonolayer)/Au(111) bimetallic catalyst ( $$p_{\rm{H}_{2}}$$ = 1.5 bar, 298 K), where the surface topography and chemical fingerprint information were simultaneously mapped with nanoscale resolution (~10 nm). TERS imaging of the surface after catalytic hydrogenation confirms that the reaction occurs beyond the location of Pd sites. The results demonstrate that hydrogen spillover accelerates hydrogenation at Au sites as far as 20 nm from the bimetallic Pd/Au boundary. Density functional theory was used to elucidate the thermodynamics of interfacial hydrogen transfers. We demonstrate TERS to be a powerful analytical tool that provides a unique approach to spatially investigate the local structure–reactivity relationship in catalysis. Visualizing catalytic processes at the nanoscale is crucial to establish structure–activity relations, but remains very challenging. Here, hydrogen spillover is revealed with a 10 nm spatial resolution during hydrogenation of chloronitrobenzenethiol on a bimetallic Pd/Au catalyst by means of tip-enhanced Raman spectroscopy.

Journal ArticleDOI
06 Jan 2020-ChemRxiv
TL;DR: In this article, measures to improve the cycling performance and stability of bulk-type all-solid-state batteries (SSBs) are developed with the goal of substituting conventional lithium-ion battery.
Abstract: Measures to improve the cycling performance and stability of bulk-type all-solid-state batteries (SSBs) are currently being developed with the goal of substituting conventional lithium-ion battery ...

Posted ContentDOI
15 Apr 2020-ChemRxiv
TL;DR: A surface plasmon resonance sensor detecting nucleocapsid antibodies specific against the novel coronavirus 2019 (SARS-CoV-2) in undiluted human serum paves the way to point-of-care and label-free rapid testing for antibodies.
Abstract: We report a surface plasmon resonance (SPR) sensor detecting nucleocapsid antibodies specific against the novel coronavirus 2019 (SARS-CoV-2) in undiluted human serum When exposed to SARS-CoV-2, the immune system responds by expressing antibodies at levels that can be detected and monitored to identify the patient population immunized against SARD-CoV-2 and support efforts to deploy a vaccine strategically A SPR sensor coated with a peptide monolayer and functionalized with SARS-CoV-2 nucleocapsid recombinant protein detected anti-SARS-CoV-2 antibodies in the nanomolar range This bioassay was performed on a portable SPR instrument in undiluted human serum and results were collected within 15 minutes of sample/sensor contact This strategy paves the way to point-of-care and label-free rapid testing for antibodies

Posted ContentDOI
21 Jul 2020-ChemRxiv
TL;DR: This study presents a two-step framework for a machine learning driven high-throughput microfluidic platform to rapidly produce silver nanoparticles with a desired absorbance spectrum by combining a Gaussian Process based Bayesian Optimization with a Deep Neural Network.
Abstract: In materials science, the discovery of recipes that yield nanomaterials with defined optical properties is costly and time-consuming. In this study, we present a two-step framework for a machine learning driven high-throughput microfluidic platform to rapidly produce silver nanoparticles with a desired absorbance spectrum. Combining a Gaussian Process based Bayesian Optimization (BO) with a Deep Neural Network (DNN), the algorithmic framework is able to converge towards the target spectrum after sampling 120 conditions. Once the dataset is large enough to train the DNN with sufficient accuracy in the region of the target spectrum, the DNN is used to predict the colour palette accessible with the reaction synthesis. While remaining interpretable by humans, the proposed framework efficiently optimizes the nanomaterial synthesis, and can extract fundamental knowledge of the relationship between chemical composition and optical properties, such as the role of each reactant on the shape and amplitude of the absorbance spectrum.

