Xiang Simon Wang

• PhD
• Professor at Howard University

Agouti-related protein (AGRP) is one of only two naturally known antagonists of G-protein-coupled receptors (GPCRs) identified to date. Specifically, AGRP antagonizes the brain melanocortin-3 and -4 receptors involved in energy homeostasis. Alpha-melanocyte stimulating hormone (alpha-MSH) is one of the known endogenous agonists for these melanocort...

Inhibitors of histone deacetylases (HDACIs) have emerged as a new class of drugs for the treatment of human cancers and other diseases because of their effects on cell growth, differentiation, and apoptosis. In this study we have developed several quantitative structure-activity relationship (QSAR) models for 59 chemically diverse histone deacetyla...

Benchmarking data sets have become common in recent years for the purpose of virtual screening, though the main focus had been placed on the structure-based virtual screening (SBVS) approaches. Due to the lack of crystal structures, there is great need for unbiased benchmarking sets to evaluate various ligand-based virtual screening (LBVS) methods...

Structure-based virtual screening (SBVS) has become an indispensable technique for hit identification at the early stage of drug discovery. However, the accuracy of current scoring functions is not high enough to confer success to every targets thus remains to be improved. Precedently, we developed binary pose filter (PF) using knowledge derived fr...

Farnesoid X receptor (FXR) agonists can reverse dysregulated bile acid metabolism thus are potential therapeutics to prevent and treat non-alcoholic fatty liver disease. The low success rate of FXR agonists R&D and the side effects of the clinical candidates such as obeticholic acid make it urgent to discover new chemotypes. Unfortunately, structur...

Adeno-associated virus (AAV) vectors have emerged as powerful tools in gene therapy, potentially treating various genetic disorders. Engineering the AAV capsids through computational methods enables the customization of these vectors to enhance their effectiveness and safety. This engineering allows for the development of gene therapies that are no...

Artificial intelligence (AI)/machine learning (ML) is emerging as pivotal in synthetic chemistry, offering revolutionary potential in retrosynthetic analysis, reaction conditions and reaction prediction. We have combined chemical descriptors, primarily based on Density Functional Theory (DFT) calculations, with various AI/ML tools such as Multi‐Lay...

Virtual screening (VS) plays an increasingly important role in the modern drug discovery. However, there is a great deficit in the unbiased benchmarking data for VS, especially the emerging machine learning methods. This paper reports our innovative construction of synthetic Maximal Unbiased Benchmarking Datasets (MUBDsyn) as a solution. This bench...

Machine learning (ML) has been used to build high-performance prediction models in the past without considering race. African Americans (AA) are vulnerable to acute kidney injury (AKI) at a higher eGFR level than Caucasians. AKI increases mortality, length of hospital stays, and incidence of chronic kidney disease (CKD) and end-stage renal disease...

Deep learning is a type of machine learning that teaches computers how to learn like humans through the use of deep (multi-layered) neural networks. Similarly, to our brains, this technology enables computers to continuously pick up signals from the physical world and uncover new insights—sometimes even discovering things not directly taught throug...

Introduction: Structure-based virtual screening (SBVS) is an essential strategy for hit identification in early drug discovery. SBVS primarily uses molecular docking, which exploits the protein–ligand binding mode and associated affinity score for compound ranking. Previous studies have shown that computational representation of protein–ligand inte...

CCR2 antagonists that disrupt CCR2/MCP‐1 interaction are expected to treat a variety of inflammatory and autoimmune diseases. The lack of CCR2 crystal structure limits the application of structure‐based drug design (SBDD) to this target. Although a few three‐dimensional theoretical models have been reported, their accuracy remains to be improved in...

The manual is also available at https://github.com/jwxia2014/MUBD-DecoyMaker2.0.

Ligand enrichment assessment based on bench-marking data sets has become a necessity for the rational selection of the best-suited approach for prospective data mining of drug-like molecules. Up to now, a variety of benchmarking data sets had been generated and frequently used. Among them, MUBD-HDACs from our prior research efforts was regarded as...

