Dock around the Clock – Current Status of Small Molecule Docking and Scoring

Environmentally friendly catalyst- and solvent-free synthesis of 2-anilino nicotinic acids derivatives as potential lead COX inhibitors

In this study, an environmentally friendly, solvent- and catalyst-free synthesis of 2-anilino nicotinic acids derivatives is reported. This operationally simple and green procedure was applied to a selection of primary aromatic amines giving rise to 23 derivatives of 2-anilino nicotinic acids in a very short reaction time (15-120 min) with good to excellent yield. Next, similarity searches were executed on these derivatives to find the possible biological target. These products were screened for inhibition of COX-1 and COX-2 by molecular docking and dynamic studies. In silico studies revealed that among these derivatives, the structure 10 bearing meta-chlorine substitutions could act as COX-1 and COX-2 inhibitors. These results can be used in designing important lead compounds for further development as potential anti-inflammatory drugs.

Approaching the Dimerization Mechanism of Small Molecule Inhibitors Targeting PD-L1 with Molecular Simulation

Inhibitors blocking the PD-1/PD-L1 immune checkpoint demonstrate impressive anti-tumor immunity, and small molecule inhibitors disclosed by the Bristol-Myers Squibb (BMS) company have become a hot topic. In this work, by modifying the carbonyl group of BMS-202 into a hydroxyl group to achieve two enantiomers (MS and MR) with a chiral center, we found that this is an effective way to regulate its hydrophobicity and thus to reduce the negative effect of polar solvation free energy, which enhances the stability of PD-L1 dimer/inhibitor complexes. Moreover, we studied the binding modes of BMS-200 and BMS-202-related small molecule inhibitors by molecular dynamics simulation to explore their inhibitory mechanism targeting PD-L1 dimerization. The results showed that the size exclusion effect of the inhibitors triggered the rearrangement of the residue _ATyr56, leading to the formation of an axisymmetric tunnel-shaped pocket, which is an important structural basis for improving the binding affinity of symmetric inhibitors with PD-L1. Furthermore, after inhibitor dissociation, the conformation of _ATyr123 and _BMet115 rearranged, which blocked the entrance of the binding pocket, while the reverse rearrangements of the same residues occurred when the PD-L1 monomer was complexed with the inhibitors, preparing PD-L1 for dimerization. Overall, this study casts a new light on the inhibitory mechanism of BMS inhibitors targeting PD-L1 dimerization and provides an idea for designing novel small molecule inhibitors for future cancer immunotherapy.

Identification of novel antilipogenic agents targeting fatty acid biosynthesis through structure-based virtual screening

An Asinex Gold Platinium chemical library subset of 12 055 compounds was screened employing docking simulations in the active site of the human FAS KS domain. Among them, 13 compounds were further evaluated for their ability to inhibit fatty acid biosynthesis. Four compounds were found to be active in particular ASN05064661 and ASN05374526 with IC50 values of 6.6 and 10.5 μm, respectively. A binding mode study was further conducted with these two compounds structurally related to benzene sulfonamide and aromatic polyamide. This study showed that they fit tightly with the active site with several interactions, notably with the key residues Cys161, His293, and His331.

High-throughput and in silico screenings in drug discovery

BACKGROUND

In the current situation of weak drug pipelines, impending patent expiration of several blockbuster drugs, industry consolidation and changing business models that target special diseases like cancer, diabetes, Alzheimer's and obesity, the pharmaceutical industry is under intense pressure to generate a strong drug pipeline distinguished by better productivity, diversity and cost effectiveness. The goal is discovering high-quality leads in the initial stages of the development cycle, to minimize the costs associated with failures at later ones.

OBJECTIVE

Thus, there is a great amount of interest in further developing and optimizing high-throughput screening and in silico screening, the two methods responsible for generating most of the lead compounds. Although high-throughput screening is the predominant starting point for discovery programs, in silico methods have gradually made inroads by their more rational approach, to expedite the drug discovery and development process.

CONCLUSION

Modern drug discovery strategies include both methods in tandem or in an iterative way. This review primarily provides a succinct overview and comparison of experimental and in silico screening techniques, selected case studies where both methods were used in concert to investigate their performance and complementary nature and a statement on the developments in experimental and in silico approaches in the near future.

Using RosettaLigand for small molecule docking into comparative models

Computational small molecule docking into comparative models of proteins is widely used to query protein function and in the development of small molecule therapeutics. We benchmark RosettaLigand docking into comparative models for nine proteins built during CASP8 that contain ligands. We supplement the study with 21 additional protein/ligand complexes to cover a wider space of chemotypes. During a full docking run in 21 of the 30 cases, RosettaLigand successfully found a native-like binding mode among the top ten scoring binding modes. From the benchmark cases we find that careful template selection based on ligand occupancy provides the best chance of success while overall sequence identity between template and target do not appear to improve results. We also find that binding energy normalized by atom number is often less than -0.4 in native-like binding modes.

