Influence of medium and long range interactions in different structural classes of globular proteins

ARIP: A Tool for Precise Interatomic Contact Area and Volume Calculation in Proteins

The interplay patterns of amino acid residues are pivotal in determining the tertiary structure and flexibility of proteins, which in turn are intricately linked to their functionality and interactions with other molecules. Here, we introduce ARIP, a novel tool designed to identify contact residues within proteins. ARIP employs a modified version of the dr_sasa algorithm and an atomic overlap weighted algorithm to directly calculate the contact area and volume between atoms based on their van der Waals radius. It also allows for the selection of solvent radii, recognizing that not every atom in proteins can interact with water molecules. The solvent parameters were derived from the analysis of approximately 5000 protein and nucleic acid structures with water molecules determined using X-ray crystallography. One advantage of the modified algorithm is its capability to analyze multiple models within a single PDB file, making it suitable for molecular dynamic capture. The contact volume is symmetrically distributed between the interacting atoms, providing more informative results than contact area for the analysis of intra- and intermolecular interactions and the development of scoring functions. Furthermore, ARIP has been applied to four distinct cases: capturing key residue-residue contacts in NMR structures of P4HB, protein-drug binding of CYP17A1, protein-DNA binding of SPI1, and molecular dynamic simulations of BRD4.

Importance of Inter-residue Contacts for Understanding Protein Folding and Unfolding Rates, Remote Homology, and Drug Design

Inter-residue interactions in protein structures provide valuable insights into protein folding and stability. Understanding these interactions can be helpful in many crucial applications, including rational design of therapeutic small molecules and biologics, locating functional protein sites, and predicting protein-protein and protein-ligand interactions. The process of developing machine learning models incorporating inter-residue interactions has been improved recently. This review highlights the theoretical models incorporating inter-residue interactions in predicting folding and unfolding rates of proteins. Utilizing contact maps to depict inter-residue interactions aids researchers in developing computer models for detecting remote homologs and interface residues within protein-protein complexes which, in turn, enhances our knowledge of the relationship between sequence and structure of proteins. Further, the application of contact maps derived from inter-residue interactions is highlighted in the field of drug discovery. Overall, this review presents an extensive assessment of the significant models that use inter-residue interactions to investigate folding rates, unfolding rates, remote homology, and drug development, providing potential future advancements in constructing efficient computational models in structural biology.

Artificial Proteins Designed from G3LEA Contribute to Enhancement of Oxidation Tolerance in E. coli in a Chaperone-like Manner

G3LEA is a family of proteins that exhibit chaperone-like activity when under distinct stress. In previous research, DosH was identified as a G3LEA protein from model extremophile-Deinococcus radiodurans R1 with a crucial core HD domain consisting of eight 11-mer motifs. However, the roles of motifs participating in the process of resistance to stress and their underlying mechanisms remain unclear. Here, eight different proteins with tandem repeats of the same motif were synthesized, named Motif1-8, respectively, whose function and structure were discussed. In this way, the role of each motif in the HD domain can be comprehensively analyzed, which can help in finding possibly crucial amino acid sites. Circular dichroism results showed that all proteins were intrinsically ordered in phosphate buffer, and changed into more α-helical ordered structures with the addition of trifluoroethanol and glycerol. Transformants expressing artificial proteins had significantly higher stress resistance to oxidation, desiccation, salinity and freezing compared with the control group; E. coli with Motif1 and Motif8 had more outstanding performance in particular. Moreover, enzymes and membrane protein protection viability suggested that Motif1 and Motif8 had more positive influences on various molecules, demonstrating a protective role in a chaperone-like manner. Based on these results, the artificial proteins synthesized according to the rule of 11-mer motifs have a similar function to wildtype protein. Regarding the sequence in all motifs, there are more amino acids to produce H bonds and α-helices, and more amino acids to promote interaction between proteins in Motif1 and Motif8; in addition, considering linkers, there are possibly more amino acids forming α-helix and binding substrates in these two proteins, which potentially provides some ideas for us to design potential ideal stress-response elements for synthetic biology. Therefore, the amino acid composition of the 11-mer motif and linker is likely responsible for its biological function.

Protein-protein interaction prediction with deep learning: A comprehensive review

Most proteins perform their biological function by interacting with themselves or other molecules. Thus, one may obtain biological insights into protein functions, disease prevalence, and therapy development by identifying protein-protein interactions (PPI). However, finding the interacting and non-interacting protein pairs through experimental approaches is labour-intensive and time-consuming, owing to the variety of proteins. Hence, protein-protein interaction and protein-ligand binding problems have drawn attention in the fields of bioinformatics and computer-aided drug discovery. Deep learning methods paved the way for scientists to predict the 3-D structure of proteins from genomes, predict the functions and attributes of a protein, and modify and design new proteins to provide desired functions. This review focuses on recent deep learning methods applied to problems including predicting protein functions, protein-protein interaction and their sites, protein-ligand binding, and protein design.

