Pharmacophore Elucidation Research Articles

PharmRL: Pharmacophore elucidation with Deep Geometric Reinforcement Learning.

Molecular interactions between proteins and their ligands are important for drug design. A pharmacophore consists of favorable molecular interactions in a protein binding site and can be utilized for virtual screening. Pharmacophores are easiest to identify from co-crystal structures of a bound protein-ligand complex. In this work, however, we develop a deep learning method that can identify pharmacophores in the absence of a ligand. Specifically, we train a CNN model to identify potential favorable interactions in the the binding site, and develop a deep geometric Q-learning algorithm that attempts to select an optimal subset of these interaction points to form a pharmacophore. With this algorithm, we show better prospective virtual screening performance, in terms of F1 scores, on the DUD-E dataset than random selection of ligand identified features from co-crystal structures. We also conduct experiments on the LIT-PCBA dataset and show that it provides efficient solutions for identifying active molecules. Finally, we test our method by screening the COVID moonshot dataset and show that it would be effective in identifying prospective lead molecules even in the absence of fragment screening experiments. Alongside, we provide a Google Colab notebook for ease of use of the developed method.

Computational Methods for Anticancer Drug Discovery; The MCT4 Paradigm.

Modern anticancer research has employed advanced computational techniques and artificial intelligence methods for drug discovery and development, along with the massive amount of generated clinical and in silico data over the last decades. Diverse computational techniques and state-of-the-art algorithms are being developed to enhance traditional Rational Drug Design pipelines and achieve cost-efficient and successful anticancer candidates to promote human health. Towards this direction, we have developed a pharmacophore- based drug design approach against MCT4, a member of the monocarboxylate transporter family (MCT), which is the main carrier of lactate across the membrane and highly involved in cancer cell metabolism. Specifically, MCT4 is a promising target for therapeutic strategies as it overexpresses in glycolytic tumors, and its inhibition has shown promising anticancer effects. Due to the lack of experimentally determined structure, we have elucidated the key features of the protein through an in silico drug design strategy, including for molecular modelling, molecular dynamics, and pharmacophore elucidation, towards the identification of specific inhibitors as a novel anti-cancer strategy.

A Holistic Evolutionary and 3D Pharmacophore Modelling Study Provides Insights into the Metabolism, Function, and Substrate Selectivity of the Human Monocarboxylate Transporter 4 (hMCT4).

Monocarboxylate transporters (MCTs) are of great research interest for their role in cancer cell metabolism and their potential ability to transport pharmacologically relevant compounds across the membrane. Each member of the MCT family could potentially provide novel therapeutic approaches to various diseases. The major differences among MCTs are related to each of their specific metabolic roles, their relative substrate and inhibitor affinities, the regulation of their expression, their intracellular localization, and their tissue distribution. MCT4 is the main mediator for the efflux of L-lactate produced in the cell. Thus, MCT4 maintains the glycolytic phenotype of the cancer cell by supplying the molecular resources for tumor cell proliferation and promotes the acidification of the extracellular microenvironment from the co-transport of protons. A promising therapeutic strategy in anti-cancer drug design is the selective inhibition of MCT4 for the glycolytic suppression of solid tumors. A small number of studies indicate molecules for dual inhibition of MCT1 and MCT4; however, no selective inhibitor with high-affinity for MCT4 has been identified. In this study, we attempt to approach the structural characteristics of MCT4 through an in silico pipeline for molecular modelling and pharmacophore elucidation towards the identification of specific inhibitors as a novel anti-cancer strategy.

Potential of hydrocarbon and oxygenated monoterpenes against Culex pipiens larvae: Toxicity, biochemical, pharmacophore modeling and molecular docking studies

Culex pipiens is a main vector for Bancroftian filariasis, Rift Valley Fever and diseases caused by other viruses, leaving several peoples with disabilities. In recent years, plant derived compounds have received much attention as potential alternatives to synthetic chemicals due to their low toxicity to mammals and environmental persistence. Twenty-one monoterpenes from different chemical groups (hydrocarbons and oxygenated products) were evaluated against Culex pipiens larvae. In addition, in vivo biochemical studies including effects on acetylcholine esterase (AChE), acid and alkaline phosphatases (ACP and ALP), total adenosine triphosphatase (ATPase) and gamma-aminobutyric acid transaminase (GABA-T) were investigated. Furthermore, in silico studies including pharmacophore elucidation, ADMET analysis and molecular docking of these compounds were performed. Among all tested monoterpenes, hydrocarbons [p-cymene, (R)-(+)-limonene and (+)-α-pinene], acetates (cinnamyl acetate, citronellyl acetate, eugenyl acetate and terpinyl acetate), alcohols [(±)-β-citronellol and terpineol], aldehydes [citral and (1R)-(−)-myrtenal] and ketone [(R)-(+)-pulegone] exhibited the highest larval toxicity with LC50 = 14.88, 27.97, 26.13, 2.62, 3.81, 2.74, 21.65, 1.64, 21.70, 21.76, 1.68 and 1.90 mg/L after 48 h of exposure, respectively. The compounds proved a significant inhibition of all tested enzymes except total ATPase. The biochemical and molecular docking studies proved that AChE and GABA-T were the main targets for the tested monoterpenes.

