scholarly journals Protein structure from experimental evolution

2019 ◽  
Author(s):  
Michael A Stiffler ◽  
Frank J Poelwijk ◽  
Kelly Brock ◽  
Richard R Stein ◽  
Joan Teyra ◽  
...  
Keyword(s):  
Single Gene ◽  
Protein Structures ◽  
Sequence Information ◽  
Structural Constraints ◽  
3D Structures ◽  
Resistance Proteins ◽  
Variation Patterns ◽  
Multiple Cycles ◽  
Rich Information ◽  
And Function

AbstractNatural evolution encodes rich information about the structure and function of biomolecules in the genetic record. Previously, statistical analysis of co-variation patterns in natural protein families has enabled the accurate computation of 3D structures. Here, we explored whether similar information can be generated by laboratory evolution, starting from a single gene and performing multiple cycles of mutagenesis and functional selection. We evolved two bacterial antibiotic resistance proteins, β-lactamase PSE1 and acetyltransferase AAC6, and obtained hundreds of thousands of diverse functional sequences. Using evolutionary coupling analysis, we inferred residue interactions in good agreement with contacts in the crystal structures, confirming genetic encoding of structural constraints in the selected sequences. Computational protein folding with contact constraints yielded 3D structures with the same fold as that of natural relatives. Evolution experiments combined with inference of residue interactions from sequence information opens the door to a new experimental method for the determination of protein structures.

scholarly journals Matching of PDB chain sequences to information in public databases as a prerequisite for 3D functional site visualization

2004 ◽  
Vol 1 (1) ◽  
pp. 80-89
Author(s):  
Guido Dieterich ◽  
Dirk W. Heinz ◽  
Joachim Reichelt
Keyword(s):  
Genetic Disorders ◽  
Protein Structures ◽  
3D Structure ◽  
Data Bank ◽  
Mendelian Inheritance ◽  
Biological Information ◽  
Structure Comparison ◽  
3D Structures ◽  
Functional Sites ◽  
And Function

Abstract The 3D structures of biomacromolecules stored in the Protein Data Bank [1] were correlated with different external, biological information from public databases. We have matched the feature table of SWISS-PROT [2] entries as well InterPro [3] domains and function sites with the corresponding 3D-structures. OMIM [4] (Online Mendelian Inheritance in Man) records, containing information of genetic disorders, were extracted and linked to the structures. The exhaustive all-against-all 3D structure comparison of protein structures stored in DALI [5] was condensed into single files for each PDB entry. Results are stored in XML format facilitating its incorporation into related software. The resulting annotation of the protein structures allows functional sites to be identified upon visualization.

scholarly journals Compositional Variability and Mutation Spectra of Monophyletic SARS-CoV-2 Clades

2020 ◽  
Author(s):  
Xufei Teng ◽  
Qianpeng Li ◽  
Zhao Li ◽  
Yuansheng Zhang ◽  
Guangyi Niu ◽  
...  
Keyword(s):  
Molecular Mechanisms ◽  
Clinical Information ◽  
Sequence Information ◽  
Synonymous Mutations ◽  
Variation Patterns ◽  
Sense Strand ◽  
Diagnostic Applications ◽  
Proteome Changes ◽  
And Function ◽  
Mutation Spectra

AbstractCOVID-19 and its causative pathogen SARS-CoV-2 have rushed the world into a staggering pandemic in a few months and a global fight against both is still going on. Here, we describe an analysis procedure where genome composition and its variables are related, through the genetic code, to molecular mechanisms based on understanding of RNA replication and its feedback loop from mutation to viral proteome sequence fraternity including effective sites on replicase-transcriptase complex. Our analysis starts with primary sequence information and identity-based phylogeny based on 22,051 SARS-CoV-2 genome sequences and evaluation of sequence variation patterns as mutation spectrum and its 12 permutations among organized clades tailored to two key mechanisms: strand-biased and function-associated mutations. Our findings include: (1) The most dominant mutation is C-to-U permutation whose abundant second-codon-position counts alter amino acid composition toward higher molecular weight and lower hydrophobicity albeit assumed most slightly deleterious. (2) The second abundance group includes: three negative-strand mutations U-to-C, A-to-G, G-to-A and a positive-strand mutation G-to-U generated through an identical mechanism as C-to-U. (3) A clade-associated and biased mutation trend is found attributable to elevated level of the negative-sense strand synthesis. (4) Within-clade permutation variation is very informative for associating non-synonymous mutations and viral proteome changes. These findings demand a bioinformatics platform where emerging mutations are mapped on to mostly subtle but fast-adjusting viral proteomes and transcriptomes to provide biological and clinical information after logical convergence for effective pharmaceutical and diagnostic applications. Such thoughts and actions are in desperate need, especially in the middle of the War against COVID-19.

