Discovery of novel SARS-CoV-2 3CL protease covalent inhibitors using deep learning-based screen

A SARS-CoV-2 Mpro fluorescent sensor for exploring pharmacodynamic substances from traditional Chinese medicine

The main protease of SARS-CoV-2 (SARS-CoV-2 Mpro) plays a critical role in the replication and life cycle of the virus. Currently, how to screen SARS-CoV-2 Mpro inhibitors from complex traditional Chinese medicine (TCM) is the bottleneck for exploring the pharmacodynamic substances of TCM against SARS-CoV-2. In this study, a simple, cost-effective, rapid, and selective fluorescent sensor (TPE-S-TLG sensor) was designed with an AIE (aggregation-induced emission) probe (TPE-Ph-In) and the SARS-CoV-2 Mpro substrate (S-TLG). The TPE-S-TLG sensor was characterized using UV-Vis absorption spectroscopy, fluorescence spectroscopy, dynamic light scattering (DLS), transmission electron microscopy (TEM), zeta potential, and Fourier transform infrared (FTIR) spectroscopy techniques. The limit of detection of this method to detect SARS-CoV-2 Mpro was measured to be 5 ng mL-1. Furthermore, the TPE-S-TLG sensor was also successfully applied to screen Mpro inhibitors from Xuebijing injection using the separation and collection of the HPLC-fully automatic partial fraction collector (HPLC-FC). Six active compounds, including protocatechualdehyde, chlorogenic acid, hydroxysafflower yellow A, caffeic acid, isoquercetin, and pentagalloylglucose, were identified using UHPLC-Q-TOF/MS that could achieve 90% of the Mpro inhibition rate for the Xuebijing injection. Accordingly, the strategy can be broadly applied in the detection of disease-related proteases as well as screening active substances from TCM.

Non-peptidic inhibitors targeting SARS-CoV-2 main protease: A review

The COVID-19 pandemic continues to pose a threat to global health, and sounds the alarm for research & development of effective anti-coronavirus drugs, which are crucial for the patients and urgently needed for the current epidemic and future crisis. The main protease (Mpro) stands as an essential enzyme in the maturation process of SARS-CoV-2, playing an irreplaceable role in regulating viral RNA replication and transcription. It has emerged as an ideal target for developing antiviral agents against SARS-CoV-2 due to its high conservation and the absence of homologous proteases in the human body. Among the SARS-CoV-2 Mpro inhibitors, non-peptidic compounds hold promising prospects owing to their excellent antiviral activity and improved metabolic stability. In this review, we offer an overview of research progress concerning non-peptidic SARS-CoV-2 Mpro inhibitors since 2020. The efforts delved into molecular structures, structure-activity relationships (SARs), biological activity, and binding modes of these inhibitors with Mpro. This review aims to provide valuable clues and insights for the development of anti-SARS-CoV-2 agents as well as broad-spectrum coronavirus Mpro inhibitors.

Discovery of Covalent Lead Compounds Targeting 3CL Protease with a Lateral Interactions Spiking Neural Network

Covalent drugs exhibit advantages in that noncovalent drugs cannot match, and covalent docking is an important method for screening covalent lead compounds. However, it is difficult for covalent docking to screen covalent compounds on a large scale because covalent docking requires determination of the covalent reaction type of the compound. Here, we propose to use deep learning of a lateral interactions spiking neural network to construct a covalent lead compound screening model to quickly screen covalent lead compounds. We used the 3CL protease (3CL Pro) of SARS-CoV-2 as the screen target and constructed two classification models based on LISNN to predict the covalent binding and inhibitory activity of compounds. The two classification models were trained on the covalent complex data set targeting cysteine (Cys) and the compound inhibitory activity data set targeting 3CL Pro, respected, with good prediction accuracy (ACC > 0.9). We then screened the screening compound library with 6 covalent binding screening models and 12 inhibitory activity screening models. We tested the inhibitory activity of the 32 compounds, and the best compound inhibited SARS-CoV-2 3CL Pro with an IC50 value of 369.5 nM. Further assay implied that dithiothreitol can affect the inhibitory activity of the compound to 3CL Pro, indicating that the compound may covalently bind 3CL Pro. The selectivity test showed that the compound had good target selectivity to 3CL Pro over cathepsin L. These correlation assays can prove the rationality of the covalent lead compound screening model. Finally, covalent docking was performed to demonstrate the binding conformation of the compound with 3CL Pro. The source code can be obtained from the GitHub repository (https://github.com/guzh970630/Screen_Covalent_Compound_by_LISNN).

