Tutorial on Umbrella Sampling Simulation with a Combined QM/MM Potential: The Potential of Mean Force for an S2 Reaction in Water.

We present a tutorial to carry out umbrella-sampling free-energy simulations with a combined quantum mechanical and molecular mechanical (QM/MM) potential, which may also be used in a computational or biophysical chemistry curriculum for first-year graduate and undergraduate students. In this article, we choose the Type II S2 Menshutkin reaction between ammonia and chloromethane to construct the potential of mean force (PMF) for the reaction in aqueous solution. In this exercise, we wish to accomplish three tasks: (1) an understanding of the concept of PMF and the umbrella-sampling free-energy simulation method, (2) the use of a combined QM/MM potential in molecular dynamics simulation of chemical reactions, and (3) an understanding of solvent effects and intermolecular interactions on chemical reactions through comparison with gas-phase results.

New Insights into the Dependence of CPEB3 Ribozyme Cleavage on Mn and Mg.

CPEB3 ribozyme is a self-cleaving RNA that occurs naturally in mammals and requires divalent metal ions for efficient activity. Ribozymes exhibit preferences for specific metal ions, but the exact differences in the catalytic mechanisms of various metal ions on the CPEB3 ribozyme remain unclear. Our findings reveal that Mn functions as a more effective cofactor for CPEB3 ribozyme catalysis compared to Mg, as confirmed by its stronger binding affinity to CPEB3 by EPR.

Glycosylated, Lipid-Binding, CDR-Like Domains of SARS-CoV-2 ORF8 Indicate Unique Sites of Immune Regulation.

The outbreak of the novel coronavirus SARS-CoV-2 has posed a significant threat to human health and the global economy since the end of 2019. Unfortunately, due to the virus's rapid evolution, preventingand controlling the epidemic remains challenging. The ORF8 protein is a unique accessory protein in SARS-CoV-2 that plays a crucial role in immune regulation, but its molecular details are still largely unknown.

Inhibiting the transcription and replication of Ebola viruses by disrupting the nucleoprotein and VP30 protein interaction with small molecules.

Ebola virus (EBOV) causes hemorrhagic fever in humans with high morbidity and fatality. Although over 45 years have passed since the first EBOV outbreak, small molecule drugs are not yet available. Ebola viral protein VP30 is a unique RNA synthesis cofactor, and the VP30/NP interaction plays a critical role in initiating the transcription and propagation of EBOV.

Investigating Derivatives of Tanshinone IIA Sulfonate Sodium and Chloroxine for Their Inhibition Activities against the SARS-CoV-2 Papain-like Protease.

SARS-CoV-2 has caused a global pandemic of COVID-19, posing a huge threat to public health. The SARS-CoV-2 papain-like cysteine protease (PLpro) plays a significant role in virus replication and host immune regulation, which is a promising antiviral drug target. Several potential inhibitors have been identified in vitro.

EVlncRNA-Dpred: improved prediction of experimentally validated lncRNAs by deep learning.

Long non-coding RNAs (lncRNAs) played essential roles in nearly every biological process and disease. Many algorithms were developed to distinguish lncRNAs from mRNAs in transcriptomic data and facilitated discoveries of more than 600 000 of lncRNAs. However, only a tiny fraction (<1%) of lncRNA transcripts (~4000) were further validated by low-throughput experiments (EVlncRNAs).

Biomotors, viral assembly, and RNA nanobiotechnology: Current achievements and future directions.

The International Society of RNA Nanotechnology and Nanomedicine (ISRNN) serves to further the development of a wide variety of functional nucleic acids and other related nanotechnology platforms. To aid in the dissemination of the most recent advancements, a biennial discussion focused on biomotors, viral assembly, and RNA nanobiotechnology has been established where international experts in interdisciplinary fields such as structural biology, biophysical chemistry, nanotechnology, cell and cancer biology, and pharmacology share their latest accomplishments and future perspectives. The results summarized here highlight advancements in our understanding of viral biology and the structure-function relationship of frame-shifting elements in genomic viral RNA, improvements in the predictions of SHAPE analysis of 3D RNA structures, and the understanding of dynamic RNA structures through a variety of experimental and computational means.

