Coronavirus Antiviral Research Database (CoV-RDB): An Online Database Designed to Facilitate Comparisons between Candidate Anti-Coronavirus Compounds.

BACKGROUND: To prioritize the development of antiviral compounds, it is necessary to compare their relative preclinical activity and clinical efficacy. METHODS: We reviewed in vitro, animal model, and clinical studies of candidate anti-coronavirus compounds and placed extracted data in an online relational database. RESULTS: As of August 2020, the Coronavirus Antiviral Research Database (CoV-RDB; covdb.stanford.edu) contained over 2800 cell culture, entry assay, and biochemical experiments, 259 animal model studies, and 73 clinical studies from over 400 published papers. SARS-CoV-2, SARS-CoV, and MERS-CoV account for 85% of the data. Approximately 75% of experiments involved compounds with known or likely mechanisms of action, including monoclonal antibodies and receptor binding inhibitors (21%), viral protease inhibitors (17%), miscellaneous host-acting inhibitors (10%), polymerase inhibitors (9%), interferons (7%), fusion inhibitors (5%), and host protease inhibitors (5%). Of 975 compounds with known or likely mechanism, 135 (14%) are licensed in the U.S. for other indications, 197 (20%) are licensed outside the U.S. or are in human trials, and 595 (61%) are pre-clinical investigational compounds. CONCLUSION: CoV-RDB facilitates comparisons between different candidate antiviral compounds, thereby helping scientists, clinical investigators, public health officials, and funding agencies prioritize the most promising compounds and repurposed drugs for further development.

Genetic Variability of HIV-1 for Drug Resistance Assay Development.

A hybridization-based point-of-care (POC) assay for HIV-1 drug resistance would be useful in low- and middle-income countries (LMICs) where resistance testing is not routinely available. The major obstacle in developing such an assay is the extreme genetic variability of HIV-1. We analyzed 27,203 reverse transcriptase (RT) sequences from the Stanford HIV Drug Resistance Database originating from six LMIC regions. We characterized the variability in a 27-nucleotide window surrounding six clinically important drug resistance mutations (DRMs) at positions 65, 103, 106, 181, 184, and 190. The number of distinct codons at each DRM position ranged from four at position 184 to 11 at position 190. Depending on the mutation, between 11 and 15 of the 24 flanking nucleotide positions were variable. Nonetheless, most flanking sequences differed from a core set of 10 flanking sequences by just one or two nucleotides. Flanking sequence variability was also lower in each LMIC region compared with overall variability in all regions. We also describe an online program that we developed to perform similar analyses for mutations at any position in RT, protease, or integrase.

The efficacy of an anti-CD4 monoclonal antibody for HIV-1 treatment.

The availability of 24 antiretroviral (ARV) drugs within six distinct drug classes has transformed HIV-1 infection (AIDS) into a treatable chronic disease. However, the ability of HIV-1 to develop resistance to multiple classes continues to present challenges to the treatment of many ARV treatment-experienced patients. In this case report, we describe the response to ibalizumab, an investigational CD4-binding monoclonal antibody (mAb), in a patient with advanced immunodeficiency and high-level five-class antiretroviral resistance. After starting an ibalizumab-based salvage regimen, the patient had an approximately 4.0 log(10) reduction in viral load. An inadvertently missed infusion at week 32 led to the rapid loss of virologic response and decreased susceptibility to the remainder of the patient's salvage therapy regimen. Following the reinstitution of ibalizumab, phenotypic and genotypic resistance to ibalizumab was detected. Nonetheless, plasma HIV-1 RNA levels stabilized at ∼2.0 log(10) copies/ml below pre-ibalizumab levels. Continued ARV drug development may yield additional clinical and public health benefits. This report illustrates the promise of mAbs for HIV-1 therapy in highly treatment-experienced patients. Therapeutic mAbs may also have a role in pre-exposure prophylaxis in high-risk uninfected populations and may facilitate directly observed therapy (DOT) if two or more synergistic long acting agents become available.

A classification model for G-to-A hypermutation in hepatitis B virus ultra-deep pyrosequencing reads.

