The measurement of molecular diversity by receptor site interaction simulation

The assembly of large compound libraries for the purpose of screening against various receptor targets to identify chemical leads for drug discovery programs has created a need for methods to measure the molecular diversity of such libraries. The method described here, for which we propose the acronym RESIS (for Receptor Site Interaction Simulation), relates directly to this use. A database is built of three-dimensional representations of the compounds in the library and a set of three-point three-dimensional theoretical receptor sites is generated based on putative hydrophobic and polar interactions. A series of flexible, three-dimensional searches is then performed over the database, using each of the theoretical sites as the basis for one such search. The resulting pattern of hits across the grid of theoretical receptor sites provides a measure of the molecular diversity of the compound library. This can be conveniently displayed as a density map which provides a readily comprehensible visual impression of the library diversity characteristics. A library of 7500 drug compounds derived from the CIPSLINEPC databases was characterized with respect to molecular diversity using the RESIS method. Some specific uses for the information obtained from application of the method are discussed. A comparison was made of the results from the RESIS method with those from a recently published two-dimensional approach for assessing molecular diversity using sets of compounds from the Maybridge database (MAY).     

MEPSIM: A computational package for analysis and comparison of molecular electrostatic potentials

Summary MEPSIM is a computational system which allows an integrated computation, analysis, and comparison of molecular electrostatic potential (MEP) distributions. It includes several modules. Module MEPPLA supplies MEP values for the points of a grid defined on a plane which is specified by a set of three points. The results of this program can easily be converted into MEP maps using third-parties graphical software. Module MEPMIN allows to find automatically the MEP minima of a molecular system. It supplies the cartesian coordinates of these minima, their values, and all the geometrical relationships between them (distances, angles, and dihedral angles). Module MEPCOMP computes a similarity coefficient between the MEP distributions of two molecules and finds their relative position that maximizes the similarity. Module MEPCONF performs the same process as MEPCOMP, considering not only the relative position of both molecules but also a conformational degree of freedom of one of them. The most recently developed module, MEPPAR, is another modification of MEPCOMP in order to compute the MEP similarity between two molecules, but only taking into account a particular plane. The latter module is particularly useful to compare MEP distributions generated by systems of aromatic rings. MEPSIM can use several wavefunction computation approaches to obtain MEP distributions. MEPSIM has a menu type interface to simplify the following tasks: creation of input files from output files of external programs (GAUSSIAN and AMPAC/MOPAC), setting the parameters for the current computation, and submitting jobs to the batch queues of the computer. MEPSIM has been coded in FORTRAN and its current version runs on VMS/VAX computers.     

A novel approach to molecular similarity

Summary We review briefly the general problem of assessing the similarity between one molecule and another. We propose a novel approach to the quantitative estimation of the similarity of two electron distributions. The procedure is based on momentum space concepts, and avoids many of the difficulties associated with the usual position space definitions. Results are presented for the model systems CH₃CH₂CH₃, CH₃OCH₃, CH₃SCH₃, H₂O and H₂S.     

Scoring noncovalent protein-ligand interactions: A continuous differentiable function tuned to compute binding affinities

Summary Exploitation of protein structures for potential drug leads by molecular docking is critically dependent on methods for scoring putative protein-ligand interactions. An ideal function for scoring must exhibit predictive accuracy and high computational speed, and must be tolerant of variations in the relative protein-ligand molecular alignment and conformation. This paper describes the development of an empirically derived scoring function, based on the binding affinities of protein-ligand complexes coupled with their crystallographically determined structures. The function's primary terms involve hydrophobic and polar complementarity, with additional terms for entropic and solvation effects. The issue of alignment/conformation dependence was solved by constructing a continuous differentiable nonlinear function with the requirement that maxima in ligand conformation/alignment space corresponded closely to crystallographically determined structures. The expected error in the predicted affinity based on cross-validation was 1.0 log unit. The function is sufficiently fast and accurate to serve as the objective function of a molecular-docking search engine. The function is particularly well suited to the docking problem, since it has spatially narrow maxima that are broadly accessible via gradient descent.     

Computer-aided drug design: A free energy perturbation study on the binding of methyl-substituted pterins and N5-deazapterins to dihydrofolate reductase

Summary Molecular dynamics simulation and free energy perturbation techniques have been used to study the relative binding free energies of 8-methylpterins and 8-methyl-N5-deazapterins to dihydrofolate reductase (DHFR). Methyl-substitution at the 5, 6 and 7 positions in the N-heterocyclic ring gives rise to a variety of ring substituent patterns and biological activity: several of these methyl derivatives of the 8-methyl parent compounds (8-methylpterin and 8-methyl-N5-deazapterin) have been identified as substrates or inhibitors of vertebrate DHFR in previous work. The calculated free energy differences reveal that the methyl-substituted compounds are thermodynamically more stable than the primary compounds (8-methylpterin and 8-methyl-N5-deazapterin) when bound to the enzyme, due largely to hydrophobic hydration phenomena. Methyl substitution at the 5 and/or 7 positions in the 6-methyl-substituted compounds has only a small effect on the stability of ligand binding. Furthermore, repulsive interactions between the 6-methyl substituent and DHFR are minimal, suggesting that the 6-methyl position is optimal for binding. The results also show that similarly substituted 8-methylpterins and 8-methyl-N5-deazapterins have very similar affinities for binding to DHFR. The computer simulation predictions are in broad agreement with experimental data obtained from kinetic studies, i.e. 6,8-dimethylpterin is a more efficient substrate than 8-methylpterin and 6,8-dimethyl-N5-deazapterin is a better inhibitor than 8-methyl-N5-deazapterin.     

