Proteins, as pivotal players in biological processes, undergo evolutionary changes due to mutations, whether spontaneous or induced by external factors. These mutations lead to significant genomic differences, contributing to the emergence of new species. From the basic principles of evolution, including variation, selection, fitness, inheritance, and reproduction, to the detailed analysis of specific proteins in different taxonomic groups, this dissertation explores the intricate field of protein evolution. In this thesis the study of bacterial and eukaryotic proteins is covered. It includes the study of enzymes in bacteria, such as CCA-adding enzyme and poly(A) polymerase, providing insights into the evolutionary divergence of these vital proteins. An analysis of existing species protein sequences and the prediction of corresponding ancestral sequences reveals a putative ancestral gammaproteobacterial CCA-adding enzyme, which is functional, thermotolerant and has a high specificity for CCA incorporation and substrate interactions. To address the challenges of suboptimal protein sequence data quality, the develop- ment of the ExceS-A split aligner is presented, which provides an automated solution to search for high quality protein sequences across diverse species groups. It is designed for exon-by-exon comparisons of coding sequences. The computation of exon/intron structure, inherent in spliced alignment procedures, is crucial for distinguishing paralo- gous members within gene families. The simplicity and effectiveness of this blat-based approach offer distinct advantages, especially for genes with extensive introns and applications involving fragmented genome assemblies, outperforming established tools in these scenarios. The application of the tool ExceS-A is then demonstrated in the study of neu- ropeptide Y/RFamide-like receptors in nematodes, shedding light on the evolutionary dynamics within this G protein-coupled receptor (GPCR) family. The Neuropeptide Y/RFamide-like receptors play crucial roles in locomotion, feeding, and reproduction. This extensively studied receptor group in Caenorhabditis elegans, comprising 41 recep- tors, served as a starting point for understanding the family’s expansion in nematodes. 159 nematode genomes revealed a total of 1557 neuropeptide Y/RFamide-like receptor sequences. The high conservation of these receptors across nematoda underscores their significance while highlighting family diversification in nematode evolution, with clade-specific duplications and losses across the phylum and unique patterns observed in the genus Caenorhabditis. Further, the dissertation focuses on the detailed analysis of GPCRs, with a particular interest in the ADRB2 and ADRB1 and Y1R and Y2R receptor, unraveling their conservation patterns and investigating their roles in G protein coupling. The investigation extends to the broader context of GPCR signaling pathways, emphasizing the crucial long-distance signaling and proposing hypotheses regarding amino acid conservation within chordates. Molecular dynamics simulations are used to uncover allosteric mechanisms and networks, providing valuable insights into protein dynamics and interactions. The investigation aimed at determining whether the conservation of amino acids within the chordate group is higher along the transmission pathway of GPCRs compared to the normal shortest path. Contrary to the hypothesis, results for ADRB2 and Y2R receptors, both with ligands and G-proteins, showed no significant difference in conservation rates between weighted and unweighted paths. Analysis revealed that unweighted paths favor hydrophobic interactions, while weighted paths predominantly involve peptide bonds, emphasizing their importance in allosteric signal transmission. Possible reasons for the lack of a significant increase in conservation values include the overall high conservation of amino acids in transmembrane helix 2-6 and the need for more precise information about mutual information in conservation score calculations. Future efforts will explore modified k-shortest path algorithms to identify alternative geometrically related contacts. The dissertation concludes by highlighting the crucial role of bioinformatics in performing complex analyses and processing large datasets. The basics laid here provide a foundation for interdisciplinary collaboration and contribute significant insights into the evolution of proteins. As a comprehensive knowledge framework, this work is able to guide future research efforts and underscores the ongoing importance of uncovering the complex interactions that govern protein evolution in the field of biological research.