Exploring protein functions from structural flexibility using CABS-flex modeling.

Understanding protein function often necessitates characterizing the flexibility of protein structures. However, simulating protein flexibility poses significant challenges due to the complex dynamics of protein systems, requiring extensive computational resources and accurate modeling techniques. In response to these challenges, the CABS-flex method has been developed as an efficient modeling tool that combines coarse-grained simulations with all-atom detail.

Computational Pipeline for Reference-Free Comparative Analysis of RNA 3D Structures Applied to SARS-CoV-2 UTR Models.

RNA is a unique biomolecule that is involved in a variety of fundamental biological functions, all of which depend solely on its structure and dynamics. Since the experimental determination of crystal RNA structures is laborious, computational 3D structure prediction methods are experiencing an ongoing and thriving development. Such methods can lead to many models; thus, it is necessary to build comparisons and extract common structural motifs for further medical or biological studies.

Molecular insights into RNA recognition and gene regulation by the TRIM-NHL protein Mei-P26.

The TRIM-NHL protein Meiotic P26 (Mei-P26) acts as a regulator of cell fate in Its activity is critical for ovarian germline stem cell maintenance, differentiation of oocytes, and spermatogenesis. Mei-P26 functions as a post-transcriptional regulator of gene expression; however, the molecular details of how its NHL domain selectively recognizes and regulates its mRNA targets have remained elusive. Here, we present the crystal structure of the Mei-P26 NHL domain at 1.

Constrained peptides mimic a viral suppressor of RNA silencing.

The design of high-affinity, RNA-binding ligands has proven very challenging. This is due to the unique structural properties of RNA, often characterized by polar surfaces and high flexibility. In addition, the frequent lack of well-defined binding pockets complicates the development of small molecule binders.

RNA and DNA G-quadruplexes bind to human dicer and inhibit its activity.

Guanine (G)-rich single-stranded nucleic acids can adopt G-quadruplex structures. Accumulating evidence indicates that G-quadruplexes serve important regulatory roles in fundamental biological processes such as DNA replication, transcription, and translation, while aberrant G-quadruplex formation is linked to genome instability and cancer. Understanding the biological functions played by G-quadruplexes requires detailed knowledge of their protein interactome.

Genome-wide mapping of SARS-CoV-2 RNA structures identifies therapeutically-relevant elements.

SARS-CoV-2 is a betacoronavirus with a linear single-stranded, positive-sense RNA genome, whose outbreak caused the ongoing COVID-19 pandemic. The ability of coronaviruses to rapidly evolve, adapt, and cross species barriers makes the development of effective and durable therapeutic strategies a challenging and urgent need. As for other RNA viruses, genomic RNA structures are expected to play crucial roles in several steps of the coronavirus replication cycle.

Modeling of Three-Dimensional RNA Structures Using SimRNA.

The molecules of the ribonucleic acid (RNA) perform a variety of vital roles in all living cells. Their biological function depends on their structure and dynamics, both of which are difficult to experimentally determine but can be theoretically inferred based on the RNA sequence. SimRNA is one of the computational methods for molecular simulations of RNA 3D structure formation.

A structure-based model for the prediction of protein-RNA binding affinity.

Protein-RNA recognition is highly affinity-driven and regulates a wide array of cellular functions. In this study, we have curated a binding affinity data set of 40 protein-RNA complexes, for which at least one unbound partner is available in the docking benchmark. The data set covers a wide affinity range of eight orders of magnitude as well as four different structural classes.

QRNAS: software tool for refinement of nucleic acid structures.

Background: Computational models of RNA 3D structure often present various inaccuracies caused by simplifications used in structure prediction methods, such as template-based modeling or coarse-grained simulations. To obtain a high-quality model, the preliminary RNA structural model needs to be refined, taking into account atomic interactions. The goal of the refinement is not only to improve the local quality of the model but to bring it globally closer to the true structure.

Computational modeling of RNA 3D structure based on experimental data.

RNA molecules are master regulators of cells. They are involved in a variety of molecular processes: they transmit genetic information, sense cellular signals and communicate responses, and even catalyze chemical reactions. As in the case of proteins, RNA function is dictated by its structure and by its ability to adopt different conformations, which in turn is encoded in the sequence.