SDOVS: A solvent dipole ordering‐based method for virtual screening

We previously reported that solvent dipole ordering (SDO) at the ligand binding site of a protein indicates an outline of the preferred shape and binding pose of the ligands. We suggested that SDO‐mimetic pseudo‐molecules that mimic the 3D shape of the SDO region could be used as molecular queries with a shape similarity matching method in virtual screening. In this work, a virtual screening method based on SDO, named SDOVS, was proposed. This method was applied to virtual screening of ligands for four typical drug target proteins and the performance compared with that of FRED (well‐known rigid docking method); the efficiency of SDOVS was demonstrated to be better than FRED. © 2010 Wiley Periodicals, Inc. J Comput Chem, 2010     

Compass: A shape-based machine learning tool for drug design

Summary Building predictive models for iterative drug design in the absence of a known target protein structure is an important challenge. We present a novel technique, Compass, that removes a major obstacle to accurate prediction by automatically selecting conformations and alignments of molecules without the benefit of a characterized active site. The technique combines explicit representation of molecular shape with neural network learning methods to produce highly predictive models, even across chemically distinct classes of molecules. We apply the method to predicting human perception of musk odor and show how the resulting models can provide graphical guidance for chemical modifications.     

A molecular model for the active site of S-adenosyl-l-homocysteine hydrolase

Summary S-adenosyl-l-homocysteine hydrolase (AdoHcy hydrolase, EC 3.3.1.1.), a specific target for antiviral drug design, catalyzes the hydrolysis of AdoHcy to adenosine (Ado) and homocysteine (Hcy) as well as the synthesis of AdoHcy from Ado and Hcy. The enzyme isolated from different sources has been shown to contain tightly bound NAD⁺.Based on the 2.0 Å-resolution X-ray crystal structure of dogfish lactate dehydrogenase (LDH), which is functionally homologous to AdoHcy hydrolase, and the primary sequence of rat liver AdoHcy hydrolase, we have derived a molecular model of an extended active site for AdoHcy hydrolase. The computational mutation was performed using the software MUTAR (Yeh et al., University of Kansas, Lawrence), followed by molecular mechanics optimizations using the programs AMBER (Singh et al., University of California, San Francisco) and YETI (Vedani, University of Kansas). Solvation of the model structure was achieved by use of the program SOLVGEN (Jacober, University of Kansas); 56 water molecules were explicitly included in all refinements. Some of these may be involved in the catalytic reaction.We also studied a model of the complex of AdoHcy hydrolase with NAD⁺, as well as the ternary complexes of the redox reaction catalyzed by AdoHcy hydrolase and has been used to differentiate the relative binding strength of inhibitors.     

Affinity chromatography on vancomycin coupled to reversed phase liquid chromatography/ electrospray-ion trap mass spectrometry for the screening of combinatorial libraries

Summary The combination affinity chromatography-mass spectrometry can be drastically improved by introducing a reversed phase column prior to the mass spectrometric detection. The interactions of the macrocyclic antibiotic vancomycin with oligopeptides were used to illustrate the performance of the technique. A library of 36 peptides was successfully screened and the active compounds identified by electrospray MS⁽ⁿ⁾. The strong affinity of compounds ending with (D)-alanine and with (D)-alanine or an aromatic (D)-amino acid in the penultimate position with vancomycin was confirmed.     

Platform synthesis: A useful strategy for rapid and systematic generation of molecular diversity

Emergence of library-based approaches have changed the way of developing new functional molecules in materials science and pharmaceutical science. Therefore, reliable methods for rapid and systematic generation of functional molecules are highly called for in this field. We herein describe our concept of "platform synthesis" as a useful strategy for generating molecular diversity. This simple yet powerful strategy realizes the synthesis of a number of interesting multifunctional molecules, such as multisubstituted olefins, in a programmable and diversity-oriented format. As well as applications to the synthesis of pharmaceutically important molecules, such as tamoxifen and CDP840, applications to materials science, which have led to the discovery of interesting fluorescent materials and properties, are also described.     

