MHC2AffyPred: A machine-learning approach to estimate affinity of MHC class II peptides based on structural interaction fingerprints.

Understanding how MHC class II (MHC-II) binding peptides with differing lengths exhibit specific interaction at the core and extended sites within the large MHC-II pocket is a very important aspect of immunological research for designing peptides. Certain efforts were made to generate peptide conformations amenable for MHC-II binding and calculate the binding energy of such complex formation but not directed toward developing a relationship between the peptide conformation in MHC-II structures and the binding affinity (BA) (IC50 ). We present here a machine-learning approach to calculate the BA of the peptides within the MHC-II pocket for HLA-DRA1, HLA-DRB1, HLA-DP, and HLA-DQ allotypes. Instead of generating ensembles of peptide conformations conventionally, the biased mode of conformations was created by considering the peptides in the crystal structures of pMHC-II complexes as the templates, followed by site-directed peptide docking. The structural interaction fingerprints generated from such docked pMHC-II structures along with the Moran autocorrelation descriptors were trained using a random forest regressor specific to each MHC-II peptide lengths (9-19). The entire workflow is automated using Linux shell and Perl scripts to promote the utilization of MHC2AffyPred program to any characterized MHC-II allotypes and is made for free access at https://github.com/SiddhiJani/MHC2AffyPred. The MHC2AffyPred attained better performance (correlation coefficient [CC] of .612-.898) than MHCII3D (.03-.594) and NetMHCIIpan-3.2 (.289-.692) programs in the HLA-DRA1, HLA-DRB1 types. Similarly, the MHC2AffyPred program achieved CC between .91 and .98 for HLA-DP and HLA-DQ peptides (13-mer to 17-mer). Further, a case study on MHC-II binding 15-mer peptides of severe acute respiratory syndrome coronavirus-2 showed very close competency in computing the IC50 values compared to the sequence-based NetMHCIIpan v3.2 and v4.0 programs with a correlation of .998 and .570, respectively.

Unveiling the nature's fruit basket to computationally identify Citrus sinensis csi-mir169-3p as a probable plant miRNA against Reference and Omicron SARS-CoV-2 genome.

The fundamental role of microRNAs (miRNAs) has long been associated with regulation of gene expression during transcription and post transcription of mRNA's 3'UTR by the RNA interference mechanism. Also, the process of how miRNAs tend to induce mRNA degradation has been predominantly studied in many infectious diseases. In this article, we would like to discuss the interaction of dietary plant miRNAs derived from fresh fruits against the viral genome of the causative agent of COVID-19, specifically targeting the 3'UTR of SARS-CoV-2 (Severe acute respiratory syndrome coronavirus 2) genome. Expanding the analysis, we have also identified plant miRNAs that interact against the Omicron (B.1.1.529) variant of SARS-CoV-2 across 37 countries/territories throughout the world. This cross-species virus-plant interaction led us to identify the alignment of dietary plant miRNAs found in fruits like Citrus sinensis (Orange), Prunus persica (Peaches), Vitis vinifera (Grapes) and Malus domestica (Apple) onto the viral genomes. In particular, the interaction of C. sinensis miRNA - csi-miR169-3p and SARS-CoV-2 is noteworthy, as the targeted 3'UTR region "CTGCCT" is found conserved amongst all curated 772 Omicron variants across the globe. Hence this site "CTGCCT" and miRNA csi-miR169-3p may become promising therapeutic candidates to induce viral genome silencing. Thereby, this study reveals the mechanistic way of how fruits tend to enact a fight against viruses like SARS-CoV-2 and aid in maintaining a strong immune system of an individual.

Identification of antiviral phytochemicals as a potential SARS-CoV-2 main protease (Mpro) inhibitor using docking and molecular dynamics simulations.

Novel SARS-CoV-2, an etiological factor of Coronavirus disease 2019 (COVID-19), poses a great challenge to the public health care system. Among other druggable targets of SARS-Cov-2, the main protease (Mpro) is regarded as a prominent enzyme target for drug developments owing to its crucial role in virus replication and transcription. We pursued a computational investigation to identify Mpro inhibitors from a compiled library of natural compounds with proven antiviral activities using a hierarchical workflow of molecular docking, ADMET assessment, dynamic simulations and binding free-energy calculations. Five natural compounds, Withanosides V and VI, Racemosides A and B, and Shatavarin IX, obtained better binding affinity and attained stable interactions with Mpro key pocket residues. These intermolecular key interactions were also retained profoundly in the simulation trajectory of 100 ns time scale indicating tight receptor binding. Free energy calculations prioritized Withanosides V and VI as the top candidates that can act as effective SARS-CoV-2 Mpro inhibitors.

Identifying potential human and medicinal plant microRNAs against SARS-CoV-2 3'UTR region: A computational genomics assessment.

The coronavirus disease of 2019 (COVID-19) began as an outbreak and has taken a toll on human lives. The current pandemic requires scientific attention; hence we designed a systematic computational workflow to identify the cellular microRNAs (miRNAs) from human host possessing the capability to target and silence 3'UTR of SARS-CoV-2 genome. Based on this viewpoint, we extended our miRNA search to medicinal plants like Ocimum tenuiflorum, Zingiber officinale and Piper nigrum, which are well-known to possess antiviral properties, and are often consumed raw or as herbal decoctions. Such an approach, that makes use of miRNA of one species to interact and silence genes of another species including viruses is broadly categorized as cross-kingdom interactions. As a part of our genomics study on host-virus-plant interaction, we identified one unique 3'UTR conserved site 'GGAAGAG' amongst 5024 globally submitted SARS-CoV-2 complete genomes, which can be targeted by the human miRNA 'hsa-miR-1236-3p' and by Z. officinale miRNA 'zof-miR2673b'. Additionally, we also predicted that the members of miR477 family commonly found in these three plant genomes possess an inherent potential to silence viral genome RNA and facilitate antiviral defense against SARS-CoV-2 infection. In conclusion, this study reveals a universal site in the SARS-CoV-2 genome that may be crucial for targeted therapeutics to cure COVID-19.