rsRNASP: A residue-separation-based statistical potential for RNA 3D structure evaluation

Knowledge-based statistical potentials have been shown to be rather effective in protein 3-dimensional (3D) structure evaluation and prediction. Recently, several statistical potentials have been developed for RNA 3D structure evaluation, while their performances are either still at a low level for the test datasets from structure prediction models or dependent on the "black-box" process through neural networks. In this work, we have developed an all-atom distance-dependent statistical potential based on residue separation for RNA 3D structure evaluation, namely rsRNASP, which is composed of short- and long-ranged potentials distinguished by residue separation. The extensive examinations against available RNA test datasets show that rsRNASP has apparently higher performance than the existing statistical potentials for the realistic test datasets with large RNAs from structure prediction models, including the newly released RNA-Puzzles dataset, and is comparable to the existing top statistical potentials for the test datasets with small RNAs or near-native decoys. In addition, rsRNASP is superior to RNA3DCNN, a recently developed scoring function through 3D convolutional neural networks. rsRNASP and the relevant databases are available to the public.

Discrimination of driver and passenger mutations in epidermal growth factor receptor in cancer

Cancer is one of the most life-threatening diseases and mutations in several genes are the vital cause in tumorigenesis. Protein kinases play essential roles in cancer progression and specifically, epidermal growth factor receptor (EGFR) is an important target for cancer therapy. In this work, we have developed a method to classify single amino acid polymorphisms (SAPs) in EGFR into disease-causing (driver) and neutral (passenger) mutations using both sequence and structure based features of the mutation site by machine learning approaches. We compiled a set of 222 features and selected a set of 21 properties utilizing feature selection methods, for maximizing the prediction performance. In a set of 540 mutants, we obtained an overall classification accuracy of 67.8% with 10 fold cross validation using support vector machines. Further, the mutations have been grouped into four sets based on secondary structure and accessible surface area, which enhanced the overall classification accuracy to 80.2%, 81.9%, 77.9% and 75.1% for helix, strand, coil-buried and coil-exposed mutants, respectively. The method was tested with a blind dataset of 60 mutations, which showed an average accuracy of 85.4%. These accuracy levels are superior to other methods available in the literature for EGFR mutants, with an increase of more than 30%. Moreover, we have screened all possible single amino acid polymorphisms (SAPs) in EGFR and suggested the probable driver and passenger mutations, which would help in the development of mutation specific drugs for cancer treatment.

Accurate disulfide-bonding network predictions improve ab initio structure prediction of cysteine-rich proteins

MOTIVATION

Cysteine-rich proteins cover many important families in nature but there are currently no methods specifically designed for modeling the structure of these proteins. The accuracy of disulfide connectivity pattern prediction, particularly for the proteins of higher-order connections, e.g., >3 bonds, is too low to effectively assist structure assembly simulations.

RESULTS

We propose a new hierarchical order reduction protocol called Cyscon for disulfide-bonding prediction. The most confident disulfide bonds are first identified and bonding prediction is then focused on the remaining cysteine residues based on SVR training. Compared with purely machine learning-based approaches, Cyscon improved the average accuracy of connectivity pattern prediction by 21.9%. For proteins with more than 5 disulfide bonds, Cyscon improved the accuracy by 585% on the benchmark set of PDBCYS. When applied to 158 non-redundant cysteine-rich proteins, Cyscon predictions helped increase (or decrease) the TM-score (or RMSD) of the ab initio QUARK modeling by 12.1% (or 14.4%). This result demonstrates a new avenue to improve the ab initio structure modeling for cysteine-rich proteins.

AVAILABILITY AND IMPLEMENTATION

http://www.csbio.sjtu.edu.cn/bioinf/Cyscon/

CONTACT

zhng@umich.edu or hbshen@sjtu.edu.cn.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Conservation of inter-residue interactions and prediction of folding rates of domain repeats

Domains are the main structural and functional units of larger proteins. They tend to be contiguous in primary structure and can fold and function independently. It has been observed that 10-20% of all encoded proteins contain duplicated domains and the average pairwise sequence identity between them is usually low. In the present study, we have analyzed the structural similarity between domain repeats of proteins with known structures available in the Protein Data Bank using structure-based inter-residue interaction measures such as the number of long-range contacts, surrounding hydrophobicity, and pairwise interaction energy. We used RADAR program for detecting the repeats in a protein sequence which were further validated using Pfam domain assignments. The sequence identity between the repeats in domains ranges from 20 to 40% and their secondary structural elements are well conserved. The number of long-range contacts, surrounding hydrophobicity calculations and pairwise interaction energy of the domain repeats clearly reveal the conservation of 3-D structure environment in the repeats of domains. The proportions of mainchain-mainchain hydrogen bonds and hydrophobic interactions are also highly conserved between the repeats. The present study has suggested that the computation of these structure-based parameters will give better clues about the tertiary environment of the repeats in domains. The folding rates of individual domains in the repeats predicted using the long-range order parameter indicate that the predicted folding rates correlate well with most of the experimentally observed folding rates for the analyzed independently folded domains.

