From genome to drug lead: identification of a small-molecule inhibitor of the SARS virus

Structure and function of SARS-CoV and SARS-CoV-2 main proteases and their inhibition: A comprehensive review

Severe acute respiratory syndrome-associated coronavirus (SARS-CoV) identified in 2003 infected ∼8000 people in 26 countries with 800 deaths, which was soon contained and eradicated by syndromic surveillance and enhanced quarantine. A closely related coronavirus SARS-CoV-2, the causative agent of COVID-19 identified in 2019, has been dramatically more contagious and catastrophic. It has infected and caused various flu-like symptoms of billions of people in >200 countries, including >6 million people died of or with the virus. Despite the availability of several vaccines and antiviral drugs against SARS-CoV-2, finding new therapeutics is needed because of viral evolution and a possible emerging coronavirus in the future. The main protease (Mpro) of these coronaviruses plays important roles in their life cycle and is essential for the viral replication. This article represents a comprehensive review of the function, structure and inhibition of SARS-CoV and -CoV-2 Mpro, including structure-activity relationships, protein-inhibitor interactions and clinical trial status.

Suggestion of active 3-chymotrypsin like protease (3CLPro) inhibitors as potential anti-SARS-CoV-2 agents using predictive QSAR model based on the combination of ALASSO with an ANN model

The novel severe acute respiratory syndrome coronavirus (SARS CoV-2) was introduced as an epidemic in 2019 and had millions of deaths worldwide. Given the importance of this disease, the recommendation and design of new active compounds are crucial. 3-chymotrypsin-like protease (3 CL^pro) inhibitors have been identified as potent compounds for treating SARS-CoV-2 disease. So, the design of new 3 CL^pro inhibitors was proposed using a quantitative structure-activity relationship (QSAR) study. In this context, a powerful adaptive least absolute shrinkage and selection operator (ALASSO) penalized variable selection method with inherent advantages coupled with a nonlinear artificial neural network (ANN) modelling method were used to provide a QSAR model with high interpretability and predictability. After evaluating the accuracy and validity of the developed ALASSO-ANN model, new compounds were proposed using effective descriptors, and the biological activity of the new compounds was predicted. Ligand-receptor (LR) interactions were also performed to confirm the interaction strength of the compounds using molecular docking (MD) study. The pharmacokinetics properties and calculated Lipinski's rule of five were applied to all proposed compounds. Due to the ease of synthesis of these suggested new compounds, it is expected that they have acceptable pharmacological properties.

Structure-Based Virtual Screening to Discover Potential Lead Molecules for the SARS-CoV-2 Main Protease

The COVID-19 disease is caused by a new strain of the coronavirus family (SARS-CoV-2), and it has affected at present millions of people all over the world. The indispensable role of the main protease (Mpro) in viral replication and gene expression makes this enzyme an attractive drug target. Therefore, inhibition of SARS-CoV-2 Mpro as a proposition to halt virus ingression is being pursued by scientists globally. Here we carried out a study with two objectives: the first being to perform comparative protein sequence and 3D structural analysis to understand the effect of 12 point mutations on the active site. Among these, two mutations, viz., Ser46 and Phe134, were found to cause a significant change at the active sites of SARS-CoV-2. The Ser46 mutation present at the entrance of the S5 subpocket of SARS-CoV-2 increases the contribution of other two hydrophilic residues, while the Phe134 mutation, present in the catalytic cysteine loop, can cause an increase in catalytic efficiency of Mpro by facilitating fast proton transfer from the Cys145 to His41 residue. It was observed that active site remained conserved among Mpro of both SARS-CoVs, except at the entrance of the S5 subpocket, suggesting sustenance of substrate specificity. The second objective was to screen the inhibitory effects of three different data sets (natural products, coronaviruses main protease inhibitors, and FDA-approved drugs) using a structure-based virtual screening approach. A total of 73 hits had a combo score >2.0. Eight different structural scaffold classes were identified, such as one/two tetrahydropyran ring(s), dipeptide/tripeptide/oligopeptide, large (approximately 20 atoms) cyclic peptide, and miscellaneous. The screened hits showed key interactions with subpockets of the active site. Further, molecular dynamics studies of selected screened compounds confirmed their perfect fitting into the subpockets of the active site. This study suggests promising structures that can fit into the SARS-CoV-2 Mpro active site and also offers direction for further lead optimization and rational drug design.