Covalent drugs based on small molecules and peptides for disease theranostics

Biomacromolecules, such as proteins, nucleic acids and polysaccharides, are widely distributed in the human body, and some of them have been recognized as the targets of drugs for disease theranostics. Drugs typically act on targets in two ways: non-covalent bond and covalent bond. Non-covalent bond-based drugs have some disadvantages, such as structural instability and environmental sensitivity. Covalent interactions between drugs and targets have a longer action time, higher affinity and controllability than non-covalent interactions of conventional drugs. With the development of artificial intelligence, covalent drugs have received more attention and have been developed rapidly in pharmaceutical research in recent years. From the perspective of covalent drugs, this review summarizes the design methods and the effects of covalent drugs. Finally, we discuss the application of covalent peptide drugs and expect to provide a new reference for cancer treatment.

On the origins of SARS-CoV-2 main protease inhibitors

In order to address the world-wide health challenge caused by the COVID-19 pandemic, the 3CL protease/SARS-CoV-2 main protease (SARS-CoV-2-Mpro) coded by its nsp5 gene became one of the biochemical targets for the design of antiviral drugs. In less than 3 years of research, 4 inhibitors of SARS-CoV-2-Mpro have actually been authorized for COVID-19 treatment (nirmatrelvir, ensitrelvir, leritrelvir and simnotrelvir) and more such as EDP-235, FB-2001 and STI-1558/Olgotrelvir or five undisclosed compounds (CDI-988, ASC11, ALG-097558, QLS1128 and H-10517) are undergoing clinical trials. This review is an attempt to picture this quite unprecedented medicinal chemistry feat and provide insights on how these cysteine protease inhibitors were discovered. Since many series of covalent SARS-CoV-2-Mpro inhibitors owe some of their origins to previous work on other proteases, we first provided a description of various inhibitors of cysteine-bearing human caspase-1 or cathepsin K, as well as inhibitors of serine proteases such as human dipeptidyl peptidase-4 or the hepatitis C protein complex NS3/4A. This is then followed by a description of the results of the approaches adopted (repurposing, structure-based and high throughput screening) to discover coronavirus main protease inhibitors.

Discovery of SARS-CoV-2 Inhibitors Featuring Novel Histidine α-Nitrile Motif

As COVID-19 infection caused severe public health concerns recently, the development of novel antivirals has become the need of the hour. Main protease (Mpro ) has been an attractive target for antiviral drugs since it plays a vital role in polyprotein processing and virus maturation. Herein we report the discovery of a novel class of inhibitors against the SARS-CoV-2, bearing histidine α-nitrile motif embedded on a simple dipeptide framework. In-vitro and in-silico studies revealed that the histidine α-nitrile motif envisioned to target the Mpro contributes to the inhibitory activity. Among a series of dipeptides synthesized featuring this novel structural motif, some dipeptides displayed strong viral reduction (EC50 =0.48 μM) with a high selectivity index, SI>454.54. These compounds also exhibit strong binding energies in the range of -28.7 to -34.2 Kcal/mol. The simple dipeptide structural framework, amenable to quick structural variations, coupled with ease of synthesis from readily available commercial starting materials are the major attractive features of this novel class of SARS-CoV-2 inhibitors. The histidine α-nitrile dipeptides raise the hope of discovering potent drug candidates based on this motif to fight the dreaded SARS-CoV-2.