High-throughput mapping of RNA solvent accessibility at the single-nucleotide resolution by RtcB ligation between a fixed 5'-OH-end linker and unique 3'-P-end fragments from hydroxyl radical cleavage.

Given the challenges for the experimental determination of RNA tertiary structures, probing solvent accessibility has become increasingly important to gain functional insights. Among various chemical probes developed, backbone-cleaving hydroxyl radical is the only one that can provide unbiased detection of all accessible nucleotides. However, the readouts have been based on reverse transcription (RT) stop at the cleaving sites, which are prone to false positives due to PCR amplification bias, early drop-off of reverse transcriptase, and the use of random primers in RT reaction.

Predicting RNA distance-based contact maps by integrated deep learning on physics-inferred secondary structure and evolutionary-derived mutational coupling.

Motivation: Recently, AlphaFold2 achieved high experimental accuracy for the majority of proteins in Critical Assessment of Structure Prediction (CASP 14). This raises the hope that one day, we may achieve the same feat for RNA structure prediction for those structured RNAs, which is as fundamentally and practically important similar to protein structure prediction. One major factor in the recent advancement of protein structure prediction is the highly accurate prediction of distance-based contact maps of proteins.

Computational Prediction of N- and O-Linked Glycosylation Sites for Human and Mouse Proteins.

Protein glycosylation is one of the most complex posttranslational modifications (PTM) that play a fundamental role in protein function. Identification and annotation of these sites using experimental approaches are challenging and time consuming. Hence, there is a demand to build fast and efficient computational methods to address this problem.

Long Non-Coding RNAs Profiling Using Microarray in Papillary Thyroid Carcinoma.

Long non-coding RNAs (lncRNAs) have been implicated in various cancers, including papillary thyroid carcinomas (PTCs). Genome-wide analysis (GWAS) of lncRNAs expression in PTC samples exhibited up and down regulation of lncRNAs, thus, acting as tumor promoting oncogenes or tumor suppressors in the pathogenesis of PTC by interacting with target genes. For example, lncRNAs such as HOTAIR, NEAT1, MALAT1, FAL1, HOXD-AS1, etc.

Liposomal siRNA Delivery in Papillary Thyroid Carcinoma Cells.

The discovery of RNA interference (RNAi) has opened a new strategy in cancer therapy, especially by silencing target genes. Pharmacologically it can be achieved by introducing of small (19-21 base pairs) dsRNA molecules known as small interfering RNA (siRNA) targeting interested genes. siRNA mediated gene has been widely investigated for its utility in treating various diseases including cancer.

Reaching alignment-profile-based accuracy in predicting protein secondary and tertiary structural properties without alignment.

Protein language models have emerged as an alternative to multiple sequence alignment for enriching sequence information and improving downstream prediction tasks such as biophysical, structural, and functional properties. Here we show that a method called SPOT-1D-LM combines traditional one-hot encoding with the embeddings from two different language models (ProtTrans and ESM-1b) for the input and yields a leap in accuracy over single-sequence-based techniques in predicting protein 1D secondary and tertiary structural properties, including backbone torsion angles, solvent accessibility and contact numbers for all six test sets (TEST2018, TEST2020, Neff1-2020, CASP12-FM, CASP13-FM and CASP14-FM). More significantly, it has a performance comparable to profile-based methods for those proteins with homologous sequences.

Probing RNA structures and functions by solvent accessibility: an overview from experimental and computational perspectives.

Characterizing RNA structures and functions have mostly been focused on 2D, secondary and 3D, tertiary structures. Recent advances in experimental and computational techniques for probing or predicting RNA solvent accessibility make this 1D representation of tertiary structures an increasingly attractive feature to explore. Here, we provide a survey of these recent developments, which indicate the emergence of solvent accessibility as a simple 1D property, adding to secondary and tertiary structures for investigating complex structure-function relations of RNAs.

High-throughput split-protein profiling by combining transposon mutagenesis and regulated protein-protein interactions with deep sequencing.

Splitting a protein at a position may lead to self- or assisted-complementary fragments depending on whether two resulting fragments can reconstitute to maintain the native function spontaneously or require assistance from two interacting molecules. Assisted complementary fragments with high contrast are an important tool for probing biological interactions. However, only a small number of assisted-complementary split-variants have been identified due to manual, labour-intensive optimization of a candidate gene.