Pharmacological Therapeutics Targeting RNA-Dependent RNA Polymerase, Proteinase and Spike Protein: From Mechanistic Studies to Clinical Trials for COVID-19

An outbreak of novel coronavirus-related pneumonia COVID-19, that was identified in December 2019, has expanded rapidly, with cases now confirmed in more than 211 countries or areas. This constant transmission of a novel coronavirus and its ability to spread from human to human have prompted scientists to develop new approaches for treatment of COVID-19. A recent study has shown that remdesivir and chloroquine effectively inhibit the replication and infection of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2, 2019-nCov) in vitro. In the United States, one case of COVID-19 was successfully treated with compassionate use of remdesivir in January of 2020. In addition, a clinically proven protease inhibitor, camostat mesylate, has been demonstrated to inhibit Calu-3 infection with SARS-CoV-2 and prevent SARS-2-spike protein (S protein)-mediated entry into primary human lung cells. Here, we systemically discuss the pharmacological therapeutics targeting RNA-dependent RNA polymerase (RdRp), proteinase and S protein for treatment of SARS-CoV-2 infection. This review should shed light on the fundamental rationale behind inhibition of SARS-CoV-2 enzymes RdRp as new therapeutic approaches for management of patients with COVID-19. In addition, we will discuss the viability and challenges in targeting RdRp and proteinase, and application of natural product quinoline and its analog chloroquine for treatment of coronavirus infection. Finally, determining the structural-functional relationships of the S protein of SARS-CoV-2 will provide new insights into inhibition of interactions between S protein and angiotensin-converting enzyme 2 (ACE2) and enable us to develop novel therapeutic approaches for novel coronavirus SARS-CoV-2.

Use of multiple picosecond high-mass molecular dynamics simulations to predict crystallographic B-factors of folded globular proteins

Predicting crystallographic B-factors of a protein from a conventional molecular dynamics simulation is challenging, in part because the B-factors calculated through sampling the atomic positional fluctuations in a picosecond molecular dynamics simulation are unreliable, and the sampling of a longer simulation yields overly large root mean square deviations between calculated and experimental B-factors. This article reports improved B-factor prediction achieved by sampling the atomic positional fluctuations in multiple picosecond molecular dynamics simulations that use uniformly increased atomic masses by 100-fold to increase time resolution. Using the third immunoglobulin-binding domain of protein G, bovine pancreatic trypsin inhibitor, ubiquitin, and lysozyme as model systems, the B-factor root mean square deviations (mean ± standard error) of these proteins were 3.1 ± 0.2–9 ± 1 Ų for Cα and 7.3 ± 0.9–9.6 ± 0.2 Ų for Cγ, when the sampling was done for each of these proteins over 20 distinct, independent, and 50-picosecond high-mass molecular dynamics simulations with AMBER forcefield FF12MC or FF14SB. These results suggest that sampling the atomic positional fluctuations in multiple picosecond high-mass molecular dynamics simulations may be conducive to a priori prediction of crystallographic B-factors of a folded globular protein.

Techniques used for the discovery of therapeutic compounds: The case of SARS

Severe acute respiratory syndrome coronavirus (SARS-CoV) is the etiological agent of SARS disease, which has ever severely menaced humans from the end of 2002 to June 2003. To date, great efforts have been made for the discovery of therapeutic compounds by using various technologies. In this report, we present a survey of these techniques and their applications in the development of promising anti-SARS agents.:

The role of protein structural analysis in the next generation sequencing era

Proteins are macromolecules that serve a cell’s myriad processes and functions in all living organisms via dynamic interactions with other proteins, small molecules and cellular components. Genetic variations in the protein-encoding regions of the human genome account for >85% of all known Mendelian diseases, and play an influential role in shaping complex polygenic diseases. Proteins also serve as the predominant target class for the design of small molecule drugs to modulate their activity. Knowledge of the shape and form of proteins, by means of their three-dimensional structures, is therefore instrumental to understanding their roles in disease and their potentials for drug development. In this chapter we outline, with the wide readership of non-structural biologists in mind, the various experimental and computational methods available for protein structure determination. We summarize how the wealth of structure information, contributed to a large extent by the technological advances in structure determination to date, serves as a useful tool to decipher the molecular basis of genetic variations for disease characterization and diagnosis, particularly in the emerging era of genomic medicine, and becomes an integral component in the modern day approach towards rational drug development.

Biomolecularmodeling and simulation: a field coming of age

We assess the progress in biomolecular modeling and simulation, focusing on structure prediction and dynamics, by presenting the field’s history, metrics for its rise in popularity, early expressed expectations, and current significant applications. The increases in computational power combined with improvements in algorithms and force fields have led to considerable success, especially in protein folding, specificity of ligand/biomolecule interactions, and interpretation of complex experimental phenomena (e.g. NMR relaxation, protein-folding kinetics and multiple conformational states) through the generation of structural hypotheses and pathway mechanisms. Although far from a general automated tool, structure prediction is notable for proteins and RNA that preceded the experiment, especially by knowledge-based approaches. Thus, despite early unrealistic expectations and the realization that computer technology alone will not quickly bridge the gap between experimental and theoretical time frames, ongoing improvements to enhance the accuracy and scope of modeling and simulation are propelling the field onto a productive trajectory to become full partner with experiment and a field on its own right.

Small-molecule inhibitor leads of ribosome-inactivating proteins developed using the doorstop approach

Ribosome-inactivating proteins (RIPs) are toxic because they bind to 28S rRNA and depurinate a specific adenine residue from the α-sarcin/ricin loop (SRL), thereby inhibiting protein synthesis. Shiga-like toxins (Stx1 and Stx2), produced by Escherichia coli, are RIPs that cause outbreaks of foodborne diseases with significant morbidity and mortality. Ricin, produced by the castor bean plant, is another RIP lethal to mammals. Currently, no US Food and Drug Administration-approved vaccines nor therapeutics exist to protect against ricin, Shiga-like toxins, or other RIPs. Development of effective small-molecule RIP inhibitors as therapeutics is challenging because strong electrostatic interactions at the RIP•SRL interface make drug-like molecules ineffective in competing with the rRNA for binding to RIPs. Herein, we report small molecules that show up to 20% cell protection against ricin or Stx2 at a drug concentration of 300 nM. These molecules were discovered using the doorstop approach, a new approach to protein•polynucleotide inhibitors that identifies small molecules as doorstops to prevent an active-site residue of an RIP (e.g., Tyr80 of ricin or Tyr77 of Stx2) from adopting an active conformation thereby blocking the function of the protein rather than contenders in the competition for binding to the RIP. This work offers promising leads for developing RIP therapeutics. The results suggest that the doorstop approach might also be applicable in the development of other protein•polynucleotide inhibitors as antiviral agents such as inhibitors of the Z-DNA binding proteins in poxviruses. This work also calls for careful chemical and biological characterization of drug leads obtained from chemical screens to avoid the identification of irrelevant chemical structures and to avoid the interference caused by direct interactions between the chemicals being screened and the luciferase reporter used in screening assays.

Discovery of novel SERCA inhibitors by virtual screening of a large compound library

Two screening protocols based on recursive partitioning and computational ligand docking methodologies, respectively, were employed for virtual screens of a compound library with 345,000 entries for novel inhibitors of the enzyme sarco/endoplasmic reticulum calcium ATPase (SERCA), a potential target for cancer chemotherapy. A total of 72 compounds that were predicted to be potential inhibitors of SERCA were tested in bioassays and 17 displayed inhibitory potencies at concentrations below 100 μM. The majority of these inhibitors were composed of two phenyl rings tethered to each other by a short link of one to three atoms. Putative interactions between SERCA and the inhibitors were identified by inspection of docking-predicted poses and some of the structural features required for effective SERCA inhibition were determined by analysis of the classification pattern employed by the recursive partitioning models.

