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Artificial intelligence (AI) development imitates the workings of the human brain to comprehend modern problems. The traditional approaches such as high throughput screening (HTS) and combinatorial chemistry are lengthy and expensive to the pharmaceutical industry as they can only handle a smaller dataset. Deep learning (DL) is a sophisticated AI method that uses a thorough comprehension of particular systems. The pharmaceutical industry is now adopting DL techniques to enhance the research and development process. Multi-oriented algorithms play a crucial role in the processing of QSAR analysis, de novo drug design, ADME evaluation, physicochemical analysis, preclinical development, followed by clinical trial data precision. In this study, we investigated the performance of several algorithms, including deep neural networks (DNN), convolutional neural networks (CNN) and multi-task learning (MTL), with the aim of generating high-quality, interpretable big and diverse databases for drug design and development. Studies have demonstrated that CNN, recurrent neural network and deep belief network are compatible, accurate and effective for the molecular description of pharmacodynamic properties. In Covid-19, existing pharmacological compounds has also been repurposed using DL models. In the absence of the Covid-19 vaccine, remdesivir and oseltamivir have been widely employed to treat severe SARS-CoV-2 infections. In conclusion, the results indicate the potential benefits of employing the DL strategies in the drug discovery process.Communicated by Ramaswamy H. Sarma.

Parmotremaperlatum is traditionally used in different areas of Pakistan to treat gastrointestinal, respiratory, and vascular diseases. This study evaluates the underlying mechanisms for traditional uses of P. perlatum in diarrhea, asthma, and hypertension. In vitro pharmacological studies were conducted using isolated jejunum, trachea, and aortic preparations, while the cytotoxic study was conducted in mice. Crude extract of P. perlatum(Pp.Cr), comprising appreciable quantities of alkaloids and flavonoids, relaxed spontaneously contracting jejunum preparation, K+ (80 mM)-induced, and carbachol (1 µM)-induced jejunum contractions in a concentration-dependent manner similar to dicyclomine and dantrolene. Pp.Cr showed a rightward parallel shift of concentration-response curves (CRCs) of Cch after a non-parallel shift similarto dicyclomine and shifted CRCs of Ca+2 to rightward much likeverapamil and dantrolene, demonstrating the coexistence of antimuscarinic and Ca+2 antagonistic mechanism. Furthermore, Pp.Cr, dicyclomine, and dantrolene relaxed K+ (80 mM)-induced and Cch (1 µM)-induced tracheal contractions and shifted rightward CRCs of Cch similar to dicyclomine, signifying the dual blockade. Additionally, Pp.Cr also relaxed the K+ (80 mM)-induced and phenylephrine (1 µM)-induced aortic contraction, similarly to verapamil and dantrolene, suggesting Ca+2 channel antagonism. Here, we explored for the first time thespasmolytic and bronchodilator effects of Pp.Crand whether they maybe due to the dual blockade of Ca+2 channels and muscarinic receptors, while the vasodilator effect might be owing to Ca+2 antagonism. Our results provide the pharmacological evidence that P. perlatum could be a new potential therapeutic option to treat gastrointestinal, respiratory, and vascular diseases. Hence, there is a need for further research to explore bioactive constituent of P. perlatum as well as further investigation by suitable experimental models are required to further confirm the importance and usefulness of P. perlatum in diarrhea, asthma, and hypertension treatment.