Bioinformatics methods to predict protein structure and function. A practical approach

Structures prediction and replica exchange molecular dynamics simulations of α-synuclein: A case study for intrinsically disordered proteins

In recent years, a variety of three-dimensional structure prediction tools, including AlphaFold2, AlphaFold3, I-TASSER, C-I-TASSER, Phyre2, ESMFold, and RoseTTAFold, have been employed in the investigation of intrinsically disordered proteins. However, a comprehensive validation of these tools specifically for intrinsically disordered proteins has yet to be conducted. In this study, we utilize AlphaFold2, AlphaFold3, I-TASSER, C-I-TASSER, Phyre2, ESMFold, and RoseTTAFold to predict the structure of a model intrinsically disordered α-synuclein protein. Additionally, extensive replica exchange molecular dynamics simulations of the intrinsically disordered protein are conducted. The resulting structures from both structure prediction tools and replica exchange molecular dynamics simulations are analyzed for radius of gyration, secondary and tertiary structure properties, as well as Cα and Hα chemical shift values. A comparison of the obtained results with experimental data reveals that replica exchange molecular dynamics simulations provide results in excellent agreement with experimental observations. However, none of the structure prediction tools utilized in this study can fully capture the structural characteristics of the model intrinsically disordered protein. This study shows that a cluster of ensembles are required for intrinsically disordered proteins. Artificial-intelligence based structure prediction tools such as AlphaFold3 and C-I-TASSER could benefit from stochastic sampling or Monte Carlo simulations for generating an ensemble of structures for intrinsically disordered proteins.

Structural Analysis of the Drosophila melanogaster GSTome

Glutathione transferase (GST) is a superfamily of ubiquitous enzymes, multigenic in numerous organisms and which generally present homodimeric structures. GSTs are involved in numerous biological functions such as chemical detoxification as well as chemoperception in mammals and insects. GSTs catalyze the conjugation of their cofactor, reduced glutathione (GSH), to xenobiotic electrophilic centers. To achieve this catalytic function, GSTs are comprised of a ligand binding site and a GSH binding site per subunit, which is very specific and highly conserved; the hydrophobic substrate binding site enables the binding of diverse substrates. In this work, we focus our interest in a model organism, the fruit fly Drosophila melanogaster (D. mel), which comprises 42 GST sequences distributed in six classes and composing its GSTome. The goal of this study is to describe the complete structural GSTome of D. mel to determine how changes in the amino acid sequence modify the structural characteristics of GST, particularly in the GSH binding sites and in the dimerization interface. First, we predicted the 3D atomic structures of each GST using the AlphaFold (AF) program and compared them with X-ray crystallography structures, when they exist. We also characterized and compared their global and local folds. Second, we used multiple sequence alignment coupled with AF-predicted structures to characterize the relationship between the conservation of amino acids in the sequence and their structural features. Finally, we applied normal mode analysis to estimate thermal B-factors of all GST structures of D. mel. Particularly, we extracted flexibility profiles of GST and identify key residues and motifs that are systematically involved in the ligand binding/dimerization processes and thus playing a crucial role in the catalytic function. This methodology will be extended to guide the in silico design of synthetic GST with new/optimal catalytic properties for detoxification applications.

A comprehensive review on genomics, systems biology and structural biology approaches for combating antimicrobial resistance in ESKAPE pathogens: computational tools and recent advancements

In recent decades, antimicrobial resistance has been augmented as a global concern to public health owing to the global spread of multidrug-resistant strains from different ESKAPE pathogens. This alarming trend and the lack of new antibiotics with novel modes of action in the pipeline necessitate the development of non-antibiotic ways to treat illnesses caused by these isolates. In molecular biology, computational approaches have become crucial tools, particularly in one of the most challenging areas of multidrug resistance. The rapid advancements in bioinformatics have led to a plethora of computational approaches involving genomics, systems biology, and structural biology currently gaining momentum among molecular biologists since they can be useful and provide valuable information on the complex mechanisms of AMR research in ESKAPE pathogens. These computational approaches would be helpful in elucidating the AMR mechanisms, identifying important hub genes/proteins, and their promising targets together with their interactions with important drug targets, which is a crucial step in drug discovery. Therefore, the present review aims to provide holistic information on currently employed bioinformatic tools and their application in the discovery of multifunctional novel therapeutic drugs to combat the current problem of AMR in ESKAPE pathogens. The review also summarizes the recent advancement in the AMR research in ESKAPE pathogens utilizing the in silico approaches.