Biomolecular Structure and Modeling: Historical Perspective

physics, chemistry, and biology have been connected by a web of causal explanation organized by induction-based theories that telescope into one another. … Thus, quantum theory underlies atomic physics, which is the foundation of reagent chemistry and its specialized offshoot biochemistry, which interlock with molecular biology — essentially, the chemistry of organic macromolecules — and hence, through successively higher levels of organization, cellular, organismic, and evolutionary biology. … Such is the unifying and highly productive understanding of the world that has evolved in the natural sciences.

Biomolecular Structure and Modeling: Problem and Application Perspective

The experimental progress described in the previous chapter has been accompanied by an increasing desire to relate the complex three-dimensional (3D) shapes of biomolecules to their biological functions and interactions with other molecular systems. Structural biology, computational biology, genomics, proteomics, bioinformatics, chemoinformatics, and others are natural partner disciplines in such endeavors.

Therapies for coronaviruses. Part 2: Inhibitors of intracellular life cycle

BACKGROUND

Severe acute respiratory syndrome (SARS) coronavirus emerged from an animal reservoir in 2002 and has the potential to reemerge, as shown by the occurrence of non-laboratory-associated new cases in the winter of 2003. In the absence of a vaccine, broad spectrum anticoronaviral medications are needed.

OBJECTIVE

Anticoronavirals targeting viral entry were reviewed in part I. Here we review anticoronaviral therapies directed against the intracellular life cycle, with an emphasis on allowed patents and pending patents.

METHOD

The published literature, in particular, patent publications is searched for relevant documents. The information is organized and critiqued.

RESULTS/CONCLUSION

Many promising anticoronaviral strategies are identified. Monoclonal antibodies, protease inhibitors, interferon-based drugs and nucleic-acid based antivirals are most advanced, each having its own advantages and disadvantages. A multi-pronged approach, keeping all venues open, is advocated.

Shuffling multivariate adaptive regression splines and adaptive neuro-fuzzy inference system as tools for QSAR study of SARS inhibitors

In this work, the inhibitory activity of pyridine N-oxide derivatives against human severe acute respiratory syndrome (SARS) is predicted in terms of quantitative structure–activity relationship (QSAR) models. These models were developed with the aid of multivariate adaptive regression spline (MARS) and adaptive neuro-fuzzy inference system (ANFIS) combined with shuffling cross-validation technique. A shuffling MARS algorithm is utilized to select the most important variables in QSAR modeling and then these variables were used as inputs of ANFIS to predict SARS inhibitory activities of pyridine N-oxide derivatives. A data set of 119 drug-like compounds was coded with over hundred calculated meaningful molecular descriptors. The best descriptors describing the inhibition mechanism were solvation connectivity index, length to breadth ratio, relative negative charge, harmonic oscillator of aromatic index, average molecular weight and total path count. These parameters are among topological, electronic, geometric, constitutional and aromaticity descriptors. The statistical parameters of R² and root mean square error (RMSE) are 0.884 and 0.359, respectively. The accuracy and robustness of shuffling MARS–ANFIS model in predicting inhibition behavior of pyridine N-oxide derivatives (pIC₅₀) was illustrated using leave-one-out and leave-multiple-out cross-validation techniques and also by Y-randomization. Comparison of the results of the proposed model with those of GA-PLS-ANFIS shows that the shuffling MARS–ANFIS model is superior and can be considered as a tool for predicting the inhibitory behavior of SARS drug-like molecules.

Lead Discovery Using Virtual Screening

The practice of virtual screening (VS) to identify chemical leads to known or novel targets is becoming a core function of the computational chemist within industry. By employing a range of techniques, when attempting to identify compounds with activity against a biological target, a small focused subset of a larger collection of compounds can be identified and tested, often with results much better than selecting a similar number of compounds at random. We will review the key methods available, their relative success, and provide practical insights into best practices and key gaps. We will also argue that the capability of VS methods has grown to a point where fuller integration with experimental methods, including HTS, could increase the effectiveness of both.