Posted ContentDOI
19 May 2020-ChemRxiv
TL;DR: In this article, the 3C-like protease (main protease, Mpro) was co-crystallized both with covalent and non-covalent ligands.
Abstract: One of the most important SARS-CoV-2 protein targets for therapeutics is the 3C-like protease (main protease, Mpro) In our previous work1​we used the first Mpro crystal structure to become available, 6LU7 On February 4, 2020 Insilico Medicine released the first potential novel protease inhibitors designed using a ​de novo,​AI-driven generative chemistry approach Nearly 100 X-ray structures of Mpro co-crystallized both with covalent and non-covalent ligands have been published since then Here we utilize the recently published 6W63 crystal structure of Mpro complexed with a non-covalent inhibitor and combined two approaches used in our previous study: ligand-based and crystal structure-based We published 10 representative structures for potential development with 3D representation in PDformat and welcome medicinal chemists for broad discussion and generated output analysis The molecules in SDF format and PDB-models for generated protein-ligand complexes are available here and at https://insilico com/ncov-sprint/ ​Medicinal chemistry VR analysis was provided by ​Nanome team and the video of VR session is available at ​https://bit ly/ncov-vr ​ / / / / /div

Posted ContentDOI
30 Mar 2020-ChemRxiv
TL;DR: Folic acid (folate), a water-soluble B vitamin, is introduced for the first time for the inhibition of furin activity, which may help to prevent or alleviate the respiratory involvement associated with COVID-19.
Abstract: Entrance of coronavirus into cells happens through the spike proteins on the virus surface, for which the spike protein should be cleaved into S1 and S2 domains. This cleavage is mediated by furin, which can specifically cleave Arg-X-X-Arg↓ sites of the substrates. Furin, a member of proprotein convertases family, is moved from the trans-Golgi network to the cell membrane and activates many precursor proteins. A number of pathological conditions such as atherosclerosis, cancer, and viral infectious diseases, are linked with the impaired activity of this enzyme. Despite the urgent need to control COVID-19, no approved treatment is currently known. Here, folic acid (folate), a water-soluble B vitamin, is introduced for the first time for the inhibition of furin activity. As such, folic acid, as a safe drug, may help to prevent or alleviate the respiratory involvement associated with COVID-19.

Posted ContentDOI
23 Jul 2020-ChemRxiv
TL;DR: In this article, the Massey University Framework (MUF) was used to capture CO2 with high affinity in its one-dimensional channels, and the position of CO2 molecules sequestered in the framework pores, as determined by X-ray crystallography, illustrate how complementary noncovalent interactions envelop the CO2 while repelling other guest molecules.
Abstract: Efficient and sustainable methods for carbon dioxide (CO2) capture are highly sought after. Mature technologies involve chemical reactions that absorb CO2, but they have many drawbacks. Energy-efficient alternatives may be realized by porous physisorbents with void spaces that are complementary in size and electrostatic potential to molecular CO2. Here, we present a robust, recyclable and inexpensive adsorbent termed MUF-16 (MUF = Massey University Framework). This metal-organic framework captures CO2 with a high affinity in its one-dimensional channels. The position of the CO2 molecules sequestered in the framework pores, as determined by X-ray crystallography, illustrate how complementary noncovalent interactions envelop the CO2 while repelling other guest molecules. The low affinity of the MUF-16 pores for these competing gases underpins new benchmarks for the adsorption of CO2 over methane, acetylene, ethylene, ethane, propylene and propane. IAST calculations show that for 50/50 mixtures at 293 K and 1 bar, the CO2/CH4 selectivity is 6690 and the CO2/C2H2 selectivity is 510, for example. Breakthrough gas separations under dynamic conditions benefit from short time lags in the elution of the weakly-adsorbed component to deliver high-purity hydrocarbon products. Ultimately, MUF-16 may be applicable to the removal of CO2 from sources such as natural gas and chemical feedstocks.

