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Article ; Online ; E-Book: Protein interactions

Helms, Volkhard / Kalinina, Olga V.

the molecular basis of interactomics

2023

Author's details	edited by Volkhard Helms and Olga V. Kalinina
Language	English
Size	1 Online-Ressource (xvi, 411 Seiten), Illustrationen, Diagramme
Publisher	Wiley-VCH
Publishing place	Weinheim
Publishing country	Germany
Document type	Article ; Online ; E-Book
Remark	Zugriff für angemeldete ZB MED-Nutzerinnen und -Nutzer
HBZ-ID	HT021593661
ISBN	978-3-527-83051-0 ; 978-3-527-83052-7 ; 978-3-527-83050-3 ; 9783527348640 ; 3-527-83051-0 ; 3-527-83052-9 ; 3-527-83050-2 ; 3527348646
Database	ZB MED Catalogue: Medicine, Health, Nutrition, Environment, Agriculture

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Article: GlyLES: Grammar-based Parsing of Glycans from IUPAC-condensed to SMILES.

Joeres, Roman / Bojar, Daniel / Kalinina, Olga V

Journal of cheminformatics

2023 Volume 15, Issue 1, Page(s) 37

Abstract: Glycans are important polysaccharides on cellular surfaces that are bound to glycoproteins and glycolipids. These are one of the most common post-translational modifications of proteins in eukaryotic cells. They play important roles in protein folding, ... ...

Abstract	Glycans are important polysaccharides on cellular surfaces that are bound to glycoproteins and glycolipids. These are one of the most common post-translational modifications of proteins in eukaryotic cells. They play important roles in protein folding, cell-cell interactions, and other extracellular processes. Changes in glycan structures may influence the course of different diseases, such as infections or cancer. Glycans are commonly represented using the IUPAC-condensed notation. IUPAC-condensed is a textual representation of glycans operating on the same topological level as the Symbol Nomenclature for Glycans (SNFG) that assigns colored, geometrical shapes to the main monomers. These symbols are then connected in tree-like structures, visualizing the glycan structure on a topological level. Yet for a representation on the atomic level, notations such as SMILES should be used. To our knowledge, there is no easy-to-use, general, open-source, and offline tool to convert the IUPAC-condensed notation to SMILES. Here, we present the open-access Python package GlyLES for the generalizable generation of SMILES representations out of IUPAC-condensed representations. GlyLES uses a grammar to read in the monomer tree from the IUPAC-condensed notation. From this tree, the tool can compute the atomic structures of each monomer based on their IUPAC-condensed descriptions. In the last step, it merges all monomers into the atomic structure of a glycan in the SMILES notation. GlyLES is the first package that allows conversion from the IUPAC-condensed notation of glycans to SMILES strings. This may have multiple applications, including straightforward visualization, substructure search, molecular modeling and docking, and a new featurization strategy for machine-learning algorithms. GlyLES is available at https://github.com/kalininalab/GlyLES .
Language	English
Publishing date	2023-03-23
Publishing country	England
Document type	Journal Article
ZDB-ID	2486539-4
ISSN	1758-2946
ISSN	1758-2946
DOI	10.1186/s13321-023-00704-0
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Article ; Online: PanPA: generation and alignment of panproteome graphs.

Dabbaghie, Fawaz / Srikakulam, Sanjay K / Marschall, Tobias / Kalinina, Olga V

Bioinformatics advances

2023 Volume 3, Issue 1, Page(s) vbad167

Abstract: Motivation: Compared to eukaryotes, prokaryote genomes are more diverse through different mechanisms, including a higher mutation rate and horizontal gene transfer. Therefore, using a linear representative reference can cause a reference bias. Graph- ... ...