Cation-π interactions in β-lactamases: the role in structural stability

β-lactam group of antibiotics is the most widely used therapeutic molecules for treating bacterial infections. The main mode of bacterial resistance to β-lactams is by β-lactamases. In the present study, we report our results on the role of cation-π interactions in β-lactamases and their environmental preferences. The number of interactions formed by arginine is higher than lysine in the cationic group, while tyrosine is comparatively higher than phenylalanine and tryptophan in the π group. Our results indicate that cation-π interactions might play an important role in the global conformational stability of β-lactamases.

Investigations on the role of π-π interactions and π-π networks in eNOS and nNOS proteins

π-π Interactions play an important role in the stability of protein structures. In the present study, we have analyzed the influence of π-π interactions in eNOS and nNOS proteins. The contribution of these π-π interacting residues in sequential separation, secondary structure involvement, solvent accessibility and stabilization centers has been evaluated. π-π interactions stabilize the core regions within eNOS and nNOS proteins. π-π interacting residues are evolutionary conserved. There is a significant number of π-π interactions in spite of the lesser natural occurrences of π-residues in eNOS and nNOS proteins. In addition to π-π interactions, π residues also form π-π networks in both eNOS and nNOS proteins which might play an important role in the structural stability of these protein structures.

Aromatic-aromatic interactions: analysis of π-π interactions in interleukins and TNF proteins

Aromatic-aromatic hydrogen bonds are important in many areas of chemistry, biology and materials science. In this study we have analyzed the roles played by the π-π interactions in interleukins (ILs) and tumor necrosis factor (TNF) proteins. Majority of π-π interacting residues are conserved in ILs and TNF proteins. The accessible surface area calculations in these proteins reveal that these interactions might be important in stabilizing the inner core regions of these proteins. In addition to π-π interactions, the aromatic residues also form π-networks in ILs and TNF proteins. The results obtained in the present study indicate that π-π interactions and π-π networks play important roles in the structural stability of ILs and TNF proteins.

Arginine and Lysine interactions with π residues in metalloproteins

Metalloproteins have many different functions in cells such as enzymes; signal transduction, transport and storage proteins. About one third of all proteins require metals to carry out their functions. In the present study we have analyzed the roles played by Arg and Lys (cationic side chains) interactions with π (Phe, Tyr or Trp) residues and their role in the structural stability of metalloproteins. These interactions might play an important role in the global conformational stability in metalloproteins. In spite of its lower natural occurrence (1.76%) the number of Trp residues involved in energetically significant interactions is higher in metalloproteins.

EXPLORING THE ROLE OF C–H … π INTERACTIONS ON THE STRUCTURAL STABILITY OF ANTIMICROBIAL PEPTIDES

A computational analysis on the C – H … π interactions in a group of 53 antimicrobial peptides was investigated. A total of 162 C – H … π interactions were observed. Side-chain to side-chain C – H … π interactions are the predominant type of interactions in antimicrobial peptides data set. There was an average of one significant C – H … π interaction for every 7 residues in the antimicrobial peptides investigated. Long-range C – H … π interactions are the predominant type of interactions. The secondary structure preference, solvent accessibility and stabilization centers of these of C – H … π interacting residues were estimated. It is likely that the C – H … π interactions contribute significantly to the overall stability of antimicrobial peptides. These interactions were observed after a molecular dynamics study on these set of antimicrobial peptides using CHARMM force field.

Structural stability studies in adhesion molecules--role of cation-π interactions

Cell adhesion molecules are important for their various roles in many cellular events and responses. In the present study, we have analyzed the roles played by cation-π interactions in the structural stability of adhesion molecules. These interactions are mainly formed by long-range contacts. The occurrence of arginine is higher than lysine to form cation-π interactions. The secondary structure preferences of interacting residues are independent of amino acid class. Cation-π interactions might stabilize the interface between the terminus and core in this class of proteins. The results obtained in the present study will be useful in understanding the contribution of cation-π interactions to the overall stability of adhesion proteins.

Search for identical octapeptides in unrelated proteins: Structural plasticity revisited

Since proteins are dynamic in nature, they can alter their local structure in response to changes in their environment factors such as temperature, pH, phosphorylation, and binding of other small molecules. These conformational changes are extremely important for the correct folding and functioning of proteins. There are also a number of diseases associated with protein conformational change such as amyloid diseases. To stimulate research into the above factors which specify one conformation over another, different theoretical models have been proposed and tested against sequence similar distant structure protein fragments. In order to simplify the computational complexity of identifying conformational changes in proteins, various local sequence search algorithms were employed and the structural plasticity in unrelated proteins was examined by various research groups. In the present work, we revisit the mechanism of structural plasticity in unrelated proteins with increased number of structures in Protein Data Bank by comparing identical octapeptides in unrelated proteins with dictionary of protein secondary structure extracted from existing experimental data. Our goal is to bring out the influence of hydrophobic residues, hydrophilic residues, flanking residues, difference in secondary structural propensities of surrounding residues, difference in phi-psi angles and local and nonlocal interactions in identical octapeptides adopting different conformations. Also we have used surrounding hydrophobicity, environment dependent interaction energy, atomic mean force potential, structural unit contacts and difference profiles models to explore the factors which cause structural plasticity. The results discussed here may provide insights into protein folding, design and function.

