A Review on Protease Inhibitors of Herbal Origin to Combat Malignancy.

Protease is the enzyme accountable for the breakdown of proteins i.e., proteolysis. Proteases are reportedly involved in the events of growth, development, progression and metastasis of cancers. If any agent could inhibit/retard the protease enzyme, i.e., protease inhibitor, it would arrest the cancer; thus indicating the significance of exploring protease inhibitors for latest anti-malignant drug discovery. Higher plants are the rich sources of different protease inhibitors that are effective against several types of malignancies both at preclinical and clinical stages. Natural protease inhibitors of herbal origin have both cancer chemopreventive and chemotherapeutic properties together with inhibitory activity against different types of pertinent proteases. Clinically, these herbal agents are found to be safe unlike the synthetic antineoplastic agents. Further studies in this direction are necessary in pursuit of newer generation drugs without adverse reactions for the prevention and treatment of malignancies.

An orally bioavailable SARS-CoV-2 main protease inhibitor exhibits improved affinity and reduced sensitivity to mutations.

Inhibitors of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) main protease (Mpro) such as nirmatrelvir (NTV) and ensitrelvir (ETV) have proven effective in reducing the severity of COVID-19, but the presence of resistance-conferring mutations in sequenced viral genomes raises concerns about future drug resistance. Second-generation oral drugs that retain function against these mutants are thus urgently needed. We hypothesized that the covalent hepatitis C virus protease inhibitor boceprevir (BPV) could serve as the basis for orally bioavailable drugs that inhibit SARS-CoV-2 Mpro more efficiently than existing drugs. Performing structure-guided modifications of BPV, we developed a picomolar-affinity inhibitor, ML2006a4, with antiviral activity, oral pharmacokinetics, and therapeutic efficacy similar or superior to those of NTV. A crucial feature of ML2006a4 is a derivatization of the ketoamide reactive group that improves cell permeability and oral bioavailability. Last, ML2006a4 was found to be less sensitive to several mutations that cause resistance to NTV or ETV and occur in the natural SARS-CoV-2 population. Thus, anticipatory design can preemptively address potential resistance mechanisms to expand future treatment options against coronavirus variants.

HIV protease resistance mutations in patients receiving second-line antiretroviral therapy in Libreville, Gabon.

INTRODUCTION: In 2022, the WHO reported that 29.8 million people around the world were living with HIV (PLHIV) and receiving antiretroviral treatment (ART), including 25| 375 people in Gabon (54% of all those living with HIV in the country). The literature reports a frequency of therapeutic failure with first-line antiretrovirals (ARVs) of between 20% and 82%. Unfortunately, data relating to the failure of second-line ARVs are scarce in Gabon. This study aims to determine the profiles of HIV drug resistance mutations related to protease inhibitors in Gabon. METHODOLOGY: Plasma from 84 PLHIV receiving ARVs was collected from 2019 to 2021, followed by RNA extraction, amplification, and sequencing of the protease gene. ARV resistance profiles were generated using the Stanford interpretation algorithm version 8.9-1 ( https://hivdb.stanford.edu ) and statistical analyses were performed using EpiInfo software version 7.2.1.0 (CDC, USA). RESULTS: Of 84 HIV plasma samples collected from 45 men and 39 women, 342 mutations were detected. Of these, 43.3% (148/342) were associated with nucleoside reverse transcriptase inhibitors (NRTIs), 30.4% (104/342) with non-nucleoside reverse transcriptase inhibitors (NNRTIs), and 26.3% (90/342) with protease inhibitors (PIs). Most NRTI mutations were associated with thymidine analogues (TAMs) (50.7%; 75/148), including T215F/V (14.9%; 22/148), D67DN/E/G/N/T (10.1%; 15/148), M41L (9.5%; 14/148), and K70E/KN/S/R (9.5%; 14/148). Resistance mutations related to non-TAM NRTIs (33.1%; 49/148) were M184V (29.1%; 43/148), and L74I/V (8.1%; 12/148). NNRTI mutations were predominantly K103N/S (32.7%; 34/104), V108I (10.6%; 11/104), A98G (10.6%; 11/104), and P225H (9.6%; 10/104). Minor mutations associated with PIs (60.0%; 54/90) were predominantly K20I (15.6%; 14/90) and L10F/I/V (14.5%; 13/90). The major mutations associated with PIs (40.0%; 36/90) were M41L (12.2%; 11/90), I84V (6.7%; 06/90), and V82A (6.7%; 06/90). The four most prescribed therapeutic regimens were TDF + 3TC + LPV/r (20.3%; 17/84), ABC + DDI + LPV/r (17.9%; 15/84), TDF + FTC + LPV/r (11.9%; 10/84), and ABC + 3TC + LPV/r (11.9%; 10/84). CONCLUSION: This study revealed that HIV drug resistance mutations are common in Gabon. The major mutations associated with PIs were M41L, I84V, and V82A. There is a need for access to new NRTIs, NNRTIs, and PIs for a better therapeutic management of PLHIV in Gabon.