Bioinformatic characterization of a triacylglycerol lipase produced by Aspergillus flavus isolated from the decaying seed of Cucumeropsis mannii

Lipases are enzymes of industrial importance responsible for the hydrolysis of ester bonds of triglycerides. A lipolytic fungus was isolated and subsequently identified based on the ITS sequence analysis as putative Aspergillus flavus with accession number LC424503. The gene coding for extracellular triacylglycerol lipase was isolated from Aspergillus flavus species, sequenced, and characterised using bioinformatics tools. An open reading frame of 420 amino acid sequence was obtained and designated as Aspergillus flavus lipase (AFL) sequence. Alignment of the amino acid sequence with other lipases revealed the presence GHSLG sequence which is the lipase consensus sequence Gly-X1-Ser-X2-Gly indicating that it a classical lipase. A catalytic active site lid domain composed of TYITDTIIDLS amino acids sequence was also revealed. This lid protects the active site, control the catalytic activity and substrate selectivity in lipases. The 3-Dimensional structural model shared 34.08% sequence identity with a lipase from Yarrowia lipolytica covering 272 amino acid residues of the template model. A search of the lipase engineering database using AFL sequence revealed that it belongs to the class GX-lipase, superfamily abH23 and homologous family abH23.02, molecular weight and isoelectric point values of 46.95 KDa and 5.7, respectively. N-glycosylation sites were predicted at residues 164, 236 and 333, with potentials of 0.7250, 0.7037 and 0.7048, respectively. O-glycosylation sites were predicted at residues 355, 358, 360 and 366. A signal sequence of 37 amino acids was revealed at the N-terminal of the polypeptide. This is a short peptide sequence that marks a protein for transport across the cell membrane and indicates that AFL is an extracellular lipase. The findings on the structural and molecular properties of Aspergillus flavus lipase in this work will be crucial in future studies aiming at engineering the enzyme for biotechnology applications.Communicated by Ramaswamy H. Sarma.

Molecular Evolution Bioinformatics Toward Structural Biology of TRPV1-4 Channels

Bioinformatics is a very resourceful tool to understand evolution of membrane proteins, such as transient receptor potential channels. Expert bioinformatics users rely on specialized scripting and programming skills. Several web servers and standalone tools are available for nonadvanced users willing to develop projects to understand their system of choice. In this case, we present a desktop-based protocol to develop evostructural hypotheses based on basic bioinformatics skills and resources, specifically for a small subgroup of TRPV channels, which can be further implemented for larger datasets.

Molecular and in silico analyses validates pathogenicity of homozygous mutations in the NPR2 gene underlying variable phenotypes of Acromesomelic dysplasia, type Maroteaux

