SynergyFinder 3.0: an interactive analysis and consensus interpretation of multi-drug synergies across multiple samples

Nucleic Acids Research, Journal Year: 2022, Volume and Issue: 50(W1), P. W739 - W743

Published: April 29, 2022

SynergyFinder (https://synergyfinder.fimm.fi) is a free web-application for interactive analysis and visualization of multi-drug combination response data. Since its first release in 2017, has become popular tool multi-dose data analytics, partly because the development functionality graphical interface been driven by diverse user community, including both chemical biologists computational scientists. Here, we describe latest upgrade this community-effort, 3.0, introducing number novel features that support multi-sample synergy, consensus synergy score combines multiple scoring models, an improved outlier detection eliminates false positive results, along with many other post-analysis options such as weighting drug concentrations distinguishing between different modes (potency efficacy). Based on requests, several additional improvements were also implemented, new visualizations export combinations. With these improvements, 3.0 supports robust identification consistent combinatorial synergies discovery clinical translation.

Language: Английский

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SARS-CoV-2 Omicron variant is highly sensitive to molnupiravir, nirmatrelvir, and the combination

Cell Research, Journal Year: 2022, Volume and Issue: 32(3), P. 322 - 324

Published: Jan. 20, 2022

Language: Английский

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Deep learning in drug discovery: an integrative review and future challenges

Artificial Intelligence Review, Journal Year: 2022, Volume and Issue: 56(7), P. 5975 - 6037

Published: Nov. 17, 2022

Recently, using artificial intelligence (AI) in drug discovery has received much attention since it significantly shortens the time and cost of developing new drugs. Deep learning (DL)-based approaches are increasingly being used all stages development as DL technology advances, drug-related data grows. Therefore, this paper presents a systematic Literature review (SLR) that integrates recent technologies applications Including, drug-target interactions (DTIs), drug-drug similarity (DDIs), sensitivity responsiveness, drug-side effect predictions. We present more than 300 articles between 2000 2022. The benchmark sets, databases, evaluation measures also presented. In addition, provides an overview how explainable AI (XAI) supports problems. dosing optimization success stories discussed well. Finally, digital twining (DT) open issues suggested future research challenges for Challenges to be addressed, directions identified, extensive bibliography is included.

Language: Английский

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Omicron variant (B.1.1.529) and its sublineages: What do we know so far amid the emergence of recombinant variants of SARS-CoV-2?

Biomedicine & Pharmacotherapy, Journal Year: 2022, Volume and Issue: 154, P. 113522 - 113522

Published: Aug. 15, 2022

Since the start of COVID-19 pandemic, numerous variants SARS-CoV-2 have been reported worldwide. The advent concern (VOCs) raises severe concerns amid serious containment efforts against that include physical measures, pharmacological repurposing, immunization, and genomic/community surveillance. Omicron variant (B.1.1.529) has identified as a highly modified, contagious, crucial among five VOCs SARS-CoV-2. increased affinity spike protein (S-protein), host receptor, angiotensin converting enzyme-2 (ACE-2), due to higher number mutations in receptor-binding domain (RBD) S-protein proposed primary reason for decreased efficacy majorly available vaccines transmissible nature variant. Because its significant competitive advantage, sublineages swiftly surpassed other become dominant circulating lineages nations. prevalent strain United Kingdom South Africa. Furthermore, emergence recombinant through conjunction with or by mixing variant's sublineages/subvariants poses major threat humanity. This various issues hazards regarding sublineages, such an breakout susceptible populations fully vaccinated persons. As result, understanding features genetic implications this is crucial. Hence, we explained depth evolution analyzed repercussions on infectiousness, dissemination ability, viral entry mechanism, immune evasion. We also presented viewpoint feasible strategies precluding counteracting any future catastrophic spread omicron could result detrimental wave cases.

Language: Английский

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Lassa fever — the road ahead

Nature Reviews Microbiology, Journal Year: 2022, Volume and Issue: 21(2), P. 87 - 96

Published: Sept. 12, 2022

Language: Английский

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A dual graph neural network for drug–drug interactions prediction based on molecular structure and interactions

PLoS Computational Biology, Journal Year: 2023, Volume and Issue: 19(1), P. e1010812 - e1010812

Published: Jan. 26, 2023

Expressive molecular representation plays critical roles in researching drug design, while effective methods are beneficial to learning representations and solving related problems discovery, especially for drug-drug interactions (DDIs) prediction. Recently, a lot of work has been put forward using graph neural networks (GNNs) forecast DDIs learn representations. However, under the current GNNs structure, majority approaches from one-dimensional string or two-dimensional interaction information between chemical substructure remains rarely explored, it is neglected identify key substructures that contribute significantly Therefore, we proposed dual network named DGNN-DDI features by structure interactions. Specifically, first designed directed message passing with attention mechanism (SA-DMPNN) adaptively extract substructures. Second, order improve final features, separated into pairwise each drug’s unique Then, adopted predict probability DDI tuple. We evaluated DGNN–DDI on real-world dataset. Compared state-of-the-art methods, model improved prediction performance. also conducted case study existing drugs aiming combinations may be novel coronavirus disease 2019 (COVID-19). Moreover, visual interpretation results proved was sensitive able detect DDIs. These advantages demonstrated method enhanced performance capability modeling.