Discovery of CMX990: A Potent SARS-CoV-2 3CL Protease Inhibitor Bearing a Novel Warhead.

There remains a need to develop novel SARS-CoV-2 therapeutic options that improve upon existing therapies by an increased robustness of response, fewer safety liabilities, and global-ready accessibility. Functionally critical viral main protease (Mpro, 3CLpro) of SARS-CoV-2 is an attractive target due to its homology within the coronaviral family, and lack thereof toward human proteases. In this disclosure, we outline the advent of a novel SARS-CoV-2 3CLpro inhibitor, CMX990, bearing an unprecedented trifluoromethoxymethyl ketone warhead. Compared with the marketed drug nirmatrelvir (combination with ritonavir = Paxlovid), CMX990 has distinctly differentiated potency (∼5× more potent in primary cells) and human in vitro clearance (>4× better microsomal clearance and >10× better hepatocyte clearance), with good in vitro-to-in vivo correlation. Based on its compelling preclinical profile and projected once or twice a day dosing supporting unboosted oral therapy in humans, CMX990 advanced to a Phase 1 clinical trial as an oral drug candidate for SARS-CoV-2.

Low-level HIV viraemia during antiretroviral therapy: Longitudinal patterns and predictors of viral suppression.

OBJECTIVES: Our objective was to characterize longitudinal patterns of viraemia and factors associated with viral suppression in people with HIV and low-level viraemia (LLV) during antiretroviral therapy (ART). METHODS: We included people with HIV in the EuResist Integrated Database with LLV following ART initiation after 2005. LLV was defined as two or more consecutive viral load (VL) measurements of 51-199 copies/mL 30-365 days apart after >12 months of ART. Viraemia patterns were analyzed over 24 months. Factors associated with viral suppression at 12 months after LLV episodes were identified using univariable and multivariable logistic regression. RESULTS: Of 25 113 people with HIV, 2474 (9.9%) had LLV. Among 1387 participants with 24 months of follow-up after LLV, 406 (29%) had persistent suppression, 669 (48%) had transient viraemic episodes, 29 (2%) had persistent LLV, and 283 (20%) had virological failure. Following LLV episodes, the proportion with detectable viraemia declined (p for trend <0.001 and 0.034, in the first and second year, respectively). At 12 months, 68% had undetectable VL, which was associated with suppression before LLV (adjusted odds ratio [aOR] 1.7; 95% confidence interval [CI] 1.2-2.4) and ART modification after LLV (aOR 1.6; 95% CI 1.0-2.4). The following factors were negatively associated with undetectable VL at 12 months: higher VL during LLV (aOR 0.57 per log10 copies/mL; 95% CI 0.37-0.89), injecting drug use (aOR 0.67; 95% CI 0.47-0.96), and regimens with protease inhibitors (aOR 0.65; 95% CI 0.49-0.87) or combined anchor drugs (aOR 0.52; 95% CI 0.32-0.85). CONCLUSION: Most people with LLV did not experience sustained viral suppression during 24-month follow-up, supporting the association between LLV and inferior treatment outcome.

