Structure-based Ligand Discovery and Design

Principal Investigator

VERMA Ravi Kumar, LIN Fu
Senior Post Doc Research Fellows

JALADANKI Chaitanya Kumar, Krishna Deepak R.N.V, HARTONO Yossa Dwi
Post Doc Research Fellows

Ms. LO Wing Kwan Catharine *
Research Officer

Alessandro BARBIERI, Kevin Jie Han LIM, Srdan MASIREVIC
PhD Students

* Joint with Dr. Cheng Li's Lab

The broad goal is to develop computational techniques to study protein-ligand interactions. The developed methods are applied to GPCRs, transporters, and kinases, to contribute to a better understanding and regulation of biological processes, as well as the discovery of new therapeutics. The computational predictions are tested experimentally through collaborations. Our computational techniques are also generally applicable to structural and functional studies of other protein families.

Membrane Protein Ligand Discovery and Functional Mechanism Study

GPCRs play important roles in cell signaling pathways. Their dysfunction causes many human developmental and metabolic disorders, as well as certain cancers. Glucose-dependent insulinotropic receptor (GPR119) is known to modulate insulin release and GLP-1 secretion. GPR119 has been of interest in the development of therapeutic interventions to diagnose and treat diabetes. We have been collaborating with Dr. Edward Robins and Dr. Weiping Han from SBIC, A*STAR, combining in-silico modelling and medicinal chemistry approach, to develop highly potent GPR119 ligands that may be developed as PET imaging probes for the quantification of β-cell mass to further understand the pathology of diabetes. The designed ligand candidates were predicted by computation and tested in cAMP functional assay. The most potent ligands confirmed were further tested in radioligand binding assay, some showing sub- nanomolar potency. Meanwhile, we are also interested in GPCRs that are standard sweet, bitter, or umami taste receptors. Ligand binding at the taste receptors activate second messenger cascades to depolarize the taste cell. We are collaborating with Dr. Nic Lindley and Dr. Heng Phon Too in BioTrans, A*STAR to rationally design novel ligands for taste receptors. Ligand candidates were suggested by docking screens against 3D homology models of human sweet receptors and a few candidates have been confirmed by the sweet receptor cell-based assays showing novel chemical scaffolds and remarkable biological efficacy.

The Major Facilitator Superfamily (MFS) is the largest known superfamily of secondary carriers found in the biosphere. The Major Facilitator Superfamily Domain containing 2A (Mfsd2a) was characterized as a sodium-dependent lysophosphatidylcholine (LPC) transporter expressed at the blood-brain barrier endothelium. It is the primary route for importation of docosohexaenoic acid (DHA) and other long-chain fatty acids into foetal and adult brain, and is essential for mouse and human brain growth and function. We collaborated with Dr. David Silver at Duke-NUS, establishing a structural model of Mfsd2a using molecular modelling/docking and biochemical analyses of altered transporters. This is the first molecular model of this critical transporter, and could prove important for the development of therapeutic agents that need to be delivered to the brain - across the blood-brain barrier. The lysophospholipid transporter (LplT) is involved in the recycling of phospholipids in the cell membranes of gram- negative bacteria, including several human pathogens. Therefore LplT is a potential target for the rational structure-based design/identification of antibacterial agents. As a first step in this direction, we collaborated with Dr. Lei Zheng at UTHealth Medical School, Texas USA, establishing a structural model of LplT from a human pathogen Klebsiella pneumonia using molecular modelling/docking, mutagenesis, and functional assays. This verified Lplt model can facilitate the discovery of potential antibacterial compounds.

Figure 1
^ Figure 1: The human sweet receptor T1R3 TMD domain modelled in complex with a positive allosteric modulator.
Figure 3
^ Figure 2: The Overall architecture of LplT-Kp model in the outward-open conformation with a docked conformation of lyso-PE.