MOTIVATION: G → A hypermutation is an innate antiviral defense mechanism, mediated by host enzymes, which leads to the mutational impairment of viruses. Sensitive and specific identification of host-mediated G → A hypermutation is a novel sequence analysis challenge, particularly for viral deep sequencing studies. For example, two of the most common hepatitis B virus (HBV) reverse transcriptase (RT) drug-resistance mutations, A181T and M204I, arise from G → A changes and are routinely detected as low-abundance variants in nearly all HBV deep sequencing samples. RESULTS: We developed a classification model using measures of G → A excess and predicted indicators of lethal mutation and applied this model to 325 920 unique deep sequencing reads from plasma virus samples from 45 drug treatment-naïve HBV-infected individuals. The 2.9% of sequence reads that were classified as hypermutated by our model included most of the reads with A181T and/or M204I, indicating the usefulness of this model for distinguishing viral adaptive changes from host-mediated viral editing. AVAILABILITY: Source code and sequence data are available at http://hivdb.stanford.edu/pages/resources.html. CONTACT: ereuman@stanfordalumni.org SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Consensus drug resistance mutations for epidemiological surveillance: basic principles and potential controversies.

Programmes that monitor local, national and regional levels of transmitted HIV-1 drug resistance inform treatment guidelines and provide feedback on the success of HIV-1 treatment and prevention programmes. The World Health Organization (WHO) has established a global programme for genotypic surveillance of HIV-1 drug resistance and has recommended the adoption of a consensus definition of genotypic drug resistance. Such a definition is necessary to accurately compare transmitted drug resistance rates across geographical regions and time periods. HIV-1 diversity and the large number of mutations associated with antiretroviral drug resistance complicate the development of a consensus definition for genotypic drug resistance. This paper reviews the data that must be considered to determine which of the many HIV-1 drug resistance mutations are likely to be both sensitive and specific indicators of transmitted drug resistance. The process used to create a previously published list of drug resistance mutations for HIV-1 surveillance is reviewed and alternative approaches to this process are discussed.

Comparison of the precision and sensitivity of the Antivirogram and PhenoSense HIV drug susceptibility assays.

OBJECTIVE: Although 2 widely used susceptibility assays have been developed, their precision and sensitivity have not been assessed. DESIGN AND METHODS: To assess the precision of the Antivirogram and PhenoSense assays, we examined susceptibility results of HIV-1 isolates lacking drug resistance mutations and containing matching patterns of drug resistance mutations. To assess sensitivity, we determined for each assay the proportion of isolates with common patterns of matching drug resistance mutations having reductions in susceptibility greater than those in isolates without drug resistance mutations. RESULTS: We analyzed protease inhibitor (PI) susceptibility results obtained by the Antivirogram assay for 293 isolates and by the PhenoSense assay for 300 isolates. We analyzed reverse transcriptase (RT) inhibitor susceptibility results obtained by the Antivirogram assay for 202 isolates and by the PhenoSense assay for 126 isolates. For wild-type and mutant isolates, the median absolute deviance of the fold resistance of nucleoside RT inhibitor susceptibility results was significantly lower for the PhenoSense assay than for the Antivirogram assay. The PhenoSense assay was also significantly more likely than the Antivirogram assay to detect resistance to abacavir, didanosine, and stavudine in isolates with the common drug resistance mutations M41L, M184V, and T215Y (+/-L210W). We found no significant differences between the 2 assays for detecting PI and nonnucleoside RT inhibitor resistance. CONCLUSION: The PhenoSense assay is more precise than the Antivirogram assay and superior at detecting resistance to abacavir, didanosine, and stavudine.

Subtle decreases in stavudine phenotypic susceptibility predict poor virologic response to stavudine monotherapy in zidovudine-experienced patients.

To identify the level of phenotypic susceptibility for stavudine (d4T) that is associated with a diminished virologic response to d4T therapy, phenotyping was performed on archived baseline HIV isolates from 26 subjects who received d4T monotherapy in AIDS Clinical Trials Group (ACTG) 302 who had received >3 years of prior zidovudine (ZDV) monotherapy. Seven of 26 subjects achieved a virologic response of >0.3-log10 copies/mL reduction in plasma HIV RNA after 8 weeks of d4T. Responders had lower fold changes in susceptibility to d4T (1.0 vs. 1.6, p=.003), lower baseline viral loads (4.26 vs. 4.74 log10 copies/mL, p=.004), and fewer thymidine analog mutations (TAMS) (1 vs. 2, p=.059). Lower baseline d4T fold change in susceptibility predicted greater reductions in HIV RNA from baseline to week 8 after adjusting for baseline HIV RNA, ZDV fold change in susceptibility, and number of TAMS. Using the same phenotypic assay, drug susceptibility among 240 antiretroviral-naive patients found all HIV isolates to have d4T susceptibility