Design, synthesis, ADME prediction and pharmacological evaluation of novel benzimidazole-1,2,3-triazole-sulfonamide hybrids as antimicrobial and antiproliferative agents

BackgroundNitrogen heterocyclic rings and sulfonamides have attracted attention of several researchers.ResultsA series of regioselective imidazole-based mono- and bis-1,4-disubstituted-1,2,3-triazole-sulfonamide conjugates 4a–f and 6a–f were designed and synthesized. The first step in the synthesis was a regioselective propargylation in the presence of the appropriate basic catalyst (Et3N and/or K2CO3) to afford the corresponding mono-2 and bis-propargylated imidazoles 5. Second, the ligation of the terminal C≡C bond of mono-2 and/or bis alkynes 5 to the azide building blocks of sulfa drugs 3a–f using optimized conditions for a Huisgen copper (I)-catalysed 1,3-dipolar cycloaddition reaction yielded targeted 1,2,3-triazole hybrids 4a–f and 6a–f. The newly synthesized compounds were screened for their in vitro antimicrobial and antiproliferative activities. Among the synthesized compounds, compound 6a emerged as the most potent antimicrobial agent with MIC values ranging between 32 and 64 µg/mL. All synthesized molecules were evaluated against three aggressive human cancer cell lines, PC-3, HepG2, and HEK293, and revealed sufficient antiproliferative activities with IC50 values in the micromolar range (55–106 μM). Furthermore, we conducted a receptor-based electrostatic analysis of their electronic, steric and hydrophobic properties, and the results were in good agreement with the experimental results. In silico ADMET prediction studies also supported the experimental biological results and indicated that all compounds are nonmutagenic and noncarcinogenic.ConclusionIn summary, we have successfully synthesized novel targeted benzimidazole-1,2,3-triazole-sulfonamide hybrids through 1,3-dipolar cycloaddition reactions between the mono- or bis-alkynes based on imidazole and the appropriate sulfonamide azide under the optimized Cu(I) click conditions. The structures of newly synthesized sulfonamide hybrids were confirmed by means of spectroscopic analysis. All newly synthesized compounds were evaluated for their antimicrobial and antiproliferative activities. Our results showed that the benzimidazole-1,2,3-triazole-sulfonamide hybrids inhibited microbial and fungal strains within MIC values from 32 to 64 μg/mL. The antiproliferative evaluation of the synthesized compounds showed sufficient antiproliferative activities with IC50 values in the micromolar range (55–106 μM). In conclusion, compound 6a has remarkable antimicrobial activity. Pharmacophore elucidation of the compounds was performed based on in silico ADMET evaluation of the tested compounds. Screening results of drug-likeness rules showed that all compounds follow the accepted rules, meet the criteria of drug-likeness and follow Lipinski’s rule of five. In addition, the toxicity results showed that all compounds are nonmutagenic and noncarcinogenic.

Development and Validation of Molecular Overlays Derived from Three-Dimensional Hydrophobic Similarity with PharmScreen.

Molecular alignment is a standard procedure for three-dimensional (3D) similarity measurements and pharmacophore elucidation. This process is influenced by several factors, such as the physicochemical descriptors utilized to account for the molecular determinants of biological activity and the reference templates. Relying on the hypothesis that the maximal achievable binding affinity for a drug-like molecule is largely due to desolvation, we explore a novel strategy for 3D molecular overlays that exploits the partitioning of molecular hydrophobicity into atomic contributions in conjunction with information about the distribution of hydrogen-bond (HB) donor/acceptor groups. A brief description of the method, as implemented in the software package PharmScreen, including the derivation of the fractional hydrophobic contributions within the quantum mechanical version of the Miertus-Scrocco-Tomasi (MST) continuum model, and the procedure utilized for the optimal superposition between molecules, is presented. The computational procedure is calibrated by using a data set of 402 molecules pertaining to 14 distinct targets taken from the literature and validated against the AstraZeneca test, which comprises 121 experimentally derived sets of molecular overlays. The results point out the suitability of the MST-based hydrophobic parameters for generating molecular overlays, as correct predictions were obtained for 94%, 79%, and 54% of the molecules classified into easy, moderate, and hard sets, respectively. Moreover, the results point out that this accuracy is attained at a much lower degree of identity between the templates used by hydrophobic/HB fields and electrostatic/steric ones. These findings support the usefulness of the hydrophobic/HB descriptors to generate complementary overlays that may be valuable to rationalize structure-activity relationships and for virtual screening campaigns.

