Is there a difference between leads and drugs? A historical perspective

To be considered for further development, lead structures should display the following properties: (1) simple chemical features, amenable for chemistry optimization; (2) membership to an established SAR series; (3) favorable patent situation; and (4) good absorption, distribution, metabolism, and excretion (ADME) properties. There are two distinct categories of leads: those that lack any therapeutic use (i.e., "pure" leads), and those that are marketed drugs themselves but have been altered to yield novel drugs. We have previously analyzed the design of leadlike combinatorial libraries starting from 18 lead and drug pairs of structures (S. J. Teague et al. Angew. Chem., Int. Ed. Engl. 1999, 38, 3743-3748). Here, we report results based on an extended dataset of 96 lead-drug pairs, of which 62 are lead structures that are not marketed as drugs, and 75 are drugs that are not presumably used as leads. We examined the following properties: MW (molecular weight), CMR (the calculated molecular refractivity), RNG (the number of rings), RTB (the number of rotatable bonds), the number of hydrogen bond donors (HDO) and acceptors (HAC), the calculated logarithm of the n-octanol/water partition (CLogP), the calculated logarithm of the distribution coefficient at pH 7.4 (LogD(74)), the Daylight-fingerprint druglike score (DFPS), and the property and pharmacophore features score (PPFS). The following differences were observed between the medians of drugs and leads: DeltaMW = 69; DeltaCMR = 1.8; DeltaRNG = DeltaHAC =1; DeltaRTB = 2; DeltaCLogP = 0.43; DeltaLogD(74) = 0.97; DeltaHDO = 0; DeltaDFPS = 0.15; DeltaPPFS = 0.12. Lead structures exhibit, on the average, less molecular complexity (less MW, less number of rings and rotatable bonds), are less hydrophobic (lower CLogP and LogD(74)), and less druglike (lower druglike scores). These findings indicate that the process of optimizing a lead into a drug results in more complex structures. This information should be used in the design of novel combinatorial libraries that are aimed at lead discovery.     

Small Targeted Cytotoxics: Current State and Promises from DNA‐Encoded Chemical Libraries

The targeted delivery of potent cytotoxic agents has emerged as a promising strategy for the treatment of cancer and other serious conditions. Traditionally, antibodies against markers of disease have been used as drug‐delivery vehicles. More recently, lower molecular weight ligands have been proposed for the generation of a novel class of targeted cytotoxics with improved properties. Advances in this field crucially rely on efficient methods for the identification and optimization of organic molecules capable of high‐affinity binding and selective recognition of target proteins. The advent of DNA‐encoded chemical libraries allows the construction and screening of compound collections of unprecedented size. In this Review, we survey developments in the field of small ligand‐based targeted cytotoxics and show how innovative library technologies will help develop the drugs of the future.     

Substrate activity screening: a fragment-based method for the rapid identification of nonpeptidic protease inhibitors

A new fragment-based method for the rapid development of novel and distinct classes of nonpeptidic protease inhibitors, Substrate Activity Screening (SAS), is described. This method consists of three steps: (1) a library of N-acyl aminocoumarins with diverse, low molecular weight N-acyl groups is screened to identify protease substrates using a simple fluorescence-based assay, (2) the identified N-acyl aminocoumarin substrates are optimized by rapid analogue synthesis and evaluation, and (3) the optimized substrates are converted to inhibitors by direct replacement of the aminocoumarin with known mechanism-based pharmacophores. The SAS method was successfully applied to the cysteine protease cathepsin S, which is implicated in autoimmune diseases. Multiple distinct classes of nonpeptidic substrates were identified upon screening an N-acyl aminocoumarin library. Two of the nonpeptidic substrate classes were optimized to substrates with >8000-fold improvements in cleavage efficiency for each class. Select nonpeptidic substrates were then directly converted to low molecular weight, novel aldehyde inhibitors with nanomolar affinity to cathepsin S. This study demonstrates the unique characteristics and merits of this first substrate-based method for the rapid identification and optimization of weak fragments and provides the framework for the development of completely nonpeptidic inhibitors to many different proteases.     