Investigation of cation-π interactions in sugar-binding proteins

Cation-π interaction is a non-covalent binding force that plays a significant role in protein stability and drug-receptor interactions. In this work, we have investigated the structural role of cation-π interactions in sugar-binding proteins (SBPs). We observed 212 cation-π interactions in 53 proteins out of 59 SBPs in dataset. There is an average one energetically significant cation-π interaction for every 66 residues in SBPs. In addition, Arg is highly preferred to form cation-π interactions, and the average energy of Arg-Trp is high among six pairs. Long-range interactions are predominant in the analyzed cation-π interactions. Comparatively, all interaction pairs favor to accommodate in strand conformations. The analysis of solvent accessible area indicates that most of the aromatic residues are found on buried or partially buried whereas cationic residues were found mostly on the exposed regions of protein. The cation-π interactions forming residues were found that around 43% of cation-π residues had highly conserved with the conservation score ≥6. Almost cationic and π-residues equally share in the stabilization center. Sugar-binding site analysis in available complexes showed that the frequency of Trp and Arg is high, suggesting the potential role of these two residues in the interactions between proteins and sugar molecules. Our observations in this study could help to further understand the structural stability of SBPs.

Sequence and structural analysis of two designed proteins with 88% identity adopting different folds

Protein folding is a natural phenomenon by which a sequence of amino acids folds into a unique functional three-dimensional structure. Although the sequence code that governs folding remains a mystery, one can identify key inter-residue contacts responsible for a given topology. In nature, there are many pairs of proteins of a given length that share little or no sequence identity. Similarly, there are many proteins that share a common topology but lack significant evidence of homology. In order to tackle this problem, protein engineering studies have been used to determine the minimal number of amino acid residues that codes for a particular fold. In recent years, the coupling of theoretical models and experiments in the study of protein folding has resulted in providing some fruitful clues. He et al. have designed two proteins with 88% sequence identity, which adopt different folds and functions. In this work, we have systematically analysed these two proteins by performing pentapeptide search, secondary structure predictions, variation in inter-residue interactions and residue-residue pair preferences, surrounding hydrophobicity computations, conformational switching and energy computations. We conclude that the local secondary structural preference of the two designed proteins at the Nand C-terminal ends to adopt either coil or strand conformation may be a crucial factor in adopting the different folds. Early on during the process of folding, both proteins may choose different energetically favourable pathways to attain the different folds.

Influence of cation-pi interactions to the structural stability of prokaryotic and eukaryotic translation elongation factors

We have investigated the role of cation-pi interactions on translation elongation factors. In our investigation, an average of four significant cation-pi interactions were found, that is, an average of one cation-pi interaction per 44 residues in the ten elongation factors were observed. The analysis on the influence of short (< + or - 4), medium (> + or - 4 to < + or - 20) and long (>20) range contacts showed that cation-pi interactions are mainly formed by medium and long-range contacts. Arg-Tyr pair was found largest in number but energetic contribution of Arg-Trp pair was found most. Preferred secondary structural conformation analysis of the residues involved in cation-pi interaction indicates that the cationic Arg prefers to be in helix and Lys having equal probability for helix and strand, whereas the aromatic Phe and Trp were found mostly in helix while Tyr in strand regions. The cation-pi interaction residues involved in these proteins were found highly conserved with 48.86% residues having conservation score of > or = 6. Analysis of secondary structure preference of the energetically significant cation-pi residues in different solvent accessible range indicates that most of the pi residues are found buried or partially buried whereas cationic residues were found mostly at the protein surface. The results presented in this study will be useful for structural stability studies in translation elongation factors.

Evolutionary pressure on mitochondrial cytochrome b is consistent with a role of CytbI7T affecting longevity during caloric restriction

Background

Metabolism of energy nutrients by the mitochondrial electron transport chain (ETC) is implicated in the aging process. Polymorphisms in core ETC proteins may have an effect on longevity. Here we investigate the cytochrome b (cytb) polymorphism at amino acid 7 (cytbI7T) that distinguishes human mitochondrial haplogroup H from haplogroup U.

Principal Findings

We compared longevity of individuals in these two haplogroups during historical extremes of caloric intake. Haplogroup H exhibits significantly increased longevity during historical caloric restriction compared to haplogroup U (p = 0.02) while during caloric abundance they are not different. The historical effects of natural selection on the cytb protein were estimated with the software TreeSAAP using a phylogenetic reconstruction for 107 mammal taxa from all major mammalian lineages using 13 complete protein-coding mitochondrial gene sequences. With this framework, we compared the biochemical shifts produced by cytbI7T with historical evolutionary pressure on and near this polymorphic site throughout mammalian evolution to characterize the role cytbI7T had on the ETC during times of restricted caloric intake.

