👤 M Martini

A drug Mechanism of Action (MoA) is a complex biological phenomenon that describes how a bioactive compound produces a pharmacological effect. The complete knowledge of MoA is fundamental to fully understanding the drug activity. Over the years, many experimental methods have been developed and a huge quantity of data has been produced. Nowadays, considering the increasing omics data availability and the improvement of the accessible computational resources, the study of a drug MoA is conducted by integrating experimental and bioinformatics approaches. The development of new in silico solutions for this type of analysis is continuously ongoing; herein, an updating review on such bioinformatic methods is presented. The methodologies cited are based on multi-omics data integration in biochemical networks and Machine Learning (ML). The multiple types of usable input data and the advantages and disadvantages of each method have been analyzed, with a focus on their applications. Three specific research areas (i.e. cancer drug development, antibiotics discovery, and drug repurposing) have been chosen for their importance in the drug discovery fields in which the study of drug MoA, through novel bioinformatics approaches, is particularly productive. Show less

Background Chemotherapy, radiotherapy, targeted therapy and immunotherapy have demonstrated expected clinical efficacy, while drug resistance remains the predominant limiting factor to therapeutic failure in patients with colorectal cancer (CRC). Although there have been numerous basic and clinical studies on CRC resistance in recent years, few publications utilized the bibliometric method to evaluate this field. The objective of current study was to provide a comprehensive analysis of the current state and changing trends of drug resistance in CRC over the past 20 years. Methods The Web of Science Core Collection (WOSCC) was utilized to extracted all studies regarding drug resistance in CRC during 2002-2021. CiteSpace and online platform of bibliometrics were used to evaluate the contributions of various countries/regions, institutions, authors and journals in this field. Moreover, the recent research hotspots and promising future trends were identified through keywords analysis by CiteSpace and VOSviewer. Results 1451 related publications from 2002 to 2021 in total were identified and collected. The number of global publications in this field has increased annually. China and the USA occupied the top two places with respect to the number of publications, contributing more than 60% of global publications. Sun Yat-sen University and Oncotarget were the institution and journal which published the most papers, respectively. Bardelli A from Italy was the most prolific writer and had the highest H-index. Keywords burst analysis identified that “Growth factor receptor”, “induced apoptosis” and “panitumumab” were the ones with higher burst strength in the early stage of this field. Analysis of keyword emergence time showed that “oxaliplatin resistance”, “MicroRNA” and “epithelial mesenchymal transition (EMT)” were the keywords with later average appearing year (AAY). Conclusions The number of publications and research interest on drug resistance in CRC have been increasing annually. The USA and China were the main driver and professor Bardelli A was the most outstanding researcher in this field. Previous studies have mainly concentrated on growth factor receptor and induced apoptosis. Oxaliplatin resistance, microRNA and EMT as recently appeared frontiers of research that should be closely tracked in the future. Show less

The association of proteins with metals, metalation, is challenging because the tightest binding metals are rarely the correct ones. Inside cells, correct metalation is enabled by controlled bioavailability plus extra mechanisms for tricky combinations such as iron and manganese. Show less