Therapeutic Intervention of Serine Protease Inhibitors against Hepatitis C Virus.

Hepatitis C virus (HCV) is a globally prevalent and hazardous disorder that is responsible for inducing several persistent and potentially fatal liver diseases. Current treatment strategies offer limited efficacy, often accompanied by severe and debilitating adverse effects. Consequently, there is an urgent and compelling need to develop novel therapeutic interventions that can provide maximum efficacy in combating HCV while minimizing the burden of adverse effects on patients. One promising target against HCV is the NS3-4A serine protease, a complex composed of two HCV-encoded proteins. This non-covalent heterodimer is crucial in the viral life cycle and has become a primary focus for therapeutic interventions. Although peginterferon, combined with ribavirin, is commonly employed for HCV treatment, its efficacy is hampered by significant adverse effects that can profoundly impact patients' quality of life. In recent years, the development of direct-acting antiviral agents (DAAs) has emerged as a breakthrough in HCV therapy. These agents exhibit remarkable potency against the virus and have demonstrated fewer adverse effects when combined with other DAAs. However, it is important to note that there is a potential for developing resistance to DAAs due to alterations in the amino acid position of the NS3-4A protease. This emphasizes the need for ongoing research to identify strategies that can minimize the emergence of resistance and ensure long-term effectiveness. While the combination of DAAs holds promise for HCV treatment, it is crucial to consider the possibility of drug-drug interactions. These interactions may occur when different DAAs are used concurrently, potentially compromising their therapeutic efficacy. Therefore, carefully evaluating and monitoring potential drug interactions are vital to optimize treatment outcomes. In the pursuit of novel therapeutic interventions for HCV, the field of computational biology and bioinformatics has emerged as a valuable tool. These advanced technologies and methodologies enable the development and design of new drugs and therapeutic agents that exhibit maximum efficacy, reduced risk of resistance, and minimal adverse effects. By leveraging computational approaches, researchers can efficiently screen and optimize potential candidates, accelerating the discovery and development of highly effective treatments for HCV, treatments.

A Molecular Generative Model of COVID-19 Main Protease Inhibitors Using Long Short-Term Memory-Based Recurrent Neural Network.

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused a serious threat to public health and prompted researchers to find anti-coronavirus 2019 (COVID-19) compounds. In this study, the long short-term memory-based recurrent neural network was used to generate new inhibitors for the coronavirus. First, the model was trained to generate drug compounds in the form of valid simplified molecular-input line-entry system strings. Then, the structures of COVID-19 main protease inhibitors were applied to fine-tune the model. After fine-tuning, the network could generate new molecular structures as novel SARS-CoV-2 main protease inhibitors. Molecular docking exhibited that some generated compounds have the proper affinity to the active site of the protease. Molecular Dynamics simulations explored binding free energies of the compounds over simulation trajectories. In addition, in silico absorption, distribution, metabolism, and excretion studies showed that some novel compounds could be formulated as orally active agents. Based on molecular docking and molecular dynamics simulation studies, compound AADH possessed significant binding affinity and presumably inhibition against the SARS-CoV-2 main protease enzyme. Therefore, the proposed deep learning-based model was capable of generating promising anti-COVID-19 drugs.

Effect of Hepatic Impairment on the Pharmacokinetics of Nirmatrelvir/Ritonavir, the First Oral Protease Inhibitor for the Treatment of COVID-19.

