Molecular Modeling, Interacting Residues and other Structural Analyses for Human SOCS3, Gp130 and JAK Proteins: A Detailed Computational Approach for Proteins Involved in Feedback Inhibition

Background: When STAT3 is activated only by the IL6 family of proteins, then gp130 (having a phosphopeptide motif) interacts with human SOCS3 which further binds to JAK and inhibits its protein kinase activity. Interaction of gp130 with SOCS3 targets only the IL-6 signaling cascade. The interaction occurs when SOCS3 binds to a particular motif on gp130 (centered upon pTyr759) after its phosphorylation. Previously, wet laboratory studies were done but computational exploration for the participating residues remained unexplored. Methodology: The 3D structure of human SOCS3 protein was modeled and its stereo-chemical parameters were satisfied. Crystallographic structures of gp130-phosphopeptide and JAK were studied. After protein docking, the complex underwent minimization and molecular dynamics simulation. Different stability parameters and binding patterns with residues were evaluated Results, Discussion and Conclusion: The best modeled structure of SOCS3 protein was selected and found that it had three helices and seven sheets interspersed with coils. Arg133, Tyr137 and Tyr98 from SOCS3 formed manifold binding patterns with gp130 (mainly with pTyr759 and Glu758). Lys62, Lys63 and Arg65 from SOCS3 were also found to interact with Val762 of gp130. Interactions with JAK were also studied. Residue 53, 62-65, 98, 133, 136 and 137 formed the predominant binding pockets in SOCS3. They can serve as important target sites as well. Altogether, it created elctrostatically charged pockets to accommodate the partner proteins for each other. Gp130 phosphopeptide was observed to be tightly accommodated in the electrostatically positive zones on SOCS3 surface. Net area for solvent accessibility was also found to get drastically reduced implying high participation of residues. Earlier studies documented that the interaction of these three proteins occurs with affinity and have satisfactory association with each other. Here in this study, free energy of binding for the triple protein interaction through the ΔG values helped to infer that SOCS3 interacted spontaneously (in thermodynamic sense). Many helical conformations formed coiled-coils providing high flexibility to interact spontaneously. Most of the interactions were through the responsible SH2 domain (46-127 residue length) of SOCS3. Residues 53, 62-64 and 98 formed coils while the residue number 137adopted sheet conformation from coils. Future Scope: This study shall instigate to block the gp130-binding sites of SOCS3 through targeting of drugs, thereby preventing SOCS3-gp130 interaction. This would allow JAK-STAT signaling cascade which is paramount for several biological functions

Protein folding stabilities are a major determinant of oxidation rates for buried methionine residues

The oxidation of protein-bound methionines to form methionine sulfoxides has a broad range of biological ramifications, making it important to delineate factors that influence methionine oxidation rates within a protein. This is especially important for biopharmaceuticals, where oxidation can lead to deactivation and degradation. Previously, neighboring residue effects and solvent accessibility (SA) have been shown to impact the susceptibility of methionine residues to oxidation. In this study, we provide proteome-wide evidence that oxidation rates of buried methionine residues are also strongly influenced by the thermodynamic folding stability of proteins. We surveyed the E. coli proteome using several proteomic methodologies and globally measured oxidation rates of methionines in the presence and absence of tertiary structure, as well as folding stabilities of methionine containing domains. The data indicate that buried methionines have a wide range of protection factors against oxidation which correlate strongly with folding stabilities. Concordantly, we show that in comparison to E. coli, the proteome of the thermophile T. thermophilus is significantly more stable and thus more resistant to methionine oxidation. These results indicate that oxidation rates of buried methionines from the native state of proteins can be used as a metric of folding stability. To demonstrate the utility of this correlation, we used native methionine oxidation rates to survey the folding stabilities of E. coli and T. thermophilus proteomes at various temperatures and suggest a model that relates the temperature dependence of the folding stabilities of these two species to their optimal growth temperatures.

Origin of Increased Solvent Accessibility of Peptide Bonds in Mutual Synergetic Folding Proteins

Mutual Synergetic Folding (MSF) proteins belong to a recently discovered class of proteins. These proteins are disordered in their monomeric but ordered in their oligomeric forms. Their amino acid composition is more similar to globular proteins than to disordered ones. Our preceding work shed light on important structural aspects of the structural organization of these proteins, but the background of this behavior is still unknown. We suggest that solvent accessibility is an important factor, especially solvent accessibility of the peptide bonds can be accounted for this phenomenon. The side chains of the amino acids which form a peptide bond have a high local contribution to the shielding of the peptide bond from the solvent. During the oligomerization step, other non-local residues contribute to the shielding. We investigated these local and non-local effects of shielding based on Shannon information entropy calculations. We found that MSF and globular homodimeric proteins have different local contributions resulting from different amino acid pair frequencies. Their non-local distribution is also different because of distinctive inter-subunit contacts.