Computer Aided Enzyme Design and Ligand Discovery

Quorum sensing is an integral part of microbial interaction and is responsible for mediating virulence of pathogenic bacteria. Quorum quenching, an attenuation of the quorum-sensing pathway, has been shown to be an effective antivirulence strategy. We are collaborating with Dr. Wen Shan Yew at Department of Biochemistry, NUS, developing quorum-quenching lactonase that catalyzes the quorum sensing signal N-acyl homoserine lactones (AHLs), as antivirulence therapeutic agents. We start from a thermostable GKL (lactonase from Geobacillus kaustophilus) enzyme, suggest mutations in the enzyme active site by computational approaches, and test these mutations in enzyme functional assays. Some mutations show increased catalytic efficiencies and a broadened substrate range. They will have higher clinic value than the original enzyme, providing a promising potential in the alternative antibiotic drug development given the increasing incidences of drug resistance in pathogenic bacteria.

Kinase inhibitors are essential research reagents and valuable therapeutics. One approach to improve the specificity of kinase inhibitors is to target allosteric sites distinct from the ATP-binding pocket. We collaborated with Dr. James Wells at UCSF, investigating the utility of virtual screening as a site-directed approach to discover new ligands for the allosteric site called PIF pocket in 3-phosphoinositide-dependent protein kinase 1 (PDK1). We identified a compound that binds to the PIF pocket in PDK1 with single- digit micromolar affinity. We confirmed the docking poses by determining the crystal structure of PDK1 in complex with this compound. Because the PIF pocket appears to be a recurring feature of the kinase fold, known generally as the helix αC patch, our approach may lead to the discovery of allosteric modulators for a number of additional kinases.

Chemical Toxicity Prediction

High-throughput (HTP) models are required for assessing the hazards posed by the large numbers of existing or novel xenobiotics used in pharmaceutical, food, personal-care, agricultural, chemical, and other industries. Most toxic xenobiotics have diverse and often unknown intracellular targets and injury mechanisms. Short chain fatty acids (SCFAs) are postulated to modulate the immune development of neonates via epigenetic regulations such as histone deacetylase (HDAC) inhibition. We collaborated with Dr. Eric Chun Yong Chan at Department of Pharmacy, NUS, investigating the structure-inhibition relationships of SCFAs with class I HDAC3 and class IIa HDAC7 using in-silico docking simulation and in-vitro human recombinant HDAC inhibition assay. We found that he inhibition of HDAC3 and HDAC7 by gut-derived SCFAs is influenced by the aliphatic chain length and impeded by branching of SCFAs. Future investigation of human disposition of SCFAs is important to establish their effects on innate versus adaptive immunity.

The family of cytochrome P450 (CYP) enzymes plays an important role in the metabolism of a large number of endogenous and exogenous compounds, including most of the drugs currently on the market. To date, the utility of the protein-based methods in CYP-ligand binding and toxicity prediction has not been systematically evaluated. We collaborate with Dr. Lit-Hsin Loo in BII, A*STAR, benchmarking and further improving existing state-of-art protein-based methods, to facilitate CYP-ligand binding mediated organ-specific toxicity prediction. This project will provide important basis for the in-silico and in-vitro tissue or multi-organ toxicity models that we aim to develop in the near future.

Figure 3
^ Figure 3: 4-methylvaleric acid docked in HDAC3 active site.

Computational Method Development

The broad goal is to develop computational techniques to effectively and accurately model protein-ligand interactions. The developed methods will be applied to therapeutic targets such as GPCRs, transporters, and downstream kinases, to contribute to a better understanding and regulation of biological processes; to the discovery of new ingredients for food and nutrition, chemical probes, and drug leads; and to the development of an in-silico platform for chemical toxicity prediction.

Structure-based Ligand Discovery and Design Members

Dr. FAN Hao
Principal Investigator
  Biography Details
Dr. FAN HaoPrincipal Investigator
Dr. VERMA Ravi KumarPostdoctoral Fellow
Dr. LIN FuPostdoctoral Fellow
Dr. HARTONO Yossa DwiPostdoctoral Fellow
Dr. Krishna DeepakPostdoctoral Fellow
Dr. JALADANKI Chaitanya KumarPostdoctoral Fellow
Ms. LO Wing Kwan Catharine ( joint with Dr. Cheng Li's lab )Research Officer
Mr. MASIREVIC Srdjan PhD student
Mr. LIM Jie Han, Kevin PhD student
Mr. Alessandro BARBIERI PhD student
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