A blockchain, at its fundamental core, is a time-stamped series of data based on three core principles: decentralization, immutability, and transparency. The science behind the technology is that all users have access to information created, edited and stored, thus creating a high degree of control, autonomy and trust of the data. Having already sh...

Virtual reality (VR) is an interactive computer technology taking place within a simulated environment. This immersive environment can be similar to the real world but with add-on digital features, or it can be totally fantastical. In recent years, VR is emerging to be the next step for the evolution of 21st century education, showing great potenti...

Protein tyrosine phosphatase 1B (PTP1B) has recently been identified as a potential target of Norathyriol. Unfortunately, Norathyriol is not a potent PTP1B inhibitor, which somewhat hinders its further application. Based on the fact that no study on the relationship of chemical structure and PTP1B inhibitory activity of Norathyriol has been reporte...

The MUBD-hCRs are also available at https://github.com/jwxia2014/MUBD-hCRs.

seases and HIV-1 infection. As a powerful technique, virtual screening (VS) has been widely applied to identifying small molecule leads for modern drug targets including CRs. For rational selection of a wide variety of VS approaches, ligand enrichment assessment based on a benchmarking data set has become an indispensable practice. However, the lac...

Histone deacetylase 3 (HDAC3) is a potential target for the treatment of human diseases such as cancers, diabetes, chronic inflammation and neurodegenerative diseases. Previously, we proposed a virtual screening (VS) pipeline named “Hypo1_FRED_SAHA-3” for the discovery of HDAC3 inhibitors (HDAC3Is) and had thoroughly validated it by theoretical cal...

Quionolone carboxylic acid derivatives as inhibitors of HIV-1 integrase were investigated as a potential class of drugs for the treatment of acquired immunodeficiency syndrome (AIDS). Hologram quantitative structure-activity relationships (HQSAR) and translocation comparative molecular field vector analysis (topomer CoMFA) were applied to a series...

Inhibition of apoptosis is a potential therapy to treat human diseases such as neurodegenerative disorders (e.g., Parkinson’s disease), stroke, and sepsis. Due to the lack of druggable targets, it remains a major challenge to discover apoptosis inhibitors. The recent repositioning of a marketed drug (i.e., terazosin) as an anti-apoptotic agent unco...

Quantitative structure–activity relationship (QSAR) modeling is the major chemin- formatics approach to exploring and exploiting the dependency of chemical, biological, toxicological, or other types of activities or properties on their molecular features. QSAR modeling has been traditionally used as a lead optimization approach in drug discovery re...

Histone deacetylase 3 (HDAC3) has been recently identified as a potential target for the treatment of cancer and other diseases, such as chronic inflammation, neurodegenerative diseases, and diabetes. Virtual screening (VS) is currently a routine technique for hit identification, but its success depends on rational development of VS strategies. To...

The ULS-UDS is also available at https://pan.baidu.com/s/1eybnkObSzsovUEXCgEZE6g ; password：dhti OR https://github.com/jwxia2014/ULS-UDS

Quantitative structure–activity relationship (QSAR) modeling is the major chemin- formatics approach to exploring and exploiting the dependency of chemical, biological, toxicological, or other types of activities or properties on their molecular features. QSAR modeling has been traditionally used as a lead optimization approach in drug discovery re...

Ligand based virtual screening (LBVS) approaches could be broadly divided into those relying on chemical similarity searches and those employing Quantitative Structure-Activity Relationship (QSAR) models. We have compared the predictive power of these approaches using some datasets of compounds tested against several G-Protein Coupled Receptors (GP...

Receptor Tyrosine Kinases (RTKs) are essential components for regulating cell-cell signaling and communication events in cell growth, proliferation, differentiation, survival and metabolism. Deregulation of RTKs and their associated signaling pathways can lead to a wide variety of human diseases such as immunodeficiency, diabetes, arterosclerosis,...