Statistical potential for modeling and ranking of protein-ligand interactions

Applications in structural biology and medicinal chemistry require protein-ligand scoring functions for two distinct tasks: (i) ranking different poses of a small molecule in a protein binding site and (ii) ranking different small molecules by their complementarity to a protein site. Using probability theory, we developed two atomic distance-dependent statistical scoring functions: PoseScore was optimized for recognizing native binding geometries of ligands from other poses and RankScore was optimized for distinguishing ligands from nonbinding molecules. Both scores are based on a set of 8,885 crystallographic structures of protein-ligand complexes but differ in the values of three key parameters. Factors influencing the accuracy of scoring were investigated, including the maximal atomic distance and non-native ligand geometries used for scoring, as well as the use of protein models instead of crystallographic structures for training and testing the scoring function. For the test set of 19 targets, RankScore improved the ligand enrichment (logAUC) and early enrichment (EF(1)) scores computed by DOCK 3.6 for 13 and 14 targets, respectively. In addition, RankScore performed better at rescoring than each of seven other scoring functions tested. Accepting both the crystal structure and decoy geometries with all-atom root-mean-square errors of up to 2 Å from the crystal structure as correct binding poses, PoseScore gave the best score to a correct binding pose among 100 decoys for 88% of all cases in a benchmark set containing 100 protein-ligand complexes. PoseScore accuracy is comparable to that of DrugScore(CSD) and ITScore/SE and superior to 12 other tested scoring functions. Therefore, RankScore can facilitate ligand discovery, by ranking complexes of the target with different small molecules; PoseScore can be used for protein-ligand complex structure prediction, by ranking different conformations of a given protein-ligand pair. The statistical potentials are available through the Integrative Modeling Platform (IMP) software package (http://salilab.org/imp) and the LigScore Web server (http://salilab.org/ligscore/).

AADS--an automated active site identification, docking, and scoring protocol for protein targets based on physicochemical descriptors

We report here a robust automated active site detection, docking, and scoring (AADS) protocol for proteins with known structures. The active site finder identifies all cavities in a protein and scores them based on the physicochemical properties of functional groups lining the cavities in the protein. The accuracy realized on 620 proteins with sizes ranging from 100 to 600 amino acids with known drug active sites is 100% when the top ten cavity points are considered. These top ten cavity points identified are then submitted for an automated docking of an input ligand/candidate molecule. The docking protocol uses an all atom energy based Monte Carlo method. Eight low energy docked structures corresponding to different locations and orientations of the candidate molecule are stored at each cavity point giving 80 docked structures overall which are then ranked using an effective free energy function and top five structures are selected. The predicted structure and energetics of the complexes agree quite well with experiment when tested on a data set of 170 protein-ligand complexes with known structures and binding affinities. The AADS methodology is implemented on an 80 processor cluster and presented as a freely accessible, easy to use tool at http://www.scfbio-iitd.res.in/dock/ActiveSite_new.jsp .

LuxR dependent quorum sensing inhibition by N,N'-disubstituted imidazolium salts

Thirty N,N'-disubstituted imidazolium salts have been synthesized and evaluated as LuxR antagonists. Substitution on one of the imidazolium nitrogen atoms includes benzhydryl, fluorenyl or cyclopentyl substituent, and alkyl chains of various lengths on the second one. Most of these compounds displayed antagonist activity, with IC(50) reaching the micromolar range for the most active ones. The disubstituted imidazolium scaffold is thus shown to be a new pertinent pharmacophore in the field of AHL dependent QS inhibition.

VoteDock: consensus docking method for prediction of protein-ligand interactions

Molecular recognition plays a fundamental role in all biological processes, and that is why great efforts have been made to understand and predict protein-ligand interactions. Finding a molecule that can potentially bind to a target protein is particularly essential in drug discovery and still remains an expensive and time-consuming task. In silico, tools are frequently used to screen molecular libraries to identify new lead compounds, and if protein structure is known, various protein-ligand docking programs can be used. The aim of docking procedure is to predict correct poses of ligand in the binding site of the protein as well as to score them according to the strength of interaction in a reasonable time frame. The purpose of our studies was to present the novel consensus approach to predict both protein-ligand complex structure and its corresponding binding affinity. Our method used as the input the results from seven docking programs (Surflex, LigandFit, Glide, GOLD, FlexX, eHiTS, and AutoDock) that are widely used for docking of ligands. We evaluated it on the extensive benchmark dataset of 1300 protein-ligands pairs from refined PDBbind database for which the structural and affinity data was available. We compared independently its ability of proper scoring and posing to the previously proposed methods. In most cases, our method is able to dock properly approximately 20% of pairs more than docking methods on average, and over 10% of pairs more than the best single program. The RMSD value of the predicted complex conformation versus its native one is reduced by a factor of 0.5 Å. Finally, we were able to increase the Pearson correlation of the predicted binding affinity in comparison with the experimental value up to 0.5.

