Machine learning and molecular dynamics simulations assisted evolutionary design and discovery pipeline to screen the efficient small molecule acceptors for PTB7-Th based organic solar cells with over 15% efficiency

Organic solar cells are the most promising candidates for future commercialization. This goal can be quickly achieved by designing new materials and predicting their performance without experimentation to reduce the...

Drug Repurposing for Tuberculosis

Tuberculosis (TB), caused by Mycobacterium tuberculosis, is a major global health concern given the increase in multiple forms of drug-resistant TB. This underscores the importance of a continuous pipeline of new anti-TB agents. From recent studies, it is evident that the increase in drug efficacy is being achieved through re-engineering old TB-drug families and repurposing known drugs. This approach has led to producing a newer class of compounds which not only saves time and investment in developing newer drugs but is also effective in identifying drug candidates with novel mechanisms to treat multi-drug resistant strains. The repurposed drugs moxifloxacin, linezolid, and clofazimine are used to treat extensively drug-resistant TB when first- and/or second-line drugs fail. The chapter covers a detailed background on the current status of the repurposed drugs in the TB drug-discovery pipeline and discusses a potential way forward.

Development and implementation of an enterprise-wide predictive model for early absorption, distribution, metabolism and excretion properties

Background: Accurate prediction of absorption, distribution, metabolism and excretion (ADME) properties can facilitate the identification of promising drug candidates. Methodology & Results: The authors present the Janssen generic Target Product Profile (gTPP) model, which predicts 18 early ADME properties, employs a graph convolutional neural network algorithm and was trained on between 1000–10,000 internal data points per predicted parameter. gTPP demonstrated stronger predictive power than pretrained commercial ADME models and automatic model builders. Through a novel logging method, the authors report gTPP usage for more than 200 Janssen drug discovery scientists. Conclusion: The investigators successfully enabled the rapid and systematic implementation of predictive ML tools across a drug discovery pipeline in all therapeutic areas. This experience provides useful guidance for other large-scale AI/ML deployment efforts.

Tuberculosis Drug Discovery: A Decade of Hit Assessment for Defined Targets

More than two decades have elapsed since the publication of the first genome sequence of Mycobacterium tuberculosis (Mtb) which, shortly thereafter, enabled methods to determine gene essentiality in the pathogen. Despite this, target-based approaches have not yielded drugs that have progressed to clinical testing. Whole-cell screening followed by elucidation of mechanism of action has to date been the most fruitful approach to progressing inhibitors into the tuberculosis drug discovery pipeline although target-based approaches are gaining momentum. This review discusses scaffolds that have been identified over the last decade from screens of small molecule libraries against Mtb or defined targets where mechanism of action investigation has defined target-hit couples and structure-activity relationship studies have described the pharmacophore.

In vitro screening as an anthelmintic discovery pipeline for Calicophoron daubneyi: nutritive media and rumen environment-based approaches

Paramphistomosis can lead to morbidity and mortality of ruminant livestock within tropical and sub-tropical climates. In recent decades, rumen fluke has become an emerging infection in temperate climates across Western Europe, with Calicophoron daubneyi, the primary species present. Clinical outbreaks with C. daubneyi larvae are reported and adults might be responsible for production losses. There is not currently a widely licensed anthelmintic product available to control C. daubneyi. In this study, three existing flukicide anthelmintics were tested for efficacy against mature C. daubneyi, comparing a standard in vitro culturing assay and a new more relevant rumen fluid based in vitro compound screening protocol. The new rumen based screen confirmed that oxyclozanide was active against adult C. daubneyi and identified activity with praziquantel. The study highlighted the downstream value of incorporating relevant in vitro screening for anthelmintic discovery pipelines.

In silico trial to test COVID-19 candidate vaccines: a case study with UISS platform

Background SARS-CoV-2 is a severe respiratory infection that infects humans. Its outburst entitled it as a pandemic emergence. To get a grip on this outbreak, specific preventive and therapeutic interventions are urgently needed. It must be said that, until now, there are no existing vaccines for coronaviruses. To promptly and rapidly respond to pandemic events, the application of in silico trials can be used for designing and testing medicines against SARS-CoV-2 and speed-up the vaccine discovery pipeline, predicting any therapeutic failure and minimizing undesired effects. Results We present an in silico platform that showed to be in very good agreement with the latest literature in predicting SARS-CoV-2 dynamics and related immune system host response. Moreover, it has been used to predict the outcome of one of the latest suggested approach to design an effective vaccine, based on monoclonal antibody. Universal Immune System Simulator (UISS) in silico platform is potentially ready to be used as an in silico trial platform to predict the outcome of vaccination strategy against SARS-CoV-2. Conclusions In silico trials are showing to be powerful weapons in predicting immune responses of potential candidate vaccines. Here, UISS has been extended to be used as an in silico trial platform to speed-up and drive the discovery pipeline of vaccine against SARS-CoV-2.