Structure and function of SARS-CoV and SARS-CoV-2 main proteases and their inhibition: A comprehensive review

Severe acute respiratory syndrome-associated coronavirus (SARS-CoV) identified in 2003 infected ∼8000 people in 26 countries with 800 deaths, which was soon contained and eradicated by syndromic surveillance and enhanced quarantine. A closely related coronavirus SARS-CoV-2, the causative agent of COVID-19 identified in 2019, has been dramatically more contagious and catastrophic. It has infected and caused various flu-like symptoms of billions of people in >200 countries, including >6 million people died of or with the virus. Despite the availability of several vaccines and antiviral drugs against SARS-CoV-2, finding new therapeutics is needed because of viral evolution and a possible emerging coronavirus in the future. The main protease (Mpro) of these coronaviruses plays important roles in their life cycle and is essential for the viral replication. This article represents a comprehensive review of the function, structure and inhibition of SARS-CoV and -CoV-2 Mpro, including structure-activity relationships, protein-inhibitor interactions and clinical trial status.

Discovery of highly potent covalent SARS-CoV-2 3CLpro inhibitors bearing 2-sulfoxyl-1,3,4-oxadiazole scaffold for combating COVID-19

The coronavirus disease (COVID-19) pandemic, caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has emerged as a major public health crisis, posing a significant threat to human well-being. Despite the availability of vaccines, COVID-19 continues to spread owing to the emergence of SARS-CoV-2 mutants. This highlights the urgent need for the discovery of more effective drugs to combat COVID-19. As an important target for COVID-19 treatment, 3C-like protease (3CLpro) plays a crucial role in the replication of SARS-CoV-2. In our previous research, we demonstrated the potent inhibitory activities of compound A1, which contains a 2-sulfonyl-1,3,4-oxadiazole scaffold, against SARS-CoV-2 3CLpro. Herein, we present a detailed investigation of structural optimization of A1 and conduct a study on the structure-activity relationship. Among the various compounds tested, sulfoxide D6 demonstrates a potent irreversible inhibitory activity (IC50 = 0.030 μM) against SARS-CoV-2 3CLpro, as well as a favorable selectivity towards host cysteine proteases such as cathepsin B and cathepsin L. Utilizing mass spectrometry-based peptide profiling, we found that D6 covalently binds to Cys145 of SARS-CoV-2 3CLpro. Some representative compounds, namely C11, D9 and D10 also demonstrates antiviral activity against SARS-CoV-2 in Vero E6 cells. Overall, the investigation of the 2-sulfoxyl-1,3,4-oxadiazole scaffold as a novel cysteine reactive warhead would provide valuable insights into the design of potent covalent 3CLpro inhibitors for COVID-19 treatment.

Entropy driven cooperativity effect in multi-site drug optimization targeting SARS-CoV-2 papain-like protease

Papain-like protease (PLpro), a non-structural protein encoded by SARS-CoV-2, is an important therapeutic target. Regions 1 and 5 of an existing drug, GRL0617, can be optimized to produce cooperativity with PLpro binding, resulting in stronger binding affinity. This work investigated the origin of the cooperativity using molecular dynamics simulations combined with the interaction entropy (IE) method. The regions' improvement exhibits cooperativity by calculating the binding free energies between the complex of PLpro-inhibitor. The thermodynamic integration method further verified the cooperativity generated in the drug improvement. To further determine the specific source of cooperativity, enthalpy and entropy in the complexes were calculated using molecular mechanics/generalized Born surface area and IE. The results show that the entropic change is an important contributor to the cooperativity. Our study also identified residues P248, Q269, and T301 that play a significant role in cooperativity. The optimization of the inhibitor stabilizes these residues and minimizes the entropic loss, and the cooperativity observed in the binding free energy can be attributed to the change in the entropic contribution of these residues. Based on our research, the application of cooperativity can facilitate drug optimization, and provide theoretical ideas for drug development that leverage cooperativity by reducing the contribution of entropy through multi-locus binding.

