COVID-19: inflammatory responses, structure-based drug design and potential therapeutics

Computational and Experimental Studies on the α-Functionalization of Ketones Using Domino Reactions: A Strategy to Increase Chemoselectivity at the α-Carbon of Ketones

A facile strategy to increase the chemoselectivity of domino reactions was proposed and successfully applied in the α-functionalization of ketones. The strategy involved widening the activation energy of the main reaction and side reaction through intermolecular interactions, thereby increasing the chemoselectivity of the domino reaction. In the proposed α-functionalization reaction, TMSCF3 acted as an excellent reagent which increased the nucleophilicity of DMF through the Van der Waals force and reduced the nucleophilicity of H2O through a hydrogen bond. We found that TMSCF3 can increase the activation energy difference between the main reaction and side reaction using DFT calculations, which greatly increased chemoselectivity and avoided the formation of by-products. TMSCF3 was recycled by rectification, and the average recovery rate was 87.2%. DFT calculations, XRD experiments, and control experiments were performed to support this mechanism. We are confident that this strategy has the potential to deliver significant practical advancements while simultaneously fostering broader innovation in the field of domino synthesis.

Advancing Women in Chemistry: A Step Toward Gender Parity

As chemistry progressed over the years, modern society witnessed the significant contribution of women chemists. However, the persisting gender imbalance in the scientific community, attributed to improper societal norms and several other reasons, is a matter of concern. The manuscript highlights some great women chemists, such as Nobel Prize awardees, who have created history through their outstanding research work and are role models for other women. Since women continue to encounter recurring obstacles to moving forward in their area, the "leaky pipeline" of women in chemical science remains problematic. Numerous factors, including having to shoulder the labor of childcare and household work and a lack of awareness of regulations and possibilities, contribute to prejudices and the gender gap in higher-level administrative and decision-making roles. To close the gender gap and empower women chemists, we highlight some initiatives (awards, fellowships, schemes, and grants) that have been put forth by governments, organizations, foundations, companies, industries, and publishing societies. As per statistics, only 4% of female scientists have been awarded the Nobel Prize in chemistry until now. Only 35%, 22%, 14%, 26%, and 5% of women are serving as editors-in-chief, while 38%, 40%, 18%, 22%, and 21% are working as associate editors of the American Chemical Society (ACS), Royal Society of Chemistry (RSC), Wiley, Elsevier, and Springer journals, respectively. A further issue is that women receive far fewer honors in chemistry. To promote a more encouraging atmosphere for women scientists at all career phases, we listed some recommendations that research grant funders, academic institutions, publishers, and scientific organizations can follow. For gender parity, the paper sought to address the current situation of women in the chemical sciences. Women's contributions to chemistry will promote innovation and progress in the field.

Review of preclinical data of PF-07304814 and its active metabolite derivatives against SARS-CoV-2 infection

Main protease (M^pro) is a superior target for anti-SARS-COV-2 drugs. PF-07304814 is a phosphate ester prodrug of PF-00835231 that is rapidly metabolized into the active metabolite PF-00835231 by alkaline phosphatase (ALP) and then suppresses SARS-CoV-2 replication by inhibiting M^pro. PF-07304814 increased the bioavailability of PF-00835231 by enhancing plasma protein binding (PPB). P-glycoprotein (P-gp) inhibitors and cytochrome P450 3A (CYP3A) inhibitors increased the efficacy of PF-00835231 by suppressing its efflux from target cells and metabolism, respectively. The life cycle of SARS-CoV-2 is approximately 4 h. The mechanisms and efficacy outcomes of PF-00835231 occur simultaneously. PF-00835231 can inhibit not only cell infection (such as Vero E6, 293T, Huh-7.5, HeLa^{+angiotensin-converting enzyme 2 (ACE2)}, A549^+ACE2, and MRC-5) but also the human respiratory epithelial organ model and animal model infection. PF-07304814 exhibits a short terminal elimination half-life and is cleared primarily through renal elimination. There were no significant adverse effects of PF-07304814 administration in rats. Therefore, PF-07304814 exhibits good tolerability, pharmacology, pharmacodynamics, pharmacokinetics, and safety in preclinical trials. However, the Phase 1 data of PF-07304814 were not released. The Phase 2/3 trial of PF-07304814 was also suspended. Interestingly, the antiviral activities of PF-00835231 derivatives (compounds 5–22) are higher than, similar to, or slightly weaker than those of PF-00835231. In particular, compound 22 exhibited the highest potency and had good safety and stability. However, the low solubility of compound 22 limits its clinical application. Prodrugs, nanotechnology and salt form drugs may solve this problem. In this review, we focus on the preclinical data of PF-07304814 and its active metabolite derivatives to hopefully provide knowledge for researchers to study SARS-CoV-2 infection.

