Structure-based virtual screening against multiple Plasmodium falciparum kinases reveals antimalarial compounds

Godara, Priya; Reddy, K. Sony; Sahu, Welka; Naik, Biswajit; Srivastava, Varshita; Das, Rusham; Mahor, Ajay; Kumar, Prateek; Giri, Rajanish; Anirudh, Jivanage; Tak, Harshita; Banavath, Hemanth Naick; Bhatt, Tarun Kumar; Goyal, Amit Kumar; Prusty, Dhaneswar

doi:10.1007/s11030-023-10770-z

Cited by 2 publications

(1 citation statement)

References 80 publications

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“…This suggests that a compound's efficacy may increase with an increase in the number of proteins it targets, assuming the targets are validated. Compounds with multiple targets are more appealing as antimalarial drugs, as they are more likely to be potent, and pathogens are less prone to develop resistance against such molecules due to improbability of generating poly-mutations and the higher fitness cost of associated genetic changes [ 24 , 25 ]. Drug-combination therapies leverage the fact that combined drugs target different pathways and possess various mechanisms of action and resistance [ 10 ].…”

Section: Discussionmentioning

confidence: 99%

Protein target similarity is positive predictor of in vitro antipathogenic activity: a drug repurposing strategy for Plasmodium falciparum

Mogire,

Miruka,

Juma

et al. 2024

J Cheminform

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Drug discovery is an intricate and costly process. Repurposing existing drugs and active compounds offers a viable pathway to develop new therapies for various diseases. By leveraging publicly available biomedical information, it is possible to predict compounds’ activity and identify their potential targets across diverse organisms. In this study, we aimed to assess the antiplasmodial activity of compounds from the Repurposing, Focused Rescue, and Accelerated Medchem (ReFRAME) library using in vitro and bioinformatics approaches. We assessed the in vitro antiplasmodial activity of the compounds using blood-stage and liver-stage drug susceptibility assays. We used protein sequences of known targets of the ReFRAME compounds with high antiplasmodial activity (EC50 < 10 uM) to conduct a protein-pairwise search to identify similar Plasmodium falciparum 3D7 proteins (from PlasmoDB) using NCBI protein BLAST. We further assessed the association between the compounds' in vitro antiplasmodial activity and level of similarity between their known and predicted P. falciparum target proteins using simple linear regression analyses. BLAST analyses revealed 735 P. falciparum proteins that were similar to the 226 known protein targets associated with the ReFRAME compounds. Antiplasmodial activity of the compounds was positively associated with the degree of similarity between the compounds’ known targets and predicted P. falciparum protein targets (percentage identity, E value, and bit score), the number of the predicted P. falciparum targets, and their respective mutagenesis index and fitness scores (R2 between 0.066 and 0.92, P < 0.05). Compounds predicted to target essential P. falciparum proteins or those with a druggability index of 1 showed the highest antiplasmodial activity.

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Section: Discussionmentioning

confidence: 99%

Protein target similarity is positive predictor of in vitro antipathogenic activity: a drug repurposing strategy for Plasmodium falciparum

Mogire,

Miruka,

Juma

et al. 2024

J Cheminform

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CACTI: an in silico chemical analysis tool through the integration of chemogenomic data and clustering analysis

Godinez-Macias,

Winzeler

2024

J Cheminform

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It is well-accepted that knowledge of a small molecule’s target can accelerate optimization. Although chemogenomic databases are helpful resources for predicting or finding compound interaction partners, they tend to be limited and poorly annotated. Furthermore, unlike genes, compound identifiers are often not standardized, and many synonyms may exist, especially in the biological literature, making batch analysis of compounds difficult. Here, we constructed an open-source annotation and target hypothesis prediction tool that explores some of the largest chemical and biological databases, mining these for both common name, synonyms, and structurally similar molecules. We used this Chemical Analysis and Clustering for Target Identification (CACTI) tool to analyze the Pathogen Box collection, an open-source set of 400 drug-like compounds active against a variety of microbial pathogens. Our analysis resulted in 4,315 new synonyms, 35,963 pieces of new information and target prediction hints for 58 members.Scientific contributionsWith the employment of this tool, a comprehensive report with known evidence, close analogs and drug-target prediction can be obtained for large-scale chemical libraries that will facilitate their evaluation and future target validation and optimization efforts.

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Structure-based virtual screening against multiple Plasmodium falciparum kinases reveals antimalarial compounds

Cited by 2 publications

References 80 publications

Protein target similarity is positive predictor of in vitro antipathogenic activity: a drug repurposing strategy for Plasmodium falciparum

Protein target similarity is positive predictor of in vitro antipathogenic activity: a drug repurposing strategy for Plasmodium falciparum

CACTI: an in silico chemical analysis tool through the integration of chemogenomic data and clustering analysis

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