pLoc-mVirus: Predict subcellular localization of multi-location virus proteins via incorporating the optimal GO information into general PseAAC.

Knowledge of subcellular locations of proteins is crucially important for in-depth understanding their functions in a cell. With the explosive growth of protein sequences generated in the postgenomic age, it is highly demanded to develop computational tools for timely annotating their subcellular locations based on the sequence information alone. The current study is focused on virus proteins.

iRNA-2methyl: Identify RNA 2'-O-methylation Sites by Incorporating Sequence-Coupled Effects into General PseKNC and Ensemble Classifier.

Objective: Being a kind of post-transcriptional modification (PTCM) in RNA, the 2'-Omethylation modification occurs in the processes of life development and disease formation as well. Accordingly, from the angles of both basic research and drug development, we are facing a challenging problem: given an uncharacterized RNA sequence formed by many nucleotides of A (adenine), C (cytosine), G (guanine), and U (uracil), which one can be of 2-O'-methylation modification, and which one cannot? Unfortunately, so far no computational method whatsoever has been developed to address such a problem.

Method: To fill this empty area, we propose a predictor called iRNA-2methyl.

2L-piRNA: A Two-Layer Ensemble Classifier for Identifying Piwi-Interacting RNAs and Their Function.

Involved with important cellular or gene functions and implicated with many kinds of cancers, piRNAs, or piwi-interacting RNAs, are of small non-coding RNA with around 19-33 nt in length. Given a small non-coding RNA molecule, can we predict whether it is of piRNA according to its sequence information alone? Furthermore, there are two types of piRNA: one has the function of instructing target mRNA deadenylation, and the other does not. Can we discriminate one from the other? With the avalanche of RNA sequences emerging in the postgenomic age, it is urgent to address the two problems for both basic research and drug development.

iRNA-PseColl: Identifying the Occurrence Sites of Different RNA Modifications by Incorporating Collective Effects of Nucleotides into PseKNC.

There are many different types of RNA modifications, which are essential for numerous biological processes. Knowledge about the occurrence sites of RNA modifications in its sequence is a key for in-depth understanding of their biological functions and mechanism. Unfortunately, it is both time-consuming and laborious to determine these sites purely by experiments alone.

iPGK-PseAAC: Identify Lysine Phosphoglycerylation Sites in Proteins by Incorporating Four Different Tiers of Amino Acid Pairwise Coupling Information into the General PseAAC.

Background: Occurring at Lys residues, the PGK (lysine phosphoglycerylation) is a special kind of post-translational modification (PTM). It may invert the charge potential of the modified residue and change the protein structures and functions, causing various diseases in liver, brain, and kidney.

Objective: From the angles of both basic research and drug development, we are facing a critical challenging problem: for an uncharacterized protein sequence containing many Lys residues, which ones can be of phosphoglycerylation, and which ones cannot?

Method: To address this problem, we have developed a predictor called iPGK-PseAAC by incorporating into the general PseAAC (pseudo amino acid composition) with four different tiers of amino acid pairwise coupling information, where tiers 1, 2, 3, and 4 refer to the amino acid pairwise couplings between all the 1st, 2nd, 3rd, and 4th most contiguous residues along a protein segment, respectively.

Chlorella vulgaris Induces Apoptosis of Human Non-Small Cell Lung Carcinoma (NSCLC) Cells.

Objective: Chlorella vulgaris (C. vulgaris), a unicellular green microalga, has been widely used as a food supplement and reported to have antioxidant and anticancer properties. The current study was designed to assess the cytotoxic, apoptotic, and DNA-damaging effects of C.

iPhos-PseEvo: Identifying Human Phosphorylated Proteins by Incorporating Evolutionary Information into General PseAAC via Grey System Theory.

Protein phosphorylation plays a critical role in human body by altering the structural conformation of a protein, causing it to become activated/deactivated, or functional modification. Given an uncharacterized protein sequence, can we predict whether it may be phosphorylated or may not? This is no doubt a very meaningful problem for both basic research and drug development. Unfortunately, to our best knowledge, so far no high throughput bioinformatics tool whatsoever has been developed to address such a very basic but important problem due to its extremely complexity and lacking sufficient training data.

iRNAm5C-PseDNC: identifying RNA 5-methylcytosine sites by incorporating physical-chemical properties into pseudo dinucleotide composition.

