Uncovering protein structure

Structural biology is the study of the molecular arrangement and dynamics of biological macromolecules, particularly proteins. The resulting structures are then used to help explain how proteins function. This article gives the reader an insight into protein structure and the underlying chemistry and physics that is used to uncover protein structure. We start with the chemistry of amino acids and how they interact within, and between proteins, we also explore the four levels of protein structure and how proteins fold into discrete domains. We consider the thermodynamics of protein folding and why proteins misfold. We look at protein dynamics and how proteins can take on a range of conformations and states. In the second part of this review, we describe the variety of methods biochemists use to uncover the structure and properties of proteins that were described in the first part. Protein structural biology is a relatively new and exciting field that promises to provide atomic-level detail to more and more of the molecules that are fundamental to life processes

Uncovering protein function: from classification to complexes

Almost all interactions and reactions that occur in living organisms involve proteins. The various biological roles of proteins include, but are not limited to, signal transduction, gene transcription, cell death, immune function, structural support, and catalysis of all the chemical reactions that enable organisms to survive. The varied roles of proteins have led to them being dubbed 'the workhorses of all living organisms'. This article discusses the functions of proteins and how protein function is studied in a laboratory setting. In this article, we begin by examining the functions of protein domains, followed by a discussion of some of the major classes of proteins based on their function. We consider protein binding in detail, which is central to protein function. We then examine how protein function can be altered through various mechanisms including post-translational modification, and changes to environment, oligomerisation and mutations. Finally, we consider a handful of the techniques employed in the laboratory to understand and measure the function of proteins

Demonstrator training needs to be active and focused on personalized student learning in bioscience teaching laboratories

Demonstrators spend significant time with students on a weekly basis in instructional laboratories and are well poised to offer students meaningful learning. Most often, effective demonstrator training is neglected due to time and resource restraints and it is clear more attention is needed. We hypothesized that students’ learning experience in laboratories would improve if demonstrators were well trained particularly across three overlapping learning domains: subject‐specific knowledge (cognitive and psychomotor), problem solving (cognitive) and group management including personalized student learning strategies (affective). We assessed both students and demonstrators on the impact of this extensive demonstrator training in 1st‐ and 2nd‐year bioscience practical courses over two years. The results show that all students rated the demonstrators’ performance higher after the extensive training. Students from both years valued the provision of problem‐solving skills; however, 1st‐year students placed greater value on the demonstrator’s ability to address student inclusivity, whereas 2nd‐year students preferred the provision of strong subject knowledge. Interestingly, demonstrators’ own perception of their teaching ability was different from student feedback on their performance, which may be due to lack of reflective practice. We propose a multimodal training framework that includes inclusivity/approachability and reflection as an integral part of training. This study further suggests that demonstrator training needs to be tailored to the changing needs of students as they progress through the different levels of their degree. Our proposed framework is particularly relevant to the current pandemic which has affected young people’s mental health, confidence and openness to new experiences

Most yeast SH3 domains bind peptide targets with high intrinsic specificity

<div><p>A need exists to develop bioinformatics for predicting differences in protein function, especially for members of a domain family who share a common fold, yet are found in a diverse array of proteins. Many domain families have been conserved over large evolutionary spans and representative genomic data during these periods are now available. This allows a simple method for grouping domain sequences to reveal common and unique/specific binding residues. As such, we hypothesize that sequence alignment analysis of the yeast SH3 domain family across ancestral species in the fungal kingdom can determine whether each member encodes specific information to bind unique peptide targets. With this approach, we identify important specific residues for a given domain as those that show little conservation within an alignment of yeast domain family members (paralogs) but are conserved in an alignment of its direct relatives (orthologs). We find most of the yeast SH3 domain family members have maintained unique amino acid conservation patterns that suggest they bind peptide targets with high intrinsic specificity through varying degrees of non-canonical recognition. For a minority of domains, we predict a less diverse binding surface, likely requiring additional factors to bind targets specifically. We observe that our predictions are consistent with high throughput binding data, which suggests our approach can probe intrinsic binding specificity in any other interaction domain family that is maintained during evolution.</p></div

Specific conservation values for the yeast SH3 domain family.

<p>A. Alignment of the core 60 positions colored by ortholog SC values as a heat map (red high and yellow low SC values, with domains sorted alphabetically). The average SC value across the family is indicated for each position at the bottom of the table, along with the paralog positional entropy, surface labels and secondary structure. Dark Boxes indicate the 2 principal loop regions where high SC values are found. B. Specific conservation across the domain. The line is set at an SC value of 1.7, which is considered a potential threshold for significant specific conservation (where ortholog conservation is almost twice that of paralog conservation).</p

Example sequence conservation analysis for orthologs of Abp1 SH3 domain.

