Revisiting the Ramachandran plot from a new angle

AAontology: An Ontology of Amino Acid Scales for Interpretable Machine Learning

Amino acid scales are crucial for protein prediction tasks, many of them being curated in the AAindex database. Despite various clustering attempts to organize them and to better understand their relationships, these approaches lack the fine-grained classification necessary for satisfactory interpretability in many protein prediction problems. To address this issue, we developed AAontology-a two-level classification for 586 amino acid scales (mainly from AAindex) together with an in-depth analysis of their relations-using bag-of-word-based classification, clustering, and manual refinement over multiple iterations. AAontology organizes physicochemical scales into 8 categories and 67 subcategories, enhancing the interpretability of scale-based machine learning methods in protein bioinformatics. Thereby it enables researchers to gain a deeper biological insight. We anticipate that AAontology will be a building block to link amino acid properties with protein function and dysfunctions as well as aid informed decision-making in mutation analysis or protein drug design.

Natural compound plumbagin based inhibition of hIAPP revealed by Markov state models based on MD data along with experimental validations

Human islet amyloid polypeptide (amylin or hIAPP) is a 37 residue hormone co-secreted with insulin from β cells of the pancreas. In patients suffering from type-2 diabetes, amylin self-assembles into amyloid fibrils, ultimately leading to the death of the pancreatic cells. However, a research gap exists in preventing and treating such amyloidosis. Plumbagin, a natural compound, has previously been demonstrated to have inhibitory potential against insulin amyloidosis. Our investigation unveils collapsible regions within hIAPP that, upon collapse, facilitates hydrophobic and pi-pi interactions, ultimately leading to aggregation. Intriguingly plumbagin exhibits the ability to bind these specific collapsible regions, thereby impeding the aforementioned interactions that would otherwise drive hIAPP aggregation. We have used atomistic molecular dynamics approach to determine secondary structural changes. MSM shows metastable states forming native like hIAPP structure in presence of PGN. Our in silico results concur with in vitro results. The ThT assay revealed a striking 50% decrease in fluorescence intensity at a 1:1 ratio of hIAPP to Plumbagin. This finding suggests a significant inhibition of amyloid fibril formation by plumbagin, as ThT fluorescence directly correlates with the presence of these fibrils. Further TEM images revealed disappearance of hIAPP fibrils in plumbagin pre-treated hIAPP samples. Also, we have shown that plumbagin disrupts the intermolecular hydrogen bonding in hIAPP fibrils leading to an increase in the average beta strand spacing, thereby causing disaggregation of pre-formed fibrils demonstrating overall disruption of the aggregation machinery of hIAPP. Our work is the first to report a detailed atomistic simulation of 22 μs for hIAPP. Overall, our studies put plumbagin as a potential candidate for both preventive and therapeutic candidate for hIAPP amyloidosis.

Interaction analysis of SARS-CoV-2 omicron BA1 and BA2 of RBD with fifty monoclonal antibodies: Molecular dynamics approach

This report provides detailed insights into the interaction of fifty monoclonal antibodies with two recent Omicron variants, BA1 and BA2. It has been observed that numerous mutations in the receptor binding domain (RBD) result in significant structural changes in Omicron, enhancing its ability to mediate viral infections compared to other variants of concern. The following antibodies, namely JX3S304, 7KMG, 7CH4, 7BELCOVOX45, 7CDJ, 7C01, 7JX3S2H14, 6XCA, 7CDI, 7JMO, 7B3O, 6ZER, 6XC7CR3022, JX3S309, 6XC7CC123, 7CM4, 7KMI, 7L7EAZD8895, exhibit a superior binding affinity towards the Spike when compared to the reference CR3022. Four best-docked systems were subjected to further testing through molecular dynamics (MD) simulations. The MM/GBSA free energy for the top-scored complexes of BA1 variant are BA1_JX3S3O4, BA1_7KMI, BA1_7CH4, and BA1_7KMG, with respective values of -56.120 kcal/mol, -41.30 kcal/mol, -17.546 kcal/mol, and -8.527 kcal/mol; and of BA2 variant are BA2_JX3S3O4, BA2_7CM4, BA2_KMG, and BA2_7CH4, with respective values of -40.903 kcal/mol, -23.416 kcal/mol, -17.350 kcal/mol, and -5.460 kcal/mol. Detailed structural/energetic parameters, principal component analysis, and free energy landscape (FEL) studies reveal a significant decrease in antibody resistance due to the disappearance of numerous hydrogen bond interactions and various metastable states. We believe that these crucial mechanistic insights will contribute to breakthroughs in SARS-CoV-2 research.

Construction of an aerolysin-based multi-epitope vaccine against Aeromonas hydrophila: an in silico machine learning and artificial intelligence-supported approach

Aeromonas hydrophila, a gram-negative coccobacillus bacterium, can cause various infections in humans, including septic arthritis, diarrhea (traveler's diarrhea), gastroenteritis, skin and wound infections, meningitis, fulminating septicemia, enterocolitis, peritonitis, and endocarditis. It frequently occurs in aquatic environments and readily contacts humans, leading to high infection rates. This bacterium has exhibited resistance to numerous commercial antibiotics, and no vaccine has yet been developed. Aiming to combat the alarmingly high infection rate, this study utilizes in silico techniques to design a multi-epitope vaccine (MEV) candidate against this bacterium based on its aerolysin toxin, which is the most toxic and highly conserved virulence factor among the Aeromonas species. After retrieval, aerolysin was processed for B-cell and T-cell epitope mapping. Once filtered for toxicity, antigenicity, allergenicity, and solubility, the chosen epitopes were combined with an adjuvant and specific linkers to create a vaccine construct. These linkers and the adjuvant enhance the MEV's ability to elicit robust immune responses. Analyses of the predicted and improved vaccine structure revealed that 75.5%, 19.8%, and 1.3% of its amino acids occupy the most favored, additional allowed, and generously allowed regions, respectively, while its ERRAT score reached nearly 70%. Docking simulations showed the MEV exhibiting the highest interaction and binding energies (-1,023.4 kcal/mol, -923.2 kcal/mol, and -988.3 kcal/mol) with TLR-4, MHC-I, and MHC-II receptors. Further molecular dynamics simulations demonstrated the docked complexes' remarkable stability and maximum interactions, i.e., uniform RMSD, fluctuated RMSF, and lowest binding net energy. In silico models also predict the vaccine will stimulate a variety of immunological pathways following administration. These analyses suggest the vaccine's efficacy in inducing robust immune responses against A. hydrophila. With high solubility and no predicted allergic responses or toxicity, it appears safe for administration in both healthy and A. hydrophila-infected individuals.