Abstract	Motivation: Compared to eukaryotes, prokaryote genomes are more diverse through different mechanisms, including a higher mutation rate and horizontal gene transfer. Therefore, using a linear representative reference can cause a reference bias. Graph-based pangenome methods have been developed to tackle this problem. However, comparisons in DNA space are still challenging due to this high diversity. In contrast, amino acid sequences have higher similarity due to evolutionary constraints, whereby a single amino acid may be encoded by several synonymous codons. Coding regions cover the majority of the genome in prokaryotes. Thus, panproteomes present an attractive alternative leveraging the higher sequence similarity while not losing much of the genome in non-coding regions. Results: We present PanPA, a method that takes a set of multiple sequence alignments of protein sequences, indexes them, and builds a graph for each multiple sequence alignment. In the querying step, it can align DNA or amino acid sequences back to these graphs. We first showcase that PanPA generates correct alignments on a panproteome from 1350 Availalability and implementation: PanPA is available at https://github.com/fawaz-dabbaghieh/PanPA.
Language	English
Publishing date	2023-11-24
Publishing country	England
Document type	Journal Article
ISSN	2635-0041
ISSN (online)	2635-0041
DOI	10.1093/bioadv/vbad167
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Article ; Online: Phylogenetic inference of changes in amino acid propensities with single-position resolution.

Klink, Galya V / Kalinina, Olga V / Bazykin, Georgii A

PLoS computational biology

2022 Volume 18, Issue 2, Page(s) e1009878

Abstract: Fitness conferred by the same allele may differ between genotypes and environments, and these differences shape variation and evolution. Changes in amino acid propensities at protein sites over the course of evolution have been inferred from sequence ... ...

Abstract	Fitness conferred by the same allele may differ between genotypes and environments, and these differences shape variation and evolution. Changes in amino acid propensities at protein sites over the course of evolution have been inferred from sequence alignments statistically, but the existing methods are data-intensive and aggregate multiple sites. Here, we develop an approach to detect individual amino acids that confer different fitness in different groups of species from combined sequence and phylogenetic data. Using the fact that the probability of a substitution to an amino acid depends on its fitness, our method looks for amino acids such that substitutions to them occur more frequently in one group of lineages than in another. We validate our method using simulated evolution of a protein site under different scenarios and show that it has high specificity for a wide range of assumptions regarding the underlying changes in selection, while its sensitivity differs between scenarios. We apply our method to the env gene of two HIV-1 subtypes, A and B, and to the HA gene of two influenza A subtypes, H1 and H3, and show that the inferred fitness changes are consistent with the fitness differences observed in deep mutational scanning experiments. We find that changes in relative fitness of different amino acid variants within a site do not always trigger episodes of positive selection and therefore may not result in an overall increase in the frequency of substitutions, but can still be detected from changes in relative frequencies of different substitutions.
MeSH term(s)	Amino Acid Substitution ; Amino Acids/genetics ; Evolution, Molecular ; Humans ; Influenza, Human/genetics ; Phylogeny ; Sequence Alignment
Chemical Substances	Amino Acids
Language	English
Publishing date	2022-02-18
Publishing country	United States
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	2193340-6
ISSN	1553-7358 ; 1553-734X
ISSN (online)	1553-7358
ISSN	1553-734X
DOI	10.1371/journal.pcbi.1009878
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Article ; Online: SphereCon-a method for precise estimation of residue relative solvent accessible area from limited structural information.

Gress, Alexander / Kalinina, Olga V

Bioinformatics (Oxford, England)

2020 Volume 36, Issue 11, Page(s) 3372–3378

Abstract: Motivation: In proteins, solvent accessibility of individual residues is a factor contributing to their importance for protein function and stability. Hence one might wish to calculate solvent accessibility in order to predict the impact of mutations, ... ...