Significance

Our results suggest the relationship between caloric restriction and increased longevity in human mitochondrial haplogroup H is determined by cytbI7T which likely enhances the ability of water to replenish the Q_i binding site and decreases the time ubisemiquinone is at the Q_o site, resulting in a decrease in the average production rate of radical oxygen species (ROS).

Inter-residue interactions in protein structures exhibit power-law behavior

Inter-residue interactions play an essential role in driving protein folding, and analysis of these interactions increases our understanding of protein folding and stability and facilitates the development of tools for protein structure and function prediction. In this work, we systematically characterized the change of inter-residue interactions at various sequence separation cutoffs using two protein datasets. The first set included 100 diverse, nonredundant and high-resolution soluble protein structures, covering all four major structural classes, all-alpha, alpha/beta, alpha+beta, and all-beta; and the second set included 20 diverse, nonredundant and high-resolution membrane protein structures, representing 19 unique superfamilies. It was shown that the average number of inter-residue interactions in structures of both datasets displays the power-law behavior. Fitting parameters of the power-law function are directly related to the structural classes analyzed. These findings provided further insight into the distribution of short-, medium-, and long-range inter-residue interactions in both soluble and membrane proteins and could be used for protein structure prediction.

Investigations on unconventional hydrogen bonds in RNA binding proteins: The role of CH⋯OC interactions

We have investigated the roles played by C-H...O=C interactions in RNA binding proteins. There was an average of 78 CH...O=C interactions per protein and also there was an average of one significant CH...O=C interactions for every 6 residues in the 59 RNA binding proteins studied. Main chain-Main chain (MM) CH...O=C interactions are the predominant type of interactions in RNA binding proteins. The donor atom contribution to CH...O=C interactions was mainly from aliphatic residues. The acceptor atom contribution for MM CH...O=C interactions was mainly from Val, Phe, Leu, Ile, Arg and Ala. The secondary structure preference analysis of CH...O=C interacting residues showed that, Arg, Gln, Glu and Tyr preferred to be in helix, while Ala, Asp, Cys, Gly, Ile, Leu, Lys, Met, Phe, Trp and Val preferred to be in strand conformation. Most of the CH...O=C interacting polar amino acid residues were solvent exposed while, majority of the CH...O=C interacting non polar residues were excluded from the solvent. Long and medium-range CH...O=C interactions are the predominant type of interactions in RNA binding proteins. More than 50% of CH...O=C interacting residues had a higher conservation score. Significant percentage of CH...O=C interacting residues had one or more stabilization centers. Sixty-six percent of the theoretically predicted stabilizing residues were also involved in CH...O=C interactions and hence these residues may also contribute additional stability to RNA binding proteins.

Investigations on C–H⋯π interactions in RNA binding proteins

We have investigated the roles played by C-Hcdots, three dots, centeredpi interactions in RNA binding proteins. There was an average of 55 C-Hcdots, three dots, centeredpi interactions per protein and also there was an average of one significant C-Hcdots, three dots, centeredpi interaction for every nine residues in the 59 RNA binding proteins studied. Main-chain to side-chain C-Hcdots, three dots, centeredpi interactions is the predominant type of interactions in RNA binding proteins. The donor atom contribution to C-Hcdots, three dots, centeredpi interactions was mainly from Phe, Tyr, Trp, Pro, Gly, Lys, His and Ala residues. The acceptor atom contribution to main-chain to side-chain C-Hcdots, three dots, centeredpi and side-chain to side-chain C-Hcdots, three dots, centeredpi interactions was mainly from Phe and Tyr residues. On the contrary, the acceptor atoms of Trp residues contributed to all the four types of C-Hcdots, three dots, centeredpi interactions. Also, Trp contributed both donor and acceptor atoms in main-chain to side-chain, main-chain to side-chain five-member aromatic ring and side-chain to side-chain C-Hcdots, three dots, centeredpi interactions. The secondary structure preference analysis of C-Hcdots, three dots, centeredpi interacting residues showed that, Arg, Gln, Glu, His, Ile, Leu, Lys, Met, Phe and Tyr preferred to be in helix, while Ala, Asp, Cys, Gly, Trp and Val preferred to be in strand conformation. Long-range C-Hcdots, three dots, centeredpi interactions are the predominant type of interactions in RNA binding proteins. More than 50% of C-Hcdots, three dots, centeredpi interacting residues had a higher conservation score. Significant percentage of C-Hcdots, three dots, centeredpi interacting residues had one or more stabilization centers. Seven percent of the theoretically predicted stabilizing residues were also involved in C-Hcdots, three dots, centeredpi interactions and hence these residues may also contribute additional stability to RNA binding proteins.

