Spherical harmonics coeffcients for ligand-based virtual screening of cyclooxygenase inhibitors

Background: Molecular descriptors are essential for many applications in computational chemistry, such as ligand-based similarity searching. Spherical harmonics have previously been suggested as comprehensive descriptors of molecular structure and properties. We investigate a spherical harmonics descriptor for shape-based virtual screening. Methodology/Principal Findings: We introduce and validate a partially rotation-invariant three-dimensional molecular shape descriptor based on the norm of spherical harmonics expansion coefficients. Using this molecular representation, we parameterize molecular surfaces, i.e., isosurfaces of spatial molecular property distributions. We validate the shape descriptor in a comprehensive retrospective virtual screening experiment. In a prospective study, we virtually screen a large compound library for cyclooxygenase inhibitors, using a self-organizing map as a pre-filter and the shape descriptor for candidate prioritization. Conclusions/Significance: 12 compounds were tested in vitro for direct enzyme inhibition and in a whole blood assay. Active compounds containing a triazole scaffold were identified as direct cyclooxygenase-1 inhibitors. This outcome corroborates the usefulness of spherical harmonics for representation of molecular shape in virtual screening of large compound collections. The combination of pharmacophore and shape-based filtering of screening candidates proved to be a straightforward approach to finding novel bioactive chemotypes with minimal experimental effort

Study of ligand-based virtual screening tools in computer-aided drug design

Virtual screening is a central technique in drug discovery today. Millions of molecules can be tested in silico with the aim to only select the most promising and test them experimentally. The topic of this thesis is ligand-based virtual screening tools which take existing active molecules as starting point for finding new drug candidates. One goal of this thesis was to build a model that gives the probability that two molecules are biologically similar as function of one or more chemical similarity scores. Another important goal was to evaluate how well different ligand-based virtual screening tools are able to distinguish active molecules from inactives. One more criterion set for the virtual screening tools was their applicability in scaffold-hopping, i.e. finding new active chemotypes. In the first part of the work, a link was defined between the abstract chemical similarity score given by a screening tool and the probability that the two molecules are biologically similar. These results help to decide objectively which virtual screening hits to test experimentally. The work also resulted in a new type of data fusion method when using two or more tools. In the second part, five ligand-based virtual screening tools were evaluated and their performance was found to be generally poor. Three reasons for this were proposed: false negatives in the benchmark sets, active molecules that do not share the binding mode, and activity cliffs. In the third part of the study, a novel visualization and quantification method is presented for evaluation of the scaffold-hopping ability of virtual screening tools.Siirretty Doriast

Merging Ligand-Based and Structure-Based Methods in Drug Discovery: An Overview of Combined Virtual Screening Approaches

Virtual screening (VS) is an outstanding cornerstone in the drug discovery pipeline. A variety of computational approaches, which are generally classified as ligand-based (LB) and structure-based (SB) techniques, exploit key structural and physicochemical properties of ligands and targets to enable the screening of virtual libraries in the search of active compounds. Though LB and SB methods have found widespread application in the discovery of novel drug-like candidates, their complementary natures have stimulated continued e orts toward the development of hybrid strategies that combine LB and SB techniques, integrating them in a holistic computational framework that exploits the available information of both ligand and target to enhance the success of drug discovery projects. In this review, we analyze the main strategies and concepts that have emerged in the last years for defining hybrid LB + SB computational schemes in VS studies. Particularly, attention is focused on the combination of molecular similarity and docking, illustrating them with selected applications taken from the literature

Visualisation and subsets of the chemical universe database GDB-13 for virtual screening

The chemical universe database GDB-13, which enumerates 977million organic molecules up to 13 atoms of C, N, O, S and Cl following simple chemical stability and synthetic feasibility rules, represents a vast reservoir for new fragments. GDB-13 was classified using the MQN-system discussed in the preceding paper for the analysis of PubChem fragments. Two hundred and fifty-five subsets of GDB-13 were generated by the combinatorial use of eight restrictive criteria, including fragment-like ("rule of three”) and scaffold-like (no acyclic carbon atoms) filters. Virtual screening for analogs of 15 commercial drugs of 13 non-hydrogen atoms or less shows that retrieving MQN-neighbors of a query molecule from GDB-13 or its subsets provides on average a 38-fold enrichment in structural analogs (Daylight-type substructure fingerprint Tanimoto T SF>0.7), and a 75-fold enrichment in shape-similar analogs (ROCS TanimotoCombo score>1.4). An MQN-searchable version of GDB-13 is provided at www.gdb.unibe.ch. Graphical Abstrac

Hierarchical Virtual Screening of Potential Insectides Inhibitors of Acetylcholinesterase and Juvenile Hormone from Temephos

