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The novel coronavirus SARS-CoV2, the causative agent of the pandemic disease COVID-19, emerged in December 2019 forcing lockdown of communities in many countries. The absence of specific drugs and vaccines, the rapid transmission of the virus, and the increasing number of deaths worldwide necessitated the discovery of new substances for anti-COVID-19 drug development. With the aid of bioinformatics and computational modelling, ninety seven antiviral secondary metabolites from fungi were docked onto five SARS-CoV2 enzymes involved in viral attachment, replication, post-translational modification, and host immunity evasion infection mechanisms followed by molecular dynamics simulation and in silico ADMET prediction (absorption, distribution, metabolism, excretion and toxicity) of the hit compounds. Thus, three fumiquinazoline alkaloids scedapin C (15), quinadoline B (19) and norquinadoline A (20), the polyketide isochaetochromin D1 (8), and the terpenoid 11a-dehydroxyisoterreulactone A (11) exhibited high binding affinities on the target proteins, papain-like protease (PLpro), chymotrypsin-like protease (3CLpro), RNA-directed RNA polymerase (RdRp), non-structural protein 15 (nsp15), and the spike binding domain to GRP78. Molecular dynamics simulation was performed to optimize the interaction and investigate the stability of the top-scoring ligands in complex with the five target proteins. All tested complexes were found to have dynamic stability. Of the five top-scoring metabolites, quinadoline B (19) was predicted to confer favorable ADMET values, high gastrointestinal absorptive probability and poor blood-brain barrier crossing capacities.

Identification of predictors of long COVID-19 is essential for managing healthcare plans of patients. This systematic literature review and meta-analysis aimed to identify risk factors not associated with Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) infection, but rather potentially predictive of the development of long COVID-19. MEDLINE, CINAHL, PubMed, EMBASE, and Web of Science databases, as well as medRxiv and bioRxiv preprint servers were screened through 15 September 2022. Peer-reviewed studies or preprints evaluating potential pre-SARS-CoV-2 infection risk factors for the development of long-lasting symptoms were included. The methodological quality was assessed using the Quality in Prognosis Studies (QUIPSs) tool. Random-effects meta-analyses with calculation of odds ratio (OR) were performed in those risk factors where a homogenous long COVID-19 definition was used. From 1978 studies identified, 37 peer-reviewed studies and one preprint were included. Eighteen articles evaluated age, sixteen articles evaluated sex, and twelve evaluated medical comorbidities as risk factors of long COVID-19. Overall, single studies reported that old age seems to be associated with long COVID-19 symptoms (n = 18); however, the meta-analysis did not reveal an association between old age and long COVID-19 (n = 3; OR 0.86, 95% CI 0.73 to 1.03, p = 0.17). Similarly, single studies revealed that female sex was associated with long COVID-19 symptoms (n = 16); which was confirmed in the meta-analysis (n = 7; OR 1.48, 95% CI 1.17 to 1.86, p = 0.01). Finally, medical comorbidities such as pulmonary disease (n = 4), diabetes (n = 1), obesity (n = 6), and organ transplantation (n = 1) were also identified as potential risk factors for long COVID-19. The risk of bias of most studies (71%, n = 27/38) was moderate or high. In conclusion, pooled evidence did not support an association between advancing age and long COVID-19 but supported that female sex is a risk factor for long COVID-19. Long COVID-19 was also associated with some previous medical comorbidities.