Glucocorticoids and COVID-19

Coronavirus Disease 19 (COVID-19) is associated with high morbidity and mortality rates globally, representing the greatest health and economic challenge today. Several drugs are currently approved for the treatment of COVID-19. Among these, glucocorticoids (GCs) have received particular attention due to their anti-inflammatory and immunosuppressive effects. In fact, GC are widely used in current clinical practice to treat inflammatory, allergic and autoimmune diseases. Major mechanisms of GC action include inhibition of innate and adaptive immune activity. In particular, an important role is played by the inhibition of pro-inflammatory cytokines and chemokines, and the induction of proteins with anti-inflammatory activity. Overall, as indicated by various national and international regulatory agencies, GCs are recommended for the treatment of COVID-19 in patients requiring oxygen therapy, with or without mechanical ventilation. Regarding the use of GCs for the COVID-19 treatment of non-hospitalized patients at an early stage of the disease, many controversial studies have been reported and regulatory agencies have not recommended their use. The decision to start GC therapy should be based not only on the severity of COVID-19 disease, but also on careful considerations of the benefit/risk profile in individual patients, including monitoring of adverse events. In this review we summarize the effects of GCs on the major cellular and molecular components of the inflammatory/immune system, the benefits and the adverse common reactions in the treatment of inflammatory/autoimmune diseases, as well as in the management of COVID-19.

A multi-population-based genomic analysis uncovers unique haplotype variants and crucial mutant genes in SARS-CoV-2

Background

COVID-19 is a disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Rigorous detection and treatment strategies against SARS-CoV-2 have become very challenging due to continuous evolutions to the viral genome. Therefore, careful genomic analysis is sorely needed to understand transmission, the cellular mechanism of pathogenicity, and the development of vaccines or drugs.

Objective

In this study, we intended to identify SARS-CoV-2 genome variants that may help understand the cellular and molecular foundation of coronavirus infections required to develop effective intervention strategies.

Methods

SARS-CoV-2 genome sequences were downloaded from an open-source public database, processed, and analyzed for variants in target detection sites and genes.

Results

We have identified six unique variants, G---AAC, T---AAC---T, AAC---T, AAC--------T, C----------T, and C--------C, at the nucleocapsid region and eleven major hotspot mutant genes: nsp3, surface glycoprotein, nucleocapsid phosphoprotein, ORF8, nsp6, nsp2, nsp4, helicase, membrane glycoprotein, 3′-5′ exonuclease, and 2′-O-ribose methyltransferases. In addition, we have identified eleven major mutant genes that may have a crucial role in SARS-CoV-2 pathogenesis.

Conclusion

Studying haplotype variants and 11 major mutant genes to understand the mechanism of action of fatal pathogenicity and inter-individual variations in immune responses is inevitable for managing target patient groups with identified variants and developing effective anti-viral drugs and vaccines.

Supplementary Information

The online version contains supplementary material available at 10.1186/s43141-022-00431-3.