Occurring at cytosine (C) of RNA, 5-methylcytosine (m5C) is an important post-transcriptional modification (PTCM). The modification plays significant roles in biological processes by regulating RNA metabolism in both eukaryotes and prokaryotes. It may also, however, cause cancers and other major diseases.

Microbial Routes to (2R,3R)-2,3-Butanediol: Recent Advances and Future Prospects.

(2R,3R)-2,3-Butanediol has many industrial applications, such as it is used as an antifreeze agent and low freezing point fuel. In addition, it is particularly important to provide chiral groups in drugs. In recent years, this valuable bio-based chemical has attracted increasing attention, and significant progress has been made in the development of microbial cell factories for (2R,3R)-2,3-butanediol production.

Prediction of the aquatic toxicity of aromatic compounds to tetrahymena pyriformis through support vector regression.

Toxicity evaluation is an extremely important process during drug development. It is usually initiated by experiments on animals, which is time-consuming and costly. To speed up such a process, a quantitative structure-activity relationship (QSAR) study was performed to develop a computational model for correlating the structures of 581 aromatic compounds with their aquatic toxicity to tetrahymena pyriformis.

iPreny-PseAAC: Identify C-terminal Cysteine Prenylation Sites in Proteins by Incorporating Two Tiers of Sequence Couplings into PseAAC.

Background: Occurring at the cysteine residue in the C-terminal of a protein, prenylation is a special kind of post-translational modification (PTM), which may play a key role for statin in altering immune function. Therefore, knowledge of the prenylation sites in proteins is important for drug development as well as for in-depth understanding the biological process concerned.

Objective: Given a query protein whose C-terminal contains some cysteine residues, which one can be of prenylation or none of them can be prenylated?

Methods: To address this problem, we have developed a new predictor, called "iPreny-PseAAC", by incorporating two tiers of sequence pair coupling effects into the general form of PseAAC (pseudo amino acid composition).

An Unprecedented Revolution in Medicinal Chemistry Driven by the Progress of Biological Science.

The eternal or ultimate goal of medicinal chemistry is to find most effective ways to treat various diseases and extend human beings' life as long as possible. Human being is a biological entity. To realize such an ultimate goal, the inputs or breakthroughs from the advances in biological science are no doubt most important that may even drive medicinal science into a revolution.

The Intrinsic Relationship Between Structure and Function of the Sialyltransferase ST8Sia Family Members.

As a subset of glycosyltransferases, the family of sialyltransferases catalyze transfer of sialic acid (Sia) residues to terminal non-reducing positions on oligosaccharide chains of glycoproteins and glycolipids, utilizing CMP-Neu5Ac as the activated sugar nucleotide donor. In the four known sialyltransferase families (ST3Gal, ST6Gal, ST6GalNAc and ST8Sia), the ST8Sia family catalyzes synthesis of α2, 8-linked sialic/polysialic acid (polySia) chains according to their acceptor specificity. We have determined the 3D structural models of the ST8Sia family members, designated ST8Sia I (1), II(2), IV(4), V(5), and VI(6) using the Phyre2 server.

Drug Design and Discovery: Principles and Applications.

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Exploring the possibility to store the mixed oxygen-hydrogen cluster in clathrate hydrate in molar ratio 1:2 (O+2H).

An interesting possibility is explored: storing the mixture of oxygen and hydrogen in clathrate hydrate in molar ratio 1:2. The interaction energies between oxygen, hydrogen, and clathrate hydrate are calculated using high level quantum chemical methods. The useful conclusion points from this study are summarized as follows.

iATC-mISF: a multi-label classifier for predicting the classes of anatomical therapeutic chemicals.

Motivation: Given a compound, can we predict which anatomical therapeutic chemical (ATC) class/classes it belongs to? It is a challenging problem since the information thus obtained can be used to deduce its possible active ingredients, as well as its therapeutic, pharmacological and chemical properties. And hence the pace of drug development could be substantially expedited. But this problem is by no means an easy one.

Active Hydrogen Bond Network (AHBN) and Applications for Improvement of Thermal Stability and pH-Sensitivity of Pullulanase from Bacillus naganoensis.

A method, so called "active hydrogen bond network" (AHBN), is proposed for site-directed mutations of hydrolytic enzymes. In an enzyme the AHBN consists of the active residues, functional residues, and conservative water molecules, which are connected by hydrogen bonds, forming a three dimensional network. In the catalysis hydrolytic reactions of hydrolytic enzymes AHBN is responsible for the transportation of protons and water molecules, and maintaining the active and dynamic structures of enzymes.