Design of a novel multi-epitopes vaccine against Escherichia fergusonii: a pan-proteome based in- silico approach

Escherichia fergusonii a gram-negative rod-shaped bacterium in the Enterobacteriaceae family, infect humans, causing serious illnesses such as urinary tract infection, cystitis, biliary tract infection, pneumonia, meningitis, hemolytic uremic syndrome, and death. Initially treatable with penicillin, antibiotic misuse led to evolving resistance, including resistance to colistin, a last-resort drug. With no licensed vaccine, the study aimed to design a multi-epitope vaccine against E. fergusonii. The study started with the retrieval of the complete proteome of all known strains and proceeded to filter the surface exposed virulent proteins. Seventeen virulent proteins (4 extracellular, 4 outer membranes, 9 periplasmic) with desirable physicochemical properties were identified from the complete proteome of known strains. Further, these proteins were processed for B-cell and T-cell epitope mapping. Obtained epitopes were evaluated for antigenicity, allergenicity, solubility, MHC-binding, and toxicity and the filtered epitopes were fused by specific linkers and an adjuvant into a vaccine construct. Structure of the vaccine candidate was predicted and refined resulting in 78.1% amino acids in allowed regions and VERIFY3D score of 81%. Vaccine construct was docked with TLR-4, MHC-I, and MHC-II, showing binding energies of -1040.8 kcal/mol, -871.4 kcal/mol, and -1154.6 kcal/mol and maximum interactions. Further, molecular dynamic simulation of the docked complexes was carried out resulting in a significant stable nature of the docked complexes (high B-factor and deformability values, lower Eigen and high variance values) in terms of intermolecular binding conformation and interactions. The vaccine was also reported to stimulate a variety of immunological pathways after administration. In short, the designed vaccine revealed promising predictions about its immune protective potential against E. fergusonii infections however experimental validation is needed to validate the results.

Disallowed spots in protein structures

Ramachandran (ϕ, ψ) steric map was introduced in 1963 to describe available conformation space for protein structures. Subsequently, residues were observed in high-energy disallowed regions of the map. To unequivocally identify the locations of disallowed conformations of residues, we got 36 noise-free protein structures (resolution ≤1 Å, Rwork/Rfree ≤ 0.10). These stringent criteria were applied to rule out data or model errors or any crystallographic disorders. No disallowed conformation was found in the dataset. Further, we also examined disallowed conformations in a larger dataset (resolution ≤1.5 Å, devoid of any model errors, or disorders). The observed locations of disallowed residues are referred as disallowed spots. These spots include short loops of 3-5 residues, and locations where residues participate in disulfide bonding or intramolecular interactions or inter-molecular interactions with neighboring water, metals or ligands. Conformational sampling revealed that short loops in between secondary structures hardly have any opportunity to relieve from conformational strain. Residues involved in interactions, which provide energetic compensation for high-energy conformational states, were relieved from strain once the causative interaction was removed. The present study aims to identify disallowed spots in the native state of proteins, wherein residues are forced to be trapped in high-energy disallowed conformations. Moreover, it was also observed that pre-Pro, Ser, Asp, trans-Pro, Val, Asn & Gly have higher tendency to occur in disallowed conformation, which could be attributed to factors such as conformational restrictions, residue propensity of secondary structures and compensating sidechain and mainchain interactions, stabilizing turn-mimics.

Computational Insights into the Selecting Mechanism of α-Amylase Immobilized on Cellulose Nanocrystals: Unveiling the Potential of α-Amylases Immobilized for Efficient Poultry Feed Hydrolysis

The selection of an appropriate amylase for hydrolysis poultry feed is crucial for achieving improved digestibility and high-quality feed. Cellulose nanocrystals (CNCs), which are known for their high surface area, provide an excellent platform for enzyme immobilization. Immobilization greatly enhances the operational stability of α-amylases and the efficiency of starch bioconversion in poultry feeds. In this study, we immobilized two metagenome-derived α-amylases, PersiAmy2 and PersiAmy3, on CNCs and employed computational methods to characterize and compare the degradation efficiencies of these enzymes for poultry feed hydrolysis. Experimental in vitro bioconversion assessments were performed to validate the computational outcomes. Molecular docking studies revealed the superior hydrolysis performance of PersiAmy3, which displayed stronger electrostatic interactions with CNCs. Experimental characterization demonstrated the improved performance of both α-amylases after immobilization at high temperatures (80 °C). A similar trend was observed under alkaline conditions, with α-amylase activity reaching 88% within a pH range of 8.0 to 9.0. Both immobilized α-amylases exhibited halotolerance at NaCl concentrations up to 3 M and retained over 50% of their initial activity after 13 use cycles. Notably, PersiAmy3 displayed more remarkable improvements than PersiAmy2 following immobilization, including a significant increase in activity from 65 to 80.73% at 80 °C, an increase in activity to 156.48% at a high salinity of 3 M NaCl, and a longer half-life, indicating greater thermal stability within the range of 60 to 80 °C. These findings were substantiated by the in vitro hydrolysis of poultry feed, where PersiAmy3 generated 53.53 g/L reducing sugars. This comprehensive comparison underscores the utility of computational methods as a faster and more efficient approach for selecting optimal enzymes for poultry feed hydrolysis, thereby providing valuable insights into enhancing feed digestibility and quality.

Identification of novel potential inhibitor of thymidylate kinase from Variola virus

A hit compound was designed using Fragment Based Drug Designing (FBDD) approach, density functional theory (DFT) calculations were performed to find the structural and electronic properties. Additionally, pharmacokinetic properties were studied to understand the biological response of the compound. Docking studies were carried out with the protein structure of VrTMPK and HssTMPK with the reported hit compound. The favored docked complex was further carried to perform MD simulations; the RMSD plot and H-bond analysis was done for 200 ns. Also, MM-PBSA was done to understand the binding energy constituents and stability of the complex. A comparative study of the designed hit compound was done with FDA approved Tecovirimat. As a result, it was found that the reported compound (POX-A)is a potential selective inhibitor for Variola virus. Hence, it can be used to study further in vivo and in vitro behavior of the compound.Communicated by Ramaswamy H. Sarma.