Homozygous and/or heterozygous loss of function mutations in the natriuretic peptide receptor B (NPR2) have been reported in causing acromesomelic dysplasia, type Maroteaux with variable clinical features and idiopathic short stature with nonspecific skeletal deformities. On the other hand, gain of function mutations in the same gene result in overgrowth disorder suggesting that NPR2 and its ligand, natriuretic peptide precursor C (CNP), are the key players of endochondral bone growth. However, the precise mechanism behind phenotypic variability of the NPR2 mutations is not fully understood so far. In the present study, three consanguineous families of Pakistani origin (A, B, C) with variable phenotypes of acromesomelic dysplasia, type Maroteaux were evaluated at clinical and molecular levels. Linkage analysis followed by Sanger sequencing of the NPR2 gene revealed three homozygous mutations including p.(Leu314 Arg), p.(Arg371*), and p.(Arg1032*) in family A, B and C, respectively. In silico structural and functional analyses substantiated that a novel missense mutation [p.(Leu314 Arg)] in family A allosterically affects binding of NPR2 homodimer to its ligand (CNP) which ultimately results in defective guanylate cyclase activity. A nonsense mutation [p.(Arg371*)] in family B entirely removed the transmembrane domain, protein kinase domain and guanylate cyclase domains of the NPR2 resulting in abolishing its guanylate cyclase activity. Another novel mutation [p.(Arg1032*)], found in family C, deteriorated the guanylate cyclase domain of the protein and probably plundered its guanylate cyclase activity. These results suggest that guanylate cyclase activity is the most critical function of the NPR2 and phenotypic severity of the NPR2 mutations is proportional to the reduction in its guanylate cyclase activity.

Bioinformatics-based tools in drug discovery: the cartography from single gene to integrative biological networks

Originally developed for the analysis of biological sequences, bioinformatics has advanced into one of the most widely recognized domains in the scientific community. Despite this technological evolution, there is still an urgent need for nontoxic and efficient drugs. The onus now falls on the 'omics domain to meet this need by implementing bioinformatics techniques that will allow for the introduction of pioneering approaches in the rational drug design process. Here, we categorize an updated list of informatics tools and explore the capabilities of integrative bioinformatics in disease control. We believe that our review will serve as a comprehensive guide toward bioinformatics-oriented disease and drug discovery research.

Structure and sequence based functional annotation of Zika virus NS2b protein: Computational insights

While Zika virus (ZIKV) outbreaks are a growing concern for global health, a deep understanding about the virus is lacking. Here we report a contribution to the basic science on the virus- a detailed computational analysis of the non structural protein NS2b. This protein acts as a cofactor for the NS3 protease (NS3Pro) domain that is important on the viral life cycle, and is an interesting target for drug development. We found that ZIKV NS2b cofactor is highly similar to other virus within the Flavivirus genus, especially to West Nile Virus, suggesting that it is completely necessary for the protease complex activity. Furthermore, the ZIKV NS2b has an important role to the function and stability of the ZIKV NS3 protease domain even when presents a low conservation score. In addition, ZIKV NS2b is mostly rigid, which could imply a non dynamic nature in substrate recognition. Finally, by performing a computational alanine scanning mutagenesis, we found that residues Gly 52 and Asp 83 in the NS2b could be important in substrate recognition.

In Silico Design of a Chimeric Protein Containing Antigenic Fragments of Helicobacter pylori; A Bioinformatic Approach

Helicobacter pylori is a global health problem which has encouraged scientists to find new ways to diagnose, immunize and eradicate the H. pylori infection. In silico studies are a promising approach to design new chimeric antigen having the immunogenic potential of several antigens. In order to obtain such benefit in H. pylori vaccine study, a chimeric gene containing four fragments of FliD sequence (1-600 bp), UreB (327-334 bp),VacA (744-805 bp) and CagL(51-100 bp) which have a high density of B- and T-cell epitopes was designed. The secondary and tertiary structures of the chimeric protein and other properties such as stability, solubility and antigenicity were analyzed. The in silico results showed that after optimizing for the purpose of expression in Escherichia coli BL21, the solubility and antigenicity of the construct fragments were highly retained. Most regions of the chimeric protein were found to have a high antigenic propensity and surface accessibility. These results would be useful in animal model application and accounted for the development of an epitope-based vaccine against the H. pylori.