Nirmatrelvir, a novel, potent, orally bioavailable severe acute respiratory syndrome coronavirus 2 main protease inhibitor, coadministered with ritonavir for pharmacokinetic (PK) enhancement is licensed for the treatment of mild to moderate COVID-19 in individuals at increased risk of progression to severe disease. Cytochrome P450 3A4 is the primary metabolic enzyme responsible for nirmatrelvir metabolism; however, when cytochrome P450 3A4 is inhibited by ritonavir, nirmatrelvir is primarily excreted, unchanged, in urine. Because of intended use of nirmatrelvir among individuals with hepatic impairment, this Phase 1 study (NCT05005312) evaluated the effects of hepatic impairment on nirmatrelvir PK parameters to assess the potential need for any dose adjustments in this population. Participants with normal hepatic function or moderate hepatic impairment (n = 8 each) were administered a single 100-mg nirmatrelvir dose, with 100 mg of ritonavir administered 12 hours before, together with, and 12 and 24 hours after nirmatrelvir. Nirmatrelvir median plasma concentrations and systemic exposure measured by area under the plasma concentration-time curve from time zero extrapolated to infinite time and maximum observed plasma concentration values were comparable in both groups. Nirmatrelvir/ritonavir had an acceptable safety profile in both groups, and no clinically significant changes in laboratory measurements, vital signs, or electrocardiogram assessments were observed. Based on these results, no dose adjustment is deemed necessary in patients with moderate hepatic impairment and, by extension, in patients with mild hepatic impairment.

Cardiovascular challenges in the era of antiretroviral therapy for AIDS/ HIV: A comprehensive review of research advancements, pathophysiological insights, and future directions.

Cardiovascular disease, particularly coronary heart disease, is becoming more common among those living with HIV. Individuals with HIV face an increased susceptibility to myocardial infarction, also known as a heart attack, as compared to the general population in developed countries. This heightened risk can be attributed mainly to the presence of effective antiretroviral drugs and the resulting longer lifespan. Some cardiac issues linked to non-antiretroviral medications, including myocarditis, endocarditis, cardiomyopathy with dilation, pulmonary hypertension, and oedema of the heart, may affect those not undergoing highly active antiretroviral therapy (ART). Impaired immune function and systemic inflammation are significant contributors to this phenomenon after initiating highly aggressive antiretroviral treatment ART. It is becoming more challenging to determine the best course of treatment for HIV-associated cardiomyopathy due to new research suggesting that protease inhibitors might have a negative impact on the development of HF. Currently, the primary focus of research on ART medications is centered on the cardiovascular adverse effects of nucleoside reverse transcriptase inhibitors and protease inhibitors. This review paper thoroughly evaluates the advancements achieved in cardiovascular disease research and explores the potential implications for prospects. Additionally, it considers the field's future prospects while examining how ART might be altered and its clinical applications.

Developing a SARS-CoV-2 main protease binding prediction random forest model for drug repurposing for COVID-19 treatment.

The coronavirus disease 2019 (COVID-19) global pandemic resulted in millions of people becoming infected with the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus and close to seven million deaths worldwide. It is essential to further explore and design effective COVID-19 treatment drugs that target the main protease of SARS-CoV-2, a major target for COVID-19 drugs. In this study, machine learning was applied for predicting the SARS-CoV-2 main protease binding of Food and Drug Administration (FDA)-approved drugs to assist in the identification of potential repurposing candidates for COVID-19 treatment. Ligands bound to the SARS-CoV-2 main protease in the Protein Data Bank and compounds experimentally tested in SARS-CoV-2 main protease binding assays in the literature were curated. These chemicals were divided into training (516 chemicals) and testing (360 chemicals) data sets. To identify SARS-CoV-2 main protease binders as potential candidates for repurposing to treat COVID-19, 1188 FDA-approved drugs from the Liver Toxicity Knowledge Base were obtained. A random forest algorithm was used for constructing predictive models based on molecular descriptors calculated using Mold2 software. Model performance was evaluated using 100 iterations of fivefold cross-validations which resulted in 78.8% balanced accuracy. The random forest model that was constructed from the whole training dataset was used to predict SARS-CoV-2 main protease binding on the testing set and the FDA-approved drugs. Model applicability domain and prediction confidence on drugs predicted as the main protease binders discovered 10 FDA-approved drugs as potential candidates for repurposing to treat COVID-19. Our results demonstrate that machine learning is an efficient method for drug repurposing and, thus, may accelerate drug development targeting SARS-CoV-2.

Design, Synthesis, and Biological Evaluation of Trisubstituted Piperazine Derivatives as Noncovalent Severe Acute Respiratory Syndrome Coronavirus 2 Main Protease Inhibitors with Improved Antiviral Activity and Favorable Druggability.