Abstract	Motivation: In proteins, solvent accessibility of individual residues is a factor contributing to their importance for protein function and stability. Hence one might wish to calculate solvent accessibility in order to predict the impact of mutations, their pathogenicity and for other biomedical applications. A direct computation of solvent accessibility is only possible if all atoms of a protein three-dimensional structure are reliably resolved. Results: We present SphereCon, a new precise measure that can estimate residue relative solvent accessibility (RSA) from limited data. The measure is based on calculating the volume of intersection of a sphere with a cone cut out in the direction opposite of the residue with surrounding atoms. We propose a method for estimating the position and volume of residue atoms in cases when they are not known from the structure, or when the structural data are unreliable or missing. We show that in cases of reliable input structures, SphereCon correlates almost perfectly with the directly computed RSA, and outperforms other previously suggested indirect methods. Moreover, SphereCon is the only measure that yields accurate results when the identities of amino acids are unknown. A significant novel feature of SphereCon is that it can estimate RSA from inter-residue distance and contact matrices, without any information about the actual atom coordinates. Availability and implementation: https://github.com/kalininalab/spherecon. Contact: alexander.gress@helmholtz-hips.de. Supplementary information: Supplementary data are available at Bioinformatics online.
MeSH term(s)	Amino Acids ; Protein Structure, Secondary ; Proteins ; Solvents
Chemical Substances	Amino Acids ; Proteins ; Solvents
Language	English
Publishing date	2020-03-10
Publishing country	England
Document type	Journal Article
ZDB-ID	1422668-6
ISSN	1367-4811 ; 1367-4803
ISSN (online)	1367-4811
ISSN	1367-4803
DOI	10.1093/bioinformatics/btaa159
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Article ; Online: MetaProFi: an ultrafast chunked Bloom filter for storing and querying protein and nucleotide sequence data for accurate identification of functionally relevant genetic variants.

Srikakulam, Sanjay K / Keller, Sebastian / Dabbaghie, Fawaz / Bals, Robert / Kalinina, Olga V

Bioinformatics (Oxford, England)

2023 Volume 39, Issue 3

Abstract: Motivation: Bloom filters are a popular data structure that allows rapid searches in large sequence datasets. So far, all tools work with nucleotide sequences; however, protein sequences are conserved over longer evolutionary distances, and only ... ...

Abstract	Motivation: Bloom filters are a popular data structure that allows rapid searches in large sequence datasets. So far, all tools work with nucleotide sequences; however, protein sequences are conserved over longer evolutionary distances, and only mutations on the protein level may have any functional significance. Results: We present MetaProFi, a Bloom filter-based tool that, for the first time, offers the functionality to build indexes of amino acid sequences and query them with both amino acid and nucleotide sequences, thus bringing sequence comparison to the biologically relevant protein level. MetaProFi implements additional efficient engineering solutions, such as a shared memory system, chunked data storage and efficient compression. In addition to its conceptual novelty, MetaProFi demonstrates state-of-the-art performance and excellent memory consumption-to-speed ratio when applied to various large datasets. Availability and implementation: Source code in Python is available at https://github.com/kalininalab/metaprofi.
MeSH term(s)	Algorithms ; Base Sequence ; Software ; Proteins ; Data Compression
Chemical Substances	Proteins
Language	English
Publishing date	2023-02-24
Publishing country	England
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	1422668-6
ISSN	1367-4811 ; 1367-4803
ISSN (online)	1367-4811
ISSN	1367-4803
DOI	10.1093/bioinformatics/btad101
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Article ; Online: Simulated Tempering-Enhanced Umbrella Sampling Improves Convergence of Free Energy Calculations of Drug Membrane Permeation.

Sousa, Carla F / Becker, Robert A / Lehr, Claus-Michael / Kalinina, Olga V / Hub, Jochen S

Journal of chemical theory and computation

2023 Volume 19, Issue 6, Page(s) 1898–1907

Abstract: Molecular dynamics simulations have been widely used to study solute permeation across biological membranes. The potential of mean force (PMF) for solute permeation is typically computed using enhanced sampling techniques such as umbrella sampling (US). ... ...