Dissecting domain-specific evolutionary pressure profiles of transient receptor potential vanilloid subfamily members 1 to 4

The transient receptor potential vanilloid family includes four ion channels–TRPV1, TRPV2, TRPV3 and TRPV4–that are represented within the vertebrate subphylum and involved in several sensory and physiological processes. These channels are related to adaptation to the environment, and probably under strong evolutionary pressure. Using multiple sequence alignments as source for evolutionary, bioinformatics and statistical analysis, we have analyzed the evolutionary profiles for TRPV1, TRPV2, TRPV3 and TRPV4. The evolutionary pressure exerted over vertebrate TRPV2 sequences compared to the other channels argues for a positive selection profile for TRPV2 compared to TRPV1, TRPV3 and TRPV4. We have analyzed the selective pressure on specific protein domains, observing a common selective pressure trend for the common TRPV scaffold, consisting of the ankyrin repeat domain, the membrane proximal domain, the transmembrane domain, and the TRP domain. Through a more detailed analysis we have identified evolutionary constraints involved in the subunit contact at the transmembrane domain level. Performing evolutionary comparison, we have translated specific channel structural information such as the transmembrane topology, and the interaction between the membrane proximal domain and the TRP box. We have also identified potential common regulatory domains among all TRPV1-4 members, such as protein-protein, lipid-protein and vesicle trafficking domains.

In silico analysis of chimeric espA, eae and tir fragments of Escherichia coli O157:H7 for oral immunogenic applications

Background

In silico techniques are highly suited for both the discovery of new and development of existing vaccines. Enterohemorrhagic Escherichia coli O157:H7 (EHEC) exhibits a pattern of localized adherence to host cells, with the formation of microcolonies, and induces a specific histopathological lesion (attaching/effacing). The genes encoding the products responsible for this phenotype are clustered on a 35-kb pathogenicity island. Among these proteins, Intimin, Tir, and EspA, which are expressed by attaching-effacing genes, are responsible for the attachment to epithelial cell that leads to lesions.

Results

We designed synthetic genes encoding the carboxy-terminal fragment of Intimin, the middle region of Tir and the carboxy-terminal part of EspA. These multi genes were synthesized with codon optimization for a plant host and were fused together by the application of four repeats of five hydrophobic amino acids as linkers. The structure of the synthetic construct gene, its mRNA and deduced protein and their stabilities were analyzed by bioinformatic software. Furthermore, the immunogenicity of this multimeric recombinant protein consisting of three different domains was predicted.

Conclusion

a structural model for a chimeric gene from LEE antigenic determinants of EHEC is presented. It may define accessibility, solubility and immunogenecity.

A comparative study of the reported performance of ab initio protein structure prediction algorithms

Protein structure prediction is one of the major challenges in bioinformatics today. Throughout the past five decades, many different algorithmic approaches have been attempted, and although progress has been made the problem remains unsolvable even for many small proteins. While the general objective is to predict the three-dimensional structure from primary sequence, our current knowledge and computational power are simply insufficient to solve a problem of such high complexity. Some prediction algorithms do, however, appear to perform better than others, although it is not always obvious which ones they are and it is perhaps even less obvious why that is. In this review, the reported performance results from 18 different recently published prediction algorithms are compared. Furthermore, the general algorithmic settings most likely responsible for the difference in the reported performance are identified, and the specific settings of each of the 18 prediction algorithms are also compared. The average normalized r.m.s.d. scores reported range from 11.17 to 3.48. With a performance measure including both r.m.s.d. scores and CPU time, the currently best-performing prediction algorithm is identified to be the I-TASSER algorithm. Two of the algorithmic settings--protein representation and fragment assembly--were found to have definite positive influence on the running time and the predicted structures, respectively. There thus appears to be a clear benefit from incorporating this knowledge in the design of new prediction algorithms.

'Crystal lattice engineering,' an approach to engineer protein crystal contacts by creating intermolecular symmetry: crystallization and structure determination of a mutant human RNase 1 with a hydrophobic interface of leucines