Advancing Translational Research by Enabling Collaborative Teamwork: The TRACT Approach

2012 ◽  
Vol 2 (3) ◽  
Author(s):  
Nedal H. Arar ◽  
Divya Nandamudi
Keyword(s):  
Content Analysis ◽  
Translational Research ◽  
Research Work ◽  
Structured Interviews ◽  
Team Collaboration ◽  
Team Members ◽  
Effective Strategies ◽  
Multiple Cycles ◽  
And Function ◽  
Collaborative Activities

Background: The work of multidisciplinary research teams (MDRTs) is vital for translational research. The objectives of this study were 1) to understand the structure and function of MDRTs, and 2) to develop effective strategies to enhance collaboration among team members. Methods and Findings: Semi-structured interviews were conducted with 23 participants involved in multidisiplinary research work at two San Antonio, Texas, institutions. Interview materials were tape-recorded, transcribed, and content analyzed using qualitative methods.Themes that emerged from the content analysis were used to develop and refine strategies to enhance the work of MDRTs. The findings showed that MDRTs operate through multiple cycles of: 1) team formation, 2) team collaboration, 3) sustainable collaborative activities, and 4) team maturity. Content analysis identified four interrelated basic elements within the MDRT tract that facilitate team cycles: 1) shared interest/vision among agreeable team leader and members, 2) viable means of communication, 3) available resources, and 4) perceived gain/benefit of teamwork.Conclusions: Our findings highlighted several opportunities and challenges in the formation, dynamics, and growth of MDRTs. Effective strategies to enhance teamwork should levearge these opportunities and address challenges, taking into consideration the interdependent aspects of the basic elements within the MDRTs tract.

scholarly journals Co-Evolution of Intrinsically Disordered Proteins with Folded Partners Witnessed by Evolutionary Couplings

2018 ◽  
Vol 19 (11) ◽  
pp. 3315 ◽  
Author(s):  
Rita Pancsa ◽  
Fruzsina Zsolyomi ◽  
Peter Tompa
Keyword(s):  
Large Scale ◽  
Intrinsically Disordered Proteins ◽  
Protein Structures ◽  
Disordered Proteins ◽  
Cellular Interaction ◽  
Structural Constraints ◽  
Protein Residues ◽  
Intrinsically Disordered ◽  
Evolutionary Changes ◽  
Folded Proteins

Although improved strategies for the detection and analysis of evolutionary couplings (ECs) between protein residues already enable the prediction of protein structures and interactions, they are mostly restricted to conserved and well-folded proteins. Whereas intrinsically disordered proteins (IDPs) are central to cellular interaction networks, due to the lack of strict structural constraints, they undergo faster evolutionary changes than folded domains. This makes the reliable identification and alignment of IDP homologs difficult, which led to IDPs being omitted in most large-scale residue co-variation analyses. By preforming a dedicated analysis of phylogenetically widespread bacterial IDP–partner interactions, here we demonstrate that partner binding imposes constraints on IDP sequences that manifest in detectable interprotein ECs. These ECs were not detected for interactions mediated by short motifs, rather for those with larger IDP–partner interfaces. Most identified coupled residue pairs reside close (<10 Å) to each other on the interface, with a third of them forming multiple direct atomic contacts. EC-carrying interfaces of IDPs are enriched in negatively charged residues, and the EC residues of both IDPs and partners preferentially reside in helices. Our analysis brings hope that IDP–partner interactions difficult to study could soon be successfully dissected through residue co-variation analysis.

scholarly journals Health dispossessions and the moralization of disease: the case of diarrhea in the Mekong Delta, Vietnam

2017 ◽  
Vol 24 (1) ◽  
pp. 87 ◽  
Author(s):  
Panagiota Kotsila
Keyword(s):  
Public Health ◽  
Rural Areas ◽  
Qualitative Interviews ◽  
Mekong Delta ◽  
Risky Behaviors ◽  
Structural Constraints ◽  
Political Purpose ◽  
Urban And Rural Areas ◽  
Can Tho City ◽  
And Function

