Development of Highly Potent Noncovalent Inhibitors of SARS-CoV-2 3CLpro.

The 3C-like protease (3CLpro) is an essential enzyme for the replication of SARS-CoV-2 and other coronaviruses and thus is a target for coronavirus drug discovery. Nearly all inhibitors of coronavirus 3CLpro reported so far are covalent inhibitors. Here, we report the development of specific, noncovalent inhibitors of 3CLpro.

Triaging of DNA-Encoded Library Selection Results by High-Throughput Resynthesis of DNA-Conjugate and Affinity Selection Mass Spectrometry.

DNA encoded library (DEL) technology allows for rapid identification of novel small-molecule ligands and thus enables early-stage drug discovery. DEL technology is well-established, numerous cases of discovered hit molecules have been published, and the technology is widely employed throughout the pharmaceutical industry. Nonetheless, DEL selection results can be difficult to interpret, as library member enrichment may derive from not only desired products, but also DNA-conjugated byproducts and starting materials.

A Strategy for the Synthesis of Sulfonamides on DNA.

An efficient method is reported to synthesize sulfonamides on DNA from sulfinic acids or sodium sulfinates and amines in the presence of iodine under mild conditions. This method demonstrates a major expansion of scope of sulfonamide formation on DNA through the utilization of a novel sodium carbonate-sodium sulfinate bifunctional reagent class.

[Study on transmission rate and quantitative structure-property relationships of alkaloids and iridoid compounds on UF membranes with MWCOS of 1000].

Objective: Taking alkaloids and iridoid as the study, relationships of quantitative molecular structure and transmission rate on UF membrane were developed initially at exploring the mechanism of UF in Chinese herb decoction and to lay a foundation for the optimal design of membrane technology in the production of Chinese drugs preparation.

Method: The transmission rate of eight alkaloids and iridoid compounds in three UF membranes was determined, and quantitative structure-property relationships between quantitative molecular structure and transmission rate were developed by the data mining method of PLS or SVM.

Result: Quantitative structure-property relationship models of three membranes were developed by the data mining method of PLS or SVM, correlation coefficients were all greater than 0.

Prediction of interactiveness of proteins and nucleic acids based on feature selections.

It is important to identify which proteins can interact with nucleic acids for the purpose of protein annotation, since interactions between nucleic acids and proteins involve in numerous cellular processes such as replication, transcription, splicing, and DNA repair. This research tries to identify proteins that can interact with DNA, RNA, and rRNA, respectively. mRMR (Minimum redundancy and maximum relevance), with its elegant mathematical formulation, has been applied widely in processing biological data and feature analysis since its introduction in 2005.

Multiple classifier integration for the prediction of protein structural classes.

Supervised classifiers, such as artificial neural network, partition trees, and support vector machines, are often used for the prediction and analysis of biological data. However, choosing an appropriate classifier is not straightforward because each classifier has its own strengths and weaknesses, and each biological dataset has its own characteristics. By integrating many classifiers together, people can avoid the dilemma of choosing an individual classifier out of many to achieve an optimized classification results (Rahman et al.