The association of SARS-CoV-2 variants with long-COVID symptoms is still scarce, but new data are appearing at a fast pace. This systematic review compares the prevalence of long-COVID symptoms according to relevant SARS-CoV-2 variants in COVID-19 survivors. The MEDLINE, CINAHL, PubMed, EMBASE and Web of Science databases, as well as the medRxiv and bioRxiv preprint servers, were searched up to 25 October 2022. Case-control and cohort studies analyzing the presence of post-COVID symptoms appearing after an acute SARS-CoV-2 infection by the Alpha (B.1.1.7), Delta (B.1.617.2) or Omicron (B.1.1.529/BA.1) variants were included. Methodological quality was assessed using the Newcastle–Ottawa Scale. From 430 studies identified, 5 peer-reviewed studies and 1 preprint met the inclusion criteria. The sample included 355 patients infected with the historical variant, 512 infected with the Alpha variant, 41,563 infected with the Delta variant, and 57,616 infected with the Omicron variant. The methodological quality of all studies was high. The prevalence of long-COVID was higher in individuals infected with the historical variant (50%) compared to those infected with the Alpha, Delta or Omicron variants. It seems that the prevalence of long-COVID in individuals infected with the Omicron variant is the smallest, but current data are heterogeneous, and long-term data have, at this stage, an obviously shorter follow-up compared with the earlier variants. Fatigue is the most prevalent long-COVID symptom in all SARS-CoV-2 variants, but pain is likewise prevalent. The available data suggest that the infection with the Omicron variant results in fewer long-COVID symptoms compared to previous variants; however, the small number of studies and the lack of the control of cofounders, e.g., reinfections or vaccine status, in some studies limit the generality of the results. It appears that individuals infected with the historical variant are more likely to develop long-COVID symptomatology.

Accumulating evidence shows a progressive decline in the efficacy of coronavirus disease 2019 (COVID‐19) (severe acute respiratory syndrome coronavirus 2 [SARS‐CoV‐2]) messenger RNA (mRNA) vaccines such as Pfizer‐BioNTech (mRNA BNT161b2) and Moderna (mRNA‐1273) in preventing breakthrough infections due to diminishing humoral immunity over time. Thus, this review characterizes the kinetics of anti‐SARS‐CoV‐2 antibodies after the second dose of a primary cycle of COVID‐19 mRNA vaccination. A systematic search of the literature was performed and a total of 18 articles ( N = 15 980 participants) were identified and reviewed. The percent difference of means of reported antibody titers was then calculated to determine the decline in humoral response after the peak levels postvaccination. Findings revealed that the peak humoral response was reached at 21–28 days after the second dose, after which serum levels progressively diminished at 4–6‐month postvaccination. Additionally, results showed that regardless of age, sex, serostatus, and presence of comorbidities, longitudinal data reporting antibody measurement exhibited a decline of both anti‐receptor binding domain immunoglobulin G (IgG) and anti‐spike IgG, ranging from 94% to 95% at 90–180 days and 55%–85% at 140–160 days, respectively, after the peak antibody response. This suggests that the rate of antibody decline may be independent of patient‐related factors and peak antibody titers but mainly a function of time and antibody class/molecular target. Hence, this study highlights the necessity of more efficient vaccination strategies to provide booster administration in attenuating the effects of waning immunity, especially in the appearance of new variants of concerns.

With the advent of the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) pandemic, several vaccines have been developed to mitigate its spread and prevent adverse consequences of the Coronavirus Disease 2019 (COVID-19). The mRNA technology is an unprecedented vaccine, usually given in two doses to prevent SARS-CoV-2 infections. Despite effectiveness and safety, inter-individual immune response heterogeneity has been observed in recipients of mRNA-based vaccines. As a novel disease, the specific immune response mechanism responsible for warding off COVID-19 remains unclear at this point. However, significant evidence suggests that humoral response plays a crucial role in affording immunoprotection and preventing debilitating sequelae from COVID-19. As such, this paper focused on the possible effects of age, sex, serostatus, and comorbidities on humoral response (i.e. total antibodies, IgG, and/or IgA) of different populations post-mRNA-based Pfizer-BioNTech vaccination. A systematic search of literature was performed through PubMed, Cochrane CENTRAL, Google Scholar, Science Direct, medRxiv, and Research Square. Studies were included if they reported humoral response to COVID-19 mRNA vaccines. A total of 32 studies were identified and reviewed, and the percent differences of means of reported antibody levels were calculated for comparison. Findings revealed that older individuals, male sex, seronegativity, and those with more comorbidities mounted less humoral immune response. Given these findings, several recommendations were proposed regarding the current vaccination practices. These include giving additional doses of vaccination for immunocompromised and elderly populations. Another recommendation is conducting clinical trials in giving a combined scheme of mRNA vaccines, protein vaccines, and vector-based vaccines.