Application and limitations of X-ray crystallographic data in structure-based ligand and drug design

Structure-based design usually focuses upon the optimization of ligand affinity. However, successful drug design also requires the optimization of many other properties. The primary source of structural information for protein-ligand complexes is X-ray crystallography. The uncertainties introduced during the derivation of an atomic model from the experimentally observed electron density data are not always appreciated. Uncertainties in the atomic model can have significant consequences when this model is subsequently used as the basis of manual design, docking, scoring, and virtual screening efforts. Docking and scoring algorithms are currently imperfect. A good correlation between observed and calculated binding affinities is usually only observed only when very large ranges of affinity are considered. Errors in the correlation often exceed the range of affinities commonly encountered during lead optimization. Some structure-based design approaches now involve screening libraries by using technologies based on NMR spectroscopy and X-ray crystallography to discover small polar templates, which are used for further optimization. Such compounds are defined as leadlike and are also sought by more traditional high-throughput screening technologies. Structure-based design and HTS technologies show important complementarity and a degree of convergence.     

不同分子量N-琥珀酰壳聚糖的制备及其与K562肿瘤细胞间亲和性的初步探讨

用化学降解法制备不同分子量的壳聚糖 ,以其为原料合成了系列N 琥珀酰壳聚糖 ,然后用异硫氰酸荧光素进行荧光标记 ,再与K5 6 2肿瘤细胞共孵育 ,通过流式细胞仪检测细胞的荧光强度来确定不同分子量N 琥珀酰壳聚糖与K5 6 2肿瘤细胞间亲和性的强弱 ,为靶向抗肿瘤药物载体的研究提供初步的参考 .结果表明N 琥珀酰壳聚糖和K5 6 2肿瘤细胞间有较强的亲和性 ,随着分子量的增加 ,其亲和性逐渐减弱 .     

The SHAPES strategy: an NMR-based approach for lead generation in drug discovery.

BACKGROUND: Recently, it has been shown that nuclear magnetic resonance (NMR) may be used to identify ligands that bind to low molecular weight protein drug targets. Recognizing the utility of NMR as a very sensitive method for detecting binding, we have focused on developing alternative approaches that are applicable to larger molecular weight drug targets and do not require isotopic labeling. RESULTS: A new method for lead generation (SHAPES) is described that uses NMR to detect binding of a limited but diverse library of small molecules to a potential drug target. The compound scaffolds are derived from shapes most commonly found in known therapeutic agents. NMR detection of low (microM-mM) affinity binding is achieved using either differential line broadening or transferred NOE (nuclear Overhauser effect) NMR techniques. CONCLUSIONS: The SHAPES method for lead generation by NMR is useful for identifying potential lead classes of drugs early in a drug design program, and is easily integrated with other discovery tools such as virtual screening, high-throughput screening and combinatorial chemistry.     

甲基丙烯酸N,N-二甲氨基乙酯/丙烯酸N,N-二甲氨基乙酯的可逆加成断裂链转移聚合研究

合成了二硫代苯甲酸2- (乙氧基羰基)异丙酯(ECPDB)、二硫代苯甲酸异丙苯酯(CDB)、二硫代苯甲酸1 苯基乙酯(PEDB) 3种二硫代苯甲酸酯链转移剂.以这3种转移剂为基础,用凝胶渗透色谱和核磁共振测试了甲基丙烯酸N ,N 二甲氨基乙酯(DMAEMA)和丙烯酸N ,N 二甲氨基乙酯(DMAEA)两种碱性单体的可逆加成断裂链转移(RAFT)聚合的聚合物分子量、分子量分布和结构.发现有的聚合体系聚合物分子量分布较窄,但实验数均分子量与理论数均分子量相差较大;有的体系则转化率很低,聚合物分子量很小.这些可能是由聚合体系中单体活性和链转移剂链转移能力之间的匹配不太协调,使可逆加成断裂链转移快速平衡反应发生偏移或破坏造成的.因此,可通过更换单体或链转移剂来调节这种匹配,从而使可逆加成断裂链转移快速平衡保持稳定,达到聚合更可控,实验分子量与理论分子量更接近,分子量分布更窄的目的.     

Affinity screening by packed capillary high-performance liquid chromatography using molecular imprinted sorbents. I. Demonstration of feasibility

Molecular imprint polymers (MIPs) are synthetic polymers capable of selectively binding a template molecule. In this work, the potential utility of MIP-based chromatographic sorbents for affinity screening of structurally similar compounds was investigated as alternatives to in vitro bioassays and biological targets bound to chromatographic supports. A group of structurally similar tricyclic antidepressant drugs and related compounds were used to simulate a combinatorial library. One of the antidepressants, nortriptyline (NOR), was selected as the template species. Using capillary HPLC columns packed with NOR-imprinted MIP particles, the simulated library was screened and the degree of selective interaction of each compound was determined. This correlated with each compound's affinity for the NOR binding site in the polymer. The results of the study revealed that library species which possess the major structural features of the template, specifically the ring structure and pendant secondary amine, were best "recognized" by the MIP, while the most structurally dissimilar compounds exhibited the least selective interaction. An investigation of the retention mechanism on these MIPs provided evidence that hydrogen bonding between the pendant amine group on the antidepressants and a methacrylic acid moiety on the polymer surface was critical in the molecular recognition process.     