The ongoing transmission of SARS-CoV-2 necessitates the development of additional potent antiviral agents capable of combating the current highly infectious variants and future coronaviruses. Here, we present the discovery of potent nonpeptide main protease (Mpro) inhibitors with prominent antiviral activity and improved pharmacokinetic properties. Three series of 1,2,4-trisubstituted piperazine derivatives were designed and synthesized, and the optimal GC-78-HCl demonstrated high enzyme-inhibitory potency (IC50 = 0.19 µM) and exhibited excellent antiviral activity (EC50 = 0.40 µM), reaching the same level as Nirmatrelvir (EC50 = 0.38 µM). Additionally, GC-78-HCl displayed potent antiviral activities against various SARS-CoV-2 variants as well as HCoV-OC43 and HCoV-229E, indicating its potential broad-spectrum anticoronaviral activity. Notably, the pharmacokinetic properties of GC-78-HCl were somewhat enhanced compared to those of the lead compound. Furthermore, the cocrystal and molecular docking elucidated the mechanism of action. In conclusion, we discovered a novel nonpeptidic Mpro inhibitor with promising antiviral activity and a favorable pharmacokinetic profile.

Metabolomic profiling of preterm birth in pregnant women living with HIV.

BACKGROUND: Preterm birth is a leading cause of death in children under the age of five. The risk of preterm birth is increased by maternal HIV infection as well as by certain antiretroviral regimens, leading to a disproportionate burden on low- and medium-income settings where HIV is most prevalent. Despite decades of research, the mechanisms underlying spontaneous preterm birth, particularly in resource limited areas with high HIV infection rates, are still poorly understood and accurate prediction and therapeutic intervention remain elusive. OBJECTIVES: Metabolomics was utilized to identify profiles of preterm birth among pregnant women living with HIV on two different antiretroviral therapy (ART) regimens. METHODS: This pilot study comprised 100 mother-infant dyads prior to antiretroviral initiation, on zidovudine monotherapy or on protease inhibitor-based antiretroviral therapy. Pregnancies that resulted in preterm births were matched 1:1 with controls by gestational age at time of sample collection. Maternal plasma and blood spots at 23-35 weeks gestation and infant dried blood spots at birth, were assayed using an untargeted metabolomics method. Linear regression and random forests classification models were used to identify shared and treatment-specific markers of preterm birth. RESULTS: Classification models for preterm birth achieved accuracies of 95.5%, 95.7%, and 80.7% in the untreated, zidovudine monotherapy, and protease inhibitor-based treatment groups, respectively. Urate, methionine sulfone, cortisone, and 17α-hydroxypregnanolone glucuronide were identified as shared markers of preterm birth. Other compounds including hippurate and N-acetyl-1-methylhistidine were found to be significantly altered in a treatment-specific context. CONCLUSION: This study identified previously known as well as novel metabolomic features of preterm birth in pregnant women living with HIV. Validation of these models in a larger, independent cohort is necessary to ascertain whether they can be utilized to predict preterm birth during a stage of gestation that allows for therapeutic intervention or more effective resource allocation.

Structure-Based Lead Optimization of Enterovirus D68 2A Protease Inhibitors.

Enterovirus D68 (EV-D68) virus is a nonpolio enterovirus that typically causes respiratory illness and, in severe cases, can lead to paralysis and death in children. There is currently no vaccine or antiviral for EV-D68. We previously discovered the viral 2A protease (2Apro) as a viable antiviral drug target and identified telaprevir as a 2Apro inhibitor. 2Apro is a viral cysteine protease that cleaves the viral VP1-2A polyprotein junction. In this study, we report the X-ray crystal structures of EV-D68 2Apro, wild-type, and the C107A mutant and the structure-based lead optimization of telaprevir. Guided by the X-ray crystal structure, we predicted the binding pose of telaprevir in 2Apro using molecular dynamics simulations. We then utilized this model to inform structure-based optimization of the telaprevir's reactive warhead and P1-P4 substitutions. These efforts led to the discovery of 2Apro inhibitors with improved antiviral activity than telaprevir. These compounds represent promising lead compounds for further development as EV-D68 antivirals.

