scholarly journals mmCSM-NA: accurately predicting effects of single and multiple mutations on protein–nucleic acid binding affinity

2021 ◽  
Vol 3 (4) ◽  
Author(s):  
Thanh Binh Nguyen ◽  
Yoochan Myung ◽  
Alex G C de Sá ◽  
Douglas E V Pires ◽  
David B Ascher
Keyword(s):  
Nucleic Acid ◽  
Binding Affinity ◽  
Single Point ◽  
Point Mutations ◽  
Multiple Point ◽  
Missense Mutations ◽  
Nucleic Acid Binding ◽  
Single Point Mutations ◽  
Protein Nucleic Acid ◽  
Nucleic Acid Interactions

Abstract While protein–nucleic acid interactions are pivotal for many crucial biological processes, limited experimental data has made the development of computational approaches to characterise these interactions a challenge. Consequently, most approaches to understand the effects of missense mutations on protein-nucleic acid affinity have focused on single-point mutations and have presented a limited performance on independent data sets. To overcome this, we have curated the largest dataset of experimentally measured effects of mutations on nucleic acid binding affinity to date, encompassing 856 single-point mutations and 141 multiple-point mutations across 155 experimentally solved complexes. This was used in combination with an optimized version of our graph-based signatures to develop mmCSM-NA (http://biosig.unimelb.edu.au/mmcsm_na), the first scalable method capable of quantitatively and accurately predicting the effects of multiple-point mutations on nucleic acid binding affinities. mmCSM-NA obtained a Pearson's correlation of up to 0.67 (RMSE of 1.06 Kcal/mol) on single-point mutations under cross-validation, and up to 0.65 on independent non-redundant datasets of multiple-point mutations (RMSE of 1.12 kcal/mol), outperforming similar tools. mmCSM-NA is freely available as an easy-to-use web-server and API. We believe it will be an invaluable tool to shed light on the role of mutations affecting protein–nucleic acid interactions in diseases.

Snapshot blotting: The transfer of nucleic acids and nucleoprotein complexes from electrophoresis gels to EM grids

1992 ◽  
Vol 50 (1) ◽  
pp. 762-763
Author(s):  
Stephen D. Jett
Keyword(s):  
Nucleic Acid ◽  
Nucleic Acids ◽  
Nucleic Acid Binding ◽  
Mobility Shift ◽  
Carbon Coated ◽  
Nucleoprotein Complexes ◽  
Mobility Shift Assay ◽  
Protein Nucleic Acid ◽  
Gel Mobility Shift ◽  
Nucleic Acid Interactions

The electrophoresis gel mobility shift assay is a popular method for the study of protein-nucleic acid interactions. The binding of proteins to DNA is characterized by a reduction in the electrophoretic mobility of the nucleic acid. Binding affinity, stoichiometry, and kinetics can be obtained from such assays; however, it is often desirable to image the various species in the gel bands using TEM. Present methods for isolation of nucleoproteins from gel bands are inefficient and often destroy the native structure of the complexes. We have developed a technique, called “snapshot blotting,” by which nucleic acids and nucleoprotein complexes in electrophoresis gels can be electrophoretically transferred directly onto carbon-coated grids for TEM imaging.

scholarly journals In Silico Insights into HIV-1 Vpu-Tetherin Interactions and Its Mutational Counterparts

2019 ◽  
Vol 7 (6) ◽  
pp. 74
Author(s):  
Patil Sneha ◽  
Urmi Shah ◽  
Seetharaman Balaji
Keyword(s):  
Cell Surface ◽  
Binding Affinity ◽  
Hydrophobic Interactions ◽  
Single Point ◽  
Resistance Mechanism ◽  
Point Mutations ◽  
Protein Docking ◽  
Host Protein ◽  
Single Point Mutations ◽  
Hiv 1

Tetherin, an interferon-induced host protein encoded by the bone marrow stromal antigen 2 (BST2/CD317/HM1.24) gene, is involved in obstructing the release of many retroviruses and other enveloped viruses by cross-linking the budding virus particles to the cell surface. This activity is antagonized in the case of human immunodeficiency virus (HIV)-1 wherein its accessory protein Viral Protein U (Vpu) interacts with tetherin, causing its downregulation from the cell surface. Vpu and tetherin connect through their transmembrane (TM) domains, culminating into events leading to tetherin degradation by recruitment of β-TrCP2. However, mutations in the TM domains of both proteins are reported to act as a resistance mechanism to Vpu countermeasure impacting tetherin’s sensitivity towards Vpu but retaining its antiviral activity. Our study illustrates the binding aspects of blood-derived, brain-derived, and consensus HIV-1 Vpu with tetherin through protein–protein docking. The analysis of the bound complexes confirms the blood-derived Vpu–tetherin complex to have the best binding affinity as compared to other two. The mutations in tetherin and Vpu are devised computationally and are subjected to protein–protein interactions. The complexes are tested for their binding affinities, residue connections, hydrophobic forces, and, finally, the effect of mutation on their interactions. The single point mutations in tetherin at positions L23Y, L24T, and P40T, and triple mutations at {L22S, F44Y, L37I} and {L23T, L37T, T45I}, while single point mutations in Vpu at positions A19H and W23Y and triplet of mutations at {V10K, A11L, A19T}, {V14T, I18T, I26S}, and {A11T, V14L, A15T} have revealed no polar contacts with minimal hydrophobic interactions between Vpu and tetherin, resulting in reduced binding affinity. Additionally, we have explored the aggregation potential of tetherin and its association with the brain-derived Vpu protein. This work is a possible step toward an understanding of Vpu–tetherin interactions.

