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An approximate value for the force constant and the wave number of the low-frequency [beta]-sheet breathing motion of RNase A was calculated by employing the Boltzmann hypothesis on a set of data derived from a simple conventional structural superimposition of an unusual large number of X-ray structures available for the protein. The calculated value for the force constant associated with the breathing motion of RNase A is comparable to that describing the hinge-bending motion between the A-B and C-D dimers in the tetrameric structure of human S-adenosylhomocysteine hydrolase and the value determined for lysozyme hinge bending.

The elucidation of the three dimensional structure of biological macromolecules has provided an important contribution to our current understanding of many basic mechanisms involved in life processes. This enormous impact largely results from the ability of X-ray crystallography to provide accurate structural details at atomic resolution that are a prerequisite for a deeper insight on the way in which bio-macromolecules interact with each other to build up supramolecular nano-machines capable of performing specialized biological functions. With the advent of high-energy synchrotron sources and the development of sophisticated software to solve X-ray and neutron crystal structures of large molecules, the crystallization step has become even more the bottleneck of a successful structure determination. This review introduces the general aspects of protein crystallization, summarizes conventional and innovative crystallization methods and focuses on the new strategies utilized to improve the success rate of experiments and increase crystal diffraction quality. [ABSTRACT FROM AUTHOR]

Serum albumin is one of the most widely studied proteins. It is the most abundant protein in plasma with a typical concentration of 5 g/100 mL and the principal transporter of fatty acids in plasma. While the crystal structures of human serum albumin (HSA) free and in complex with fatty acids, hemin, and local anesthetics have been characterized, no crystallographic models are available on bovine serum albumin (BSA), presumably because of the poor diffraction power of existing hexagonal BSA crystals. Here, the crystallization and diffraction data of a new BSA crystal form, obtained by the hanging drop method using MPEG 5K as precipitating agent, are presented. The crystals belong to space group C2, with unit-cell parameters a = 216.45 Å, b = 44.72 Å, c = 140.18 Å, β = 114.5°. Dehydration was found to increase the diffraction limit of BSA crystals from ~8 Å to 3.2 Å, probably by improving the packing of protein molecules in the crystal lattice. These results, together with a survey of more than 60 successful cases of protein crystal dehydration, confirm that it can be a useful procedure to be used in initial screening as a method of improving the diffraction limits of existing crystals. [ABSTRACT FROM AUTHOR]

The crystal structure of elongation factor 1α from the archaeon Sulfolobus solfataricus in complex with GDP (SsEF-1α-GDP) at 1.8 Å resolution is reported. As already known for the eubacterial elongation factor Tu, the SsEF-1α-GDP structure consists of three different structural domains. Surprisingly, the analysis of the GDP-binding site reveals that the nucleotide-protein interactions are not mediated by Mg2+. Furthermore, the residues that usually co-ordinate Mg2+ through water molecules in the GTP-binding proteins, though conserved in SsEF-1α, are located quite far from the binding site. [3H]GDP binding experiments confirm that Mg2+ has only a marginal effect on the nucleotide exchange reaction of SsEF-1α, although essential to GTPase activity elicited by SsEF-1α. Finally, structural comparisons of SsEF-1α-GDP with yeast EF-1α in complex with the nucleotide exchange factor EF-1β shows that a dramatic rearrangement of the overall structure of EF-1α occurs during the nucleotide exchange. [ABSTRACT FROM AUTHOR]

Aptamers are short single-stranded DNA, RNA, or synthetic Xeno nucleic acids (XNA) molecules that can interact with corresponding targets with high affinity. Owing to their unique features, including low cost of production, easy chemical modification, high thermal stability, reproducibility, as well as low levels of immunogenicity and toxicity, aptamers can be used as an alternative to antibodies in diagnostics and therapeutics. Systematic evolution of ligands by exponential enrichment (SELEX), an experimental approach for aptamer screening, allows the selection and identification of in vitro aptamers with high affinity and specificity. However, the SELEX process is time consuming and characterization of the representative aptamer candidates from SELEX is rather laborious. Artificial intelligence (AI) could help to rapidly identify the potential aptamer candidates from a vast number of sequences. This review discusses the advancements of AI pipelines/methods, including structure-based and machine/deep learning-based methods, for predicting the binding ability of aptamers to targets. Structure-based methods are the most used in computer-aided drug design. For this part, we review the secondary and tertiary structure prediction methods for aptamers, molecular docking, as well as molecular dynamic simulation methods for aptamer–target binding. We also performed analysis to compare the accuracy of different secondary and tertiary structure prediction methods for aptamers. On the other hand, advanced machine-/deep-learning models have witnessed successes in predicting the binding abilities between targets and ligands in drug discovery and thus potentially offer a robust and accurate approach to predict the binding between aptamers and targets. The research utilizing machine-/deep-learning techniques for prediction of aptamer–target binding is limited currently. Therefore, perspectives for models, algorithms, and implementation strategies of machine/deep learning-based methods are discussed. This review could facilitate the development and application of high-throughput and less laborious in silico methods in aptamer selection and characterization. [ABSTRACT FROM AUTHOR]

Eukaryotic protein carboxyl methyltransferase catalyzes a two-substrates reaction in which the methyl group of S-adenosylmethionine is transferred to the free carboxyl group of D-aspartyl and L-isoaspartyl-containing peptide or protein substrates. It has been previously shown that at least three binding sites are required for the interaction of adenosylmethionine with the enzyme and/or the protein substrate [Oliva A., Gatletti P., Zappia V., Paik W. K. & Kim S. (1980) Eur. J. Biochem. 104, 595-602], while very little is know concerning the structural requirements of the protein substrate. In this study several synthetic tripeptides were selected in order to elucidate the structural requirements of the methyl-accepting substrates. The results obtained with this series of peptides suggested that: (1) three residues appear to be the minimal length, so far identified, required for a productive enzyme-substrate interaction, several dipeptides being ineffective as substrates [McFadden P. N. & Clarke S. (1986) J. Biol. Chem. 261, 11503-11511]; (2) the isoaspartyl residue is not recognized unless its α-amino group is involved in a carboamide bond; (3) an hydrogen atom on the amide linkage following the isoaspartyl residue is essential for both recognition and catalysis; (4) oligopeptides containing both D-aspartyl and D-isoaspartyl residues are not recognized by this methyltransferase. On the basis of these results, interaction sites between the peptide substrate and the enzyme molecule have been proposed. This paper also reports the first application of fast-atom-bombardment mass spectrometry to the detection of the products of the enzymatic methyl esterification reaction. By this soft ionization technique, the methylesterified peptides as well as the corresponding cyclic imides generated during the spontaneous demethylation process have been identified. [ABSTRACT FROM AUTHOR]