Design and Evaluation of a Novel Peptide-Drug Conjugate Covalently Targeting SARS-CoV-2 Papain-like Protease.

Coronavirus disease 2019 (COVID-19) pandemic, a global health threat, was caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The SARS-CoV-2 papain-like cysteine protease (PLpro) was recognized as a promising drug target because of multiple functions in virus maturation and antiviral immune responses. Inhibitor GRL0617 occupied the interferon-stimulated gene 15 (ISG15) C-terminus-binding pocket and showed an effective antiviral inhibition.

De novo protein design by an energy function based on series expansion in distance and orientation dependence.

Motivation: Despite many successes, de novo protein design is not yet a solved problem as its success rate remains low. The low success rate is largely because we do not yet have an accurate energy function for describing the solvent-mediated interaction between amino acid residues in a protein chain. Previous studies showed that an energy function based on series expansions with its parameters optimized for side-chain and loop conformations can lead to one of the most accurate methods for side chain (OSCAR) and loop prediction (LEAP).

Repurposing clinically approved drugs for COVID-19 treatment targeting SARS-CoV-2 papain-like protease.

COVID-19 is a disease caused by SARS-CoV-2, which has led to more than 4 million deaths worldwide. As a result, there is a worldwide effort to develop specific drugs for targeting COVID-19. Papain-like protease (PLpro) is an attractive drug target because it has multiple essential functions involved in processing viral proteins, including viral genome replication and removal of post-translational ubiquitination modifications.

From "Dark Matter" to "Star": Insight Into the Regulation Mechanisms of Plant Functional Long Non-Coding RNAs.

Long non-coding RNAs (lncRNAs) play a vital role in a variety of biological functions in plant growth and development. In this study, we provided an overview of the molecular mechanisms of lncRNAs in interacting with other biomolecules with an emphasis on those lncRNAs validated only by low-throughput experiments. LncRNAs function through playing multiple roles, including sponger for sequestering RNA or DNA, guider or decoy for recruiting or hijacking transcription factors or peptides, and scaffold for binding with chromatin modification complexes, as well as precursor of microRNAs or small interfering RNAs.

Argonaute proteins: structures and their endonuclease activity.

Argonaute proteins are highly conserved and widely expressed in almost all organisms. They not only play a critical role in the biogenesis of small RNAs but also defend against invading nucleic acids via small RNA or DNA-mediated gene silencing pathways. One functional mechanism of Argonaute proteins is acting as a nucleic-acid-guided endonuclease, which can cleave targets complementary to DNA or RNA guides.

RNA Backbone Torsion and Pseudotorsion Angle Prediction Using Dilated Convolutional Neural Networks.

RNA three-dimensional structure prediction has been relied on using a predicted or experimentally determined secondary structure as a restraint to reduce the conformational sampling space. However, the secondary-structure restraints are limited to paired bases, and the conformational space of the ribose-phosphate backbone is still too large to be sampled efficiently. Here, we employed the dilated convolutional neural network to predict backbone torsion and pseudotorsion angles using a single RNA sequence as input.

RNAcmap: a fully automatic pipeline for predicting contact maps of RNAs by evolutionary coupling analysis.

Motivation: The accuracy of RNA secondary and tertiary structure prediction can be significantly improved by using structural restraints derived from evolutionary coupling or direct coupling analysis. Currently, these coupling analyses relied on manually curated multiple sequence alignments collected in the Rfam database, which contains 3016 families. By comparison, millions of non-coding RNA sequences are known.

Pairing a high-resolution statistical potential with a nucleobase-centric sampling algorithm for improving RNA model refinement.

Refining modelled structures to approach experimental accuracy is one of the most challenging problems in molecular biology. Despite many years' efforts, the progress in protein or RNA structure refinement has been slow because the global minimum given by the energy scores is not at the experimentally determined "native" structure. Here, we propose a fully knowledge-based energy function that captures the full orientation dependence of base-base, base-oxygen and oxygen-oxygen interactions with the RNA backbone modelled by rotameric states and internal energies.