Exploring protein–protein intermolecular recognition between meprin-α and endogenous protease regulator cystatinC coupled with pharmacophore elucidation

Meprins are a group of zinc metalloproteases of the astacin family which play a pivotal role in several physiological and pathologocal diseases. The inhibition of the meprins by various inhibitors, macromolecular and small molecules, is crucial in the control of several diseases. Human cystatinC, an amyloidogenic protein, is reported to be an endogenous inhibitor of meprin-α. In this computational study, we elucidate a rational model for meprinα–cystatinC complex using protein–protein docking. The complex model as well as the unbound form was evaluated by molecular dynamics simulation. A simulation study revealed higher stability of the complex owing to the presence of several interactions. Virtual alanine mutagenesis helps in identifying the hotspots on both proteins. Based on the frequency of occurrence of hotspot amino acids, it was possible to enumerate the important amino acids primarily responsible for protein stability present at the amino-terminal end of cystatin. Finally, pharmacophore elucidation carried out based on the information obtained from a series of small molecular inhibitors against meprin-α can be utilized in future for rational drug design and therapy.

AnchorQuery: Rapid online virtual screening for small-molecule protein-protein interaction inhibitors.

AnchorQuery (http://anchorquery.csb.pitt.edu) is a web application for rational structure-based design of protein-protein interaction (PPI) inhibitors. A specialized variant of pharmacophore search is used to rapidly screen libraries consisting of more than 31 million synthesizable compounds biased by design to preferentially target PPIs. Every library compound is accessible through one-step multi-component reaction (MCR) chemistry and contains an anchor motif that is bioisosteric to an amino acid residue. The inclusion of this anchor not only biases the compounds to interact with proteins, it also enables a rapid, sublinear time pharmacophore search algorithm. AnchorQuery provides all the tools necessary for users to perform online interactive virtual screens of millions of compounds, including pharmacophore elucidation and search, and enrichment analysis. Accessibility: AnchorQuery is freely accessible at http://anchorquery.csb.pitt.edu.

Genetic and structural study of DNA-directed RNA polymerase II of Trypanosoma brucei, towards the designing of novel antiparasitic agents.

Trypanosoma brucei brucei (TBB) belongs to the unicellular parasitic protozoa organisms, specifically to the Trypanosoma genus of the Trypanosomatidae class. A variety of different vertebrate species can be infected by TBB, including humans and animals. Under particular conditions, the TBB can be hosted by wild and domestic animals; therefore, an important reservoir of infection always remains available to transmit through tsetse flies. Although the TBB parasite is one of the leading causes of death in the most underdeveloped countries, to date there is neither vaccination available nor any drug against TBB infection. The subunit RPB1 of the TBB DNA-directed RNA polymerase II (DdRpII) constitutes an ideal target for the design of novel inhibitors, since it is instrumental role is vital for the parasite’s survival, proliferation, and transmission. A major goal of the described study is to provide insights for novel anti-TBB agents via a state-of-the-art drug discovery approach of the TBB DdRpII RPB1. In an attempt to understand the function and action mechanisms of this parasite enzyme related to its molecular structure, an in-depth evolutionary study has been conducted in parallel to the in silico molecular designing of the 3D enzyme model, based on state-of-the-art comparative modelling and molecular dynamics techniques. Based on the evolutionary studies results nine new invariant, first-time reported, highly conserved regions have been identified within the DdRpII family enzymes. Consequently, those patches have been examined both at the sequence and structural level and have been evaluated in regard to their pharmacological targeting appropriateness. Finally, the pharmacophore elucidation study enabled us to virtually in silico screen hundreds of compounds and evaluate their interaction capabilities with the enzyme. It was found that a series of chlorine-rich set of compounds were the optimal inhibitors for the TBB DdRpII RPB1 enzyme. All-in-all, herein we present a series of new sites on the TBB DdRpII RPB1 of high pharmacological interest, alongside the construction of the 3D model of the enzyme and the suggestion of a new in silico pharmacophore model for fast screening of potential inhibiting agents.