Abstract Despite the swift development of Vietnam's water supply and sanitation (wat/san) sector, over the last ten years there have been 1.5 million annual documented cases of diarrhea. Western perspectives blame insufficient medical or economic advancement for failing to prevent diarrhea and its treatment, failing to grasp how disease is shaped in the cultural, moral and political domain. This article examines the nature and function of public health policy and discourse against the spread of the disease in Can Tho City, Mekong Delta. Some 94 qualitative interviews were conducted with government representatives, medical staff and water experts, and a survey of 131 households in urban and rural areas. Focusing only on improving the construction of wat/san 'hardware' does not improve 'cultural software', and ignores the needs of vulnerable minorities, compromising the control of diarrhea. I also show how state discourse follows neoliberal approaches in individualizing health responsibilities, and moralizing disease. Local (mis)perceptions and risky behaviors emerge as the result of structural constraints that include poverty, a lack of access to useful health information, and the cultivation of stigma around diarrhea. These types of health dispossessions serve a political purpose, where the state escapes responsibility for public health failures, and thus enhancing its efforts to maintain legitimacy as a good implementer and a 'caring head.' Keywords: Vietnam, public health, health individualization, moralization of disease, blame discourse, diarrhea.

scholarly journals Self-Supervised Representation Learning of Protein Tertiary Structures (PtsRep): Protein Engineering as A Case Study

2020 ◽  
Author(s):  
Junwen Luo ◽  
Yi Cai ◽  
Jialin Wu ◽  
Hongmin Cai ◽  
Xiaofeng Yang ◽  
...  
Keyword(s):  
Deep Learning ◽  
Protein Engineering ◽  
Structural Information ◽  
Representation Learning ◽  
Sequence Information ◽  
Structural Representation ◽  
Tertiary Structures ◽  
Structural Space ◽  
General Protein ◽  
And Function

AbstractIn recent years, deep learning has been increasingly used to decipher the relationships among protein sequence, structure, and function. Thus far deep learning of proteins has mostly utilized protein primary sequence information, while the vast amount of protein tertiary structural information remains unused. In this study, we devised a self-supervised representation learning framework to extract the fundamental features of unlabeled protein tertiary structures (PtsRep), and the embedded representations were transferred to two commonly recognized protein engineering tasks, protein stability and GFP fluorescence prediction. On both tasks, PtsRep significantly outperformed the two benchmark methods (UniRep and TAPE-BERT), which are based on protein primary sequences. Protein clustering analyses demonstrated that PtsRep can capture the structural signals in proteins. PtsRep reveals an avenue for general protein structural representation learning, and for exploring protein structural space for protein engineering and drug design.

scholarly journals FingerprintContacts: Predicting Alternative Conformations of Proteins from Coevolution

2020 ◽  
Author(s):  
Jiangyan Feng ◽  
Diwakar Shukla
Keyword(s):  
Ligand Binding ◽  
Structure Prediction ◽  
De Novo ◽  
Three Dimensional ◽  
Sequence Information ◽  
Structural Constraints ◽  
Complex Signals ◽  
Residue Contacts ◽  
Small Clusters ◽  
Functional Mechanisms

AbstractProteins are dynamic molecules which perform diverse molecular functions by adopting different three-dimensional structures. Recent progress in residue-residue contacts prediction opens up new avenues for the de novo protein structure prediction from sequence information. However, it is still difficult to predict more than one conformation from residue-residue contacts alone. This is due to the inability to deconvolve the complex signals of residue-residue contacts, i.e. spatial contacts relevant for protein folding, conformational diversity, and ligand binding. Here, we introduce a machine learning based method, called FingerprintContacts, for extending the capabilities of residue-residue contacts. This algorithm leverages the features of residue-residue contacts, that is, (1) a single conformation outperforms the others in the structural prediction using all the top ranking residue-residue contacts as structural constraints, and (2) conformation specific contacts rank lower and constitute a small fraction of residue-residue contacts. We demonstrate the capabilities of FingerprintContacts on eight ligand binding proteins with varying conformational motions. Furthermore, FingerprintContacts identifies small clusters of residue-residue contacts which are preferentially located in the dynamically fluctuating regions. With the rapid growth in protein sequence information, we expect FingerprintContacts to be a powerful first step in structural understanding of protein functional mechanisms.