An idea whose time has come

A response to An idea whose time has gone by Gregory A Petsko, Genome Biology 2007, 8:107.

A response to An idea whose time has gone by Gregory A Petsko, Genome Biology 2007, 8:107.

Flexibility of aromatic residues in the active-site gorge of acetylcholinesterase: X-ray versus molecular dynamics

The high aromatic content of the deep and narrow active-site gorge of acetylcholinesterase (AChE) is a remarkable feature of this enzyme. Here, we analyze conformational flexibility of the side chains of the 14 conserved aromatic residues in the active-site gorge of Torpedo californica AChE based on the 47 three-dimensional crystal structures available for the native enzyme, and for its complexes and conjugates, and on a 20-ns molecular dynamics (MD) trajectory of the native enzyme. The degree of flexibility of these 14 aromatic side chains is diverse. Although the side-chain conformations of F330 and W279 are both very flexible, the side-chain conformations of F120, W233, W432, Y70, Y121, F288, F290 and F331 appear to be fixed. Residues located on, or adjacent to, the Omega-loop (C67-C94), namely W84, Y130, Y442, and Y334, display different flexibilities in the MD simulations and in the crystal structures. An important outcome of our study is that the majority of the side-chain conformations observed in the 47 Torpedo californica AChE crystal structures are faithfully reproduced by the MD simulation on the native enzyme. Thus, the protein can assume these conformations even in the absence of the ligand that permitted their experimental detection. These observations are pertinent to structure-based drug design.

Current topics in computer-aided drug design

The addition of computer-aided drug design (CADD) technologies to the research and drug discovery approaches could lead to a reduction of up to 50% in the cost of drug design. Designing a drug is the process of finding or creating a molecule which has a specific activity on a biological organism. Development and drug discovery is a time-consuming, expensive, and interdisciplinary process whereas scientific advancements during the past two decades have altered the way pharmaceutical research produces new bioactive molecules. Advances in computational techniques and hardware solutions have enabled in silico methods to speed up lead optimization and identification. We will review current topics in computer-aided molecular design underscoring some of the most recent approaches and interdisciplinary processes. We will discuss some of the most efficient pathways and design.

Structure-based virtual screening against SARS-3CL(pro) to identify novel non-peptidic hits

Severe acute respiratory syndrome is a highly infectious upper respiratory tract disease caused by SARS-CoV, a previously unidentified human coronavirus. SARS-3CL(pro) is a viral cysteine protease critical to the pathogen's life cycle and hence a therapeutic target of importance. The recently elucidated crystal structures of this enzyme provide an opportunity for the discovery of inhibitors through rational drug design. In the current study, Gold docking program was utilized to conduct extensive docking studies against the target crystal structure to develop a robust and predictive docking protocol. The validated docking protocol was used to conduct a structure-based virtual screening of the Asinex Platinum collection. Biological evaluation of a screened selection of compounds was carried out to identify novel inhibitors of the viral protease.

Molecular docking identifies the binding of 3-chloropyridine moieties specifically to the S1 pocket of SARS-CoV Mpro

The 3C-like main proteinase of the severe acute respiratory syndrome (SARS) coronavirus, SARS-CoV M^pro, is widely considered to be a major drug target for the development of anti-SARS treatment. Based on the chemical structure of a lead compound from a previous screening, we have designed and synthesized a number of non-peptidyl inhibitors, some of which have shown significantly improved inhibitory activity against SARS-CoV M^pro with IC₅₀ values of ∼60 nM. In the absence of SARS-CoV M^pro crystal structures in complex with these synthetic inhibitors, molecular docking tools have been employed to study possible interactions between these inhibitors and SARS-CoV M^pro. The docking results suggest two major modes for the initial binding of these inhibitors to the active site of SARS-CoV M^pro. They also establish a structural basis for the ‘core design’ of these inhibitors by showing that the 3-chloropyridine functions common to all of the present inhibitors tend to cluster in the S1 specificity pocket. In addition, intrinsic flexibility in the S4 pocket allows for the accommodation of bulky groups such as benzene rings, suggesting that this structural plasticity can be further exploited for optimizing inhibitor–enzyme interactions that should promote a tighter binding mode. Most importantly, our results provide the structural basis for rational design of wide-spectrum antiviral drugs targeting the chymotrypsin-like cysteine proteinases from coronaviruses and picornaviruses.