Posted ContentDOI
28 Aug 2020-ChemRxiv
TL;DR: This work presents a short peptide synthon for phase separation, made of only two dipeptide stickers linked via a flexible, hydrophilic spacer, that provides a stepping stone for new protocells made of single peptide species.
Abstract: Liquid-liquid phase separation of disordered proteins has emerged as a ubiquitous route to membraneless compartments in living cells, and similar coacervates may have played a role when the first cells formed. However, existing coacervates are typically made of multiple macromolecular components, and designing short peptide analogues capable of self-coacervation has proven difficult. Here, we present a short peptide synthon for phase separation, made of only two dipeptide stickers linked via a flexible, hydrophilic spacer. These small-molecule compounds self-coacervate into micrometre-sized liquid droplets at sub-mM concentrations, which retain up to 75 weight-% water. The design is general and we derive guidelines for the required sticker hydrophobicity and spacer polarity. To illustrate their potential as protocells, we create a disulphide-linked derivative that undergoes reversible compartmentalisation controlled by redox chemistry. The resulting coacervates sequester and melt nucleic acids, and act as microreactors that catalyse two different anabolic reactions yielding molecules of increasing complexity. This provides a stepping stone for new protocells made of single peptide species.

Posted ContentDOI
20 Apr 2020-ChemRxiv
TL;DR: This work uses virtual docking predictions to assess the hypothesis that existing drugs already approved for human use or clinical testing that are directed at the HCV NS3/4A protease might fit well into the active-site cleft of the SARS-CoV2 protease (M supro /su)
Abstract: During the current COVID-19 pandemic more than 160,000 people have died worldwide as of mid-April 2020, and the global economy has been crippled Effective control of the SARS-CoV2 virus that causes the COVID-19 pandemic requires both vaccines and antivirals Antivirals are particularly crucial to treat infected people during the period of time that an effective vaccine is being developed and deployed Because the development of specific antiviral drugs can take a considerable length of time, an important approach is to identify existing drugs already approved for use in humans which could be repurposed as COVID-19 therapeutics Here we focus on antivirals directed against the SARS-CoV2 M supro /suprotease, which is required for virus replication A structural similarity search showed that the Hepatitis C virus (HCV) NS3/4A protease has a striking three-dimensional structural similarity to the SARS-CoV2 M supro /suprotease, particularly in the arrangement of key active site residues We used virtual docking predictions to assess the hypothesis that existing drugs already approved for human use or clinical testing that are directed at the HCV NS3/4A protease might fit well into the active-site cleft of the SARS-CoV2 protease (M supro /su) AutoDock docking scores for 12 HCV protease inhibitors and 9 HIV-1 protease inhibitors were determined and compared to the docking scores for an alpha-ketoamide inhibitor of M supro /su, which has recently been shown to inhibit SARS-CoV2 virus replication in cell culture We identified eight HCV protease inhibitors that bound to the M supro /suactive site with higher docking scores than the alpha-ketoamide inhibitor, suggesting that these protease inhibitors may effectively bind to the M supro /suactive site These results provide the rationale for us to test the identified HCV protease inhibitors as inhibitors of the SARS-CoV2 protease, and as inhibitors of SARS-CoV2 virus replication Subsequently these repurposed drugs could be evaluated as COVID-19 therapeutics

Posted ContentDOI
13 Feb 2020-ChemRxiv
TL;DR: Results showed that some of the known protease inhibitors currently used in HIV infections might be helpful for the therapy of COVID-19.
Abstract: The infection by the 2019-nCoV coronavirus (COVID-19) is a world-wide emergency /The crystal structure of a protein essential for virus replication has been filed in the Protein Data /Bank recently Additionally, homology models of 24 COVID-19 proteins were made available by /the Zhang group In this paper, we present results deriving from the virtual screening of a database /of more than 3000 FDA approved drugs on two distinct targets Results showed that some of the /known protease inhibitors currently used in HIV infections might be helpful for the therapy of /COVID-19 also /div

Posted ContentDOI
11 Feb 2020-ChemRxiv
TL;DR: A visible light-mediated intermolecular aza Paternò-Büchi reaction that utilizes glyoxylate oximes as reactive intermediates activated via triplet energy transfer allows for the synthesis of highly functionalized azetidines from readily available precursors.
Abstract: Intermolecular [2+2] photocycloadditions represent a powerful method for the synthesis of highly strained, four-membered rings. While this approach is commonly employed for the synthesis of oxetanes and cyclobutanes, the synthesis of azetidines via intermolecular aza Paterno-Buchi reactions remains highly underdeveloped. Herein we report a visible light-mediated intermolecular aza Paterno-Buchi reaction that utilizes glyoxylate oximes as reactive intermediates activated via triplet energy transfer. This approach is characterized by its operational simplicity, mild conditions and broad scope, and allows for the synthesis of highly functionalized azetidines from readily available precursors.