Abstract	Molecular dynamics simulations have been widely used to study solute permeation across biological membranes. The potential of mean force (PMF) for solute permeation is typically computed using enhanced sampling techniques such as umbrella sampling (US). For bulky drug-like permeants, however, obtaining converged PMFs remains challenging and often requires long simulation times, resulting in an unacceptable computational cost. Here, we augmented US with simulated tempering (ST), an extended-ensemble technique that consists in varying the temperature of the system along a pre-defined temperature ladder. Simulated tempering-enhanced US (STeUS) was employed to improve the convergence of PMF calculations for the permeation of methanol and three common drug molecules. To obtain sufficient sampling of the umbrella histograms, which were computed only from the ground temperature, we modified the simulation time fraction spent at the ground temperature between 1/
MeSH term(s)	Methanol ; Molecular Dynamics Simulation ; Entropy ; Solutions ; Temperature
Chemical Substances	Methanol (Y4S76JWI15) ; Solutions
Language	English
Publishing date	2023-02-28
Publishing country	United States
Document type	Journal Article
ISSN	1549-9626
ISSN (online)	1549-9626
DOI	10.1021/acs.jctc.2c01162
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Article ; Online: Machine learning and phylogenetic analysis allow for predicting antibiotic resistance in M. tuberculosis.

Yurtseven, Alper / Buyanova, Sofia / Agrawal, Amay Ajaykumar / Bochkareva, Olga O / Kalinina, Olga V

BMC microbiology

2023 Volume 23, Issue 1, Page(s) 404

Abstract: Background: Antimicrobial resistance (AMR) poses a significant global health threat, and an accurate prediction of bacterial resistance patterns is critical for effective treatment and control strategies. In recent years, machine learning (ML) ... ...

Abstract	Background: Antimicrobial resistance (AMR) poses a significant global health threat, and an accurate prediction of bacterial resistance patterns is critical for effective treatment and control strategies. In recent years, machine learning (ML) approaches have emerged as powerful tools for analyzing large-scale bacterial AMR data. However, ML methods often ignore evolutionary relationships among bacterial strains, which can greatly impact performance of the ML methods, especially if resistance-associated features are attempted to be detected. Genome-wide association studies (GWAS) methods like linear mixed models accounts for the evolutionary relationships in bacteria, but they uncover only highly significant variants which have already been reported in literature. Results: In this work, we introduce a novel phylogeny-related parallelism score (PRPS), which measures whether a certain feature is correlated with the population structure of a set of samples. We demonstrate that PRPS can be used, in combination with SVM- and random forest-based models, to reduce the number of features in the analysis, while simultaneously increasing models' performance. We applied our pipeline to publicly available AMR data from PATRIC database for Mycobacterium tuberculosis against six common antibiotics. Conclusions: Using our pipeline, we re-discovered known resistance-associated mutations as well as new candidate mutations which can be related to resistance and not previously reported in the literature. We demonstrated that taking into account phylogenetic relationships not only improves the model performance, but also yields more biologically relevant predicted most contributing resistance markers.
MeSH term(s)	Humans ; Phylogeny ; Mycobacterium tuberculosis/genetics ; Genome-Wide Association Study ; Drug Resistance, Microbial/genetics ; Bacterial Infections ; Machine Learning ; Tuberculosis
Language	English
Publishing date	2023-12-20
Publishing country	England
Document type	Journal Article
ZDB-ID	2041505-9
ISSN	1471-2180 ; 1471-2180
ISSN (online)	1471-2180
ISSN	1471-2180
DOI	10.1186/s12866-023-03147-7
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Article ; Online: A shift of dynamic equilibrium between the KIT active and inactive states causes drug resistance.

Srikakulam, Sanjay K / Bastys, Tomas / Kalinina, Olga V

Proteins

2020 Volume 88, Issue 11, Page(s) 1434–1446

Abstract: Tyrosine phosphorylation, a highly regulated post-translational modification, is carried out by the enzyme tyrosine kinase (TK). TKs are important mediators in signaling cascades, facilitating diverse biological processes in response to stimuli. TKs may ... ...