Histone deacetylases (HDACs) are part of a vast family of enzymes with crucial roles in numerous biological processes, largely through their repressive influence on transcription, with serious implications in a variety of human diseases. Among different isoforms, human HDAC2 in particular draws attention as a promising target for the treatment of c...

The human 5-hydroxytryptamine receptor subtype 1A (5-HT1A) is highly expressed in the raphe nuclei region and limbic structures; for that reason 5-HT1A has been an attractive target to treat human mood disorders and neurodegenerative diseases. We have developed binary quantitative structure-activity relationship (QSAR) models for 5-HT1A binding usi...

The incorporation of Green Chemistry is a relatively new phenomenon in the drug discovery discipline, since the scale that chemists operate on in drug discovery is smaller than those of process and manufacturing chemistry. The necessary metrics are more difficult to obtain in drug discovery due to the diversity of reactions conducted. However, phar...

The MUBD-HDACs are also available at https://github.com/jwxia2014/MUBD-HDACs.

Histone Deacetylases (HDACs) are an important class of drug targets for the treatment of cancers, neurodegenerative diseases and other types of diseases. Virtual screening (VS) has become fairly effective approaches for drug discovery of novel and highly selective Histone Deacetylases Inhibitors (HDACIs). To facilitate the process, we constructed t...

Retrospective small-scale virtual screening (VS) based on benchmarking data sets has been widely used to estimate ligand enrichments of VS approaches in the prospective (i.e. real-world) efforts. However, the intrinsic differences of benchmarking sets to the real screening chemical libraries can cause biased assessment. Herein, we summarize the his...

Nanoformulations (NF) are widely explored as a potential alternative for traditional ophthalmic formulation approaches. The effective treatment of ocular diseases using conventional eye drops is often hampered by factors such as: physiological barriers, rapid elimination, protein binding, and enzymatic drug degradation. Combined, these factors are...

Despite tremendous successes of GPCR crystallog-raphy, the receptors with available structures repre-sent only a small fraction of human GPCRs. An important role of the modeling community is to maxi-mize structural insights for the remaining receptors and complexes. The community-wide GPCR Dock assessment was established to stimulate and monitor th...

The 5-hydroxytryptamine 1A (5-HT1A) serotonin receptor has been an attractive target for treating mood and anxiety disorders such as schizophrenia. We have developed binary classification Quantitative Structure-Activity Relationship (QSAR) models of 5-HT1A receptor binding activity using data retrieved from the PDSP Ki database. The prediction accu...

Despite tremendous successes of GPCR crystallography , the receptors with available structures represent only a small fraction of human GPCRs. An important role of the modeling community is to maximize structural insights for the remaining receptors and complexes. The community-wide GPCR Dock assessment was established to stimulate and monitor the...

Serotonin (5-HT) receptors are neuromodulator neurotransmitter receptors which when activated generate a signal transduction pathway within cells resulting in cell-cell communication. 5-hydroxytryptamine (serotonin) receptor 2B (5-HT2B) is a subtype of the seven members of 5-hydroxytrytamine (5-HT) family of receptors which is the largest member of...

Of great interest in recent years has been computationally predicting the novel polypharmacology of drug molecules. Here, we applied an "induced-fit" protocol to improve the homology models of 5-HT(2A) receptor, and we assessed the quality of these models in retrospective virtual screening. Subsequently, we computationally screened the FDA approved...

Recent highly expected structural characterizations of agonist-bound and antagonist-bound beta-2 adrenoreceptor (β2AR) by X-ray crystallography have been widely regarded as critical advances to enable more effective structure-based discovery of GPCRs ligands. It appears that this very important development may have undermined many previous efforts...

Poor performance of scoring functions is a well-known bottleneck in structure-based virtual screening (VS), which is most frequently manifested in the scoring functions' inability to discriminate between true ligands vs known nonbinders (therefore designated as binding decoys). This deficiency leads to a large number of false positive hits resultin...