scholarly journals Simplified geometric representations of protein structures identify complementary interaction interfaces

2019 ◽  
Author(s):  
Caitlyn L. McCafferty ◽  
Edward M. Marcotte ◽  
David W. Taylor
Keyword(s):  
Conformational Changes ◽  
Protein Interaction ◽  
Protein Function ◽  
Large Scale ◽  
Predictive Accuracy ◽  
Protein Complexes ◽  
Protein Structures ◽  
Molecular Properties ◽  
3D Structures ◽  
Geometric Representations

ABSTRACTProtein-protein interactions are critical to protein function, but three-dimensional (3D) arrangements of interacting proteins have proven hard to predict, even given the identities and 3D structures of the interacting partners. Specifically, identifying the relevant pairwise interaction surfaces remains difficult, often relying on shape complementarity with molecular docking while accounting for molecular motions to optimize rigid 3D translations and rotations. However, such approaches can be computationally expensive, and faster, less accurate approximations may prove useful for large-scale prediction and assembly of 3D structures of multi-protein complexes. We asked if a reduced representation of protein geometry retains enough information about molecular properties to predict pairwise protein interaction interfaces that are tolerant of limited structural rearrangements. Here, we describe a cuboid transformation of 3D protein accessible surfaces on which molecular properties such as charge, hydrophobicity, and mutation rate can be easily mapped, implemented in the MorphProt package. Pairs of surfaces are compared to rapidly assess partner-specific potential surface complementarity. On two available benchmarks of 85 overall known protein complexes, we observed F1 scores (a weighted combination of precision and recall) of 19-34% at correctly identifying protein interaction surfaces, comparable to more computationally intensive 3D docking methods in the annual Critical Assessment of PRedicted Interactions. Furthermore, we examined the effect of molecular motion through normal mode simulation on a benchmark receptor-ligand pair and observed no marked loss of predictive accuracy for distortions of up to 6 Å RMSD. Thus, a cuboid transformation of protein surfaces retains considerable information about surface complementarity, offers enhanced speed of comparison relative to more complex geometric representations, and exhibits tolerance to conformational changes.

Prediction of Structural and Functional Aspects of Protein

2014 ◽  
pp. 317-333
Author(s):  
Arun G. Ingale
Keyword(s):  
Protein Structure ◽  
Protein Structure Prediction ◽  
Structure Prediction ◽  
Tertiary Structure ◽  
Protein Structures ◽  
Three Dimensional ◽  
Dimensional Structure ◽  
Sequence Information ◽  
Predict Protein Structure ◽  
Basic Ideas

To predict the structure of protein from a primary amino acid sequence is computationally difficult. An investigation of the methods and algorithms used to predict protein structure and a thorough knowledge of the function and structure of proteins are critical for the advancement of biology and the life sciences as well as the development of better drugs, higher-yield crops, and even synthetic bio-fuels. To that end, this chapter sheds light on the methods used for protein structure prediction. This chapter covers the applications of modeled protein structures and unravels the relationship between pure sequence information and three-dimensional structure, which continues to be one of the greatest challenges in molecular biology. With this resource, it presents an all-encompassing examination of the problems, methods, tools, servers, databases, and applications of protein structure prediction, giving unique insight into the future applications of the modeled protein structures. In this chapter, current protein structure prediction methods are reviewed for a milieu on structure prediction, the prediction of structural fundamentals, tertiary structure prediction, and functional imminent. The basic ideas and advances of these directions are discussed in detail.

3. Proteins

2021 ◽  
pp. 34-51
Author(s):  
Mark Lorch
Keyword(s):  
Amino Acids ◽  
Protein Folding ◽  
Protein Structure ◽  
Protein Structures ◽  
Structure And Function ◽  
Vast Array ◽  
A Cell ◽  
Cellular Machinery ◽  
And Function ◽  
The Relationship

This chapter examines proteins, the dominant proportion of cellular machinery, and the relationship between protein structure and function. The multitude of biological processes needed to keep cells functioning are managed in the organism or cell by a massive cohort of proteins, together known as the proteome. The twenty amino acids that make up the bulk of proteins produce the vast array of protein structures. However, amino acids alone do not provide quite enough chemical variety to complete all of the biochemical activity of a cell, so the chapter also explores post-translation modifications. It finishes by looking as some dynamic aspects of proteins, including enzyme kinetics and the protein folding problem.

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