Repurposing of drugs for combined treatment of COVID-19 cytokine storm using machine learning

Severe acute respiratory syndrome coronavirus 2 (SARS‑CoV‑2) induced cytokine storm is the major cause of COVID-19 related deaths. Patients have been treated with drugs that work by inhibiting a specific protein partly responsible for the cytokines production. This approach provided very limited success, since there are multiple proteins involved in the complex cell signaling disease mechanisms. We targeted five proteins: Angiotensin II receptor type 1 (AT1R), A disintegrin and metalloprotease 17 (ADAM17), Nuclear Factor‑Kappa B (NF‑κB), Janus kinase 1 (JAK1) and Signal Transducer and Activator of Transcription 3 (STAT3), which are involved in the SARS‑CoV‑2 induced cytokine storm pathway. We developed machine-learning (ML) models for these five proteins, using known active inhibitors. After developing the model for each of these proteins, FDA-approved drugs were screened to find novel therapeutics for COVID‑19. We identified twenty drugs that are active for four proteins with predicted scores greater than 0.8 and eight drugs active for all five proteins with predicted scores over 0.85. Mitomycin C is the most active drug across all five proteins with an average prediction score of 0.886. For further validation of these results, we used the PyRx software to conduct protein-ligand docking experiments and calculated the binding affinity. The docking results support findings by the ML model. This research study predicted that several drugs can target multiple proteins simultaneously in cytokine storm-related pathway. These may be useful drugs to treat patients because these therapies can fight cytokine storm caused by the virus at multiple points of inhibition, leading to synergistically effective treatments.

The SGLT2-inhibitor dapagliflozin improves neutropenia and neutrophil dysfunction in a mouse model of the inherited metabolic disorder GSDIb

Glycogen Storage Disease type 1b (GSDIb) is a genetic disorder with long term severe complications. Accumulation of the glucose analog 1,5-anhydroglucitol-6-phosphate (1,5AG6P) in neutrophils inhibits the phosphorylation of glucose in these cells, causing neutropenia and neutrophil dysfunctions. This condition leads to serious infections and inflammatory bowel disease (IBD) in GSDIb patients. We show here that dapagliflozin, an inhibitor of the renal sodium-glucose co-transporter-2 (SGLT2), improves neutrophil function in an inducible mouse model of GSDIb by reducing 1,5AG6P accumulation in myeloid cells.

Site-specific PEGylation of lidamycin and its antitumor activity

In this study, N-terminal site-specific mono-PEGylation of the recombinant lidamycin apoprotein (rLDP) of lidamycin (LDM) was prepared using a polyethyleneglycol (PEG) derivative (M_w 20 kDa) through a reactive terminal aldehyde group under weak acidic conditions (pH 5.5). The biochemical properties of mPEG-rLDP-AE, an enediyne-integrated conjugate, were analyzed by SDS-PAGE, RP-HPLC, SEC-HPLC and MALDI-TOF. Meanwhile, in vitro and in vivo antitumor activity of mPEG-rLDP-AE was evaluated by MTT assays and in xenograft model. The results indicated that mPEG-rLDP-AE showed significant antitumor activity both in vitro and in vivo. After PEGylation, mPEG-rLDP still retained the binding capability to the enediyne AE and presented the physicochemical characteristics similar to that of native LDP. It is of interest that the PEGylation did not diminish the antitumor efficacy of LDM, implying the possibility that this derivative may function as a payload to deliver novel tumor-targeted drugs.

Chemokine and lymph node homing receptor expression on pDC vary by graft source

A randomized clinical trial of BM vs. blood stem cell transplants from unrelated donors showed that more plasmacytoid dendritic cells (pDCs) in BM grafts was associated with better post-transplant survival. Here, we describe differences in homing-receptor expression on pDC to explain observed differences following BM vs. blood stem cell transplantation.

Sustained virological response rates to antiviral therapy in genotype 1 and 3 chronic hepatitis C patients: a study from north India

BACKGROUND

In India, both genotype 3 and 1 are predominant genotypes in patients with chronic hepatitis C (CHC). However, there is scanty data on sustained viral response (SVR) rate with conventionally recommended dual therapy with PEG-IFN and ribavirin.

METHODS

In this retrospective study, consecutive patients of CHC of genotypes 1 and 3, attending the single unit of Gastroenterology of our hospital, who received PEG-IFN and ribavirin therapy, were included. Patients who had co-infection with HIV or HBV were excluded.

RESULTS

A total of 114 patients were included in the study median age 44 (15-72) years, 79% males. Most common presentation was with chronic hepatitis, while 10 (9%) patients had compensated cirrhosis. Nine (8%) patients had associated diabetes, 16 (14%) patients gave history of significant alcohol abuse. The median baseline HCV RNA level was 3.0 × 10(5) (1.7 × 10(3)-1.8 × 10(7)) IU/mL. The most common genotype was 3 (75%) followed by genotype 1 (25%). 70% patients received PegIFN-α2a (median dose 180 MIU/wk) and 30% patients received PegIFN-α2b (median dose 80 MIU/wk). The median ribavirin dose was 800 (range 800-1200) mg. SVR in genotype 1 was 64% (18/28) while SVR in genotype 3 was 73% (63/86). The factors predicting SVR on univariate analysis were a lower baseline HCV RNA level (less than 3.0 × 10(5)), higher hemoglobin level > 11.8 g/dl, and achievement of rapid virological response (RVR), early virological response (EVR) and end of treatment response (ETR). In multivariate analysis the only baseline factor found independently correlating with SVR was low HCV RNA level (<3.0 × 10(5) IU/mL) (P = 0.003).

CONCLUSION

In north India, HCV genotype 3 has a SVR rate of 73%, which is comparable to genotype 1 with SVR rate of 64% when treated with PEG-IFN and ribavirin therapy. A baseline HCV RNA level lower than 3.0 × 10(5) best predicts SVR in addition to achievement of RVR, EVR or ETR.