BiRDS - Binding Residue Detection from Protein Sequences using Deep ResNets

Protein-drug interactions play important roles in many biological processes and therapeutics. Prediction of the active binding site of a protein helps discover and optimise these interactions leading to the design of better ligand molecules. The tertiary structure of a protein determines the binding sites available to the drug molecule. A quick and accurate prediction of the binding site from sequence alone without utilising the three-dimensional structure is challenging. Deep Learning has been used in a variety of biochemical tasks and has been hugely successful. In this paper, a Residual Neural Network (leveraging skip connections) is implemented to predict a protein's most active binding site. An Annotated Database of Druggable Binding Sites from the Protein DataBank, sc-PDB, is used for training the network. Features extracted from the Multiple Sequence Alignments (MSAs) of the protein generated using DeepMSA, such as Position-Specific Scoring Matrix (PSSM), Secondary Structure (SS3), and Relative Solvent Accessibility (RSA), are provided as input to the network. A weighted binary cross-entropy loss function is used to counter the substantial imbalance in the two classes of binding and non-binding residues. The network performs very well on single-chain proteins, providing a pocket that has good interactions with a ligand.

Development of Web Application for the Comparison of Segment Variability with Sequence Evolution and Immunogenic Properties for Highly Variable Proteins: An Application to Viruses

High rate of mutation and structural flexibilities in viral proteins quickly make them resistant to the host immune system and existing antiviral strategies. For most of the pathogenic viruses, the key survival strategies lie in their ability to evolve rapidly through mutations that affects the protein structure and function. Along with the experimental research related to antiviral development, computational data mining also plays an important role in deciphering the molecular and genomic signatures of the viral adaptability. Uncovering conserved regions in viral proteins with diverse chemical and biological properties is an important area of research for developing antiviral therapeutics, though assigning those regions is not a trivial work. Advancement in protein structural information databases and repositories, made by experimental research accelerated the in-silico mining of the data to generate more integrative information. Despite of the huge effort on correlating the protein structural information with its sequence, it is still a challenge to defeat the high mutability and adaptability of the viral genomics structure. In this current study, the authors have developed a user-friendly web application interface that will allow users to study and visualize protein segment variabilities in viral proteins and may help to find antiviral strategies. The present work of web application development allows thorough mining of the surface properties and variabilities of viral proteins which in combination with immunogenicity and evolutionary properties make the visualization robust. In combination with previous research on 20-Dimensional Euclidian Geometry based sequence variability characterization algorithm, four other parameters has been considered for this platform: [1] predicted solvent accessibility information, [2] B-Cell epitopic potential, [3] T-Cell epitopic potential and [4] coevolving region of the viral protein. Uniqueness of this study lies in the fact that a protein sequence stretch is being characterized rather than single residue-based information, which helps to compare properties of protein segments with variability. In current work, as an example, beside presenting the web application platform, five proteins of SARS-CoV2 was presented with keeping focus on protein-S. Current web-application database contains 29 proteins from 7 viruses including a GitHub repository of the raw data used in this study. The web application is up and running in the following address: http://www.protsegvar.com.

A computational in silico approach to predict high-risk coding and non-coding SNPs of human PLCG1 gene

PLCG1 gene is responsible for many T-cell lymphoma subtypes, including peripheral T-cell lymphoma (PTCL), angioimmunoblastic T-cell lymphoma (AITL), cutaneous T-cell lymphoma (CTCL), adult T-cell leukemia/lymphoma along with other diseases. Missense mutations of this gene have already been found in patients of CTCL and AITL. The non-synonymous single nucleotide polymorphisms (nsSNPs) can alter the protein structure as well as its functions. In this study, probable deleterious and disease-related nsSNPs in PLCG1 were identified using SIFT, PROVEAN, PolyPhen-2, PhD-SNP, Pmut, and SNPS&GO tools. Further, their effect on protein stability was checked along with conservation and solvent accessibility analysis by I-mutant 2.0, MUpro, Consurf, and Netsurf 2.0 server. Some SNPs were finalized for structural analysis with PyMol and BIOVIA discovery studio visualizer. Out of the 16 nsSNPs which were found to be deleterious, ten nsSNPs had an effect on protein stability, and six mutations (L411P, R355C, G493D, R1158H, A401V and L455F) were predicted to be highly conserved. Among the six highly conserved mutations, four nsSNPs (R355C, A401V, L411P and L455F) were part of the catalytic domain. L411P, L455F and G493D made significant structural change in the protein structure. Two mutations-Y210C and R1158H had post-translational modification. In the 5’ and 3’ untranslated region, three SNPs, rs139043247, rs543804707, and rs62621919 showed possible miRNA target sites and DNA binding sites. This in silico analysis has provided a structured dataset of PLCG1 gene for further in vivo researches. With the limitation of computational study, it can still prove to be an asset for the identification and treatment of multiple diseases associated with the target gene.