Background Accessing COVID-19 vaccines is a challenge despite successful clinical trials. This burdens the COVID-19 treatment gap, thereby requiring accelerated discovery of anti-SARS-CoV-2 agents. This study explored the potential of anti-HIV reverse transcriptase (RT) phytochemicals as inhibitors of SARS-CoV-2 non-structural proteins (nsps) by targeting in silico key sites in the structures of SARS-CoV-2 nsps. One hundred four anti-HIV phytochemicals were subjected to molecular docking with nsp3, 5, 10, 12, 13, 15, and 16. Top compounds in complex with the nsps were investigated further through molecular dynamics. The drug-likeness and ADME (absorption, distribution, metabolism, and excretion) properties of the top compounds were also predicted using SwissADME. Their toxicity was likewise determined using OSIRIS Property Explorer. Results Among the top-scoring compounds, the polyphenolic functionalized natural products comprised of biflavones 1, 4, 11, 13, 14, 15; ellagitannin 9; and bisisoquinoline alkaloid 19 were multi-targeting and exhibited strongest binding affinities to at least two nsps (binding energy = − 7.7 to − 10.8 kcal/mol). The top ligands were stable in complex with their target nsps as determined by molecular dynamics. Several top-binding compounds were computationally druggable, showed good gastrointestinal absorptive property, and were also predicted to be non-toxic. Conclusions Twenty anti-HIV RT phytochemicals showed multi-targeting inhibitory potential against SARS-CoV-2 non-structural proteins 3, 5, 10, 12, 13, 15, and 16. Our results highlight the importance of polyhydroxylated aromatic substructures for effective attachment in the binding/catalytic sites of nsps involved in post-translational mechanism pathways. As such with the nsps playing vital roles in viral pathogenesis, our findings provide inspiration for the design and discovery of novel anti-COVID-19 drug prototypes.

Inhibition of the major cyclic adenosine monophosphate-metabolizing enzyme PDE4 has shown potential for the discovery of drugs for cancer, inflammation, and neurodegenerative disorders such as Alzheimer's disease. As a springboard to explore new anti-cancer and anti-Alzheimer's chemical prototypes from rare Annonaceae species, the present study evaluated anti-PDE4B along with antiproliferative and anti-cholinesterase activities of the extracts of the Philippine endemic species Uvaria alba using in vitro assays and framed the resulting biological significance through computational binding and reactivity-based experiments. Thus, the PDE4 B2B-inhibiting dichloromethane sub-extract (UaD) of U. alba elicited antiproliferative activity against chronic myelogenous leukemia (K-562) and cytostatic effects against human cervical cancer (HeLa). The extract also profoundly inhibited acetylcholinesterase (AChE), an enzyme involved in the progression of neurodegenerative diseases. Chemical profiling analysis of the bioactive extract identified 18 putative secondary metabolites. Molecular docking and molecular dynamics simulations showed strong free energy binding mechanisms and dynamic stability at 50ns simulations in the catalytic domains of PDE4 B2B, ubiquitin-specific peptidase 14, and Kelch-like ECH-associated protein 1 (KEAP-1 Kelch domain) for the benzylated dihydroflavone dichamanetin (16), and of an AChE and KEAP-1 BTB domain for 3-(3,4-dihydroxybenzyl)-3′,4′,6-trihydroxy-2,4-dimethoxychalcone (8) and grandifloracin (15), respectively. Density functional theory calculations to demonstrate Michael addition reaction of the most electrophilic metabolite and kinetically stable grandifloracin (15) with Cys151 of the KEAP-1 BTB domain illustrated favorable formation of a β-addition adduct. The top-ranked compounds also conferred favorable in silico pharmacokinetic properties.