<p>The residues are colored according to the residue equivalence groups defined for entropy and PSSM calculations. The species names end with a number that refers to their taxonomic group (<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0193128#pone.0193128.s003" target="_blank">S1 Fig</a> and <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0193128#pone.0193128.s001" target="_blank">S1 Table</a>). The SC value is calculated as (paralog entropy)/(ortholog entropy). A standard numbering system [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0193128#pone.0193128.ref046" target="_blank">46</a>] for the core 60 SH3 domain residues is indicated on the top row as well as the residue number in the full length <i>S.cerevisiae</i> protein (fifth row). The paralog entropy is calculated from an alignment of the 28 SH3 domains in <i>S.cerevisiae</i>.</p

SI and SII PSSM for yeast paralog alignment (28 domains) and example ortholog alignments for Fus1 (16 species) and Bud14 (29 species).

<p>Total occurrence for each amino acid group for each position is indicated and colored as yellow (low) to red (high). Residues are grouped into SI (left) and SII (right). Dark outlined regions indicate most common preference for the family (≥ 20 occurrences). Overall, for SI there is a family preference for aromatic residues except the less conserved positions 9, 52 and 53. Notable exceptions include Fus1 that has cysteines at positions 37 and 54 (which are usually in the FWYH group). For SII, there is a loose family preference for polar/acidic residues except at position 49 where hydrophobic residues are found. The extent of conservation in the orthlog alignments in SI and SII vary, with a much greater variation seen in SII PSSMs. PSSMs for all domains (showing both complete domain sequence and only surface I/II) can be found in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0193128#pone.0193128.s008" target="_blank">S4 File</a>.</p

General mechanisms to obtain binding specificity in domain families.

<p>A. Domains may use the interaction with an extended region that goes beyond the canonical binding site to obtain intrinsic specificity (1). For example, the Abp1p SH3 domain binds extended target peptides (17 residues) and was shown to possess high intrinsic binding specificity [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0193128#pone.0193128.ref009" target="_blank">9</a>, <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0193128#pone.0193128.ref010" target="_blank">10</a>]. Domains may also achieve intrinsic specificity through non-canonical recognition via an alternative binding surface far from the canonical one. For example, Pex13 is a peroxisomal membrane protein that contains an SH3 domain that binds Pex14p via the canonical binding surface, however, it also binds Pex5p through an alternative non-canonical surface [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0193128#pone.0193128.ref011" target="_blank">11</a>, <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0193128#pone.0193128.ref012" target="_blank">12</a>]. Furthermore, intrinsic specificity may be achieved through replacing the canonical binding site with a non-canonical one (2) that would lead to negative selection (3) with respect to proline-rich peptides that bind SH3 domains. For example, Fus1 peptide targets do not contain a canonical PxxP motif thus minimizing cross reactivity to proline containing peptides [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0193128#pone.0193128.ref013" target="_blank">13</a>]. Some domains may have potential for contextual specificity using adjacent domains (4). For example, at least 2 of the 3 adjacent SH3 domains of Nck are required to bind their targets [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0193128#pone.0193128.ref014" target="_blank">14</a>]. Spatial and temporal separation mechanisms may be another contextual specificity mechanism (6). For example, <i>in vitro</i>, Fyn SH3 domain and CD2BP2 both bind and compete with each other for the proline region in the target protein CD2. However CD2BP2 localizes to the cytosolic compartment where it interacts with CD2 in T-cells, while Fyn is present permanently in the lipid raft fraction unable to compete [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0193128#pone.0193128.ref015" target="_blank">15</a>]. In some cases, both intrinsic and contextual specificity mechanisms may be used by a domain, such as the Pex13p example above (5). We note here that contextual specificity has been used elsewhere to mean the extended regions of SH3 domain binding peptides, outside their core binding motif [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0193128#pone.0193128.ref016" target="_blank">16</a>]. This definition does not pertain to contextual specificity as discussed within this study. Figure adapted from [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0193128#pone.0193128.ref017" target="_blank">17</a>] and [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0193128#pone.0193128.ref007" target="_blank">7</a>]. B. An example of an extended peptide-domain interaction. The Ark1 peptide is represented in stick and the SH3 domain from Abp1 uses space-filling. The red region is surface I and the blue region is surface II. W36 is represented as green and is on the boundary of the two surfaces. Adapted from [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0193128#pone.0193128.ref018" target="_blank">18</a>] (pdb code 2rpn).</p