Preference of small molecules for local minimum conformations when binding to proteins

It is well known that small molecules (ligands) do not necessarily adopt their lowest potential energy conformations when binding to proteins. Analyses of protein-bound ligand crystal structures have reportedly shown that many of them do not even adopt the conformations at local minima of their potential energy surfaces (local minimum conformations). The results of these analyses raise a concern regarding the validity of virtual screening methods that use ligands in local minimum conformations. Here we report a normal-mode-analysis (NMA) study of 100 crystal structures of protein-bound ligands. Our data show that the energy minimization of a ligand alone does not automatically stop at a local minimum conformation if the minimum of the potential energy surface is shallow, thus leading to the folding of the ligand. Furthermore, our data show that all 100 ligand conformations in their protein-bound ligand crystal structures are nearly identical to their local minimum conformations obtained from NMA-monitored energy minimization, suggesting that ligands prefer to adopt local minimum conformations when binding to proteins. These results both support virtual screening methods that use ligands in local minimum conformations and caution about possible adverse effect of excessive energy minimization when generating a database of ligand conformations for virtual screening.

In silico prediction of SARS protease inhibitors by virtual high throughput screening

A structure‐based in silico virtual drug discovery procedure was assessed with severe acute respiratory syndrome coronavirus main protease serving as a case study. First, potential compounds were extracted from protein–ligand complexes selected from Protein Data Bank database based on structural similarity to the target protein. Later, the set of compounds was ranked by docking scores using a Electronic High‐Throughput Screening flexible docking procedure to select the most promising molecules. The set of best performing compounds was then used for similarity search over the 1 million entries in the Ligand.Info Meta‐Database. Selected molecules having close structural relationship to a 2‐methyl‐2,4‐pentanediol may provide candidate lead compounds toward the development of novel allosteric severe acute respiratory syndrome protease inhibitors.

Accurate reproduction of 161 small-molecule complex crystal structures using the EUDOC program: expanding the use of EUDOC to supramolecular chemistry

EUDOC is a docking program that has successfully predicted small-molecule-bound protein complexes and identified drug leads from chemical databases. To expand the application of the EUDOC program to supramolecular chemistry, we tested its ability to reproduce crystal structures of small-molecule complexes. Of 161 selected crystal structures of small-molecule guest-host complexes, EUDOC reproduced all these crystal structures with guest structure mass-weighted root mean square deviations (mwRMSDs) of <1.0 A relative to the corresponding crystal structures. In addition, the average interaction energy of these 161 guest-host complexes (-50.1 kcal/mol) was found to be nearly half of that of 153 previously tested small-molecule-bound protein complexes (-108.5 kcal/mol), according to the interaction energies calculated by EUDOC. 31 of the 161 complexes could not be reproduced with mwRMSDs of <1.0 A if neighboring hosts in the crystal structure of a guest-host complex were not included as part of the multimeric host system, whereas two of the 161 complexes could not be reproduced with mwRMSDs of <1.0 A if water molecules were excluded from the host system. These results demonstrate the significant influence of crystal packing on small molecule complexation and suggest that EUDOC is able to predict small-molecule complexes and that it is useful for the design of new materials, molecular sensors, and multimeric inhibitors of protein-protein interactions.