Network pharmacology and molecular docking analysis on potential molecular targets and mechanism of action of BRAF inhibitors for application in wound healing

Topical application of BRAF inhibitors has been shown to accelerate wound healing in murine models, which can be extrapolated into clinical applications. The aim of the study was to identify suitable pharmacological targets of BRAF inhibitors and elucidate their mechanisms of action for therapeutic applicability in wound healing, by employing bioinformatics tools including network pharmacology and molecular docking. The potential targets for BRAF inhibitors were obtained from SwissTargetPrediction, DrugBank, CTD, Therapeutic Target Database, and Binding Database. Targets of wound healing were obtained using online databases DisGeNET and OMIM (Online Mendelian Inheritance in Man). Common targets were found by using the online GeneVenn tool. Common targets were then imported to STRING to construct interaction networks. Topological parameters were assessed using Cytoscape and core targets were identified. FunRich was employed to uncover the signaling pathways, cellular components, molecular functions, and biological processes in which the core targets participate. Finally, molecular docking was performed using MOE software. Key targets for the therapeutic application of BRAF inhibitors for wound healing are peroxisome proliferator-activated receptor γ, matrix metalloproteinase 9, AKT serine/threonine kinase 1, mammalian target of rapamycin, and Ki-ras2 Kirsten rat sarcoma viral oncogene homolog. The most potent BRAF inhibitors that can be exploited for their paradoxical activity for wound healing applications are Encorafenib and Dabrafenib. By using network pharmacology and molecular docking, it can be predicted that the paradoxical activity of BRAF inhibitors can be used for their potential application in wound healing.

Recent Advances in Covalent Drug Discovery

In spite of the increasing number of biologics license applications, the development of covalent inhibitors is still a growing field within drug discovery. The successful approval of some covalent protein kinase inhibitors, such as ibrutinib (BTK covalent inhibitor) and dacomitinib (EGFR covalent inhibitor), and the very recent discovery of covalent inhibitors for viral proteases, such as boceprevir, narlaprevir, and nirmatrelvir, represent a new milestone in covalent drug development. Generally, the formation of covalent bonds that target proteins can offer drugs diverse advantages in terms of target selectivity, drug resistance, and administration concentration. The most important factor for covalent inhibitors is the electrophile (warhead), which dictates selectivity, reactivity, and the type of protein binding (i.e., reversible or irreversible) and can be modified/optimized through rational designs. Furthermore, covalent inhibitors are becoming more and more common in proteolysis, targeting chimeras (PROTACs) for degrading proteins, including those that are currently considered to be 'undruggable'. The aim of this review is to highlight the current state of covalent inhibitor development, including a short historical overview and some examples of applications of PROTAC technologies and treatment of the SARS-CoV-2 virus.

Multiple machine learning methods aided virtual screening of NaV 1.5 inhibitors

Na_v 1.5 sodium channels contribute to the generation of the rapid upstroke of the myocardial action potential and thereby play a central role in the excitability of myocardial cells. At present, the patch clamp method is the gold standard for ion channel inhibitor screening. However, this method has disadvantages such as high technical difficulty, high cost and low speed. In this study, novel machine learning models to screen chemical blockers were developed to overcome the above shortage. The data from the ChEMBL Database were employed to establish the machine learning models. Firstly, six molecular fingerprints together with five machine learning algorithms were used to develop 30 classification models to predict effective inhibitors. A validation and a test set were used to evaluate the performance of the models. Subsequently, the privileged substructures tightly associated with the inhibition of the Na_v 1.5 ion channel were extracted using the bioalerts Python package. In the validation set, the RF-Graph model performed best. Similarly, RF-Graph produced the best result in the test set in which the Prediction Accuracy (Q) was 0.9309 and Matthew's correlation coefficient was 0.8627, further indicating the model had high classification ability. The results of the privileged substructures indicated Sulfa structures and fragments with large Steric hindrance tend to block Na_v 1.5. In the unsupervised learning task of identifying sulfa drugs, MACCS and Graph fingerprints had good results. In summary, effective machine learning models have been constructed which help to screen potential inhibitors of the Na_v 1.5 ion channel and key privileged substructures with high affinity were also extracted.