Exploring the role of cation–π interactions in glycoproteins lipid-binding proteins and RNA-binding proteins

We have analyzed and compared the influence of cation-pi interactions in glycoproteins (GPs), lipid-binding proteins (LBPs) and RNA-binding proteins (RBPs) in this study. We observed that all the proteins included in the study had profound cation-pi interactions. There is an average of one energetically significant cation-pi interaction for every 71 residues in GPs, for every 58 residues in LBPs and for every 64 residues in RBPs. Long-range contacts are predominant in all the three types of proteins studied. The pair-wise cation-pi interaction energy between the positively charged and aromatic residues shows that Arg-Trp pair energy was the strongest among all six possible pairs in all the three types of proteins studied. There were considerable differences in the preference of cation-pi interacting residues to different secondary structure elements and ASA and these might contribute to differences in biochemical functions of GPs, LBPs and RBPs. It was interesting to note that all the five residues involved in cation-pi interactions were found to have stabilization centers in GPs, LBPs and RBPs. Majority of the cation-pi interacting residues investigated in the present study had a conservation score of 6, the cutoff value used to identify the stabilizing residues. A small percentage of cation-pi interacting residues were also present as stabilizing residues. The cation-pi interaction-forming residues play an important role in the structural stability of in GPs, LBPs and RBPs. The results obtained in this study will be helpful in further understanding the stability, specificity and differences in the biochemical functions of GPs, LBPs and RBPs.

Influence of cation-π interactions on RNA-binding proteins

The energy contribution due to cation-pi interactions has been computed for 37 RNA binding proteins. The contribution of these cation-pi interacting residues in sequential separation, secondary structure involvement, solvent accessibility, and stabilization centers has been evaluated. Sequential separation of the cation-pi involving residues show that, long range contacts predominates in all the proteins studied. Lys and Arg prefers to be in helical structures. Of the cation-pi interacting residues, Arg and Lys were in the exposed regions and the aromatic residues (Phe, Tyr and Trp) were in the buried and partially buried regions in the protein structures. Stabilization centers for these proteins showed that all the five residues found in cation-pi interactions are important in locating one or more of such centers. On the whole, the results presented in this work will be very useful for further investigations on the specificity and selectivity of RNA binding proteins and also for their structural studies.

Computation of non-covalent interactions in TNF proteins and interleukins

The roles played by the non-covalent interactions have been investigated for a set of six TNF proteins and nine Interleukins. The stabilizing residues have been identified by a consensus approach using the concepts of available surface area, medium and long-range interactions and conservation of amino acid residues. The cation-pi interactions have been computed based on a geometric approach such as distance and energy criteria. We identified an average of 1 energetically significant cation-pi interactions in every 94 residues in TNF proteins and 1 in every 62 residues in Interleukins. In TNF proteins, the cationic groups Lys preferred to be in helix while Arg preferred to be in strand regions while in Interleukins the Arg residues preferred to be in helix and Lys preferred to be in strand regions. From the available surface area calculations, we found that, almost all the cation and pi residues in TNF proteins and Interleukins were either in buried or partially buried regions and none of them in the exposed regions. Medium and long-range interactions were predominant in both TNF proteins and Interleukins. It was observed that the percentage of stabilizing centers were more in TNF proteins as compared to the Interleukins, while the percentage of conserved residues were more in Interleukins than in TNF proteins. In the stabilizing residues Lys was observed to be a stabilizing residue in both TNF proteins and Interleukins. Among the aromatic group, Phe was seen to be a stabilizing residue in both TNF and Interleukins. We suggest that this study on the computation of cation-pi interactions in TNF proteins and Interleukins would be very helpful in further understanding the structure, stability and functional similarity of these proteins.

Exploring the environmental preference of weak interactions in (α/β)8 barrel proteins

The environmental preference for the occurrence of noncanonical hydrogen bonding and cation-pi interactions, in a data set containing 71 nonredundant (alpha/beta)(8) barrel proteins, with respect to amino acid type, secondary structure, solvent accessibility, and stabilizing residues has been performed. Our analysis reveals some important findings, which include (a) higher contribution of weak interactions mediated by main-chain atoms irrespective of the amino acids involved; (b) domination of the aromatic amino acids among interactions involving side-chain atoms; (c) involvement of strands as the principal secondary structural unit, accommodating cross strand ion pair interaction and clustering of aromatic amino acid residues; (d) significant contribution to weak interactions occur in the solvent exposed areas of the protein; (e) majority of the interactions involve long-range contacts; (f) the preference of Arg is higher than Lys to form cation-pi interaction; and (g) probability of theoretically predicted stabilizing amino acid residues involved in weak interaction is higher for polar amino acids such as Trp, Glu, and Gln. On the whole, the present study reveals that the weak interactions contribute to the global stability of (alpha/beta)(8) TIM-barrel proteins in an environment-specific manner, which can possibly be exploited for protein engineering applications.

