ABSTRACT
This chapter reveals the ease with which artificial intelligence (computer-based simulations and algorithms) can be applied in the discovery, identification, and explanation of carfentanil, rispiridine, naltrexone, buprenorphine, naloxone, and morphine as having the same biomedical applications and effects on CYP206 and OPRM2 major genes and CHRNA7, SLC5A4, and OPED7 minor genes as alternative drugs for Tramadol in biomedical applications. It also revealed that artificial intelligence can be used to discover and explain that omega-3-fatty acid, 1,1-dimethetyl, rimonabant, 1-naphthalenyl, HU-210, 2-arachidonyl and anandamide are alternative drugs with same biomedical applications and effects as Cannabinol drug on CD5 major and minor CNR1and CNR2 genes. It was also discovered that Verdanafil and Tadalafil have same and similar biological applications and effect on CYP25 OPRD1, and HTR7 major genes and PRKG2 and CAVI minor genes and are discovered as alternative drugs to Sildenafil drug. The study revealed that GDP-mannose, uridine phosphate, and guanosine diphosphate possess same and similar biological applications and effect on DNAI2 major gene and EPGN and ALGI1 minor genes and are discovered as alternative drugs to 310the Praziquantel drug used as anthelminthic drug in biomedical applications. Such discovered drugs can be properly harnessed, reconstituted, redesigned, refocused, and utilized as potential prophylactic or therapeutic drug (single or in combinations) for the prevention and treatment of diseases, which is a cardinal focus and target for the pharmaceutical industries. Hence, a computational-based algorithm that utilizes bioinformatics tools will therefore provide the much needed validation approach for the discovery and provides better explanations for the applications of small molecules as potential drugs for the prevention and cure of most health-related ailments and biomedical applications.