Identification and characterization of differentially expressed Phaseolus vulgaris miRNAs and their targets during mungbean yellow mosaic India virus infection reveals new insight into Phaseolus-MYMIV interaction.

Phaseolus vulgaris is an economically important legume in tropical and subtropical regions of Asia, Africa, Latin-America and parts of USA and Europe. However, its production gets severely affected by mungbean yellow mosaic India virus (MYMIV). We aim to identify and characterize differentially expressed miRNAs during MYMIV-infection in P.

Bioinformatics Tools and Benchmarks for Computational Docking and 3D Structure Prediction of RNA-Protein Complexes.

RNA-protein (RNP) interactions play essential roles in many biological processes, such as regulation of co-transcriptional and post-transcriptional gene expression, RNA splicing, transport, storage and stabilization, as well as protein synthesis. An increasing number of RNP structures would aid in a better understanding of these processes. However, due to the technical difficulties associated with experimental determination of macromolecular structures by high-resolution methods, studies on RNP recognition and complex formation present significant challenges.

Dissecting water binding sites at protein-protein interfaces: a lesson from the atomic structures in the Protein Data Bank.

We dissect the protein-protein interfaces into water preservation (WP), water hydration (WH) and water dehydration (WD) sites by comparing the water-mediated hydrogen bonds (H-bond) in the bound and unbound states of the interacting subunits. Upon subunit complexation, if a H-bond between an interface water and a protein polar group is retained, we assign it as WP site; if it is lost, we assign it as WD site and if a new H-bond is created, we assign it as WH site. We find that the density of WD sites is highest followed by WH and WP sites except in antigen and (or) antibody complexes, where the density of WH sites is highest followed by WD and WP sites.

Genome-wide identification of miRNAs and lncRNAs in Cajanus cajan.

Background: Non-coding RNAs (ncRNAs) are important players in the post transcriptional regulation of gene expression (PTGR). On one hand, microRNAs (miRNAs) are an abundant class of small ncRNAs (~22nt long) that negatively regulate gene expression at the levels of messenger RNAs stability and translation inhibition, on the other hand, long ncRNAs (lncRNAs) are a large and diverse class of transcribed non-protein coding RNA molecules (> 200nt) that play both up-regulatory as well as down-regulatory roles at the transcriptional level. Cajanus cajan, a leguminosae pulse crop grown in tropical and subtropical areas of the world, is a source of high value protein to vegetarians or very poor populations globally.

A non-redundant protein-RNA docking benchmark version 2.0.

We present an updated version of the protein-RNA docking benchmark, which we first published four years back. The non-redundant protein-RNA docking benchmark version 2.0 consists of 126 test cases, a threefold increase in number compared to its previous version.

Targeting Non-Coding RNAs in Plants with the CRISPR-Cas Technology is a Challenge yet Worth Accepting.

Non-coding RNAs (ncRNAs) have emerged as versatile master regulator of biological functions in recent years. MicroRNAs (miRNAs) are small endogenous ncRNAs of 18-24 nucleotides in length that originates from long self-complementary precursors. Besides their direct involvement in developmental processes, plant miRNAs play key roles in gene regulatory networks and varied biological processes.

Probing binding hot spots at protein-RNA recognition sites.

We use evolutionary conservation derived from structure alignment of polypeptide sequences along with structural and physicochemical attributes of protein-RNA interfaces to probe the binding hot spots at protein-RNA recognition sites. We find that the degree of conservation varies across the RNA binding proteins; some evolve rapidly compared to others. Additionally, irrespective of the structural class of the complexes, residues at the RNA binding sites are evolutionary better conserved than those at the solvent exposed surfaces.

Computational prediction of miRNAs and their targets in Phaseolus vulgaris using simple sequence repeat signatures.

Background: MicroRNAs (miRNAs) are endogenous, noncoding, short RNAs directly involved in regulating gene expression at the post-transcriptional level. In spite of immense importance, limited information of P. vulgaris miRNAs and their expression patterns prompted us to identify new miRNAs in P.