Abstract	Tyrosine phosphorylation, a highly regulated post-translational modification, is carried out by the enzyme tyrosine kinase (TK). TKs are important mediators in signaling cascades, facilitating diverse biological processes in response to stimuli. TKs may acquire mutations leading to malignancy and are viable targets for anti-cancer drugs. Mast/stem cell growth factor receptor KIT is a TK involved in cell differentiation, whose dysregulation leads to various types of cancer, including gastrointestinal stromal tumors, leukemia, and melanoma. KIT can be targeted by a range of inhibitors that predominantly bind to the inactive state of the enzyme. A mutation Y823D in the activation loop of KIT is known to be responsible for the loss of sensitivity to some drugs in metastatic tumors. We used all-atom molecular dynamics simulations to study the impact of Y823D on the KIT conformation and dynamics and compared it to the effect of phosphorylation of Y823. We simulated in total 6.4 μs of wild-type, mutant and phosphorylated KIT in the active- and inactive-state conformations. We found that Y823D affects the protein dynamics differently: in the active state, the mutation increases the protein stability, whereas in the inactive state it induces local destabilization, thus shifting the dynamic equilibrium towards the active state, altering the communication between distant regulatory regions. The observed dynamics of the Y823D mutant is similar to the dynamics of KIT phosphorylated at position Y823, thus we hypothesize that this mutation mimics a constitutively active kinase, which is not responsive to inhibitors that bind its inactive conformation.
MeSH term(s)	Antineoplastic Agents/chemistry ; Antineoplastic Agents/metabolism ; Aspartic Acid/chemistry ; Aspartic Acid/metabolism ; Binding Sites ; Databases, Protein ; Drug Resistance, Neoplasm/genetics ; Humans ; Hydrogen Bonding ; Ligands ; Molecular Dynamics Simulation ; Mutation ; Phosphorylation ; Protein Binding ; Protein Conformation, alpha-Helical ; Protein Conformation, beta-Strand ; Protein Interaction Domains and Motifs ; Protein Kinase Inhibitors/chemistry ; Protein Kinase Inhibitors/metabolism ; Protein Processing, Post-Translational ; Protein Stability ; Proto-Oncogene Proteins c-kit/antagonists & inhibitors ; Proto-Oncogene Proteins c-kit/chemistry ; Proto-Oncogene Proteins c-kit/genetics ; Proto-Oncogene Proteins c-kit/metabolism ; Substrate Specificity ; Thermodynamics ; Tyrosine/chemistry ; Tyrosine/metabolism
Chemical Substances	Antineoplastic Agents ; Ligands ; Protein Kinase Inhibitors ; Aspartic Acid (30KYC7MIAI) ; Tyrosine (42HK56048U) ; KIT protein, human (EC 2.7.10.1) ; Proto-Oncogene Proteins c-kit (EC 2.7.10.1)
Language	English
Publishing date	2020-06-25
Publishing country	United States
Document type	Journal Article
ZDB-ID	806683-8
ISSN	1097-0134 ; 0887-3585
ISSN (online)	1097-0134
ISSN	0887-3585
DOI	10.1002/prot.25963
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Article ; Online: SphereCon-a method for precise estimation of residue relative solvent accessible area from limited structural information.

Gress, Alexander / Kalinina, Olga V

36 ; 11 ; 3372 ; 3378 ; Bioinformatics (Oxford, England) ; England

2020

Abstract	Motivation: In proteins, solvent accessibility of individual residues is a factor contributing to their importance for protein function and stability. Hence one might wish to calculate solvent accessibility in order to predict the impact of mutations, their pathogenicity and for other biomedical applications. A direct computation of solvent accessibility is only possible if all atoms of a protein three-dimensional structure are reliably resolved. Results: We present SphereCon, a new precise measure that can estimate residue relative solvent accessibility (RSA) from limited data. The measure is based on calculating the volume of intersection of a sphere with a cone cut out in the direction opposite of the residue with surrounding atoms. We propose a method for estimating the position and volume of residue atoms in cases when they are not known from the structure, or when the structural data are unreliable or missing. We show that in cases of reliable input structures, SphereCon correlates almost perfectly with the directly computed RSA, and outperforms other previously suggested indirect methods. Moreover, SphereCon is the only measure that yields accurate results when the identities of amino acids are unknown. A significant novel feature of SphereCon is that it can estimate RSA from inter-residue distance and contact matrices, without any information about the actual atom coordinates.
Language	English
Publishing date	2020-03-10
Publisher	Oxford Academic
Publishing country	de
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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