Revisiting the Ramachandran plot based on statistical analysis of static and dynamic characteristics of protein structures

Ramachandran plots, which describe protein structures by plotting the dihedral angle pairs of the backbone on a two-dimensional plane, have played an important role in structural biology over the past few decades. However, despite continued discovery of new protein structures to date, the Ramachandran plot is still constructed by only a small number of data points, and further it cannot reflect the steric information of proteins. Here, we investigated the secondary structure of proteins in terms of static and dynamic characteristics. As for static feature, the Ramachandran plot was revisited for the dataset consisting of 9,148 non-redundant high-resolution protein structures released in the protein data bank until April 1, 2022. By calculating amino acid propensities, it was found that the proportion of secondary structures with respect to residue depth is directly related to their hydrophobicity. As for dynamic feature, normal mode analysis (NMA) based on an elastic network model (ENM) was carried out for the dataset using our KOSMOS web server (http://bioengineering.skku.ac.kr/kosmos/). All ENM-based NMA results were stored in the KOSMOS database, allowing researchers to use them in various ways. In this process, it was commonly found that high B-factors appeared at the edge of the alpha helix region, which was elucidated by introducing residue depth. In addition, by investigating the change in dihedral angle, it was possible to quantitatively survey the contribution of structural change of protein on the Ramachandran plot. In conclusion, our statistical analysis of protein characteristics will provide insight into a range of protein structural studies.

Constructing Potential Energy Surface with Correlated Theory for Dipeptides Using Molecular Tailoring Approach

We demonstrate a cost-effective alternative employing the fragment-based molecular tailoring approach (MTA) for building the potential energy surface (PES) for two dipeptides viz. alanine-alanine and alanine-proline employing correlated theory, with augmented Dunning basis sets. About 1369 geometries are generated for each test dipeptide by systematically varying the dihedral angles Φ ${{\rm{\Phi }}}$ and Ψ ${{{\Psi }}}$ . These conformational geometries are partially optimized by relaxing all the other Z-matrix parameters, fixing the values of Φ ${{\rm{\Phi }}}$ and Ψ ${{{\Psi }}}$ . The MP2 level PES is constructed from the MTA-energies of chemically intact geometries using minimal hardware. The fidelity of MP2/aug-cc-pVDZ level PES is brought out by comparing it with its full calculation counterpart. Further, we bring out the power of the method by reporting the MTA-based CCSD/aug-cc-pVDZ level PES for these two dipeptides containing 498 and 562 basis functions respectively.

Molecular dynamics simulation and structural analysis of aquaporin Z from an Antarctic Pseudomonas sp. strain AMS3

Aquaporin is a water channel protein that facilitates the movement of water across the cell membrane. Aquaporin from the Antarctic region has been noted for its psychrophilic properties and its ability to perform at a lower temperature but there remains limited understanding of the water mechanism of Antarctic Pseudomonas sp. strain AMS3 However, studies regarding aquaporin isolated from psychrophilic Pseudomonas sp. are still scattered. Recently, the genome sequence of an Antarctic Pseudomonas sp. strain AMS3 revealed a gene sequence encoding for a putative aquaporin designated as AqpZ1 AMS3. In this study, structure analysis and a molecular dynamics (MD) simulation of a predicted model of a fully hydrated aquaporin tetramer embedded in a lipid bilayer was performed at different temperatures for structural flexibility and stability analysis. The MD simulation results revealed that the structures were able to remain stable at low to medium temperatures. The protein was observed to have high flexibility in the loop region as compared to the helices region throughout the simulated temperatures. The selectivity filter and NPA motifs play a major role in solute selectivity and the pore radius of the protein. The structural and functional characterization of this psychrophilic aquaporin provides new insights for the future applications of this protein.Communicated by Ramaswamy H. Sarma.

Easy Not Easy: Comparative Modeling with High-Sequence Identity Templates

Homology modeling is the most common technique to build structural models of a target protein based on the structure of proteins with high-sequence identity and available high-resolution structures. This technique is based on the idea that protein structure shows fewer changes than sequence through evolution. While in this scenario single mutations would minimally perturb the structure, experimental evidence shows otherwise: proteins with high conformational diversity impose a limit of the paradigm of comparative modeling as the same protein sequence can adopt dissimilar three-dimensional structures. These cases present challenges for modeling; at first glance, they may seem to be easy cases, but they have a complexity that is not evident at the sequence level. In this chapter, we address the following questions: Why should we care about conformational diversity? How to consider conformational diversity when doing template-based modeling in a practical way?

Capturing a Crucial ‘Disorder-to-Order Transition’ at the Heart of the Coronavirus Molecular Pathology—Triggered by Highly Persistent, Interchangeable Salt-Bridges

The COVID-19 origin debate has greatly been influenced by genome comparison studies of late, revealing the emergence of the Furin-like cleavage site at the S1/S2 junction of the SARS-CoV-2 Spike (FLCSSpike) containing its 681PRRAR685 motif, absent in other related respiratory viruses. Being the rate-limiting (i.e., the slowest) step, the host Furin cleavage is instrumental in the abrupt increase in transmissibility in COVID-19, compared to earlier onsets of respiratory viral diseases. In such a context, the current paper entraps a ‘disorder-to-order transition’ of the FLCSSpike (concomitant to an entropy arrest) upon binding to Furin. The interaction clearly seems to be optimized for a more efficient proteolytic cleavage in SARS-CoV-2. The study further shows the formation of dynamically interchangeable and persistent networks of salt-bridges at the Spike–Furin interface in SARS-CoV-2 involving the three arginines (R682, R683, R685) of the FLCSSpike with several anionic residues (E230, E236, D259, D264, D306) coming from Furin, strategically distributed around its catalytic triad. Multiplicity and structural degeneracy of plausible salt-bridge network archetypes seem to be the other key characteristic features of the Spike–Furin binding in SARS-CoV-2, allowing the system to breathe—a trademark of protein disorder transitions. Interestingly, with respect to the homologous interaction in SARS-CoV (2002/2003) taken as a baseline, the Spike–Furin binding events, generally, in the coronavirus lineage, seems to have preference for ionic bond formation, even with a lesser number of cationic residues at their potentially polybasic FLCSSpike patches. The interaction energies are suggestive of characteristic metastabilities attributed to Spike–Furin interactions, generally to the coronavirus lineage, which appears to be favorable for proteolytic cleavages targeted at flexible protein loops. The current findings not only offer novel mechanistic insights into the coronavirus molecular pathology and evolution, but also add substantially to the existing theories of proteolytic cleavages.