Pharmacophore elucidation of phosphoiodyn A – Potent and selective peroxisome proliferator-activated receptor β/δ agonists with neuroprotective activity

We report the pharmacophore of the peroxisome proliferator-activated receptor δ (PPARδ) agonist natural product phosphoiodyn A is the phosphonate core. Synthesis of simplified phosphonate esters 13 and 15 provide structurally novel, highly selective and potent PPARδ agonists (EC50=78 and 112nM, respectively). Further, both compounds demonstrate significant neuroprotective activity in an in vitro cellular model indicating that phosphonates may be an effective novel scaffold for the design of therapeutics for the treatment of neurodegenerative disorders.

Erratum for: Sesquiterpene Lactones from Cynara cornigera: Acetyl Cholinesterase Inhibition and In Silico Ligand Docking.

Wild artichoke (Cynara cornigera), a thistle-like perennial belonging to the Asteraceae family, is native to the Mediterranean region, northwestern Africa, and the Canary Islands. While the pleasant, albeit bitter, taste of the leaves and flowers is attributed to the sesquiterpene lactones cynaropicrin and cynarin, a comprehensive phytochemical investigation still needs to be reported. In this study seven sesquiterpene lactones were isolated from an aqueous methanol plant extract, including a new halogenated metabolite (1), the naturally isolated compound sibthorpine (2), and five metabolites isolated for the first time from C. cornigera. Structures were established by spectroscopic methods, including HREIMS, (1 )H, (13 )C, DEPT, (1 )H-(1 )H COSY, HMQC, and HMBC-NMR experiments as well as by X-ray analysis. The isolated bioactive nutrients were analyzed for their antioxidant and metal chelating activity. Compound 1 exhibited a potent metal chelating activity as well as a high antioxidant capacity. Moreover, select compounds were effective as acetyl cholinesterase inhibitors presenting the possibility for such compounds to be examined for anti-neurodegenerative activity. A computational pharmacophore elucidation and docking study was performed to estimate the pharmacophoric features and binding conformation of isolated compounds in the acetyl cholinesterase active site.

Sesquiterpene Lactones from Cynara cornigera: Acetyl Cholinesterase Inhibition and In Silico Ligand Docking.

Wild artichoke (Cynara cornigera), a thistle-like perennial belonging to the Asteraceae family, is native to the Mediterranean region, northwestern Africa, and the Canary Islands. While the pleasant, albeit bitter, taste of the leaves and flowers is attributed to the sesquiterpene lactones cynaropicrin and cynarin, a comprehensive phytochemical investigation still needs to be reported. In this study seven sesquiterpene lactones were isolated from an aqueous methanol plant extract, including a new halogenated metabolite (1), the naturally isolated compound sibthorpine (2), and five metabolites isolated for the first time from C. cornigera. Structures were established by spectroscopic methods, including HREIMS, (1 )H, (13 )C, DEPT, (1 )H-(1 )H COSY, HMQC, and HMBC-NMR experiments as well as by X-ray analysis. The isolated bioactive nutrients were analyzed for their antioxidant and metal chelating activity. Compound 1 exhibited a potent metal chelating activity as well as a high antioxidant capacity. Moreover, select compounds were effective as acetyl cholinesterase inhibitors presenting the possibility for such compounds to be examined for anti-neurodegenerative activity. A computational pharmacophore elucidation and docking study was performed to estimate the pharmacophoric features and binding conformation of isolated compounds in the acetyl cholinesterase active site.

PENG: a neural gas-based approach for pharmacophore elucidation. method design, validation, and virtual screening for novel ligands of LTA4H.

The pharmacophore concept is commonly employed in virtual screening for hit identification. A pharmacophore is generally defined as the three-dimensional arrangement of the structural and physicochemical features of a compound responsible for its affinity to a pharmacological target. Given a number of active ligands binding to a particular target in the same manner, it can reasonably be assumed that they have some shared features, a common pharmacophore. We present a growing neural gas (GNG)-based approach for the extraction of the relevant features which we called PENG (pharmacophore elucidation by neural gas). Results of retrospective validation indicate an acceptable quality of the generated models. Additionally a prospective virtual screening for leukotriene A4 hydrolase (LTA4H) inhibitors was performed. LTA4H is a bifunctional zinc metalloprotease which displays both epoxide hydrolase and aminopeptidase activity. We could show that the PENG approach is able to predict the binding mode of the ligand by X-ray crystallography. Furthermore, we identified a novel chemotype of LTA4H inhibitors.