Structure-based drug design relies on static protein structures despite significant evidence for the need to include protein dynamics as a serious consideration. In practice, dynamic motions are neglected because they are not understood well enough to model, a situation resulting from a lack of explicit experimental examples of dynamic receptor-lig...

Quantitative structure–activity relationship (QSAR) modeling is the major chemin- formatics approach to exploring and exploiting the dependency of chemical, biological, toxicological, or other types of activities or properties on their molecular features. QSAR modeling has been traditionally used as a lead optimization approach in drug discovery re...

Glutamine 5'-phosphoribosylpyrophosphate amidotransferase (GPATase) catalyzes the synthesis of 5'-phosphoribosylamine in a reaction that involves the translocation of ammonia along an intramolecular tunnel linking the two active sites of the enzyme. We now report a locally enhanced sampling (LES) strategy for modeling ammonia transfer between the a...

Geranylgeranylation is critical to the function of several proteins including Rho, Rap1, Rac, Cdc42, and G-protein gamma subunits. Geranylgeranyltransferase type I (GGTase-I) inhibitors (GGTIs) have therapeutic potential to treat inflammation, multiple sclerosis, atherosclerosis, and many other diseases. Following our standard workflow, we have dev...

In a continuing study, we explored how the individual rings in neo-tanshinlactone (1) influence its potent and selective in vitro antibreast cancer activity. Accordingly, we discovered a novel class of antibreast cancer agents, 2-(furan-2-yl)naphthalen-1-ol derivatives, based on an active C-ring opened model compound 5. Further optimization led to...

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G-Protein-coupled receptors (GPCRs) adopt various functionally relevant conformational states in cell signaling processes. Recently determined crystal structures of rhodopsin and the beta 2-adrenergic receptor (beta 2-AR) offer insight into previously uncharacterized active conformations, but the molecular states of these GPCRs are likely to contai...

The Quantitative Structure-Activity Relationship (QSAR) approach has been applied to model binding affinity and receptor subtype selectivity of human 5HT1E and 5HT1F receptor-ligands. The experimental data were obtained from the PDSP Ki Database. Several descriptor types and data-mining approaches have been used in the context of combinatorial QSAR...

The use of inaccurate scoring functions in docking algorithms may result in the selection of compounds with high predicted binding affinity that nevertheless are known experimentally not to bind to the target receptor. Such falsely predicted binders have been termed 'binding decoys'. We posed a question as to whether true binders and decoys could b...

Based on the growing evidence that G-protein coupled receptors (GPCRs) form homo- and hetero-oligomers, models of GPCR signaling are now considering macromolecular assemblies rather than monomers, with the homo-dimer regarded as the minimal oligomeric arrangement required for functional coupling to the G-protein. The dynamic mechanisms of such sign...

GPCR ligands represent not only one of the major classes of current drugs but the major continuing source of novel potent pharmaceutical agents. Because 3D structures of GPCRs as determined by experimental techniques are still unavailable, ligand-based drug discovery methods remain the major computational molecular modeling approaches to the analys...

The hypothesis that the interaction of agouti-related protein (AGRP) and the melanocortin-4 receptor (MC4R) modulates feeding behavior in humans has stimulated the synthesis of conformationally constrained peptides, peptoids and small molecules in efforts to identify novel compounds that can potentially be used in the clinical treatment of obesity...

The agouti-related protein (AGRP) is an endogenous antagonist of the centrally expressed melanocortin receptors. The melanocortin-4 receptor (MC4R) is involved in energy homeostasis, food intake, sexual function, and obesity. The endogenous hAGRP protein is 132 amino acids in length, possesses five disulfide bridges at the C-terminus of the molecul...

Agouti-related protein (AGRP) is one of two known naturally occurring antagonists of G-protein coupled receptors. AGRP is synthesized in the brain and is an antagonist of the melanocortin-3 and -4 receptors (MC3R, MC4R). These three proteins are involved in the regulation of energy homeostasis and obesity in both mice and humans. The human AGRP pro...