A Rationalization of the Effect That TMAO, Glycine, and Betaine Exert on the Collapse of Elastin-like Polypeptides

Elastin-like polypeptides (ELPs) are soluble in water at low temperature, but, on increasing the temperature, they undergo a reversible and cooperative, coil-to-globule collapse transition. It has been shown that the addition to water of either trimethylamine N-oxide (TMAO), glycine, or betaine causes a significant decrease of T(collapse) in the case of a specific ELP. Traditional rationalizations of these phenomena do not work in the present case. We show that an alternative approach, grounded in the magnitude of the solvent-excluded volume effect and its temperature dependence (strictly linked to the translational entropy of solvent and co-solute molecules), is able to rationalize the occurrence of ELP collapse in water on raising the temperature, as well as the T(collapse) lowering caused by the addition to water of either TMAO, glycine, or betaine.

Toxoplasma gondii Tyrosine-Rich Oocyst Wall Protein: A Closer Look through an In Silico Prism

Toxoplasmosis is a global threat with significant zoonotic concern. The present in silico study was aimed at determination of bioinformatics features and immunogenic epitopes of a tyrosine-rich oocyst wall protein (TrOWP) of Toxoplasma gondii. After retrieving the amino acid sequence from UniProt database, several parameters were predicted including antigenicity, allergenicity, solubility and physico-chemical features, signal peptide, transmembrane domain, and posttranslational modifications. Following secondary and tertiary structure prediction, the 3D model was refined, and immunogenic epitopes were forecasted. It was a 25.57 kDa hydrophilic molecule with 236 residues, a signal peptide, and significant antigenicity scores. Moreover, several linear and conformational B-cell epitopes were present. Also, potential mouse and human cytotoxic T-lymphocyte (CTL) and helper T-lymphocyte (HTL) epitopes were predicted in the sequence. The findings of the present in silico study are promising as they render beneficial characteristics of TrOWP to be included in future vaccination experiments.

A Conceptual Framework for Integrating Cellular Protein Folding, Misfolding and Aggregation

How proteins properly fold and maintain solubility at the risk of misfolding and aggregation in the cellular environments still remains largely unknown. Aggregation has been traditionally treated as a consequence of protein folding (or misfolding). Notably, however, aggregation can be generally inhibited by affecting the intermolecular interactions leading to aggregation, independently of protein folding and conformation. We here point out that rigorous distinction between protein folding and aggregation as two independent processes is necessary to reconcile and underlie all observations regarding the combined cellular protein folding and aggregation. So far, the direct attractive interactions (e.g., hydrophobic interactions) between cellular macromolecules including chaperones and interacting polypeptides have been widely believed to mainly stabilize polypeptides against aggregation. However, the intermolecular repulsions by large excluded volume and surface charges of cellular macromolecules can play a key role in stabilizing their physically connected polypeptides against aggregation, irrespective of the connection types and induced conformational changes, underlying the generic intrinsic chaperone activity of cellular macromolecules. Such rigorous distinction and intermolecular repulsive force-driven aggregation inhibition by cellular macromolecules could give new insights into understanding the complex cellular protein landscapes that remain uncharted.

Determination of amino acids that favour the αL region using Ramachandran propensity plots. Implications for α-sheet as the possible amyloid intermediate

In amyloid diseases an insoluble amyloid fibril forms via a soluble oligomeric intermediate. It is this intermediate that mediates toxicity and it has been suggested, somewhat controversially, that it has the α-sheet structure. Nests and α-strands are similar peptide motifs in that alternate residues lie in the α_R and γ_L regions of the Ramachandran plot for nests, or α_R and α_L regions for α-strands. In nests a concavity is formed by the main chain NH atoms whereas in α-strands the main chain is almost straight. Using "Ramachandran propensity plots" to focus on the α_L/γ_L region, it is shown that glycine favours γ_L (82% of amino acids are glycine), but disfavours α_L (3% are glycine). Most charged and polar amino acids favour α_L with asparagine having by far the highest propensity. Thus, glycine favours nests but, contrary to common expectation, should not favour α-sheet. By contrast most charged or polar amino acids should favour α-sheet by their propensity for the α_L conformation, which is more discriminating amongst amino acids than the α_R conformation. Thus, these results suggest the composition of sequences that favour α-sheet formation and point towards effective prediction of α-sheet from sequence.

Structural modelling and thermostability of a serine protease inhibitor belonging to the Kunitz-BPTI family from the Rhipicephalus microplus tick

rBmTI-A is a recombinant serine protease inhibitor that belongs to the Kunitz-BPTI family and that was cloned from Rhipicephalus microplus tick. rBmTI-A has inhibitory activities on bovine trypsin, human plasma kallikrein, human neutrophil elastase and plasmin with dissociation constants in nM range. It is characterized by two inhibitory domains and each domain presents six cysteines that form three disulfide bonds, which contribute to the high stability of its structure. Previous studies suggest that serine protease inhibitor rBmTI-A has a protective potential against pulmonary emphysema in mice and anti-inflammatory potential. Besides that, rBmTI-A presented a potent inhibitory activity against in vitro vessel formation. In this study, the tertiary structure of rBmTI-A was modeled. The structure stabilization was evaluated by molecular dynamics analysis. Circular dichroism spectroscopy data corroborated the secondary structure found by the homology modelling. Also, in circular dichroism data it was shown a thermostability of rBmTI-A until approximately 70 °C, corroborated by inhibitory assays toward trypsin.

Asymmetric Catalysis Mediated by Synthetic Peptides, Version 2.0: Expansion of Scope and Mechanisms

Low molecular weight synthetic peptides have been demonstrated to be effective catalysts for an increasingly wide array of asymmetric transformations. In many cases, these peptide-based catalysts have enabled novel multifunctional substrate activation modes and unprecedented selectivity manifolds. These features, along with their ease of preparation, modular and tunable structures, and often biomimetic attributes make peptides well-suited as chiral catalysts and of broad interest. Many examples of peptide-catalyzed asymmetric reactions have appeared in the literature since the last survey of this broad field in Chemical Reviews (Chem. Rev. 2007, 107, 5759-5812). The overarching goal of this new Review is to provide a comprehensive account of the numerous advances in the field. As a corollary to this goal, we survey the many different types of catalytic reactions, ranging from acylation to C-C bond formation, in which peptides have been successfully employed. In so doing, we devote significant discussion to the structural and mechanistic aspects of these reactions that are perhaps specific to peptide-based catalysts and their interactions with substrates and/or reagents.