Informatics, machine learning and computational medicinal chemistry

This article reviews the use of informatics and computational chemistry methods in medicinal chemistry, with special consideration of how computational techniques can be adapted and extended to obtain more and higher-quality information. Special consideration is given to the computation of protein–ligand binding affinities, to the prediction of off-target bioactivities, bioactivity spectra and computational toxicology, and also to calculating absorption-, distribution-, metabolism- and excretion-relevant properties, such as solubility.

Adaptive combinatorial design of focused compound libraries

Low-throughput screening for bioactive substances often represents the only way to discover new ligands of a drug target. This limits the number of compounds that can be tested for bioactivity. In such a situation, the design of small, focused compound libraries provides an alternative to the concept of large, maximally diverse screening collections. We present the technique of "adaptive" compound library design, which implements a simulated evolutionary process. Compound assembly and determination of bioactivity can be performed using computer-based methods (virtual screening), or in the laboratory. We show that there exists an optimal combination of the size of a screening library and the number of iterative screening rounds with the aim to keep experimental efforts at a minimum.

The scientific impact of the Cambridge Structural Database: a citation-based study

Four groups of the most highly cited scientific articles (46 in total), which either describe the Cambridge Structural Database (CSD) System or report scientific research applications of the CSD, have been selected for citation analysis. The analysis has been carried out to study the scientific importance of crystal structure information made available to the international research communityviathe CSD orviareviews and research articles that make use of the CSD as a primary information source. Two groups,AandBof ten articles each (Apublished before 1998, andBpublished post-1998), are authored by staff of the CCDC, while two further groups,CandDcontaining ten reviews and 16 research articles, respectively, are authored by external scientific users of CSD information. Citations have been analysed by their number, and in terms of the journals, scientific subject areas and geographical regions from which the citations originate. Between them, the 46 articles have received 44 381 citations with 15 articles cited more than 1000 times. Citations come from a very broad range of journals and subject areas, with chemistry and crystallography being the dominant fields as expected, but with a very significant citation rate from the life sciences, particularly from the USA. In recent years, there has been a major increase in citations arising from south Asia and the Far East, principally from China, India, Malaysia, Pakistan, Japan, Thailand and Taiwan, who together now rival, and sometimes exceed, the citation rates from Europe and the USA. The effect of citations from new journals, particularlyActa Crystallographica Section E: Structure Reports Online,Crystal Growth and DesignandCrystEngCommis clearly reflected in the data.

Quantifying interactions between G-quadruplex DNA and transition-metal complexes

Telomerase inhibition through guanine quadruplex sequestration by small-molecule drugs is of great current interest as an anticancer strategy. G-quadruplexes (GQs) can be formed at the guanine-rich sequences found at the end of the telomere. They possess a large electron-rich pi-surface which is favorable for the binding of electron-poor small molecules. Small molecules binding to GQs can sequester the telomere ends and inhibit the enzyme telomerase, which is expressed in cancer cells and absent in normal somatic cells. Transition-metal complexes present a myriad of geometries and numerous ligand coordination environments and allow for modular syntheses for development of compound libraries to target GQs. We have demonstrated the size of the pi-surface, binding selectivity and affinity of phenanthroimidazole platinum (II) complexes [PtPIX(en)](2+)2PF (6) (-) (X = naphthyl, phenyl and en = ethylenediamine) and metallosupramolecular complexes [Pt(4,4'-bpy)(en)] (4) (8+) 8PF (6) (-) (where bpy = bipyridine) to GQs can be readily tuned and assayed through a number of biophysical techniques.

Molecular docking screens using comparative models of proteins

Two orders of magnitude more protein sequences can be modeled by comparative modeling than have been determined by X-ray crystallography and NMR spectroscopy. Investigators have nevertheless been cautious about using comparative models for ligand discovery because of concerns about model errors. We suggest how to exploit comparative models for molecular screens, based on docking against a wide range of crystallographic structures and comparative models with known ligands. To account for the variation in the ligand-binding pocket as it binds different ligands, we calculate "consensus" enrichment by ranking each library compound by its best docking score against all available comparative models and/or modeling templates. For the majority of the targets, the consensus enrichment for multiple models was better than or comparable to that of the holo and apo X-ray structures. Even for single models, the models are significantly more enriching than the template structure if the template is paralogous and shares more than 25% sequence identity with the target.