Hydroxyl stereochemistry and amine number within poly(glycoamidoamine)s affect intracellular DNA delivery

Nucleic acid drugs have great potential to treat many devastating aliments, but their application has been hindered by the lack of efficacious and nontoxic delivery vehicles. Here, a new library of poly(glycoamidoamine)s (D1-D4, G1-G4, and M1-M4) has been synthesized by polycondensation of esterified d-glucaric acid (D), dimethyl-meso-galactarate (G), and d-mannaro-1,4:6,3-dilactone (M) with diethylenetriamine (1), triethylenetetramine (2), tetraethylenepentamine (3), and pentaethylenehexamine (4). The stereochemistry of the carbohydrate hydroxyl groups and the number of amine units have been systematically changed in an effort to examine how the polymer chemistry affects the plasmid DNA (pDNA) binding affinity, the compaction of pDNA into nanoparticles (polyplexes), the material cytotoxicity, and the efficacy of nucleic acid delivery. The polymers with four secondary amines (D4, G4, and M4) between the carbohydrates were found to have the highest pDNA binding affinity and the galactarate polymers generally yielded the smallest polyplexes. Delivery studies with pDNA containing the firefly luciferase or beta-galactosidase reporter genes in BHK-21, HeLa, and HepG2 cells demonstrated that all of the poly(glycoamidoamine)s deliver pDNA without cytotoxicity. Polymers D4, G4, and M4 displayed the highest delivery efficiency, where G4 was found to be a particularly effective delivery vehicle. Heparin competition assays indicated that this may be a result of the higher pDNA binding affinity displayed by G4 as compared to D4 and M4. Polyplexes formed by polymers with weaker pDNA affinities may dissociate at the cell surface due to interactions with negatively charged glycosaminoglycans, which would cause a decrease in the number of polyplexes that are endocytosed.     

Investigation of the noncovalent interactions between anti-amyloid agents and amyloid β peptides by ESI-MS

This paper describes an efficient and reproducible screening method for identifying low molecular weight compounds that bind to amyloid β peptides (Aβ) peptides using electrospray ionization mass spectrometry (ESI-MS). Low molecular weight compounds capable of interacting with soluble Aβ may be able to modulate/inhibit the Aβ aggregation process and serve as potential disease-modifying agents for AD. The present approach was used to rank the binding affinity of a library of compounds to Aβ1-40 peptide. The results obtained show that low molecular weight compounds bind similarly to Aβ1-42, Aβ1-40, as well as Aβ1-28 peptides and they underline the critical role of Aβ peptide charge motif in binding at physiological pH. Finally, some elements of structure-activity relationship (SAR) involved in the binding affinity of homotaurine to soluble Aβ peptides are discussed.     

Development and practical application of a library of CID accurate mass spectra of more than 2,500 toxic compounds for systematic toxicological analysis by LC�CQTOF-MS with data-dependent acquisition

A library of collision-induced dissociation (CID) accurate mass spectra has been developed for efficient use of liquid chromatography in combination with hybrid quadrupole time-of-flight mass spectrometry (LC-QTOF-MS) as a tool in systematic toxicological analysis. The mass spectra (Δm < 3 ppm) of more than 2,500 illegal and therapeutic drugs, pesticides, alkaloids, other toxic chemicals and metabolites were measured, by use of an Agilent 6530 instrument, by flow-injection of 1 ng of the pure substances in aqueous ammonium formate-formic acid-methanol, with positive and negative electrospray-ionization (ESI), selection of the protonated or deprotonated molecules [M+H](+) or [M-H](-) by the quadrupole, and collision induced dissociation (CID) with nitrogen as collision gas at CID energies of 10, 20, and 40 eV. The fragment mass spectra were controlled for structural plausibility, corrected by recalculation to the theoretical fragment masses and added to a database of accurate mass data and molecular formulas of more than 7,500 toxicologically relevant substances to form the "database and library of toxic compounds". For practical evaluation, blood and urine samples were spiked with a mixture of 33 drugs at seven concentrations between 0.5 and 500 ng mL(-1), prepared by dichloromethane extraction or protein precipitation, and analyzed by LC-QTOF-MS in data-dependent acquisition mode. Unambiguous identification by library search was possible for typical basic drugs down to 0.5-2 ng mL(-1) and for benzodiazepines down to 2-20 ng mL(-1). The efficiency of the method was also demonstrated by re-analysis of venous blood samples from 50 death cases and comparison with previous results. In conclusion, LC-QTOF-MS in data-dependent acquisition mode combined with an accurate mass database and CID spectra library seemed to be one of the most efficient tools for systematic toxicological analysis.     