Language: Английский

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In Silico Repurposed Drugs against Monkeypox Virus

Molecules, Journal Year: 2022, Volume and Issue: 27(16), P. 5277 - 5277

Published: Aug. 18, 2022

Monkeypox is an emerging epidemic of concern. The disease caused by the monkeypox virus and increasing global incidence with a 2022 outbreak that has spread to Europe amid COVID-19 pandemic. new associated novel, previously undiscovered mutations variants. Currently, US Food Drug Administration (FDA) approved poxvirus treatment involves use tecovirimat. However, there otherwise limited pharmacopoeia research interest in monkeypox. In this study, virtual screening molecular dynamics were employed explore potential repurposing multiple drugs FDA or other jurisdictions for applications. Several are predicted tightly bind viral proteins, which crucial replication, including molecules show high binding D13L capsid protein, whose inhibition been demonstrated suppress replication.

Language: Английский

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Discovery of Amphiphilic Xanthohumol Derivatives as Membrane-Targeting Antimicrobials against Methicillin-Resistant Staphylococcus aureus

Journal of Medicinal Chemistry, Journal Year: 2022, Volume and Issue: 66(1), P. 962 - 975

Published: Dec. 30, 2022

Infections caused by multidrug-resistant (MDR) bacteria are increasing worldwide, and with limited clinically available antibiotics, it is urgent to develop new antimicrobials combat these MDR bacteria. Here, a class of novel amphiphilic xanthohumol derivatives were prepared using building-block approach. Bioactivity assays showed that the molecule IV15 not only exhibited remarkable antibacterial effect against clinical methicillin-resistant Staphylococcus aureus (MRSA) isolates (MICs: 1–2 μg/mL) but also had advantages rapid bactericidal properties, low toxicity, good plasma stability, readily inducing bacterial resistance. Mechanistic studies indicated has membrane-targeting ability can bind phosphatidylglycerol cardiolipin in membranes, thus disrupting cell membranes causing increased intracellular reactive oxygen species leakage proteins DNA, eventually resulting death. Notably, vivo anti-MRSA efficacy, superior vancomycin, making potential candidate MRSA infections.

Language: Английский

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The Combination of Molnupiravir with Nirmatrelvir or GC376 Has a Synergic Role in the Inhibition of SARS-CoV-2 Replication In Vitro

Microorganisms, Journal Year: 2022, Volume and Issue: 10(7), P. 1475 - 1475

Published: July 21, 2022

Introduction: The development of effective vaccines has partially mitigated the trend SARS-CoV-2 pandemic; however, need for orally administered antiviral drugs persists. This study aims to investigate activity molnupiravir in combination with nirmatrelvir or GC376 on verify synergistic effect. Methods: strains 20A.EU, BA.1 and BA.2 were used infect Vero E6 presence compounds alone combinations using five two-fold serial dilution compound concentrations ≤EC90. After 48 72 h post-infection, viability was performed MTT reduction assay. Supernatants collected plaque-assay titration. All experiments triplicate, each being repeated at least three times. score calculated Synergy Finder version 2. Results: reached micromolar EC90. Molnupiravir showed a an HSA 19.33 (p < 0.0001) additive 8.61 0.0001). both 14.2 = 0.01) 13.08 0.0001), respectively. Conclusion: associated one two protease-inhibitors good additive-synergic vitro.

Language: Английский

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Systematic review of computational methods for drug combination prediction

Computational and Structural Biotechnology Journal, Journal Year: 2022, Volume and Issue: 20, P. 2807 - 2814

Published: Jan. 1, 2022

Synergistic effects between drugs are rare and highly context-dependent patient-specific. Hence, there is a need to develop novel approaches stratify patients for optimal therapy regimens, especially in the context of personalized design combinatorial treatments. Computational methods enable systematic in-silico screening combination effects, can thereby prioritize most potent combinations further testing, among massive number potential combinations. To help researchers choose prediction method that best fits various real-world applications, we carried out literature review 117 computational developed date drug prediction, classified terms their tasks input data requirements. Most current focus on or classification synergy, only few consider efficacy toxicity combinations, which key determinants therapeutic success Furthermore, dose-specific predictions across multiple doses, important clinical translation predictions, as well model-based identification biomarkers predictive heterogeneous responses. Even if reviewed anticancer many modelling also applicable antiviral other diseases indications.

Language: Английский

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