scholarly journals An in silico approach to identification, categorization and prediction of nucleic acid binding proteins

2020 ◽  
Author(s):  
Lei Xu ◽  
Shanshan Jiang ◽  
Jin Wu ◽  
Quan Zou
Keyword(s):  
Nucleic Acid ◽  
Drug Targets ◽  
Nucleic Acid Binding ◽  
Structural Protein ◽  
Interaction Sites ◽  
Trained Classifier ◽  
Nucleic Acid Binding Proteins ◽  
Protein Nucleic Acid ◽  
And Function ◽  
Nucleic Acid Interactions

Abstract The interaction between proteins and nucleic acid plays an important role in many processes, such as transcription, translation and DNA repair. The mechanisms of related biological events can be understood by exploring the function of proteins in these interactions. The number of known protein sequences has increased rapidly in recent years, but the databases for describing the structure and function of protein have unfortunately grown quite slowly. Thus, improving such databases is meaningful for predicting protein–nucleic acid interactions. Furthermore, the mechanism of related biological events, such as viral infection or designing novel drug targets, can be further understood by understanding the function of proteins in these interactions. The information for each sequence, including its function and interaction sites, were collected and identified, and a database called PNIDB was built. The proteins in PNIDB were grouped into 27 classes, such as transcription, immune system, and structural protein, etc. The function of each protein was then predicted using a machine learning method. Using our method, the predictor was trained on labeled sequences, and then the function of a protein was predicted based on the trained classifier. The prediction accuracy achieved a score of 77.43% by 10-fold cross validation.

scholarly journals mmCSM-AB: guiding rational antibody engineering through multiple point mutations

2020 ◽  
Vol 48 (W1) ◽  
pp. W125-W131 ◽  
Author(s):  
Yoochan Myung ◽  
Douglas E V Pires ◽  
David B Ascher
Keyword(s):  
Binding Affinity ◽  
Single Point ◽  
Point Mutations ◽  
Affinity Maturation ◽  
Antibody Engineering ◽  
Multiple Point ◽  
Single Point Mutation ◽  
Atomic Interaction ◽  
Therapeutic Class ◽  
Antibody Design

Abstract While antibodies are becoming an increasingly important therapeutic class, especially in personalized medicine, their development and optimization has been largely through experimental exploration. While there have been many efforts to develop computational tools to guide rational antibody engineering, most approaches are of limited accuracy when applied to antibody design, and have largely been limited to analysing a single point mutation at a time. To overcome this gap, we have curated a dataset of 242 experimentally determined changes in binding affinity upon multiple point mutations in antibody-target complexes (89 increasing and 153 decreasing binding affinity). Here, we have shown that by using our graph-based signatures and atomic interaction information, we can accurately analyse the consequence of multi-point mutations on antigen binding affinity. Our approach outperformed other available tools across cross-validation and two independent blind tests, achieving Pearson's correlations of up to 0.95. We have implemented our new approach, mmCSM-AB, as a web-server that can help guide the process of affinity maturation in antibody design. mmCSM-AB is freely available at http://biosig.unimelb.edu.au/mmcsm_ab/.

scholarly journals Single point mutations can potentially enhance infectivity of SARS-CoV-2 revealed by in silico affinity maturation and SPR assay

2020 ◽  
Author(s):  
Ting Xue ◽  
Weikun Wu ◽  
Ning Guo ◽  
Chengyong Wu ◽  
Jian Huang ◽  
...  
Keyword(s):  
Binding Affinity ◽  
In Silico ◽  
Cell Attachment ◽  
Single Point ◽  
Point Mutations ◽  
Cell Receptor ◽  
Affinity Maturation ◽  
Promising Target ◽  
Assay Result ◽  
Single Point Mutations

AbstractThe RBD (receptor binding domain) of the SARS-CoV-2 virus S (spike) protein mediates the viral cell attachment and serves as a promising target for therapeutics development. Mutations on the S-RBD may alter its affinity to cell receptor and affect the potency of vaccines and antibodies. Here we used an in-silico approach to predict how mutations on RBD affect its binding affinity to hACE2 (human angiotensin-converting enzyme2). The effect of all single point mutations on the interface was predicted. SPR assay result shows that 6 out of 9 selected mutations can strengthen binding affinity. Our prediction has reasonable agreement with the previous deep mutational scan results and recently reported mutants. Our work demonstrated in silico method as a powerful tool to forecast more powerful virus mutants, which will significantly benefit for the development of broadly neutralizing vaccine and antibody.

scholarly journals An in silico approach to identification, categorization and prediction of nucleic acid binding proteins