New aryloxy-quinone derivatives as potential anti-Chagasic agents: synthesis, trypanosomicidal activity, electrochemical properties, pharmacophore elucidation and 3D-QSAR analysis

A set of new aryloxy-quinones were synthesized and evaluatedin vitroagainst the epimastigote form ofTrypanosoma cruziand their unspecific cytotoxicity was tested on murine macrophages J-774 cells.

Identification and pharmacological characterization of 3,6-diazabicyclo[3.1.1]heptane-3-carboxamides as novel ligands for the α4β2 and α6/α3β2β3 nicotinic acetylcholine receptors (nAChRs)

We have synthesized a novel series of compounds, 3,6-diazabicyclo[3.1.1]heptane-3-carboxamides, targeting both the α4β2 and α6/α3β2β3 nAChRs. Members of the obtained chemical library are partial or full agonists at both the high sensitivity (α4)2(β2)3 and α6/α3β2β3 nAChRs. 3-(Cyclopropylcarbonyl)-3,6-diazabicyclo[3.1.1]heptane (TC-8831 or compound 7 herein) demonstrated a safe in vitro pharmacological profile and the potential for reducing or preventing l-dopa-induced dyskinesias (LID) in several in vivo animal models [1–4]. In vivo metabolism studies in rat and in vitro metabolism studies in liver microsomes from human, rat, dog and monkey showed TC-8831 to be relatively stable. In vivo pharmacokinetic analysis in the rat confirmed brain penetration, with an average brain:plasma ratio of approximately 0.3 across time points from 0.5 to 4 h. Docking into homology models predicted alternative binding modes for TC-8831 and highlighted the importance of the cationic center, hydrogen-bond acceptor, and hydrophobic aliphatic features in promoting binding affinity to both nAChRs. Pharmacophore elucidation confirmed the importance of these key interactions. QSAR modeling suggested that binding affinity is primarily driven by ligand shape, relative positive charge distribution onto the molecular surface, and molecular flexibility. Of the two subtypes, ligand binding to α6β2β3 appears to be more sensitive to bulkiness and flexibility.

Pharmacophore elucidation and 3D-QSAR analysis of a new class of highly potent inhibitors of acid ceramidase based on maximum common substructure and field fit alignment methods

Comparative molecular field analysis (CoMFA) and comparative similarity indices analysis (CoMSIA) studies have been carried on a series of 2,4-dioxopyrimidine-1-carboxamides as acid ceramidase inhibitors. Two alignment rules for the compounds were defined using maximum common substructure and field fit. The best orientation was then searched by all-orientation search strategy, to minimize the effect of the initial orientation of the structures. The Kennard Stone algorithm was used to divide the entire set into training (25 compounds) and test (7 compounds) sets. Pharmacophore model identification was also performed using DISCOtech algorithm and refinement was carried out using GASP, to highlight important structural features that could be responsible for the inhibitory activity. All constructed models showed appropriate statistical parameters in terms of q2 and rpred2. Based upon the information obtained from CoMFA, CoMSIA, and developed pharmacophore pattern, some key features that may be used to design new inhibitors for acid ceramidase have been identified.

Computational studies of novel carbonyl-containing diazabicyclic ligands interacting with α4β2 nicotinic acetylcholine receptor (nAChR) reveal alternative binding modes

We have carried out computational studies on interactions of diazabicyclic amide analogs with α4β2 nAChR using homology modeling, docking and pharmacophore elucidation techniques. We have found alternative ligand binding modes in most cases. All these diverse poses exhibit the quintessential hydrogen-bonding interaction between the ligand basic nitrogen and the backbone carbonyl oxygen atom of the highly conserved Trp-149. This hydrogen bond was always found to be shorter than the one contracted by the ligand carbonyl group and a second hydrogen-bond made by the cationic center with Tyr-93 of the principal face of the protein. In most of the poses observed, cation–π interactions involved three aromatic residues located in the principal face of the protein: Trp-149, Tyr-190 and Tyr-197. The latter amino acid residue appears to often donate a hydrogen-bond to the ligand carbonyl oxygen atom. We also describe two rings of alternative receptor-based hydrogen-bond donor features equidistantly separated from the carbonyl oxygen of the highly conserved Trp-149 approximately by 5 and 8Å, respectively. These findings could be exploited to design diverse and selective novel chemical libraries for the treatment of diseases and conditions where the α4β2 nAChR is disrupted, such as Alzheimer disease, Parkinson’s disease and l-dopa-induced dyskinesia (LID).