Secondary structure analysis of peptides with relevance to iron-sulfur cluster nesting

Peptides coordinated to iron-sulfur clusters, referred to as maquettes, represent a synthetic strategy for constructing biomimetic models of iron-sulfur metalloproteins. These maquettes have been successfully employed as building blocks of engineered heme-containing proteins with electron-transfer functionality; however, they have yet to be explored in reactivity studies. The concept of iron-sulfur nesting in peptides is a leading hypothesis in Origins-of-Life research as a plausible path to bridge the discontinuity between prebiotic chemical transformations and extant enzyme catalysis. Based on past biomimetic and biochemical research, we put forward a mechanism of maquette reconstitution that guides our development of computational tools and methodologies. In this study, we examined a key feature of the first stage of maquette formation, which is the secondary structure of aqueous peptide models using molecular dynamics simulations based on the AMBER99SB empirical force field. We compared and contrasted S…S distances, [2Fe-2S] and [4Fe-4S] nests, and peptide conformations via Ramachandran plots for dissolved Cys and Gly amino acids, the CGGCGGC 7-mer, and the GGCGGGCGGCGGW 16-mer peptide. Analytical tools were developed for following the evolution of secondary structural features related to [Fe-S] cluster nesting along 100 ns trajectories. Simulations demonstrated the omnipresence of peptide nests for preformed [2Fe-2S] clusters; however, [4Fe-4S] cluster nests were observed only for the 16-mer peptide with lifetimes of a few nanoseconds. The origin of the [4Fe-4S] nest and its stability was linked to a "kinked-ribbon" peptide conformation. Our computational approach lays the foundation for transitioning into subsequent stages of maquette reconstitution, those being the formation of iron ion/iron-sulfur coordinated peptides. © 2018 Wiley Periodicals, Inc.

Analysis of Germin-like Protein Genes (OsGLPs) Family in Rice Using Various In silico Approaches

Background:

Germin-like Proteins (GLPs) play an important role in various stresses. Rice contains 43 GLPs, among which many remain functionally unexplored. The computational analysis will provide significant insight into their function.

Objective:

To find various structural properties, functional importance, phylogeny and expression pattern of all OsGLPs using various bioinformatics tools.

Methods:

Physiochemical properties, sub-cellular localization, domain composition, Nglycosylation and Phosphorylation sites, and 3D structural models of the OsGLPs were predicted using various bioinformatics tools. Functional analysis was carried out with the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) and Blast2GO servers. The expression profile of the OsGLPs was predicted by retrieving the data for expression values from tissuespecific and hormonal stressed array libraries of RiceXPro. Their phylogenetic relationship was computed using Molecular and Evolutionary Genetic Analysis (MEGA6) tool.

Results:

Most of the OsGLPs are stable in the cellular environment with a prominent expression in the extracellular region (57%) and plasma membrane (33%). Besides, 3 basic cupin domains, 7 more were reported, among which NTTNKVGSNVTLINV, FLLAALLALASWQAI, and MASSSF were common to 99% of the sequences, related to bacterial pathogenicity, peroxidase activity, and peptide signal activity, respectively. Structurally, OsGLPs are similar but functionally they are diverse with novel enzymatic activities of oxalate decarboxylase, lyase, peroxidase, and oxidoreductase. Expression analysis revealed prominent activities in the root, endosperm, and leaves. OsGLPs were strongly expressed by abscisic acid, auxin, gibberellin, cytokinin, and brassinosteroid. Phylogenetically they showed polyphyletic origin with a narrow genetic background of 0.05%. OsGLPs of chromosome 3, 8, and 12 are functionally more important due to their defensive role against various stresses through co-expression strategy.

Conclusion:

The analysis will help to utilize OsGLPs in future food programs.

Natural selection based on coordination chemistry: computational assessment of [4Fe-4S]-maquettes with non-coded amino acids

Cysteine is the only coded amino acid in biology that contains a thiol functional group. Deprotonated thiolate is essential for anchoring iron-sulfur ([Fe-S]) clusters, as prosthetic groups to the protein matrix. [Fe-S] metalloproteins and metalloenzymes are involved in biological electron transfer, radical chemistry, small molecule activation and signalling. These are key metabolic and regulatory processes that would likely have been present in the earliest organisms. In the context of emergence of life theories, the selection and evolution of the cysteine-specific R-CH₂-SH side chain is a fascinating question to confront. We undertook a computational [4Fe-4S]-maquette modelling approach to evaluate how side chain length can influence [Fe-S] cluster binding and stability in short 7-mer and long 16-mer peptides, which contained either thioglycine, cysteine or homocysteine. Force field-based molecular dynamics simulations for [4Fe-4S] cluster nest formation were supplemented with density functional theory calculations of a ligand-exchange reaction between a preassembled cluster and the peptide. Secondary structure analysis revealed that peptides with cysteine are found with greater frequency nested to bind preformed [4Fe-4S] clusters. Additionally, the presence of the single methylene group in cysteine ligands mitigates the steric bulk, maintains the H-bonding and dipole network, and provides covalent Fe-S(thiolate) bonds that together create the optimal electronic and geometric structural conditions for [4Fe-4S] cluster binding compared to thioglycine or homocysteine ligands. Our theoretical work forms an experimentally testable hypothesis of the natural selection of cysteine through coordination chemistry.

The characterization of Thermotoga maritima Arginine Binding Protein variants demonstrates that minimal local strains have an important impact on protein stability

The Ramachandran plot is a versatile and valuable tool that provides fundamental information for protein structure determination, prediction, and validation. The structural/thermodynamic effects produced by forcing a residue to adopt a conformation predicted to be forbidden were here explored using Thermotoga maritima Arginine Binding Protein (TmArgBP) as model. Specifically, we mutated TmArgBP Gly52 that assumes a conformation believed to be strictly disallowed for non-Gly residues. Surprisingly, the crystallographic characterization of Gly52Ala TmArgBP indicates that the structural context forces the residue to adopt a non-canonical conformation never observed in any of the high-medium resolution PDB structures. Interestingly, the inspection of this high resolution structure demonstrates that only minor alterations occur. Nevertheless, experiments indicate that Gly52 replacements in TmArgBP produce destabilizations comparable to those observed upon protein truncation or dissection in domains. Notably, we show that force-fields commonly used in computational biology do not reproduce this non-canonical state. Using TmArgBP as model system we here demonstrate that the structural context may force residues to adopt conformations believed to be strictly forbidden and that barely detectable alterations produce major destabilizations. Present findings highlight the role of subtle strains in governing protein stability. A full understanding of these phenomena is essential for an exhaustive comprehension of the factors regulating protein structures.