Structure-based development and preclinical evaluation of the SARS-CoV-2 3C-like protease inhibitor simnotrelvir.

The persistent pandemic of coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and its variants accentuates the great demand for developing effective therapeutic agents. Here, we report the development of an orally bioavailable SARS-CoV-2 3C-like protease (3CLpro) inhibitor, namely simnotrelvir, and its preclinical evaluation, which lay the foundation for clinical trials studies as well as the conditional approval of simnotrelvir in combination with ritonavir for the treatment of COVID-19. The structure-based optimization of boceprevir, an approved HCV protease inhibitor, leads to identification of simnotrelvir that covalently inhibits SARS-CoV-2 3CLpro with an enthalpy-driven thermodynamic binding signature. Multiple enzymatic assays reveal that simnotrelvir is a potent pan-CoV 3CLpro inhibitor but has high selectivity. It effectively blocks replications of SARS-CoV-2 variants in cell-based assays and exhibits good pharmacokinetic and safety profiles in male and female rats and monkeys, leading to robust oral efficacy in a male mouse model of SARS-CoV-2 Delta infection in which it not only significantly reduces lung viral loads but also eliminates the virus from brains. The discovery of simnotrelvir thereby highlights the utility of structure-based development of marked protease inhibitors for providing a small molecule therapeutic effectively combatting human coronaviruses.

No role for protease inhibitors as a mitigation strategy for postpancreatectomy acute pancreatitis (PPAP): Propensity score matching analysis.

BACKGROUND: While the use of protease inhibitor gabexate mesylate (GM) is still controversial in acute pancreatitis, it has never been tested for postpancreatectomy acute pancreatitis (PPAP). This study aims to assess the impact of GM on postoperative serum hyperamylasaemia (POH) or PPAP after pancreatoduodenectomy (PD). METHODS: Consecutive patients developing POH after PD between 2016 and 2021 were included. According to GM administration, patients were divided into GM-treated and control (CTR) groups. GM was administered from postoperative day 1-3 in POH patients who underwent surgery before 2017. A 2:1 propensity matching was used to minimize the risk of bias. RESULTS: Overall, 264 patients with POH were stratified in the GM (59 patients) and CTR (104 patients) cohorts, which showed balanced baseline characteristics after matching. No difference in postoperative complications was observed between the groups (all p > 0.05), except for PPAP occurrence, which was significantly higher in the GM group (37% vs. 22%, p = 0.037). A total of 45 patients (28%) evolved to PPAP. Comparing PPAP patients in the GM and CTR groups, no significant differences in POPF, relaparotomy, and mortality (all p > 0.09) were found. No difference in intravenous crystalloid administration was found in patients with PPAP, whether or not they developed major complications or pancreatic fistula (p > 0.05) CONCLUSION: Protease inhibitor seems ineffective in preventing a PPAP after PD once a POH has occurred. Further studies are needed to achieve benchmarks for treating PPAP and identify mitigation strategies to prevent the evolution of POH into additional morbidity.

Kunitz-type protease inhibitor TFPI2 remodels stemness and immunosuppressive tumor microenvironment in glioblastoma.

Glioblastoma (GBM) tumors consist of multiple cell populations, including self-renewing glioblastoma stem cells (GSCs) and immunosuppressive microglia. Here we identified Kunitz-type protease inhibitor TFPI2 as a critical factor connecting these cell populations and their associated GBM hallmarks of stemness and immunosuppression. TFPI2 promotes GSC self-renewal and tumor growth via activation of the c-Jun N-terminal kinase-signal transducer and activator of transcription (STAT)3 pathway. Secreted TFPI2 interacts with its functional receptor CD51 on microglia to trigger the infiltration and immunosuppressive polarization of microglia through activation of STAT6 signaling. Inhibition of the TFPI2-CD51-STAT6 signaling axis activates T cells and synergizes with anti-PD1 therapy in GBM mouse models. In human GBM, TFPI2 correlates positively with stemness, microglia abundance, immunosuppression and poor prognosis. Our study identifies a function for TFPI2 and supports therapeutic targeting of TFPI2 as an effective strategy for GBM.