Novel nerve-agent antidote design based on crystallographic and mass spectrometric analyses of tabun-conjugated acetylcholinesterase in complex with antidotes

Organophosphorus compound-based nerve agents inhibit the essential enzyme acetylcholinesterase (AChE) causing acute toxicity and death. Clinical treatment of nerve-agent poisoning is to use oxime-based antidotes to reactivate the inhibited AChE. However, the nerve agent tabun is resistant to oximes. To design improved oximes, crystal structures of a tabun-conjugated AChE in complex with different oximes are needed to guide the structural modifications of known antidotes. However, this type of structure is extremely challenging to obtain because both deamidation of the tabun conjugate and reactivation of AChE occur during crystallographic experiments. Here we report, for the first time, the crystal structures of Ortho-7 and HLö-7 in complex with AChE that is conjugated to an intact tabun. These structures were determined by our new strategy of combining crystallographic and mass spectrometric analyses of AChE crystals. The results explain the relative reactivation potencies of the two oximes and offer insights into improving known medical antidotes.

Cell biology of membrane trafficking in human disease

Understanding the molecular and cellular mechanisms underlying membrane traffic pathways is crucial to the treatment and cure of human disease. Various human diseases caused by changes in cellular homeostasis arise through a single gene mutation(s) resulting in compromised membrane trafficking. Many pathogenic agents such as viruses, bacteria, or parasites have evolved mechanisms to subvert the host cell response to infection, or have hijacked cellular mechanisms to proliferate and ensure pathogen survival. Understanding the consequence of genetic mutations or pathogenic infection on membrane traffic has also enabled greater understanding of the interactions between organisms and the surrounding environment. This review focuses on human genetic defects and molecular mechanisms that underlie eukaryote exocytosis and endocytosis and current and future prospects for alleviation of a variety of human diseases.

In silico drug discovery: solving the "target-rich and lead-poor" imbalance using the genome-to-drug-lead paradigm

Advances in genomics, proteomics, and structural genomics have identified a large number of protein targets. Virtual screening has gained popularity in identifying drug leads by computationally screening large numbers of chemicals against experimentally determined protein targets. In that context, there continues to be a "target-rich and lead-poor" imbalance, reflecting an insufficiency of chemists pursuing drug discovery in academia, the challenge of engaging more chemists in this area of research, and a paucity of available protein target structures. This imbalance in manpower and structural information can be ameliorated, in part, by adapting a "genome-to-drug-lead" approach, in which chemicals can be virtually screened against computer-predicted protein targets, within the context of the US National Science Foundation's petascale computing initiative. This approach offers a solution to reduce manpower requirements for more chemists to experimentally search for drug leads, which represent one of the greatest limitations to drug discovery and better exploits the extensive availability of drug targets at the gene level, ultimately improving the success of moving discoveries from the laboratory to the patient.

Species marker for developing novel and safe pesticides

Current anticholinesterase pesticides developed during World War II are toxic to mammals because they target a catalytic serine residue of acetylcholinesterases (AChEs) in insects and in mammals. A sequence analysis of AChEs from 68 species and three-dimensional models of the greenbug and English grain aphid AChEs reported herein reveal that a cysteine residue is present at the active sites of greenbug and aphid AChEs but absent at those of mammalian AChEs. This discovery enables the design of novel and safe pesticides that target the cysteine residue rather than the ubiquitous serine residue.

Novel acetylcholinesterase target site for malaria mosquito control

Current anticholinesterase pesticides were developed during World War II and are toxic to mammals because they target a catalytic serine residue of acetylcholinesterases (AChEs) in insects and in mammals. A sequence analysis of AChEs from 73 species and a three-dimensional model of a malaria-carrying mosquito (Anopheles gambiae) AChE (AgAChE) reported here show that C286 and R339 of AgAChE are conserved at the opening of the active site of AChEs in 17 invertebrate and four insect species, respectively. Both residues are absent in the active site of AChEs of human, monkey, dog, cat, cattle, rabbit, rat, and mouse. The 17 invertebrates include house mosquito, Japanese encephalitis mosquito, African malaria mosquito, German cockroach, Florida lancelet, rice leaf beetle, African bollworm, beet armyworm, codling moth, diamondback moth, domestic silkworm, honey bee, oat or wheat aphid, the greenbug, melon or cotton aphid, green peach aphid, and English grain aphid. The four insects are house mosquito, Japanese encephalitis mosquito, African malaria mosquito, and German cockroach. The discovery of the two invertebrate-specific residues enables the development of effective and safer pesticides that target the residues present only in mosquito AChEs rather than the ubiquitous serine residue, thus potentially offering an effective control of mosquito-borne malaria. Anti-AgAChE pesticides can be designed to interact with R339 and subsequently covalently bond to C286. Such pesticides would be toxic to mosquitoes but not to mammals.