Aedes aegypti (Linnaeus, 1762; Diptera: Culicidae) is the main vector transmitting viral diseases such as dengue fever, dengue haemorrhagic fever, urban yellow fever, zika and chikungunya. Worldwide, especially in the Americas and Brazil, many cases of dengue have been reported in recent years, which have shown significant growth. The main control strategy is the elimination of the vector, carried out through various education programs, to change human habits, but the most usual is biological control, together with environmental management and chemical control. The most commonly insecticide used is temephos (an organophosphorus compound), but Aedes aegypti populations have shown resistance and the product is highly toxic, so we chose it as a template molecule to perform a ligand-based virtual screening in the ChemBrigde (DIVERSet-CL subcollection) database, searching for derivatives with similarity in shape (ROCS) and electrostatic potential (EON). Thus, fourty-five molecules were filtered based on their pharmacokinetic and toxicological properties and 11 molecules were selected by a molecular docking study, including binding affinity and mode of interaction. The L46, L66 and L68 molecules show potential inhibitory activity for both the insect (-9.28, -10.08 and -6.78 kcal/mol, respectively) and human (-6.05, 6.25 and 7.2 kcal/mol respectively) enzymes, as well as the juvenile hormone protein (-9.2; -10.96 and -8.16 kcal/mol, respectively), showing a significant difference in comparison to the template molecule temephos. Molecules L46, L66 and L68 interacted with important amino acids at each catalytic site of the enzyme reported in the literature. Thus, the molecules here investigated are potential inhibitors for both the acetylcholinesterase enzymes and juvenile hormone protein–from insect and humans, characterizing them as a potential insecticide against the Aedes aegypti mosquito

Ligand scaffold hopping combining 3D maximal substructure search and molecular similarity

International audienceBACKGROUND: Virtual screening methods are now well established as effective to identify hit and lead candidates and are fully integrated in most drug discovery programs. Ligand-based approaches make use of physico-chemical, structural and energetics properties of known active compounds to search large chemical libraries for related and novel chemotypes. While 2D-similarity search tools are known to be fast and efficient, the use of 3D-similarity search methods can be very valuable to many research projects as integration of "3D knowledge" can facilitate the identification of not only related molecules but also of chemicals possessing distant scaffolds as compared to the query and therefore be more inclined to scaffolds hopping. To date, very few methods performing this task are easily available to the scientific community. RESULTS: We introduce a new approach (LigCSRre) to the 3D ligand similarity search of drug candidates. It combines a 3D maximum common substructure search algorithm independent on atom order with a tunable description of atomic compatibilities to prune the search and increase its physico-chemical relevance. We show, on 47 experimentally validated active compounds across five protein targets having different specificities, that for single compound search, the approach is able to recover on average 52% of the co-actives in the top 1% of the ranked list which is better than gold standards of the field. Moreover, the combination of several runs on a single protein target using different query active compounds shows a remarkable improvement in enrichment. Such Results demonstrate LigCSRre as a valuable tool for ligand-based screening. CONCLUSION: LigCSRre constitutes a new efficient and generic approach to the 3D similarity screening of small compounds, whose flexible design opens the door to many enhancements. The program is freely available to the academics for non-profit research at: http://bioserv.rpbs.univ-paris-diderot.fr/LigCSRre.html

Non-peptidic Cruzain Inhibitors with Trypanocidal Activity Discovered by Virtual Screening and in Vitro Assay

A multi-step cascade strategy using integrated ligand-and target-based virtual screening methods was developed to select a small number of compounds from the ZINC database to be evaluated for trypanocidal activity. Winnowing the database to 23 selected compounds, 12 non-covalent binding cruzain inhibitors with affinity values (K-i) in the low micromolar range (3-60 mu M) acting through a competitive inhibition mechanism were identified. This mechanism has been confirmed by determining the binding mode of the cruzain inhibitor Nequimed176 through X-ray crystallographic studies. Cruzain, a validated therapeutic target for new chemotherapy for Chagas disease, also shares high similarity with the mammalian homolog cathepsin L. Because increased activity of cathepsin L is related to invasive properties and has been linked to metastatic cancer cells, cruzain inhibitors from the same library were assayed against it. Affinity values were in a similar range (4-80 mu M), yielding poor selectivity towards cruzain but raising the possibility of investigating such inhibitors for their effect on cell proliferation. in order to select the most promising enzyme inhibitors retaining trypanocidal activity for structure-activity relationship (SAR) studies, the most potent cruzain inhibitors were assayed against T. cruzi-infected cells. Two compounds were found to have trypanocidal activity. Using compound Nequimed42 as precursor, an SAR was established in which the 2-acetamidothiophene-3-carboxamide group was identified as essential for enzyme and parasite inhibition activities. the IC50 value for compound Nequimed42 acting against the trypomastigote form of the Tulahuen lacZ strain was found to be 10.6 +/- 0.1 mu M, tenfold lower than that obtained for benznidazole, which was taken as positive control. in addition, by employing the strategy of molecular simplification, a smaller compound derived from Nequimed42 with a ligand efficiency (LE) of 0.33 kcal mol(-1) atom(-1) (compound Nequimed176) is highlighted as a novel non-peptidic, non-covalent cruzain inhibitor as a trypanocidal agent candidate for optimization.Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)Univ Fed Sao Carlos, Dept Quim, BR-13560 Sao Carlos, SP, BrazilUniv São Paulo, Inst Quim Sao Carlos, Grp Quim Med IQSC USP, Sao Carlos, SP, BrazilUniv Calif San Francisco, Dept Pathol, Ctr Discovery & Innovat Parasit Dis, San Francisco, CA 94140 USAUniv São Paulo, Fac Med Ribeirao Preto, Dept Bioquim & Imunol, BR-14049 Ribeirao Preto, SP, BrazilUniversidade Federal de São Paulo, Escola Paulista Med, Dept Biofis, São Paulo, BrazilUniversidade Federal de São Paulo, Escola Paulista Med, Dept Biofis, São Paulo, BrazilFAPESP: 2011/01893-3,CNPq: 301614/2010-5CAPES: 5985/11-0Web of Scienc