Ramachandran maps for side chains in globular proteins

The Ramachandran plot for backbone ϕ,ψ-angles in a blocked monopeptide has played a central role in understanding protein structure. Curiously, a similar analysis for side chain χ-angles has been comparatively neglected. Instead, efforts have focused on compiling various types of side chain libraries extracted from proteins of known structure. Departing from this trend, the following analysis presents backbone-based maps of side chains in blocked monopeptides. As in the original ϕ,ψ-plot, these maps are derived solely from hard-sphere steric repulsion. Remarkably, the side chain biases exhibit marked similarities to corresponding biases seen in high-resolution protein structures. Consequently, some of the entropic cost for side chain localization in proteins is prepaid prior to the onset of folding events because conformational bias is built into the chain at the covalent level. Furthermore, side chain conformations are seen to experience fewer steric restrictions for backbone conformations in either the α or β basins, those map regions where repetitive ϕ,ψ-angles result in α-helices or strands of β-sheet, respectively. Here, these α and β basins are entropically favored for steric reasons alone; a blocked monopeptide is too short to accommodate the peptide hydrogen bonds that stabilize repetitive secondary structure. Thus, despite differing energetics, α/β-basins are favored for both monopeptides and repetitive secondary structure, underpinning an energetically unfrustrated compatibility between these two levels of protein structure.

Orientation effects on the nanoscale adsorption behavior of bone morphogenetic protein-2 on hydrophilic silicon dioxide

Bone Morphogenetic Protein-2 (BMP-2) is a growth factor associated with different developmental functions in regenerative medicine and tissue engineering. Because of its favorable properties for the development of bone and cartilage tissue, BMP-2 promotes the biocompatibility of medical implants. In this research, molecular dynamics simulations were implemented to simulate the interaction of BMP-2 with a flat hydrophilic silicon dioxide substrate, an important biomaterial for medical applications. We considered the influence of four orthogonal protein orientations on the adsorption behavior. Results showed that arginine and lysine were the main residues to interact with the silicon dioxide substrate, directly adsorbing onto the surface and overcoming water layers. However, between these charged residues, we observed a preference for arginine to adsorb. Orientations with the α-helix loop closer to the surface at the beginning of the simulations had greater loss of secondary structure as compared to the other configurations. Among all the orientations, the end-on B configuration had favorable adsorption characteristics with a binding energy of 14 000 kJ mol-1 and retention of 21.7% β-sheets as confirmed by the Ramachandran plots. This research provides new insights into the nanoscale interaction of BMP-2 and silicon dioxide substrate with applications in orthopedic implants and regenerative medicine.

Counteraction of denaturant-induced protein unfolding is a general property of stabilizing agents

DSC measurements on RNase A at neutral pH show that five stabilizing agents, namely trimethylamine N-oxide, glucose, sucrose, betaine and sodium sulfate, can counteract the destabilizing action of urea, sodium perchlorate, guanidinium chloride and guanidinium thiocyanate. This is an important finding inferring that counteraction has a common physical origin, regardless of the chemical differences among the stabilizing agents and among the destabilizing ones. A rationalization is provided grounded on the following line of reasoning: (a) the decrease in solvent-excluded volume effect is the main stabilizing contribution of the native state; (b) its magnitude increases on increasing the density of the aqueous solution; (c) the density increases significantly in the ternary solutions containing water, a stabilizing agent and a destabilizing one, as indicated by the present experimental data.

A novel peptide conformation: the γ-bend ribbon

Unlike the extensively investigated relationship between the peptide β-bend ribbon and its prototypical 310-helix conformation, the corresponding relationship between the narrower γ-bend ribbon and its regular γ-helix counterpart still remains to be studied, as the latter 3D-structures have not yet been experimentally authenticated. In this paper, we describe the results of the first characterization, both in the crystal state and in solution, of the γ-bend ribbon conformation using X-ray diffraction and FT-IR absorption, electronic CD and 2D-NMR spectroscopies applied to an appropriate set of synthetic, homo-chiral, sequential dipeptide oligomers based on (S)-Ala and the known γ-bend inducer, Cα-tetrasubstituted, N-alkylated α-amino acid residue (S)-Cα-methyl-azetidine-carboxylic acid.

Interspecies comparison of putative ligand binding sites of human, rat and mouse P-glycoprotein

Prior to the clinical phases of testing, safety, efficacy and pharmacokinetic profiles of lead compounds are evaluated in animal studies. These tests are primarily performed in rodents, such as mouse and rats. In order to reduce the number of animal experiments, computational models that predict the outcome of these studies and thus aid in prioritization of preclinical candidates are heavily needed. However, although computational models for human off-target interactions with decent quality are available, they cannot easily be transferred to rodents due to lack of respective data. In this study, we assess the transferability of human P-glycoprotein activity data for development of in silico models to predict in vivo effects in rats and mouse using a structure-based approach. P-glycoprotein (P-gp) is an ATP-dependent efflux transporter that transports xenobiotic compounds such as toxins and drugs out of cells and has a broad substrate and inhibitor specificity. Being mostly expressed at barriers, it influences the bioavailability of drugs and thus contributes also to toxicity. Comparison of the binding site interaction profiles of human, rat and mouse P-gp derived from docking studies with a set of common inhibitors suggests that the inhibitors share potentially similar binding modes. These findings encourage the use of in vitro human P-gp data for predicting in vivo effects in rodents and thus contributes to the 3Rs (Replace, Reduce and Refine) of animal experiments.

Conformational Design and Characterisation of a Truncated Diamine Oxidase from Arthrobacter globiformis

A functional mini protein can be developed by miniaturising its size. The minimisation technique provides an excellent model system for studying native enzymes, especially in creating an alternative novel biocatalyst. Miniaturised proteins may have enhanced stability, a crucial characteristic for large-scale production and industrial applications. In this study, a huge enzyme molecule, known as diamine oxidase (DAO, comprising 700 amino acids), was selected to undergo the process. By retaining the arrangement of the original functional sites of DAO in the fourth domain, a mini DAO can be designed via homology modelling. After several downsizing processes, a final configuration of 220 amino acids displayed high binding affinity towards histamine, a short-chain substrate that was catalysed by the parental DAO. The configuration also showed enhanced affinity towards a long-chain substrate known as spermidine. The gene for the designed protein was cloned and expressed in pET102/TOPO vector and overexpressed in E. coli BL21 (DE3). The new mini DAO had similar temperature tolerance and versatile substrates specificity characteristics as its parental protein. An active mini-protein with these characteristics is potentially useful for several applications such as detecting biogenic amines in the biological fluids and the environment that may give rise to health issues.