A protein crystal lattice consists of surface contact regions, where the interactions of specific groups play a key role in stabilizing the regular arrangement of the protein molecules. In an attempt to control protein incorporation in a crystal lattice, a leucine zipper-like hydrophobic interface (comprising four leucine residues) was introduced into a helical region (helix 2) of the human pancreatic ribonuclease 1 (RNase 1) that was predicted to form a suitable crystallization interface. Although crystallization of wild-type RNase 1 has not yet been reported, the RNase 1 mutant having four leucines (4L-RNase 1) was successfully crystallized under several different conditions. The crystal structures were subsequently determined by X-ray crystallography by molecular replacement using the structure of bovine RNase A. The overall structure of 4L-RNase 1 is quite similar to that of the bovine RNase A, and the introduced leucine residues formed the designed crystal interface. To characterize the role of the introduced leucine residues in crystallization of RNase 1 further, the number of leucines was reduced to three or two (3L- and 2L-RNase 1, respectively). Both mutants crystallized and a similar hydrophobic interface as in 4L-RNase 1 was observed. A related approach to engineer crystal contacts at helix 3 of RNase 1 (N4L-RNase 1) was also evaluated. N4L-RNase 1 also successfully crystallized and formed the expected hydrophobic packing interface. These results suggest that appropriate introduction of a leucine zipper-like hydrophobic interface can promote intermolecular symmetry for more efficient protein crystallization in crystal lattice engineering efforts.

A consensus procedure improving solvent accessibility prediction

Prediction methods of structural features in 1D represent a useful tool for the understanding of folding, classification, and function of proteins, and, in particular, for 3D structure prediction. Among the structural aspects characterizing a protein, solvent accessibility has received great attention in recent years. The available methods proposed for predicting accessibility have never considered the combination of the results deriving from different methods to construct a consensus prediction able to provide more reliable results. A consensus approach that increases prediction accuracy using three high-performance methods is described. The results of our method for three different protein data sets show that up to 3.0% improvement in prediction accuracy of solvent accessibility may be obtained by a consensus approach. The improvement also extends to the correlation coefficient. Application of our consensus approach to the accessibility prediction using only three prediction methods gives results better than single methods combined for consensus formation. Currently, the scarce availability of predictors with similar parameters defining solvent accessibility hinders the testing of other methods in our consensus procedure.

Comparative modelling of protein structure and its impact on microbial cell factories

Comparative modeling is becoming an increasingly helpful technique in microbial cell factories as the knowledge of the three-dimensional structure of a protein would be an invaluable aid to solve problems on protein production. For this reason, an introduction to comparative modeling is presented, with special emphasis on the basic concepts, opportunities and challenges of protein structure prediction. This review is intended to serve as a guide for the biologist who has no special expertise and who is not involved in the determination of protein structure. Selected applications of comparative modeling in microbial cell factories are outlined, and the role of microbial cell factories in the structural genomics initiative is discussed.

Efficient recognition of protein fold at low sequence identity by conservative application of Psi-BLAST: validation

A substantial fraction of protein sequences derived from genomic analyses is currently classified as representing 'hypothetical proteins of unknown function'. In part, this reflects the limitations of methods for comparison of sequences with very low identity. We evaluated the effectiveness of a Psi-BLAST search strategy to identify proteins of similar fold at low sequence identity. Psi-BLAST searches for structurally characterized low-sequence-identity matches were carried out on a set of over 300 proteins of known structure. Searches were conducted in NCBI's non-redundant database and were limited to three rounds. Some 614 potential homologs with 25% or lower sequence identity to 166 members of the search set were obtained. Disregarding the expect value, level of sequence identity and span of alignment, correspondence of fold between the target and potential homolog was found in more than 95% of the Psi-BLAST matches. Restrictions on expect value or span of alignment improved the false positive rate at the expense of eliminating many true homologs. Approximately three-quarters of the putative homologs obtained by three rounds of Psi-BLAST revealed no significant sequence similarity to the target protein upon direct sequence comparison by BLAST, and therefore could not be found by a conventional search. Although three rounds of Psi-BLAST identified many more homologs than a standard BLAST search, most homologs were undetected. It appears that more than 80% of all homologs to a target protein may be characterized by a lack of significant sequence similarity. We suggest that conservative use of Psi-BLAST has the potential to propose experimentally testable functions for the majority of proteins currently annotated as 'hypothetical proteins of unknown function'.