Screening of immune cell activators from Astragali Radix using a comprehensive two-dimensional NK-92MI cell membrane chromatography/C18 column/time-of-flight mass spectrometry system

Astragali Radix (AR) is a clinically used herbal medicine with multiple immunomodulatory activities that can strengthen the activity and cytotoxicity of natural killer (NK) cells. However, owing to the complexity of its composition, the specific active ingredients in AR that act on NK cells are not clear yet. Cell membrane chromatography (CMC) is mainly used to screen the active ingredients in a complex system of herbal medicines. In this study, a new comprehensive two-dimensional (2D) NK-92MI CMC/C₁₈ column/time-of-flight mass spectrometry (TOFMS) system was established to screen for potential NK cell activators. To obtain a higher column efficiency, 3-mercaptopropyltrimethoxysilane-modified silica was synthesized to prepare the NK-92MI CMC column. In total, nine components in AR were screened from this system, which could be washed out from the NK-92MI/CMC column after 10 min, and they showed good affinity for NK-92MI/CMC column. Two representative active compounds of AR, isoastragaloside I and astragaloside IV, promoted the killing effect of NK cells on K562 cells in a dose-dependent manner. It can thus suggest that isoastragaloside I and astragaloside IV are the main immunomodulatory components of AR. This comprehensive 2D NK-92MI CMC analytical system is a practical method for screening immune cell activators from other herbal medicines with immunomodulatory effects.

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A comprehensive 2D NK-92MI/CMC system was developed to screen for immune cell activators.

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Nine components of Astragali Radix were screened as potential immune activators.

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Isoastragaloside I and astragaloside IV were first confirmed to have immunomodulatory effects.

Recent Advances and Mechanistic Insights into Antibacterial Activity, Antibiofilm Activity, and Cytotoxicity of Silver Nanoparticles

The substantial increase in multidrug-resistant (MDR) pathogenic bacteria is a major threat to global health. Recently, the Centers for Disease Control and Prevention reported possibilities of greater deaths due to bacterial infections than cancer. Nanomaterials, especially small-sized (size ≤10 nm) silver nanoparticles (AgNPs), can be employed to combat these deadly bacterial diseases. However, high reactivity, instability, susceptibility to fast oxidation, and cytotoxicity remain crucial shortcomings for their uptake and clinical application. In this review, we discuss various AgNPs-based approaches to eradicate bacterial infections and provide comprehensive mechanistic insights and recent advances in antibacterial activity, antibiofilm activity, and cytotoxicity (both in vitro and in vivo) of AgNPs. The mechanistic of antimicrobial activity involves four steps: (i) adhesion of AgNPs to cell wall/membrane and its disruption; (ii) intracellular penetration and damage; (iii) oxidative stress; and (iv) modulation of signal transduction pathways. Numerous factors affecting the bactericidal activity of AgNPs such as shape, size, crystallinity, pH, and surface coating/charge have also been described in detail. The review also sheds light on antimicrobial photodynamic therapy and the role of AgNPs versus Ag⁺ ions release in bactericidal activities. In addition, different methods of synthesis of AgNPs have been discussed in brief.

Identification of Food Compounds as inhibitors of SARS-CoV-2 main protease using molecular docking and molecular dynamics simulations

SARS-CoV-2 has rapidly emerged as a global pandemic with high infection rate. At present, there is no drug available for this deadly disease. Recently, M^pro (Main Protease) enzyme has been identified as essential proteins for the survival of this virus. In the present work, Lipinski's rules and molecular docking have been performed to identify plausible inhibitors of M^pro using food compounds. For virtual screening, a database of food compounds was downloaded and then filtered using Lipinski's rule of five. Then, molecular docking was accomplished to identify hits using M^pro protein as the target enzyme. This led to identification of a Spermidine derivative as a hit. In the next step, Spermidine derivatives were collected from PubMed and screened for their binding with M^pro protein. In addition, molecular dynamic simulations (200 ns) were executed to get additional information. Some of the compounds are found to have strong affinity for M^pro, therefore these hits could be used to develop a therapeutic agent for SARS-CoV-2.

Co-crystallization and structure determination: An effective direction for anti-SARS-CoV-2 drug discovery

Safer and more-effective drugs are urgently needed to counter infections with the highly pathogenic SARS-CoV-2, cause of the COVID-19 pandemic. Identification of efficient inhibitors to treat and prevent SARS-CoV-2 infection is a predominant focus. Encouragingly, using X-ray crystal structures of therapeutically relevant drug targets (PLpro, Mpro, RdRp, and S glycoprotein) offers a valuable direction for anti-SARS-CoV-2 drug discovery and lead optimization through direct visualization of interactions. Computational analyses based primarily on MMPBSA calculations have also been proposed for assessing the binding stability of biomolecular structures involving the ligand and receptor. In this study, we focused on state-of-the-art X-ray co-crystal structures of the abovementioned targets complexed with newly identified small-molecule inhibitors (natural products, FDA-approved drugs, candidate drugs, and their analogues) with the assistance of computational analyses to support the precision design and screening of anti-SARS-CoV-2 drugs.