Comparing side chain packing in soluble proteins, protein-protein interfaces, and transmembrane proteins

We compare side chain prediction and packing of core and non-core regions of soluble proteins, protein-protein interfaces, and transmembrane proteins. We first identified or created comparable databases of high-resolution crystal structures of these 3 protein classes. We show that the solvent-inaccessible cores of the 3 classes of proteins are equally densely packed. As a result, the side chains of core residues at protein-protein interfaces and in the membrane-exposed regions of transmembrane proteins can be predicted by the hard-sphere plus stereochemical constraint model with the same high prediction accuracies (>90%) as core residues in soluble proteins. We also find that for all 3 classes of proteins, as one moves away from the solvent-inaccessible core, the packing fraction decreases as the solvent accessibility increases. However, the side chain predictability remains high (80% within 30°) up to a relative solvent accessibility, rSASA≲0.3, for all 3 protein classes. Our results show that ≈40% of the interface regions in protein complexes are "core", that is, densely packed with side chain conformations that can be accurately predicted using the hard-sphere model. We propose packing fraction as a metric that can be used to distinguish real protein-protein interactions from designed, non-binding, decoys. Our results also show that cores of membrane proteins are the same as cores of soluble proteins. Thus, the computational methods we are developing for the analysis of the effect of hydrophobic core mutations in soluble proteins will be equally applicable to analyses of mutations in membrane proteins.

Parameterization and Analysis of Peptide-Based Catalysts for the Atroposelective Bromination of 3-Arylquinazolin-4(3H)-ones

We report the development of a method to parameterize and predict the performance of structurally flexible β-turn-containing peptide catalysts, using the atroposelective bromination of 3-arylquinazolin-4(3H)-ones as a case study. The multivariate correlations obtained for tetrapeptides of two β-turn types, type I' pre-helical and type II' β-hairpin, indicate that although one conformer may be associated with a more dominant contribution to the observed enantioselectivity, it is possible that multiple conformers contribute to a complex transition state ensemble.

Everyone Is a Protagonist: Residue Conformational Preferences in High-Resolution Protein Structures

In many structural bioinformatics problems, there is a broad range of unanswered questions about protein dynamics and amino acid properties. Proteins are not strictly static objects, but rather populate ensembles of conformations. One way to understand these particularities is to analyze the information available in experimental databases. The Ramachandran plot, despite being more than half a century old, remains an utterly useful tool in the study of protein conformation. Based on its assumptions, we inspected a large data set (11,130 protein structures, amounting to 5,255,768 residues) and discriminated the conformational preferences of each residue type regarding their secondary structure participation. These data were studied for phi [Formula: see text], psi [Formula: see text], and side chain chi [Formula: see text] angles, being presented in non-Ramachandranian plots. In the largest analysis of protein conformation made so far, we propose an original plot to depict conformational preferences in relation to different secondary structure elements. Despite confirming previous observations, our results strongly support a unique character for each residue type, whereas also reinforcing the observation that side chains have a major contribution to secondary structure and, by consequence, on protein conformation. This information can be further used in the development of more robust methods and computational strategies for structural bioinformatics problems.

Dissection of Factors Affecting the Variability of the Peptide Bond Geometry and Planarity

Proteins frequently assume complex three-dimensional structures characterized by marginal thermodynamic stabilities. In this scenario, deciphering the folding code of these molecular giants with clay feet is a cumbersome task. Studies performed in last years have shown that the interplay between backbone geometry and local conformation has an important impact on protein structures. Although the variability of several geometrical parameters of protein backbone has been established, the role of the structural context in determining these effects has been hitherto limited to the valence bond angle τ (NC^αC). We here investigated the impact of different factors on the observed variability of backbone geometry and peptide bond planarity. These analyses corroborate the notion that the local conformation expressed in terms of (ϕ, ψ) dihedrals plays a predominant role in dictating the variability of these parameters. The impact of secondary structure is limited to bond angles which involve atoms that are usually engaged in H-bonds and, therefore, more susceptible to the structural context. Present data also show that the nature of the side chain has a significant impact on angles such as NC^αC^β and C^βC^αC. In conclusion, our analyses strongly support the use of variability of protein backbone geometry in structure refinement, validation, and prediction.

Packing in protein cores

Proteins are biological polymers that underlie all cellular functions. The first high-resolution protein structures were determined by x-ray crystallography in the 1960s. Since then, there has been continued interest in understanding and predicting protein structure and stability. It is well-established that a large contribution to protein stability originates from the sequestration from solvent of hydrophobic residues in the protein core. How are such hydrophobic residues arranged in the core; how can one best model the packing of these residues, and are residues loosely packed with multiple allowed side chain conformations or densely packed with a single allowed side chain conformation? Here we show that to properly model the packing of residues in protein cores it is essential that amino acids are represented by appropriately calibrated atom sizes, and that hydrogen atoms are explicitly included. We show that protein cores possess a packing fraction of [Formula: see text], which is significantly less than the typically quoted value of 0.74 obtained using the extended atom representation. We also compare the results for the packing of amino acids in protein cores to results obtained for jammed packings from discrete element simulations of spheres, elongated particles, and composite particles with bumpy surfaces. We show that amino acids in protein cores pack as densely as disordered jammed packings of particles with similar values for the aspect ratio and bumpiness as found for amino acids. Knowing the structural properties of protein cores is of both fundamental and practical importance. Practically, it enables the assessment of changes in the structure and stability of proteins arising from amino acid mutations (such as those identified as a result of the massive human genome sequencing efforts) and the design of new folded, stable proteins and protein-protein interactions with tunable specificity and affinity.

Factors affecting the amplitude of the τ angle in proteins: a revisitation

The protein folded state is the result of the fine balance of a variety of different forces. Even minor structural perturbations may have a significant impact on the stability of these macromolecules. Studies carried out in recent decades have led to the convergent view that proteins are endowed with a flexible spine. One of the open issues related to protein local backbone geometry is the identification of the factors that influence the amplitude of the τ (N—Cα—C) angle. Here, statistical analyses performed on an updated ensemble of X-ray protein structures by dissecting the contribution of the major factors that can potentially influence the local backbone geometry of proteins are reported. The data clearly indicate that the local backbone conformation has a prominent impact on the modulation of the τ angle. Therefore, a proper assessment of the impact of the other potential factors can only be appropriately evaluated when small (φ, ψ) regions are considered. Here, it is shown that when the contribution of the backbone conformation is removed by considering small (φ, ψ) areas, an impact of secondary structure, as defined byDSSP, and/or the residue type on τ is still detectable, although to a limited extent. Indeed, distinct τ-value distributions are detected for Pro/Gly and β-branched (Ile/Val) residues. The key role of the local backbone conformation highlighted here supports the use of variable local backbone geometry in protein refinement protocols.