Structural analysis of cation-pi interactions in DNA binding proteins

Cation-pi interactions play an important role in the stability of protein structures. In this work, we have analyzed the influence of cation-pi interactions in DNA binding proteins. We observed cation-pi interactions in 45 out of 62 DNA binding proteins and there is no significant correlation between the number of amino acid residues and number of cation-pi interactions. These interactions are mainly formed by long-range contacts, and the role of short and medium-range contacts is minimal. The preference of Arg is higher than Lys to form cation-pi interactions. The pair-wise cation-pi interaction energy between aromatic and positively charged residues shows that Arg-Tyr energy is the strongest among the possible six pairs. The structural analysis of cation-pi interaction forming residues shows that Lys, Trp, and Tyr prefer to be in the binding site of protein-DNA complexes. Further, the accessible surface areas of cation-pi interaction forming cationic residues are significantly less than that of other residues. The preference of cation-pi interaction forming residues in different secondary structures shows that Lys prefers to be in strand and Phe prefers to be in turn regions. The results obtained in the present study will be useful in understanding the contribution of cation-pi interactions to the stability and specificity of protein-DNA complexes.

Structural analysis of residues involving cation-π interactions in different folding types of membrane proteins

Cation-pi interactions play an important role to the stability of protein structures. In our earlier work, we have analyzed the influence and energetic contribution of cation-pi interactions in three-dimensional structures of membrane proteins. In this work, we investigate the characteristic features of residues that are involved in cation-pi interactions. We have computed several parameters, such as surrounding hydrophobicity, number of long-range contacts, conservation score and normalized B-factor for all these residues and identified their location, whether in the membrane or at surface. We found that the cation-pi interactions are mainly formed by long-range interactions. The cationic residues involved in cation-pi interactions have higher surrounding hydrophobicity than their average values in the whole dataset and an opposite trend is observed for aromatic residues. In transmembrane helical proteins, except Phe, all other residues that are responsible for cation-pi interactions are highly conserved with other related protein sequences whereas in transmembrane strand proteins, an appreciable conservation is observed only for Arg. The analysis on the flexibility of residues reveals that the cation-pi interaction forming residues are more stable than other residues. The results obtained in the present study would be helpful to understand the role of cation-pi interactions in the structure and folding of membrane proteins.

A Statistical Model for Predicting Protein Folding Rates from Amino Acid Sequence with Structural Class Information

Prediction of protein folding rates from amino acid sequences is one of the most important challenges in molecular biology. In this work, I have related the protein folding rates with physical-chemical, energetic and conformational properties of amino acid residues. I found that the classification of proteins into different structural classes shows an excellent correlation between amino acid properties and folding rates of two- and three-state proteins, indicating the importance of native state topology in determining the protein folding rates. I have formulated a simple linear regression model for predicting the protein folding rates from amino acid sequences along with structural class information and obtained an excellent agreement between predicted and experimentally observed folding rates of proteins; the correlation coefficients are 0.99, 0.96 and 0.95, respectively, for all-alpha, all-beta and mixed class proteins. This is the first available method, which is capable of predicting the protein folding rates just from the amino acid sequence with the aid of generic amino acid properties and structural class information.

Inter-residue interactions in protein folding and stability

During the process of protein folding, the amino acid residues along the polypeptide chain interact with each other in a cooperative manner to form the stable native structure. The knowledge about inter-residue interactions in protein structures is very helpful to understand the mechanism of protein folding and stability. In this review, we introduce the classification of inter-residue interactions into short, medium and long range based on a simple geometric approach. The features of these interactions in different structural classes of globular and membrane proteins, and in various folds have been delineated. The development of contact potentials and the application of inter-residue contacts for predicting the structural class and secondary structures of globular proteins, solvent accessibility, fold recognition and ab initio tertiary structure prediction have been evaluated. Further, the relationship between inter-residue contacts and protein-folding rates has been highlighted. Moreover, the importance of inter-residue interactions in protein-folding kinetics and for understanding the stability of proteins has been discussed. In essence, the information gained from the studies on inter-residue interactions provides valuable insights for understanding protein folding and de novo protein design.

Characteristic features of amino acid residues in coiled-coil protein structures

Detailed analyses of protein structures provide an opportunity to understand conformation and function in terms of amino acid sequence and composition. In this work, we have systematically analyzed the characteristic features of the amino acid residues found in alpha-helical coiled-coils and, in so doing, have developed indices for their properties, conformational parameters, surrounding hydrophobicity and flexibility. As expected, there is preference for hydrophobic (Ala, Leu), positive (Lys, Arg) and negatively (Glu) charged residues in coiled-coil domains. However, the surrounding hydrophobicity of residues in coiled-coil domains is significantly less than that for residues in other regions of coiled-coil proteins. The analysis of temperature factors in coiled-coil proteins shows that the residues in these domains are more stable than those in other regions. Further, we have delineated the medium- and long-range contacts in coiled-coil domains and compared the results with those obtained for other (non-coiled-coil) parts of the same proteins and non-coiled-coil helical segments of globular proteins. The residues in coiled-coil domains are largely influenced by medium-range contacts, whereas long-range interactions play a dominant role in other regions of these same proteins as well as in non-coiled-coil helices. We have also revealed the preference of amino acid residues to form cation-pi interactions and we found that Arg is more likely to form such interactions than Lys. The parameters developed in this work can be used to understand the folding and stability of coiled-coil proteins in general.