Use of integrase inhibitors vs protease inhibitors is associated with improved HIV viral suppression.

BACKGROUND: Current guidelines for antiretroviral therapy in pregnancy include the use of a dual-nucleoside reverse transcriptase inhibitor with either an integrase strand transfer inhibitor or a ritonavir-boosted protease inhibitor, although there is no designation of which is the preferred option. OBJECTIVE: This study aimed to compare viral suppression at delivery among patients on dual-nucleoside reverse transcriptase inhibitors combined with either an integrase strand transfer inhibitor or a protease inhibitor. A hypothesis was made that the incidence of viral suppression is higher with the use of a dual-nucleoside reverse transcriptase inhibitor backbone combined with an integrase strand transfer inhibitor than with the use of a dual-nucleoside reverse transcriptase inhibitor backbone combined with a protease inhibitor. STUDY DESIGN: This study was an observational study of pregnant patients living with HIV who received prenatal care and delivered after 20 weeks of gestation at an urban safety net hospital. All pregnant patients with HIV were referred to a centralized clinic for HIV counseling, medication management, and prenatal care. Antiretroviral therapy was continued or initiated according to protocols based on national guidance. Among patients on a dual-nucleoside reverse transcriptase inhibitor backbone combined with integrase strand transfer inhibitor vs protease inhibitor at delivery, we compared the demographics and HIV disease characteristics, including year of diagnosis, viral load, and antiretroviral therapy class. The outcome of interest was viral suppression at delivery, defined as a viral load of <50 copies/mL. RESULTS: From January 2011 to December 2021, 604 patients on dual-nucleoside reverse transcriptase inhibitor met the inclusion criteria, including 411 patients (68%) on protease inhibitor and 193 patients (32%) on integrase strand transfer inhibitor at delivery. Demographic distribution was similar, and prenatal care was initiated at 12 weeks of gestation. Among the integrase strand transfer inhibitor group, 101 (17%) were on antiretroviral therapy at initiation of prenatal care compared with 169 (28%) in the protease inhibitor group. At delivery, the frequency of viral load suppression was higher among those on an integrase strand transfer inhibitor (147/193 [76%]) than among those on a protease inhibitor (275/411 [67%]) (odds ratio, 1.59; 95% confidence interval, 1.08-2.33). Among those with a detectable virus, quantitative viral load was not different. During the study period, the use of a protease inhibitor decreased, whereas the use of an integrase strand transfer inhibitor increased. CONCLUSION: Among pregnant patients living with HIV, viral suppression was more common among those on a dual-nucleoside reverse transcriptase inhibitor backbone combined with integrase strand transfer inhibitor than among those on a dual-nucleoside reverse transcriptase inhibitor backbone protease inhibitor at delivery. Our results support the use of dual-nucleoside reverse transcriptase inhibitor with integrase strand transfer inhibitor as a first-line antiretroviral therapy regimen in pregnancy.

Successful Multidrug-Resistant Tuberculosis Treatment Without HIV Viral Suppression: A Missed Opportunity.

