More Like this

1. It takes two to tango: The dance of the permease

   https://doi.org/10.1085/jgp.201912377  

   Kaback, H. Ronald; Guan, Lan (July 2019, The Journal of General Physiology)

   The lactose permease (LacY) of Escherichia coli is the prototype of the major facilitator superfamily, one of the largest families of membrane transport proteins. Structurally, two pseudo-symmetrical six-helix bundles surround a large internal aqueous cavity. Single binding sites for galactoside and H + are positioned at the approximate center of LacY halfway through the membrane at the apex of the internal cavity. These features enable LacY to function by an alternating-access mechanism that can catalyze galactoside/H + symport in either direction across the cytoplasmic membrane. The H + -binding site is fully protonated under physiological conditions, and subsequent sugar binding causes transition of the ternary complex to an occluded intermediate that can open to either side of the membrane. We review the structural and functional evidence that has provided new insight into the mechanism by which LacY achieves active transport against a concentration gradient. 

   more » « less
2. GraphDTI: A robust deep learning predictor of drug-target interactions from multiple heterogeneous data

   https://doi.org/10.1186/s13321-021-00540-0  

   Liu, Guannan; Singha, Manali; Pu, Limeng; Neupane, Prasanga; Feinstein, Joseph; Wu, Hsiao-Chun; Ramanujam, J.; Brylinski, Michal (December 2021, Journal of Cheminformatics)

   Abstract Traditional techniques to identify macromolecular targets for drugs utilize solely the information on a query drug and a putative target. Nonetheless, the mechanisms of action of many drugs depend not only on their binding affinity toward a single protein, but also on the signal transduction through cascades of molecular interactions leading to certain phenotypes. Although using protein-protein interaction networks and drug-perturbed gene expression profiles can facilitate system-level investigations of drug-target interactions, utilizing such large and heterogeneous data poses notable challenges. To improve the state-of-the-art in drug target identification, we developed GraphDTI, a robust machine learning framework integrating the molecular-level information on drugs, proteins, and binding sites with the system-level information on gene expression and protein-protein interactions. In order to properly evaluate the performance of GraphDTI, we compiled a high-quality benchmarking dataset and devised a new cluster-based cross-validation protocol. Encouragingly, GraphDTI not only yields an AUC of 0.996 against the validation dataset, but it also generalizes well to unseen data with an AUC of 0.939, significantly outperforming other predictors. Finally, selected examples of identified drugtarget interactions are validated against the biomedical literature. Numerous applications of GraphDTI include the investigation of drug polypharmacological effects, side effects through offtarget binding, and repositioning opportunities. 

   more » « less
3. BoostMEC: predicting CRISPR-Cas9 cleavage efficiency through boosting models

   https://doi.org/10.1186/s12859-022-04998-z  

   Zarate, Oscar A.; Yang, Yiben; Wang, Xiaozhong; Wang, Ji-Ping (December 2022, BMC Bioinformatics)

   Abstract Background In the CRISPR-Cas9 system, the efficiency of genetic modifications has been found to vary depending on the single guide RNA (sgRNA) used. A variety of sgRNA properties have been found to be predictive of CRISPR cleavage efficiency, including the position-specific sequence composition of sgRNAs, global sgRNA sequence properties, and thermodynamic features. While prevalent existing deep learning-based approaches provide competitive prediction accuracy, a more interpretable model is desirable to help understand how different features may contribute to CRISPR-Cas9 cleavage efficiency. Results We propose a gradient boosting approach, utilizing LightGBM to develop an integrated tool, BoostMEC (Boosting Model for Efficient CRISPR), for the prediction of wild-type CRISPR-Cas9 editing efficiency. We benchmark BoostMEC against 10 popular models on 13 external datasets and show its competitive performance. Conclusions BoostMEC can provide state-of-the-art predictions of CRISPR-Cas9 cleavage efficiency for sgRNA design and selection. Relying on direct and derived sequence features of sgRNA sequences and based on conventional machine learning, BoostMEC maintains an advantage over other state-of-the-art CRISPR efficiency prediction models that are based on deep learning through its ability to produce more interpretable feature insights and predictions. 

   more » « less
4. Exploring Cannabinoids as Potential Inhibitors of SARS-CoV-2 Papain-like Protease: Insights from Computational Analysis and Molecular Dynamics Simulations

   https://doi.org/10.3390/v16060878  

   Holmes, Jamie; Islam, Shahidul M; Milligan, Kimberly A (June 2024, Viruses)

   The emergence of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has triggered a global COVID-19 pandemic, challenging healthcare systems worldwide. Effective therapeutic strategies against this novel coronavirus remain limited, underscoring the urgent need for innovative approaches. The present research investigates the potential of cannabis compounds as therapeutic agents against SARS-CoV-2 through their interaction with the virus’s papain-like protease (PLpro) protein, a crucial element in viral replication and immune evasion. Computational methods, including molecular docking and molecular dynamics (MD) simulations, were employed to screen cannabis compounds against PLpro and analyze their binding mechanisms and interaction patterns. The results showed cannabinoids with binding affinities ranging from −6.1 kcal/mol to −4.6 kcal/mol, forming interactions with PLpro. Notably, Cannabigerolic and Cannabidiolic acids exhibited strong binding contacts with critical residues in PLpro’s active region, indicating their potential as viral replication inhibitors. MD simulations revealed the dynamic behavior of cannabinoid–PLpro complexes, highlighting stable binding conformations and conformational changes over time. These findings shed light on the mechanisms underlying cannabis interaction with SARS-CoV-2 PLpro, aiding in the rational design of antiviral therapies. Future research will focus on experimental validation, optimizing binding affinity and selectivity, and preclinical assessments to develop effective treatments against COVID-19. 

   more » « less
5. Anti-SARS-CoV-2 Activity of Rhamnan Sulfate from Monostroma nitidum

   https://doi.org/10.3390/md19120685  

   Song, Yuefan; He, Peng; Rodrigues, Andre L.; Datta, Payel; Tandon, Ritesh; Bates, John T.; Bierdeman, Michael A.; Chen, Chen; Dordick, Jonathan; Zhang, Fuming; et al (December 2021, Marine Drugs)

   The COVID-19 pandemic is a major human health concern. The pathogen responsible for COVID-19, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), invades its host through the interaction of its spike (S) protein with a host cell receptor, angiotensin-converting enzyme 2 (ACE2). In addition to ACE2, heparan sulfate (HS) on the surface of host cells also plays a significant role as a co-receptor. Our previous studies demonstrated that sulfated glycans, such as heparin and fucoidans, show anti-COVID-19 activities. In the current study, rhamnan sulfate (RS), a polysaccharide with a rhamnose backbone from a green seaweed, Monostroma nitidum, was evaluated for binding to the S-protein from SARS-CoV-2 and inhibition of viral infectivity in vitro. The structural characteristics of RS were investigated by determining its monosaccharide composition and performing two-dimensional nuclear magnetic resonance. RS inhibition of the interaction of heparin, a highly sulfated HS, with the SARS-CoV-2 spike protein (from wild type and different mutant variants) was studied using surface plasmon resonance (SPR). In competitive binding studies, the IC50 of RS against the S-protein receptor binding domain (RBD) binding to immobilized heparin was 1.6 ng/mL, which is much lower than the IC50 for heparin (~750 ng/mL). RS showed stronger inhibition than heparin on the S-protein RBD or pseudoviral particles binding to immobilized heparin. Finally, in an in vitro cell-based assay, RS showed strong antiviral activities against wild type SARS-CoV-2 and the delta variant. 

   more » « less