Dissection of the amyloid formation pathway in AL amyloidosis

In antibody light chain (AL) amyloidosis, overproduced light chain (LC) fragments accumulate as fibrils in organs and tissues of patients. In vitro, AL fibril formation is a slow process, characterized by a pronounced lag phase. The events occurring during this lag phase are largely unknown. We have dissected the lag phase of a patient-derived LC truncation and identified structural transitions that precede fibril formation. The process starts with partial unfolding of the VL domain and the formation of small amounts of dimers. This is a prerequisite for the formation of an ensemble of oligomers, which are the precursors of fibrils. During oligomerization, the hydrophobic core of the LC domain rearranges which leads to changes in solvent accessibility and rigidity. Structural transitions from an anti-parallel to a parallel β-sheet secondary structure occur in the oligomers prior to amyloid formation. Together, our results reveal a rate-limiting multi-step mechanism of structural transitions prior to fibril formation in AL amyloidosis, which offers, in the long run, opportunities for therapeutic intervention.

3D Interaction Homology: Computational Titration of Aspartic Acid, Glutamic Acid and Histidine Can Create pH-Tunable Hydropathic Environment Maps

Aspartic acid, glutamic acid and histidine are ionizable residues occupying various protein environments and perform many different functions in structures. Their roles are tied to their acid/base equilibria, solvent exposure, and backbone conformations. We propose that the number of unique environments for ASP, GLU and HIS is quite limited. We generated maps of these residue's environments using a hydropathic scoring function to record the type and magnitude of interactions for each residue in a 2703-protein structural dataset. These maps are backbone-dependent and suggest the existence of new structural motifs for each residue type. Additionally, we developed an algorithm for tuning these maps to any pH, a potentially useful element for protein design and structure building. Here, we elucidate the complex interplay between secondary structure, relative solvent accessibility, and residue ionization states: the degree of protonation for ionizable residues increases with solvent accessibility, which in turn is notably dependent on backbone structure.

Analysis of 272 genetic variants in the upgraded interactive FXI web database reveals new insights on FXI deficiency

Coagulation Factor XI (FXI) is a plasma glycoprotein composed of four apple (Ap) domains and a serine protease (SP) domain. FXI circulates as a dimer and activates Factor IX (FIX), promoting thrombin production and preventing excess blood loss. Genetic variants that degrade FXI structure and function often lead to bleeding diatheses, commonly termed FXI deficiency. The first interactive FXI variant database underwent initial development in 2003 at https://www.factorxi.org. Here, based on a much improved FXI crystal structure, the upgraded FXI database contains information regarding 272 FXI variants (including 154 missense variants) found in 657 patients, this being a significant increase from the 183 variants identified in the 2009 update. Type I variants involve the simultaneous reduction of FXI coagulant activity (FXI:C) and FXI antigen levels (FXI:Ag), whereas Type II variants result in decreased FXI:C yet normal FXI:Ag. The database updates now highlight the predominance of Type I variants in FXI. Analysis in terms of a consensus Ap domain revealed the near-uniform distribution of 81 missense variants across the Ap domains. A further 66 missense variants were identified in the SP domain, showing that all regions of the FXI protein were important for function. The variants clarified the critical importance of changes in surface solvent accessibility, as well as those of cysteine residues and the dimer interface. Guidelines are provided below for clinicians who wish to use the database for diagnostic purposes. In conclusion, the updated database provides an easy-to-use web resource on FXI deficiency for clinicians.

Mechanism of Laccase-assisted Tyrosine Grafting on Keratin using BSA as a Model Protein

Commercial hair perming uses strong reducing agents and is harmful to hair fiber’s quality even human health. In this study, tyrosine is adopted as a cross-linking agent between thiols as the shape-changing of hair involves breakage of disulfide bonds and the rearrangement of new bonds between keratin molecules. To investigate the mechanism of the cross-linking, bovine serum albumin (BSA) is used as a model protein. Molecular dynamics simulations give an insight on Cys solvent accessibility and protein stability for the wild type BSA and a designed BSA presenting the three broken disulfide bonds. A new cross-linked peptide, NECFLSHK-Tyrosine-Tyrosine-GACLLPK, inter- or intra- BSA monomers is formed, whose reactive cysteine residues are Cys-101 and Cys-176. Moreover, curling of Asian hair is conducted using tyrosine as a perming agent by laccase-assisted reaction. The optimized operational conditions are hair with cysteine pre-treatment (50.0 mM) followed by grafting with 3.0 mM tyrosine. The reshaped hair performed a better perming performance than commercial perming product before washing, although a lower perming efficiency after washing, however without strength loss and could be easily accomplished with a blow-drier. Hence, this new methodology may lead to the development of a gentle and user-friendly approach in the hair care industry.