Molecular modeling and pharmacophore elucidation study of the Classical Swine Fever virus helicase as a promising pharmacological target

The Classical Swine Fever virus (CSFV) is a major pathogen of livestock and belongs to the flaviviridae viral family. Even though there aren’t any verified zoonosis cases yet, the outcomes of CSFV epidemics have been devastating to local communities. In an effort to shed light to the molecular mechanisms underlying the structural and drug design potential of the viral helicase, the three dimensional structure of CSFV helicase has been modeled using conventional homology modeling techniques and the crystal structure of the Hepatitis C virus (HCV) as a template. The established structure of the CSFV helicase has been in silico evaluated for its viability using a repertoire of in silico tools. The ultimate goal of this study is to introduce the 3D conformation of the CSFV helicase as a reliable structure that may be used as the designing platform for de novo, structure-based drug design experiments. In this direction using the modeled structure of CSVF helicase, a 3D pharmacophore was designed. The pharmacophore comprises of a series of key characteristics that molecular inhibitors must satisfy in order to achieve maximum predicted affinity for the given enzyme. Overall, invaluable insights and conclusions are drawn from this structural study of the CSFV helicase, which may provide the scientific community with the founding plinth in the fight against CSFV infections through the perspective of the CSFV helicase as a potential pharmacological target. Notably, to date no antiviral agent is available against the CSFV nor is expected soon. Subsequently, there is urgent need for new modern and state-of-the-art antiviral strategies to be developed.

GRID-Based Three-Dimensional Pharmacophores II: PharmBench, a Benchmark Data Set for Evaluating Pharmacophore Elucidation Methods

To date, published pharmacophore elucidation approaches typically use a handful of data sets for validation: here, we have assembled a data set for 81 targets, containing 960 ligands aligned using their cocrystallized protein targets, to provide the experimental "gold standard". The two-dimensional structures are also assembled to remove conformational bias; an ideal method would be able to take these structures as input, find the common features, and reproduce the bioactive conformations and their alignments to correspond with the X-ray-determined gold standard alignments. Here we present this data set and describe three objective measures to evaluate performance: the ability to identify the bioactive conformation, the ability to identify and correctly align this conformation for 50% of the molecules in each data set, and the pharmacophoric field similarity. We have applied this validation methodology to our pharmacophore elucidation method FLAPpharm, that is published in the first paper of this series and discuss the limitations of the data set and objective success criteria. Starting from two-dimensional structures and producing unbiased models, FLAPpharm was able to identify the bioactive conformations for 67% of the ligands and also to produce successful models according to the second metric for 67% of the Pharmbench data sets. Inspection of the unsuccessful models highlighted the limitation of this root mean square (rms)-derived metric, since many were found to be pharmacophorically reasonable, increasing the overall success rate to 83%. The PharmBench data set is available at http://www.moldiscovery.com/PharmBench , along with a web service to enable users to score model alignments coming from external methods in the same way that we have presented here and, therefore, establishes a pharmacophore elucidation benchmark data set available to be used by the community.

GRID-Based Three-Dimensional Pharmacophores I: FLAPpharm, a Novel Approach for Pharmacophore Elucidation

Pharmacophore elucidation approaches are routinely used in drug discovery, primarily with the aim of determining the three-dimensional arrangement of common features shared by ligands interacting at the site of interest; these features can then be used to investigate the structure-activity relationship between the ligands and also to screen for other molecules possessing the relevant features. Here we present a novel approach based on GRID molecular interaction fields and the derivative method FLAP that has been previously described, which provides a common reference framework to compare both small molecule ligands and macromolecular protein targets. Unlike classical pharmacophore elucidation approaches that extract simplistic molecular features, determine those which are common across the data set, and use these features to align the structures, FLAPpharm first aligns the structures and subsequently extracts the common interacting features in terms of their molecular interaction fields, pseudofields, and atomic points, representing the common pharmacophore as a more comprehensive pharmacophoric pseudomolecule. The approach is applied to a number of data sets to investigate performance in terms of reproducing the X-ray crystallography-based alignment, in terms of its discriminatory ability when applied to virtual screening and also to illustrate its ability to explain alternative binding modes. In part two of this publication, a comprehensive benchmark data set for pharmacophore elucidation is presented and the performance of FLAPpharm discussed.