Mechanistic and Predictive QSAR Analysis of Diverse Molecules to Capture Salient and Hidden Pharmacophores for Anti-Thrombotic Activity

Thrombosis is a life-threatening disease with a high mortality rate in many countries. Even though anti-thrombotic drugs are available, their serious side effects compel the search for safer drugs. In search of a safer anti-thrombotic drug, Quantitative Structure-Activity Relationship (QSAR) could be useful to identify crucial pharmacophoric features. The present work is based on a larger data set comprising 1121 diverse compounds to develop a QSAR model having a balance of acceptable predictive ability (Predictive QSAR) and mechanistic interpretation (Mechanistic QSAR). The developed six parametric model fulfils the recommended values for internal and external validation along with Y-randomization parameters such as R²_tr = 0.831, Q²_LMO = 0.828, R²_ex = 0.783. The present analysis reveals that anti-thrombotic activity is found to be correlated with concealed structural traits such as positively charged ring carbon atoms, specific combination of aromatic Nitrogen and sp2-hybridized carbon atoms, etc. Thus, the model captured reported as well as novel pharmacophoric features. The results of QSAR analysis are further vindicated by reported crystal structures of compounds with factor Xa. The analysis led to the identification of useful novel pharmacophoric features, which could be used for future optimization of lead compounds.

Applications of artificial intelligence to drug design and discovery in the big data era: a comprehensive review

Artificial intelligence (AI) renders cutting-edge applications in diverse sectors of society. Due to substantial progress in high-performance computing, the development of superior algorithms, and the accumulation of huge biological and chemical data, computer-assisted drug design technology is playing a key role in drug discovery with its advantages of high efficiency, fast speed, and low cost. Over recent years, due to continuous progress in machine learning (ML) algorithms, AI has been extensively employed in various drug discovery stages. Very recently, drug design and discovery have entered the big data era. ML algorithms have progressively developed into a deep learning technique with potent generalization capability and more effectual big data handling, which further promotes the integration of AI technology and computer-assisted drug discovery technology, hence accelerating the design and discovery of the newest drugs. This review mainly summarizes the application progression of AI technology in the drug discovery process, and explores and compares its advantages over conventional methods. The challenges and limitations of AI in drug design and discovery have also been discussed.

Identification of Anti-SARS-CoV-2 Compounds from Food Using QSAR-Based Virtual Screening, Molecular Docking, and Molecular Dynamics Simulation Analysis

Due to the genetic similarity between SARS-CoV-2 and SARS-CoV, the present work endeavored to derive a balanced Quantitative Structure-Activity Relationship (QSAR) model, molecular docking, and molecular dynamics (MD) simulation studies to identify novel molecules having inhibitory potential against the main protease (Mpro) of SARS-CoV-2. The QSAR analysis developed on multivariate GA-MLR (Genetic Algorithm-Multilinear Regression) model with acceptable statistical performance (R2 = 0.898, Q2loo = 0.859, etc.). QSAR analysis attributed the good correlation with different types of atoms like non-ring Carbons and Nitrogens, amide Nitrogen, sp2-hybridized Carbons, etc. Thus, the QSAR model has a good balance of qualitative and quantitative requirements (balanced QSAR model) and satisfies the Organisation for Economic Co-operation and Development (OECD) guidelines. After that, a QSAR-based virtual screening of 26,467 food compounds and 360 heterocyclic variants of molecule 1 (benzotriazole-indole hybrid molecule) helped to identify promising hits. Furthermore, the molecular docking and molecular dynamics (MD) simulations of Mpro with molecule 1 recognized the structural motifs with significant stability. Molecular docking and QSAR provided consensus and complementary results. The validated analyses are capable of optimizing a drug/lead candidate for better inhibitory activity against the main protease of SARS-CoV-2.