DFT,ADMET and Molecular Docking Investigations for the Antimicrobial Activity of 6,6′-Diamino-1,1′,3,3′-tetramethyl-5,5′-(4-chlorobenzylidene)bis[pyrimidine-2,4(1H,3H)-dione]

Heterocyclic compounds, including pyrimidine derivatives, exhibit a broad variety of biological and pharmacological activities. In this paper, a previously synthesized novel pyrimidine molecule is proposed, and its pharmaceutical properties are investigated. Computational techniques such as the density functional theory, ADMET evaluation, and molecular docking were applied to elucidate the chemical nature, drug likeness and antibacterial function of molecule. The viewpoint of quantum chemical computations revealed that the molecule was relatively stable and has a high electrophilic nature. The contour maps of HOMO-LUMO and molecular electrostatic potential were analyzed to illustrate the charge density distributions that could be associated with the biological activity. Natural bond orbital (NBO) analysis revealed details about the interaction between donor and acceptor within the bond. Drug likeness and ADMET analysis showed that the molecule possesses the agents of safety and the effective combination therapy as pharmaceutical drug. The antimicrobial activity was investigated using molecular docking. The investigated molecule demonstrated a high affinity for binding within the active sites of antibacterial and antimalarial proteins. The high affinity of the antibacterial protein was proved by its low binding energy (−7.97 kcal/mol) and a low inhibition constant value (1.43 µM). The formation of four conventional hydrogen bonds in ligand–protein interactions confirmed the high stability of the resulting complexes. When compared to known standard drugs, the studied molecule displayed a remarkable antimalarial activity, as indicated by higher binding affinity (B.E. −5.86 kcal/mol & Ki = 50.23 M). The pre-selected molecule could be presented as a promising drug candidate for the development of novel antimicrobial agents.     

Investigation of the behavior of HSA upon binding to amlodipine and propranolol: Spectroscopic and molecular modeling approaches

The interaction between human serum albumin (HSA) and two drugs - amlodipine and propranolol - was investigated using fluorescence, UV absorption and circular dichroism (CD) spectroscopy. In addition, the binding site was established by applying molecular modeling technique. Fluorescence data suggest that amlodipine will quench the intrinsic fluorescence of HSA; whereas propranolol enhances the fluorescence of HSA. The binding constants for the interaction of amlodipine and propranolol with HSA were found to be 3.63×10(5)M(-1) and 2.29×10(4)M(-1), respectively. The percentage of secondary structure feature of each one of the HSA-bound drugs, i.e. the α-helix content, was estimated empirically by circular dichroism. The results indicated that amlodipine causes an increase, and that propranolol leads to a decrease in α-helix content of HSA. The spectroscopic analysis indicates that the binding mechanisms of the two drugs are different from each other. The data obtained by the molecular modeling study indicated that these drugs bind, with different affinity, to different sites located in subdomain IIA and IIIA.     

Consideration of molecular weight during compound selection in virtual target-based database screening

Virtual database screening allows for millions of chemical compounds to be computationally selected based on structural complimentary to known inhibitors or to a target binding site on a biological macromolecule. Compound selection in virtual database screening when targeting a biological macromolecule is typically based on the interaction energy between the chemical compound and the target macromolecule. In the present study it is shown that this approach is biased toward the selection of high molecular weight compounds due to the contribution of the compound size to the energy score. To account for molecular weight during energy based screening, we propose normalization strategies based on the total number of heavy atoms in the chemical compounds being screened. This approach is computationally efficient and produces molecular weight distributions of selected compounds that can be selected to be (1) lower than that of the original database used in the virtual screening, which may be desirable for selection of leadlike compounds or (2) similar to that of the original database, which may be desirable for the selection of drug-like compounds. By eliminating the bias in target-based database screening toward higher molecular weight compounds it is anticipated that the proposed procedure will enhance the success rate of computer-aided drug design.     

