TSAR, Thermal Shift Analysis in R, identifies endogenous molecules that interact with HIV-1 capsid hexamers
McFadden, W. M.; Gao, X.; Ye, Z.; Wen, X.; Lorson, Z. C.; Zhang, H.; Fahim, J.; Emanuelli, A.; Kirby, K. A.; Sarafianos, S. G.
Show abstract
The thermal shift assay (TSA) is a versatile biophysical technique for studying protein-ligand interactions in vitro. Here, we report a free, open-source software tool, TSAR ("Thermal Shift Analysis in R"), to expedite the analysis of TSA data. The TSAR package incorporates multiple workflows that facilitate TSA analyses, returns publication-ready graphics, and includes an optional graphic user interface. The package is available at https://bioconductor.org/packages/TSAR/. Applying TSAR, we screened two chemical libraries and found multiple molecules that potentially interact in vitro with the capsid protein (CA) of human immunodeficiency virus type 1 (HIV-1). First, a library of vitamins exemplifies the different graphic outputs of TSAR, and we report a change in the 50% melting temperature ({Delta}Tm) for folic acid-treated CA hexamers (CAHEX). Since HIV-1 CAHEX interacts with host-derived acids like inositol hexaphosphate (IP6) or dNTPs, a second library was screened containing 96 organic, acidic metabolites; multiple anionic ligands caused a {Delta}Tm for CAHEX. Subsequent investigation of these interactions includes biolayer interferometry, antiviral activity against pseudotyped HIV-1, and endogenous reverse transcriptase assays that were used to validate and investigate the biological impact of these native ligands that thermally-stabilize CAHEX. One compound hit, gallic acid, exhibited anti-HIV-1 activity as previously reported, and we show interacts with CAHEX as a potentially novel mechanism. Overall, the TSAR package facilitated quick analysis of TSA data from multiple libraries to help identify a biologically relevant hit, gallic acid, as a molecule that can inhibit HIV-1 replication and targets CAHEX. ImportanceThe TSAR package is freely available (AGPL-3) and is designed for both experienced or new R users, having command-line code for handling large and challenging datasets while also including an optional GUI that enables easy use by non-programmers. This is the first TSA analysis program written in R, a free and open-source language; TSAR simplifies TSA analysis while maintaining diverse visualization options for small-to-large libraries and multidimensional analysis. Additionally, we report multiple endogenous metabolites that potentially interact with the HIV-1 capsid protein hexamers (CAHEX) in vitro, including folic acid, gallic acid, and multiple others, primarily from the tricarboxylic acid (TCA) cycle. Various methods validate gallic acid interactions with CAHEX, leading to a novel suggested mechanism of action, and in-line with previous reports, this metabolite has potential for natural-based treatments of HIV-1. Further, we advance the understanding of the potential mechanism(s) for HIV-1 inhibition by gallic acid treatment.
Matching journals
The top 10 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- Development of novel anti-malarial from structurally diverse library of molecules, targeting plant-like Calcium Dependent Protein Kinase 1, a multistage growth regulator of P. falciparum 94%
- Identifying SARS-CoV-2 Antiviral Compounds by Screening for Small Molecule Inhibitors of Nsp3 Papain-like Protease 92%
- Characterisation of RNA guanine-7 methyltransferase (RNMT) using a small molecule approach 92%
Similar papers in this journal
- Inhibiting the copper efflux system in microbes as a novel approach for developing antibiotics 94%
- Automated prediction of site and sequence of protein modification with ATRP initiators 94%
- Deep learning based predictive modeling to screen natural compounds against TNF-alpha for the potential management of Rheumatoid Arthritis: Virtual screening to comprehensive in silico investigation 94%
Similar papers in this journal
- Discovery of inhibitors for bacterial Arr enzymes ADP-ribosylating and inactivating rifamycin antibiotics 91%
- Overcoming Ligand Discovery Challenges: Developing Peptide-Based Tracers for SPSB2 91%
- Rational development of a small-molecule activator of CK1γ2 that decreases C99 and beta-amyloid levels 91%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.