2020 ◽  
Author(s):  
Lei Xu ◽  
Shanshan Jiang ◽  
Quan Zou
Keyword(s):  
Nucleic Acid ◽  
Drug Targets ◽  
Nucleic Acid Binding ◽  
Structural Protein ◽  
Interaction Sites ◽  
Trained Classifier ◽  
Nucleic Acid Binding Proteins ◽  
Protein Nucleic Acid ◽  
And Function ◽  
Nucleic Acid Interactions

AbstractThe interaction between proteins and nucleic acid plays an important role in many processes, such as transcription, translation and DNA repair. The mechanisms of related biological events can be understood by exploring the function of proteins in these interactions. The number of known protein sequences has increased rapidly in recent years, but the databases for describing the structure and function of protein have unfortunately grown quite slowly. Thus, improving such databases is meaningful for predicting protein-nucleic acid interactions. Furthermore, the mechanism of related biological events, such as viral infection or designing novel drug targets, can be further understood by understanding the function of proteins in these interactions. The information for each sequence, including its function and interaction sites, were collected and identified, and a database called PNIDB was built. The proteins in PNIDB were grouped into 27 classes, such as transcription, immune system, and structural protein, etc. The function of each protein was then predicted using a machine learning method. Using our method, the predictor was trained on labeled sequences, and then the function of a protein was predicted based on the trained classifier. The prediction accuracy achieved a score of 77.43% by 10-fold cross validation.Availability and ImplementationPNIDB is now fully working and can be freely accessed at: http://server.malab.cn/PNIDB/index.html. All the data are publicly available for non-commercial use, distribution, and reproduction in any [email protected]

Cupin Variants as Macromolecular Ligand Library for Stereoselective Michael Addition of Nitroalkanes

2019 ◽  
Author(s):  
Nobutaka Fujieda ◽  
Miho Yuasa ◽  
Yosuke Nishikawa ◽  
Genji Kurisu ◽  
Shinobu Itoh ◽  
...  
Keyword(s):  
Michael Addition ◽  
In Silico ◽  
Addition Reaction ◽  
Single Point ◽  
Point Mutations ◽  
Unsaturated Ketone ◽  
Michael Addition Reaction ◽  
Beta Barrel ◽  
Cupin Superfamily ◽  
Single Point Mutations

Cupin superfamily proteins (TM1459) work as a macromolecular ligand framework with a double-stranded beta-barrel structure ligating to a Cu ion through histidine side chains. Variegating the first coordination sphere of TM1459 revealed that H52A and H54A/H58A mutants effectively catalyzed the diastereo- and enantio-selective Michael addition reaction of nitroalkanes to an α,β-unsaturated ketone. Moreover, in silico substrate docking signified C106N and F104W single-point mutations, which inverted the diastereoselectivity of H52A and further improved the stereoselectivity of H54A/H58A, respectively.

Single-Point Mutations in Qβ Virus-like Particles Change Binding to Cells

2021 ◽  
Author(s):  
Marisa L. Martino ◽  
Stephen N. Crooke ◽  
Marianne Manchester ◽  
M.G. Finn
Keyword(s):  
Single Point ◽  
Point Mutations ◽  
Virus Like Particles ◽  
Single Point Mutations

scholarly journals Bioinformatic Analysis of Structure and Function of LIM Domains of Human Zyxin Family Proteins

2021 ◽  
Vol 22 (5) ◽  
pp. 2647
Author(s):  
M. Quadir Siddiqui ◽  
Maulik D. Badmalia ◽  
Trushar R. Patel
Keyword(s):  
Nucleic Acid ◽  
Nuclear Export ◽  
Consensus Sequence ◽  
Nuclear Export Signal ◽  
Bioinformatic Analysis ◽  
Nucleic Acid Binding ◽  
Protein Protein Interaction ◽  
Lim Domains ◽  
Protein Nucleic Acid ◽  
And Function

Members of the human Zyxin family are LIM domain-containing proteins that perform critical cellular functions and are indispensable for cellular integrity. Despite their importance, not much is known about their structure, functions, interactions and dynamics. To provide insights into these, we used a set of in-silico tools and databases and analyzed their amino acid sequence, phylogeny, post-translational modifications, structure-dynamics, molecular interactions, and functions. Our analysis revealed that zyxin members are ohnologs. Presence of a conserved nuclear export signal composed of LxxLxL/LxxxLxL consensus sequence, as well as a possible nuclear localization signal, suggesting that Zyxin family members may have nuclear and cytoplasmic roles. The molecular modeling and structural analysis indicated that Zyxin family LIM domains share similarities with transcriptional regulators and have positively charged electrostatic patches, which may indicate that they have previously unanticipated nucleic acid binding properties. Intrinsic dynamics analysis of Lim domains suggest that only Lim1 has similar internal dynamics properties, unlike Lim2/3. Furthermore, we analyzed protein expression and mutational frequency in various malignancies, as well as mapped protein-protein interaction networks they are involved in. Overall, our comprehensive bioinformatic analysis suggests that these proteins may play important roles in mediating protein-protein and protein-nucleic acid interactions.

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