Skin permeability of water-soluble drugs

The permeabilities of several water-soluble drugs through excised hairless rat skin from their aqueous suspensions were investigated by using newly designed two-chamber diffusion cells. Disodium cromoglycate, diclofenac sodium, dopamine hydrochloride, isoproterenol hydrochloride, diltiazem hydrochloride and papaverine hydrochloride were selected as water-soluble drugs. Indomethacin, a lipophilic drug, and deuterium oxide (D2O) were used for comparison. The skin permeability coefficients of these water-soluble drugs were 100--1000 times lower than that of indomethacin. Since these drugs have high solubility in the donor solution (distilled water or lactate buffer), however, the skin permeation rates, which are in general proportional to the product of skin permeability coefficient and solubility of drugs in the drug-donor compartment, were comparable to or higher than that of indomethacin (1.7 micrograms/cm2/h): the skin permeation rate of dopamine hydrochloride (458 micrograms/cm2/h) was about 300 times higher than that of indomethacin. The water-soluble drugs with lower molecular weight and higher solubility in water showed higher skin permeation rates. These results suggest that some water-soluble drugs with low molecular weight and high solubility in water might be good candidates for transdermal drug delivery.     

Focused combinatorial library design based on structural diversity, druglikeness and binding affinity score

The advent of focused library and virtual screening has reduced the disadvantage of combinatorial chemistry and changed it to a realizable and cost-effective tool in drug discovery. Usually, genetic algorithms (GAs) are used to quickly finding high-scoring molecules by sampling a small subset of the total combinatorial space. Therefore, scoring functions play essential roles in focused library design. Reported here is our initial attempt to establish a new approach for generating a target-focused library using the combination of the scores of structural diversity and binding affinity with our newly improved drug-likeness scoring functions. Meanwhile, a software package, named LD1.0, was developed on the basis of the new approach. One test on a cyclooxygenase (COX)2-focused library successfully reproduced the structures that have been experimentally studied as COX2-selective inhibitors. Another test is on a peroxisome proliferator-activated receptors gamma-focused library design, which not only reproduces the key fragments in the approved (thiazolidinedione) TZD drugs, but also generates some new structures that are more active than the approved drugs or published ligands. Both of the two tests took approximately 15% of the running time of the ordinary molecular docking method. Thus, our new approach is an effective, reliable, and practical way for building up a properly sized focused library with a high hit rate, novel structure, and good ADME/T profile.     

Identification of hits and lead structure candidates with limited resources by adaptive optimization

Three stochastic optimization algorithms (Simulated Annealing (SA), Evolution Strategy (ES), and Particle Swarm Optimization (PSO)) and a Random Search were assessed for their ability to generate small activity-enriched subsets of molecular compound libraries. The optimization algorithms were employed to perform an "intelligent" iterative sampling of library molecules avoiding the biological testing of the full library. This study was performed to find a suitable optimization algorithm along with suitable parametrization. Particularly, the optimal number of iterations and population size were of interest. Optimizations were performed with limited resources as the maximal number of compound evaluations was restricted to 300. Results show that all three optimization algorithms are able to produce comparably good results, clearly outperforming a Random Search. While ES was able to come up with good solutions after a few optimization cycles, SA favored high numbers of iterations and was therefore less suited for library design. We introduce PSOs as an alternative approach to focused library design. PSO was able to produce high quality solutions while exhibiting marked autoadaptivity. Its implicit step size control makes it a straightforward out-of-the-box optimization algorithm. We further demonstrate that a nearest neighbor algorithm can successfully be applied to map from continuous search space to discrete chemical space.     

Simulated molecular evolution in a full combinatorial library

BACKGROUND: The Darwinian concept of 'survival of the fittest' has inspired the development of evolutionary optimization methods to find molecules with desired properties in iterative feedback cycles of synthesis and testing. These methods have recently been applied to the computer-guided heuristic selection of molecules that bind with high affinity to a given biological target. We describe the optimization behavior and performance of genetic algorithms (GAs) that select molecules from a combinatorial library of potential thrombin inhibitors in 'artificial molecular evolution' experiments, on the basis of biological screening results. RESULTS: A full combinatorial library of 15,360 members structurally biased towards the serine protease thrombin was synthesized, and all were tested for their ability to inhibit the protease activity of thrombin. Using the resulting large structure-activity landscape, we simulated the evolutionary selection of potent thrombin inhibitors from this library using GAs. Optimal parameter sets were found (encoding strategy, population size, mutation and cross-over rate) for this artificial molecular evolution. CONCLUSIONS: A GA-based evolutionary selection is a valuable combinatorial optimization strategy to discover compounds with desired properties without needing to synthesize and test all possible combinations (i.e. all molecules). GAs are especially powerful when dealing with very large combinatorial libraries for which synthesis and screening of all members is not possible and/or when only a small number of compounds compared with the library size can be synthesized or tested. The optimization gradient or 'learning' per individual increases when using smaller population sizes and decreases for higher mutation rates.