Docking ligands into flexible and solvated macromolecules. 4. Are popular scoring functions accurate for this class of proteins?

In our previous report, we investigated the impact of protein flexibility and the presence of water molecules on the pose-prediction accuracy of major docking programs. To complete these investigations, we report herein a study of the impact of these two aspects on the accuracy of scoring functions. To this effect, we developed two sets of protein/ligand complexes made up of ligands cross-docked or cocrystallized with a large variety of proteins, featuring bridging water molecules and demonstrating protein flexibility. Efforts were made to reduce the correlation between the molecular weights of the selected ligands and their binding affinities, a major bias in some previously reported benchmark sets. Using these sets, 18 available scoring functions have been assessed for their accuracy to predict binding affinities and to rank-order compounds by their affinity to cocrystallized proteins. This study confirmed the good and similar accuracy of Xscore, GlideScore, DrugScore(CSD), GoldScore, PLP1, ChemScore, RankScore, and the eHiTS scoring function. Our next investigations demonstrated that most of the assessed scoring functions were much less accurate when the correct protein conformation was not provided. This study also revealed that considering the water molecules for scoring does not greatly affect the accuracy. Finally, this work sheds light on the high correlation between scoring functions and the poor increase in accuracy one can expect from consensus scoring.

From chemical documentation to chemoinformatics: 50 years of chemical information science

This paper summarizes the historical development of the discipline that is now called `chemoinformatics'. It shows how this has evolved, principally as a result of technological developments in chemistry and biology during the past decade, from long-established techniques for the modelling and searching of chemical molecules. A total of 30 papers, the earliest dating back to 1957, are briefly summarized to highlight some of the key publications and to show the development of the discipline.

Towards the development of universal, fast and highly accurate docking/scoring methods: a long way to go

Accelerating the drug discovery process requires predictive computational protocols capable of reducing or simplifying the synthetic and/or combinatorial challenge. Docking-based virtual screening methods have been developed and successfully applied to a number of pharmaceutical targets. In this review, we first present the current status of docking and scoring methods, with exhaustive lists of these. We next discuss reported comparative studies, outlining criteria for their interpretation. In the final section, we describe some of the remaining developments that would potentially lead to a universally applicable docking/scoring method.

Evaluation of docking programs for predicting binding of Golgi α-mannosidase II inhibitors: A comparison with crystallography

Golgi alpha-mannosidase II (GMII), a zinc-dependent glycosyl hydrolase, is a promising target for drug development in anti-tumor therapies. Using X-ray crystallography, we have determined the structure of Drosophila melanogaster GMII (dGMII) complexed with three different inhibitors exhibiting IC50's ranging from 80 to 1000 microM. These structures, along with those of seven other available dGMII/inhibitor complexes, were then used as a basis for the evaluation of seven docking programs (GOLD, Glide, FlexX, AutoDock, eHiTS, LigandFit, and FITTED). We found that small inhibitors could be accurately docked by most of the software, while docking of larger compounds (i.e., those with extended aromatic cycles or long aliphatic chains) was more problematic. Overall, Glide provided the best docking results, with the most accurately predicted binding around the active site zinc atom. Further evaluation of Glide's performance revealed its ability to extract active compounds from a benchmark library of decoys.

Docking Ligands into Flexible and Solvated Macromolecules. 1. Development and Validation of FITTED 1.0

We report the development and validation of a novel suite of programs, FITTED 1.0, for the docking of flexible ligands into flexible proteins. This docking tool is unique in that it can deal with both the flexibility of macromolecules (side chains and main chains) and the presence of bridging water molecules while treating protein/ligand complexes as realistically dynamic systems. This software relies on a genetic algorithm to account for the flexibility of the two molecules as well as the location of bridging water molecules. In addition, FITTED 1.0 features a novel application of a switching function to retain or displace key water molecules from the protein-ligand complexes. Two independent modules, ProCESS and SMART, were developed to set up the proteins and the ligands prior to the docking stage. Validation of the accuracy of the software was achieved via the application of FITTED 1.0 to the docking of inhibitors of HIV-1 protease, thymidine kinase, trypsin, factor Xa, and MMP to their respective proteins.

Basic overview of chemoinformatics

There is no particular point in time that determines when chemoinformatics was founded or established. It slowly evolved from several, often quite humble beginnings. Scientists in various fields of chemistry struggled with the development of computer methods which allowed them to manage the enormous amount of chemical information and to find relationships between the structure and properties of a compound. During the 1960s some early developments appeared that led to a flurry of activities in the 1970s. This review provides a general overview of basic methods in the specific fields of chemoinformatics, from encoding chemical compounds, storing and searching data in databases, to generating and analyzing these data. In addition, the chief interconnecting points of chemoinformatics applications are highlighted including the contributions of Johann Gasteiger to this field.