Structure-based drug design and structural biology study of novel nonpeptide inhibitors of severe acute respiratory syndrome coronavirus main protease

Severe acute respiratory syndrome coronavirus (SARS-CoV) main protease (M(pro)), a protein required for the maturation of SARS-CoV, is vital for its life cycle, making it an attractive target for structure-based drug design of anti-SARS drugs. The structure-based virtual screening of a chemical database containing 58,855 compounds followed by the testing of potential compounds for SARS-CoV M(pro) inhibition leads to two hit compounds. The core structures of these two hits, defined by the docking study, are used for further analogue search. Twenty-one analogues derived from these two hits exhibited IC50 values below 50 microM, with the most potent one showing 0.3 microM. Furthermore, the complex structures of two potent inhibitors with SARS-CoV M(pro) were solved by X-ray crystallography. They bind to the protein in a distinct manner compared to all published SARS-CoV M(pro) complex structures. They inhibit SARS-CoV M(pro) activity via intensive H-bond network and hydrophobic interactions, without the formation of a covalent bond. Interestingly, the most potent inhibitor induces protein conformational changes, and the inhibition mechanisms, particularly the disruption of catalytic dyad (His41 and Cys145), are elaborated.

TarFisDock: a web server for identifying drug targets with docking approach

TarFisDock is a web-based tool for automating the procedure of searching for small molecule-protein interactions over a large repertoire of protein structures. It offers PDTD (potential drug target database), a target database containing 698 protein structures covering 15 therapeutic areas and a reverse ligand-protein docking program. In contrast to conventional ligand-protein docking, reverse ligand-protein docking aims to seek potential protein targets by screening an appropriate protein database. The input file of this web server is the small molecule to be tested, in standard mol2 format; TarFisDock then searches for possible binding proteins for the given small molecule by use of a docking approach. The ligand-protein interaction energy terms of the program DOCK are adopted for ranking the proteins. To test the reliability of the TarFisDock server, we searched the PDTD for putative binding proteins for vitamin E and 4H-tamoxifen. The top 2 and 10% candidates of vitamin E binding proteins identified by TarFisDock respectively cover 30 and 50% of reported targets verified or implicated by experiments; and 30 and 50% of experimentally confirmed targets for 4H-tamoxifen appear amongst the top 2 and 5% of the TarFisDock predicted candidates, respectively. Therefore, TarFisDock may be a useful tool for target identification, mechanism study of old drugs and probes discovered from natural products. TarFisDock and PDTD are available at http://www.dddc.ac.cn/tarfisdock/.

Discovery of a Novel Family of SARS-CoV Protease Inhibitors by Virtual Screening and 3D-QSAR Studies

The severe acute respiratory syndrome-associated coronavirus (SARS-CoV) 3C-like protease (3CL(pro) or M(pro)) is an attractive target for the development of anti-SARS drugs because of its crucial role in the viral life cycle. In this study, a compound database was screened by the structure-based virtual screening approach to identify initial hits as inhibitors of SARS-CoV 3CL(pro). Out of the 59,363 compounds docked, 93 were selected for the inhibition assay, and 21 showed inhibition against SARS-CoV 3CL(pro) (IC(50) <or= 30 microM), with three of them having common substructures. Furthermore, a search for analogues with common substructure in the Maybridge, ChemBridge, and SPECS_SC databases led to the identification of another 25 compounds that exhibited inhibition against SARS-CoV 3CL(pro) (IC(50) = 3-1,000 microM). These compounds, 28 in total, were subjected to 3D-QSAR studies to elucidate the pharmacophore of SARS-CoV 3CL(pro).