Xiang Simon Wang

Xiang Simon Wang
Howard University | HU · College of Pharmacy

PhD

About

93
Publications
11,005
Reads
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1,094
Citations
Citations since 2016
29 Research Items
563 Citations
2016201720182019202020212022020406080
2016201720182019202020212022020406080
2016201720182019202020212022020406080
2016201720182019202020212022020406080
Introduction
Dr. Simon Wang is currently a tenured associate professor at the Department of Pharmaceutical Sciences, Howard University College of Pharmacy (HU COP). His expertise includes computer-aided drug design (CADD), artificial intelligence (AI)/machine learning (ML), structure-based drug design (SBDD), computational chemistry, and biomolecular simulation. Dr. Wang has pioneered in applying AI/ML to modern drug targets, being able to identify drug candidates for further development.
Additional affiliations
January 2011 - present
Howard University
Position
  • Professor
January 2006 - December 2010
University of North Carolina at Chapel Hill
Position
  • Professor
September 2003 - December 2005
Cornell University
Position
  • PostDoc Position

Publications

Publications (93)
Article
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...
Article
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...
Article
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...
Article
Full-text available
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...
Article
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...
Article
Full-text available
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...
Research
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...
Article
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...
Article
Full-text available
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...
Data
The manual is also available at https://github.com/jwxia2014/MUBD-DecoyMaker2.0.
Article
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...
Poster
Full-text available
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...
Poster
Full-text available
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...
Article
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...
Data
The MUBD-hCRs are also available at https://github.com/jwxia2014/MUBD-hCRs.
Article
Full-text available
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...
Article
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...
Article
Full-text available
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...
Article
Full-text available
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...
Article
Full-text available
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...
Chapter
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...
Data
The ULS-UDS is also available at https://pan.baidu.com/s/1eybnkObSzsovUEXCgEZE6g ; password:dhti OR https://github.com/jwxia2014/ULS-UDS
Article
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...
Article
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...
Article
Full-text available
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,...
Article
Full-text available
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...
Article
Full-text available
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...
Chapter
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Data
The MUBD-HDACs are also available at https://github.com/jwxia2014/MUBD-HDACs.
Article
Full-text available
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...
Article
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...
Article
Full-text available
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...
Article
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...
Article
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...
Article
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...
Article
Full-text available
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...
Article
Full-text available
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...
Article
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...
Article
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...
Article
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...
Chapter
Full-text available
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...
Article
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...
Article
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...
Article
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...
Article
Full-text available
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...
Article
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...