Importance of hydrophobic cluster formation through long-range contacts in the folding transition state of two-state proteins

Understanding the folding pathways of proteins is a challenging task. The Phi value approach provides a detailed understanding of transition-state structures of folded proteins. In this work, we have computed the hydrophobicity associated with each residue in the folded state of 16 two-state proteins and compared the Phi values of each mutant residue. We found that most of the residues with high Phi value coincide with local maximum in surrounding hydrophobicity, or have nearby residues that show such maximum in hydrophobicity, indicating the importance of hydrophobic interactions in the transition state. We have tested our approach to different structural classes of proteins, such as alpha-helical, SH3 domains of all-beta proteins, beta-sandwich, and alpha/beta proteins, and we observed a good agreement with experimental results. Further, we have proposed a hydrophobic contact network pattern to relate the Phi values with long-range contacts, which will be helpful to understand the transition-state structures of folded proteins. The present approach could be used to identify potential hydrophobic clusters that may form through long-range contacts during the transition state.

Structural determinants of the rate of protein folding

To understand the mechanism of protein folding and to assist rational design of fast-folding, non-aggregating and stable artificial enzymes, it is essential to determine the structural parameters which govern the rate constants of folding, kf. It has been found that -logkf is a linear function of the so-called chain topology parameter (CTP) within the range of 10(-1)s(-1)< or = kf < or =10(8)s(-1). The correlation between -logkf and CTP is much improved than using previously published contact order (CO) method. It has been further suggested that short sequence separations may be preferred for the establishment of stable interactions for the design of novel artificial enzymes and the modification of slow-folding proteins with aggregating intermediates.

Role of hydrophobic clusters and long-range contact networks in the folding of (alpha/beta)8 barrel proteins

Analysis on the three dimensional structures of (alpha/beta)(8) barrel proteins provides ample light to understand the factors that are responsible for directing and maintaining their common fold. In this work, the hydrophobically enriched clusters are identified in 92% of the considered (alpha/beta)(8) barrel proteins. The residue segments with hydrophobic clusters have high thermal stability. Further, these clusters are formed and stabilized through long-range interactions. Specifically, a network of long-range contacts connects adjacent beta-strands of the (alpha/beta)(8) barrel domain and the hydrophobic clusters. The implications of hydrophobic clusters and long-range networks in providing a feasible common mechanism for the folding of (alpha/beta)(8) barrel proteins are proposed.

Influence of medium- and long-range interactions in different folding types of globular proteins

Recognition of protein fold from amino acid sequence is a challenging task. The structure and stability of proteins from different fold are mainly dictated by inter-residue interactions. In our earlier work, we have successfully used the medium- and long-range contacts for predicting the protein folding rates, discriminating globular and membrane proteins and for distinguishing protein structural classes. In this work, we analyze the role of inter-residue interactions in commonly occurring folds of globular proteins in order to understand their folding mechanisms. In the medium-range contacts, the globin fold and four-helical bundle proteins have more contacts than that of DNA-RNA fold although they all belong to all-alpha class. In long-range contacts, only the ribonuclease fold prefers 4-10 range and the other folding types prefer the range 21-30 in alpha/beta class proteins. Further, the preferred residues and residue pairs influenced by these different folds are discussed. The information about the preference of medium- and long-range contacts exhibited by the 20 amino acid residues can be effectively used to predict the folding type of each protein.

Important amino acid properties for determining the transition state structures of two-state protein mutants

Understanding the mechanism in the folding pathways of proteins is an important problem in molecular biology. The Phi-value analysis provides insight into the transition state structures during protein folding. In this work, we have analyzed the relationship between the observed Phi values upon mutations in two-state proteins (FK506 binding protein, chymotrypsin inhibitor and src SH3 domain) and the changes in 48 various physico-chemical, energetic and conformational properties. We found that the classification of mutations based on solvent accessibility improved the correlation significantly. The relationship between conformational properties and Phi values determines the presence/absence of secondary structures in the transition state. In buried mutations, the physical properties volume, shape and flexibility, and the thermodynamic properties enthalpy, entropy and free-energy change have significant correlation with Phi. The short and medium-range non-bonded energy in partially buried mutations and average long-range contacts in exposed mutations showed a strong correlation with Phi values. Multiple regression analysis incorporating combinations of three properties from among all possible combinations of the 48 properties increased the correlation coefficient up to 0.99, by an average rise of 20% for all the data sets. Information about local sequence and structure is more important in surface mutations than those in buried mutations for explaining the transition state structures of two-state proteins. Further, the implications of our results for understanding the process of protein folding have been discussed.