The atom assignment problem in automated de novo drug design. 2. A method for molecular graph and fragment perception

Summary If atom assignment onto 3D molecular graphs is to be optimized, an efficient scheme for placement must be developed. The strategy adopted in this paper is to analyze the molecular graphs in terms of cyclical and non-cyclical nodes; the latter are further divided into terminal and non-terminal nodes. Molecular fragments, from a fragments database, are described in a similar way. A canonical numbering scheme for the fragments and the local subgraph of the molecular graph enables fragments to be placed efficiently onto the molecular graph. Further optimization is achieved by placing similar fragments into bins using a hashing scheme based on the canonical numbering. The graph perception algorithm is illustrated in detail.     

A Method for High-Throughput Screening of Enantioselective Catalysts

About 1000 catalytic or stoichiometric asymmetric reactions of racemic compounds or prochiral substrates bearing enantiotopic groups can be analyzed per day. In this highly efficient method the enantioselectivity is determined by electrospray ionization mass spectrometry using isotopically labeled substrates. The picture shows the mass spectrum of the mixture obtained upon hydrolysis of 1 to afford the pseudo-enantiomeric products 2 and 3 .     

The atom assignment problem in automated de novo drug design. 1. Transferability of molecular fragment properties

Summary This paper is the first of a series which examines the problems of atom assignment in automated de novo drug design. In subsequent papers, a combinatoric optimization method for fragment placement onto 3D molecular graphs is provided. Molecules are built from molecular graphs by placing fragments onto the graph. Here we examine the transferability of atomic residual charge, by fragment placement, with respect to the electrostatic potential. This transferability has been tested on 478 molecular structures extracted from the Cambridge Structural Database. The correlation found between the electrostatic potential computed from composite fragments and that computed for the whole molecule was encouraging, except for extended conjugated systems.     

Evaluation of a method for controlling molecular scaffold diversity in de novo ligand design

We describe an algorithm for the automated generation of molecular structures subject to geometric and connectivity constraints. The method relies on simulated annealing and simplex optimization of a penalty function that contains a variety of conditions and can be useful in structure-based drug design projects. The procedure controls the diversity and complexity of the generated molecules. Structure selection filters are an integral part and drive the algorithm. Several procedures have been developed to achieve reliable control. A number of template sets can be defined and combined to control the range of molecules which are searched. Ring systems are predefined. Normally, the ring-system complexity is one of the most elusive and difficult factors to control when fusion-, bridge- and spiro-structures are built by joining templates. Here this is not an issue; the decision about which systems are acceptable, and which are not, is made before the run is initiated. Queries for inclusion and exclusion spheres are incorporated into the objective function, and, by using a flexible notation, the structure generation can be directed and more focused. Simulated annealing is a reliable optimizer and converges asymptotically to the global minimum. The objective functions used here are degenerate, so it is likely that each run will produce a different set of good solutions.     

The development of a simple empirical scoring function to estimate the binding constant for a protein-ligand complex of known three-dimensional structure

Summary A new simple empirical function has been developed that estimates the free energy of binding for a given protein-ligand complex of known 3D structure. The function takes into account hydrogen bonds, ionic interactions, the lipophilic protein-ligand contact surface and the number of rotatable bonds in the ligand. The dataset for the calibration of the function consists of 45 protein-ligand complexes. The new energy function reproduces the binding constants (ranging from 2.5·10^-2 to 4·10^-14 M, corresponding to binding energies between -9 and -76 kJ/mol) of the dataset with a standard deviation of 7.9 kJ/mol, corresponding to 1.4 orders of magnitude in binding affinity. The individual contributions to protein-ligand binding obtained from the scoring function are: ideal neutral hydrogen bond: -4.7 kJ/mol; ideal ionic interaction: -8.3 kJ/mol; lipophilic contact: -0.17 kJ/mol Ų; one rotatable bond in the ligand: +1.4 kJ/mol. The function also contains a constant contribution (+5.4 kJ/mol) which may be rationalized as loss of translational and rotational entropy. The function can be evaluated very fast and is therefore also suitable for application in a 3D database search or de novo ligand design program such as LUDI.     

Discovery of potential inhibitor against human acetylcholinesterase: a molecular docking and molecular dynamics investigation

Alzheimer’s disease (AD) is a progressive neurodegenerative disease of central nervous system among elderly people. Human acetylcholinesterase (hAChE), an important enzyme in neuronal signaling, is responsible for the degradation of acetylcholine which in turn prevents the post synaptic signal transmissions. hAChE has been an attractive target of drug discovery for the search of therapeutics against AD. In the recent past hAChE has become hot target for the investigation of new potential therapeutics. We performed virtual screening of entire database against hAChE. Further, the extra precision molecular docking was carried out to refine the docking results and the best complex was passed for molecular dynamics simulations in order of understanding the hAChE dynamics and its behavior in complex with the ligand which corroborate the outcomes of virtual screening. This also provides binding free energy data that establishes the ligands efficiency for inhibiting hAChE. The computational findings discussed in this paper provide initial information of inhibitory effects of ligand, (drugbank entry DB00983), over hAChE.