Structure based classification for bile salt export pump (BSEP) inhibitors using comparative structural modeling of human BSEP

The bile salt export pump (BSEP) actively transports conjugated monovalent bile acids from the hepatocytes into the bile. This facilitates the formation of micelles and promotes digestion and absorption of dietary fat. Inhibition of BSEP leads to decreased bile flow and accumulation of cytotoxic bile salts in the liver. A number of compounds have been identified to interact with BSEP, which results in drug-induced cholestasis or liver injury. Therefore, in silico approaches for flagging compounds as potential BSEP inhibitors would be of high value in the early stage of the drug discovery pipeline. Up to now, due to the lack of a high-resolution X-ray structure of BSEP, in silico based identification of BSEP inhibitors focused on ligand-based approaches. In this study, we provide a homology model for BSEP, developed using the corrected mouse P-glycoprotein structure (PDB ID: 4M1M). Subsequently, the model was used for docking-based classification of a set of 1212 compounds (405 BSEP inhibitors, 807 non-inhibitors). Using the scoring function ChemScore, a prediction accuracy of 81% on the training set and 73% on two external test sets could be obtained. In addition, the applicability domain of the models was assessed based on Euclidean distance. Further, analysis of the protein-ligand interaction fingerprints revealed certain functional group-amino acid residue interactions that could play a key role for ligand binding. Though ligand-based models, due to their high speed and accuracy, remain the method of choice for classification of BSEP inhibitors, structure-assisted docking models demonstrate reasonably good prediction accuracies while additionally providing information about putative protein-ligand interactions.

Diversity of Secondary Structure in Catalytic Peptides with β-Turn-Biased Sequences

X-ray crystallography has been applied to the structural analysis of a series of tetrapeptides that were previously assessed for catalytic activity in an atroposelective bromination reaction. Common to the series is a central Pro-Xaa sequence, where Pro is either l- or d-proline, which was chosen to favor nucleation of canonical β-turn secondary structures. Crystallographic analysis of 35 different peptide sequences revealed a range of conformational states. The observed differences appear not only in cases where the Pro-Xaa loop-region is altered, but also when seemingly subtle alterations to the flanking residues are introduced. In many instances, distinct conformers of the same sequence were observed, either as symmetry-independent molecules within the same unit cell or as polymorphs. Computational studies using DFT provided additional insight into the analysis of solid-state structural features. Select X-ray crystal structures were compared to the corresponding solution structures derived from measured proton chemical shifts, 3J-values, and 1H-1H-NOESY contacts. These findings imply that the conformational space available to simple peptide-based catalysts is more diverse than precedent might suggest. The direct observation of multiple ground state conformations for peptides of this family, as well as the dynamic processes associated with conformational equilibria, underscore not only the challenge of designing peptide-based catalysts, but also the difficulty in predicting their accessible transition states. These findings implicate the advantages of low-barrier interconversions between conformations of peptide-based catalysts for multistep, enantioselective reactions.

Targeting the ubiquitin-conjugating enzyme E2D4 for cancer drug discovery-a structure-based approach

Cancer progression is a global burden. The incidence and mortality now reach 30 million deaths per year. Several pathways of cancer are under investigation for the discovery of effective therapeutics. The present study highlights the structural details of the ubiquitin protein 'Ubiquitin-conjugating enzyme E2D4' (UBE2D4) for the novel lead structure identification in cancer drug discovery process. The evaluation of 3D structure of UBE2D4 was carried out using homology modelling techniques. The optimized structure was validated by standard computational protocols. The active site region of the UBE2D4 was identified using computational tools like CASTp, Q-site Finder and SiteMap. The hydrophobic pocket which is responsible for binding with its natural receptor ubiquitin ligase CHIP (C-terminal of Hsp 70 interacting protein) was identified through protein-protein docking study. Corroborating the results obtained from active site prediction tools and protein-protein docking study, the domain of UBE2D4 which is responsible for cancer cell progression is sorted out for further docking study. Virtual screening with large structural database like CB_Div Set and Asinex BioDesign small molecular structural database was carried out. The obtained new ligand molecules that have shown affinity towards UBE2D4 were considered for ADME prediction studies. The identified new ligand molecules with acceptable parameters of docking, ADME are considered as potent UBE2D4 enzyme inhibitors for cancer therapy.

Steric interactions determine side-chain conformations in protein cores

We investigate the role of steric interactions in defining side-chain conformations in protein cores. Previously, we explored the strengths and limitations of hard-sphere dipeptide models in defining sterically allowed side-chain conformations and recapitulating key features of the side-chain dihedral angle distributions observed in high-resolution protein structures. Here, we show that modeling residues in the context of a particular protein environment, with both intra- and inter-residue steric interactions, is sufficient to specify which of the allowed side-chain conformations is adopted. This model predicts 97% of the side-chain conformations of Leu, Ile, Val, Phe, Tyr, Trp and Thr core residues to within 20°. Although the hard-sphere dipeptide model predicts the observed side-chain dihedral angle distributions for both Thr and Ser, the model including the protein environment predicts side-chain conformations to within 20° for only 60% of core Ser residues. Thus, this approach can identify the amino acids for which hard-sphere interactions alone are sufficient and those for which additional interactions are necessary to accurately predict side-chain conformations in protein cores. We also show that our approach can predict alternate side-chain conformations of core residues, which are supported by the observed electron density.

The effect of chirality and steric hindrance on intrinsic backbone conformational propensities: tools for protein design

The conformational propensities of amino acids are an amalgamation of sequence effects, environmental effects and underlying intrinsic behavior. Many have attempted to investigate neighboring residue effects to aid in our understanding of protein folding and improve structure prediction efforts, especially with respect to difficult to characterize states, such as disordered or unfolded states. Host-guest peptide series are a useful tool in examining the propensities of the amino acids free from the surrounding protein structure. Here, we compare the distributions of the backbone dihedral angles (φ/ψ) of the 20 proteogenic amino acids in two different sequence contexts using the AAXAA and GGXGG host-guest pentapeptide series. We further examine their intrinsic behaviors across three environmental contexts: water at 298 K, water at 498 K, and 8 M urea at 298 K. The GGXGG systems provide the intrinsic amino acid propensities devoid of any conformational context. The alanine residues in the AAXAA series enforce backbone chirality, thereby providing a model of the intrinsic behavior of amino acids in a protein chain. Our results show modest differences in φ/ψ distributions due to the steric constraints of the Ala side chains, the magnitudes of which are dependent on the denaturing conditions. One of the strongest factors modulating φ/ψ distributions was the protonation of titratable side chains, and the largest differences observed were in the amino acid propensities for the rarely sampled αL region.