Posted ContentDOI
15 Jul 2020-ChemRxiv
TL;DR: It is revealed by molecular docking the profound binding affinity of 14 selected phenolics and terpenes present in honey and propolis against the main protease (Mpro) and RNA dependent RNA polymerase (RdRp) enzymes of the novel 2019-nCoV coronavirus.
Abstract: From the early days of the COVID-19 pandemic, side by side to immense investigates to design specific drugs or to develop a potential vaccine for the novel coronavirus. Myriads of FDA approved drugs are massively repurposed for COVID-19 treatment based on molecular docking of selected protein targets that play vital for the replication cycle of the virus. Honey bee products are well known of their nutritional values and medicinal effects. Antimicrobial activity of bee products and natural honey have been documented in several clinical studies and was considered a good alternative for antiviral medications to treat some viral infections. Bee products contain bioactive compounds in the form of a collection of phenolic acids, flavonoids and terpenes of natural origin. We revealed by molecular docking the profound binding affinity of 14 selected phenolics and terpenes present in honey and propolis (bees glue) against the main protease (Mpro) and RNA dependent RNA polymerase (RdRp) enzymes of the novel 2019-nCoV coronavirus. Of these compounds, p-coumaric acid, ellagic acid, kaemferol and quercetin has the strongest interaction with the 2019-nCoV target enzymes, and they may be considered as an effective 2019-nCoV inhibitors.

Journal ArticleDOI
30 Mar 2020-ChemRxiv
TL;DR: In this article, the commercially available organoboronic esters were demonstrated to perform well in the presence of lefin hydroboration reactions, which provides efficient access to synthetically versatile and easily handled organoboric esters.
Abstract: Olefin hydroboration reactions provide efficient access to synthetically versatile and easily handled organoboronic esters. In this study, we demonstrate that the commercially available organoboran...

Posted ContentDOI
01 Apr 2020-ChemRxiv
TL;DR: In silico Screening of Food Bioactive Compounds to Predict Potential Inhibitors of COVID-19 Main protease (Mpro) and RNA-dependent RNA polymerase (RdRp)
Abstract: In silico Screening of Food Bioactive Compounds to Predict Potential Inhibitors of COVID-19 Main protease (Mpro) and RNA-dependent RNA polymerase (RdRp)

Posted ContentDOI
20 Mar 2020-ChemRxiv
TL;DR: Six compounds with predicted high binding affinity in the range of the known inhibitors are found and it is shown that a previously published weak inhibitor, Camostat, had a significantly lower binding score than these six compounds.
Abstract: The most rapid path to discovering treatment options for the novel coronavirus SARS-CoV-2 is to find existing medications that are active against the virus We have focused on identifying repurposing candidates for the transmembrane serine protease family member I(TMPRSS2), which is critical for entry of coronaviruses into cells Using known 3D structures of close homologs, we created seven homology models We also identified a set of serine protease inhibitor drugs, generated several conformations of each, and docked them into our models We used three known chemical (non-drug) inhibitors and one validated inhibitor of TMPRSS2 in MERS as benchmark compounds and found six compounds with predicted high binding affinity in the range of the known inhibitors We also showed that a previously published weak inhibitor, Camostat, had a significantly lower binding score than our six compounds All six compounds are anticoagulants with significant and potentially dangerous clinical effects and side effects Nonetheless, if these compounds significantly inhibit SARS-CoV-2 infection, they could represent a potentially useful clinical tool