A new type of two-dimensional carbon crystal prepared from 1,3,5-trihydroxybenzene.

A new two-dimensional (2D) carbon crystal, different from graphene, has been prepared from 1,3,5-trihydroxybenzene, consisting of 4-carbon and 6-carbon rings in 1:1 ratio, named 4-6 carbophene by authors, in which all carbon atoms possess sp hybrid orbitals with some distortion, forming an extensive conjugated π-bonding planar structure. The angles between the three σ-bonds of the carbon sp orbitals are roughly 120°, 90°, and 150°. Each of the three non-adjacent sides of a 6C-ring is shared with a 4C-ring; and each of the two opposite sides of a 4C-ring is shared with a 6C-ring.

Pse-Analysis: a python package for DNA/RNA and protein/ peptide sequence analysis based on pseudo components and kernel methods.

To expedite the pace in conducting genome/proteome analysis, we have developed a Python package called Pse-Analysis. The powerful package can automatically complete the following five procedures: (1) sample feature extraction, (2) optimal parameter selection, (3) model training, (4) cross validation, and (5) evaluating prediction quality. All the work a user needs to do is to input a benchmark dataset along with the query biological sequences concerned.

iRNA-AI: identifying the adenosine to inosine editing sites in RNA sequences.

Catalyzed by adenosine deaminase (ADAR), the adenosine to inosine (A-to-I) editing in RNA is not only involved in various important biological processes, but also closely associated with a series of major diseases. Therefore, knowledge about the A-to-I editing sites in RNA is crucially important for both basic research and drug development. Given an uncharacterized RNA sequence that contains many adenosine (A) residues, can we identify which one of them can be of A-to-I editing, and which one cannot? Unfortunately, so far no computational method whatsoever has been developed to address such an important problem based on the RNA sequence information alone.

In-depth comparison of somatic point mutation callers based on different tumor next-generation sequencing depth data.

Four popular somatic single nucleotide variant (SNV) calling methods (Varscan, SomaticSniper, Strelka and MuTect2) were carefully evaluated on the real whole exome sequencing (WES, depth of ~50X) and ultra-deep targeted sequencing (UDT-Seq, depth of ~370X) data. The four tools returned poor consensus on candidates (only 20% of calls were with multiple hits by the callers). For both WES and UDT-Seq, MuTect2 and Strelka obtained the largest proportion of COSMIC entries as well as the lowest rate of dbSNP presence and high-alternative-alleles-in-control calls, demonstrating their superior sensitivity and accuracy.

Multi-iPPseEvo: A Multi-label Classifier for Identifying Human Phosphorylated Proteins by Incorporating Evolutionary Information into Chou's General PseAAC via Grey System Theory.

Predicting phosphorylation protein is a challenging problem, particularly when query proteins have multi-label features meaning that they may be phosphorylated at two or more different type amino acids. In fact, human protein usually be phosphorylated at serine, threonine and tyrosine. By introducing the "multi-label learning" approach, a novel predictor has been developed that can be used to deal with the systems containing both single- and multi-label phosphorylation protein.

iOri-Human: identify human origin of replication by incorporating dinucleotide physicochemical properties into pseudo nucleotide composition.

The initiation of replication is an extremely important process in DNA life cycle. Given an uncharacterized DNA sequence, can we identify where its origin of replication (ORI) is located? It is no doubt a fundamental problem in genome analysis. Particularly, with the rapid development of genome sequencing technology that results in a huge amount of sequence data, it is highly desired to develop computational methods for rapidly and effectively identifying the ORIs in these genomes.

dRHP-PseRA: detecting remote homology proteins using profile-based pseudo protein sequence and rank aggregation.

Protein remote homology detection is an important task in computational proteomics. Some computational methods have been proposed, which detect remote homology proteins based on different features and algorithms. As noted in previous studies, their predictive results are complementary to each other.

iRSpot-EL: identify recombination spots with an ensemble learning approach.

Motivation: Coexisting in a DNA system, meiosis and recombination are two indispensible aspects for cell reproduction and growth. With the avalanche of genome sequences emerging in the post-genomic age, it is an urgent challenge to acquire the information of DNA recombination spots because it can timely provide very useful insights into the mechanism of meiotic recombination and the process of genome evolution.

Results: To address such a challenge, we have developed a predictor, called IRSPOT-EL: , by fusing different modes of pseudo K-tuple nucleotide composition and mode of dinucleotide-based auto-cross covariance into an ensemble classifier of clustering approach.