BACKGROUND: Coinfection with multidrug-resistant tuberculosis (MDR-TB) and HIV is common, but few published studies examine how undergoing MDR-TB treatment affects HIV disease indicators. METHODS: Using data from a nested, retrospective cohort of people with HIV (PWH) and successful MDR-TB treatment outcomes, we built multivariable regression models to explore correlates of HIV viral suppression at MDR-TB treatment completion. RESULTS: Among 531 PWH successfully treated for MDR-TB, mean age was 37.4 years (SD 10.2, interquartile range 30-43), 270 (50.8%) were male, 395 (74.4%) were virally suppressed at MDR-TB outcome, and 259 (48.8%) took bedaquiline. Older age (adjusted odds ratio [aOR] 1.04, 95% confidence interval [CI]: 1.01 to 1.06) increased odds of viral suppression, while having a prior TB episode (aOR 0.45, 95% CI: 0.31 to 0.64), having a detectable viral load at MDR-TB treatment initiation (aOR 0.17, 95% CI: 0.09 to 0.30), living in a township (aOR 0.49, 95% CI: 0.28 to 0.87), and being changed from efavirenz-based antiretroviral therapy (ART) to a protease inhibitor due to bedaquiline usage (aOR 0.19, 95% CI: 0.04 to 0.82) or not having an ART change while on bedaquiline (aOR 0.29, 95% CI: 0.11 to 0.75) lowered odds of viral suppression. Changing from efavirenz to nevirapine due to bedaquiline usage did not significantly affect odds of viral suppression (aOR 0.41, 95% CI: 0.16 to 1.04). CONCLUSIONS: Increased pill burden and adverse treatment effects did not significantly affect HIV viral suppression while switching ART to a protease inhibitor to accommodate bedaquiline or not changing ART while taking bedaquiline did, suggesting that PWH and MDR-TB may benefit from additional support if they must switch ART.

Conventional Understanding of SARS-CoV-2 Mpro and Common Strategies for Developing Its Inhibitors.

The Coronavirus Disease 2019 (COVID-19) pandemic has brought a widespread influence on the world, especially in the face of sudden coronavirus infections, and there is still an urgent need for specific small molecule therapies to cope with possible future pandemics. The pathogen responsible for this pandemic is Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), and understanding its structure and lifecycle is beneficial for designing specific drugs of treatment for COVID-19. The main protease (Mpro ) which has conservative and specific advantages is essential for viral replication and transcription. It is regarded as one of the most potential targets for anti-SARS-CoV-2 drug development. This review introduces the popular knowledge of SARS-CoV-2 Mpro in drug development and lists a series of design principles and relevant activities of advanced Mpro inhibitors, hoping to provide some new directions and ideas for researchers.

Weight gain following switch to integrase inhibitors from non-nucleoside reverse transcriptase or protease inhibitors in people living with HIV in the United States: analyses of electronic medical records and prescription claims.

OBJECTIVES: Real-world data evaluating weight changes in people living with HIV (PLWH) following switch to integrase strand transfer inhibitor (INSTI), specifically bictegravir (BIC), are limited. This retrospective cohort study analyzed weight changes upon switching to INSTI from non-nucleoside reverse transcriptase inhibitor (NNRTI) or protease inhibitor (PI) in treatment-experienced PLWH. METHODS: Adult PLWH (≥18 years) treated with NNRTI or PI (non-switch cohorts) and those switching to INSTI (switch cohorts) between January 1, 2014 and August 31, 2019 were identified using IQVIA's Ambulatory Electronic Medical Records linked to a prescription drug claims database. The associations of switching to INSTI and individual INSTI agents with having ≥5% weight gain at 12 months of follow-up were evaluated, adjusting for demographics and baseline clinical characteristics. RESULTS: At 12 months of follow-up, PLWH in the NNRTI-INSTI switch cohort (n = 508) were more likely to have ≥5% weight gain over 12 months compared to the NNRTI non-switch cohort (n = 614; odds ratio, OR [95% CI], 1.7 [1.2-2.4]). Switching from NNRTI to dolutegravir (DTG: OR [95% CI], 2.1 [1.4-3.0]) or BIC (2.0 [1.0-4.2]) resulted in significantly higher odds of ≥5% weight gain. PI-INSTI switch (n = 295) and non-switch (n = 228) cohorts had similar proportions of PLWH with ≥5% (21.1-23.4%) or ≥10% (7.8-7.9%) weight gain, and no significant association was found between switching from PI to INSTI and weight gain. CONCLUSION: Weight gain and related metabolic health of PLWH switching from NNRTI to DTG or BIC should be closely monitored by clinicians. Further research is needed to assess other metabolic outcomes in PLWH remaining on PI and those who switch from PI to INSTI.