Relaxed Complex Scheme Research Articles

Benchmarking ensemble docking methods in D3R Grand Challenge 4

The discovery of new drugs is a time consuming and expensive process. Methods such as virtual screening, which can filter out ineffective compounds from drug libraries prior to expensive experimental study, have become popular research topics. As the computational drug discovery community has grown, in order to benchmark the various advances in methodology, organizations such as the Drug Design Data Resource have begun hosting blinded grand challenges seeking to identify the best methods for ligand pose-prediction, ligand affinity ranking, and free energy calculations. Such open challenges offer a unique opportunity for researchers to partner with junior students (e.g., high school and undergraduate) to validate basic yet fundamental hypotheses considered to be uninteresting to domain experts. Here, we, a group of high school-aged students and their mentors, present the results of our participation in Grand Challenge 4 where we predicted ligand affinity rankings for the Cathepsin S protease, an important protein target for autoimmune diseases. To investigate the effect of incorporating receptor dynamics on ligand affinity rankings, we employed the Relaxed Complex Scheme, a molecular docking method paired with molecular dynamics-generated receptor conformations. We found that Cathepsin S is a difficult target for molecular docking and we explore some advanced methods such as distance-restrained docking to try to improve the correlation with experiments. This project has exemplified the capabilities of high school students when supported with a rigorous curriculum, and demonstrates the value of community-driven competitions for beginners in computational drug discovery.

Relaxed complex scheme and molecular dynamics simulation suggests small molecule inhibitor of human TMPRSS2 for combating COVID-19

As the coronavirus disease 19 (COVID-19) pandemic continues to pose a health and economic crisis worldwide, the quest for drugs and/or vaccines against the virus continues. The human transmembrane protease serine 2 (TMPRSS2) has attracted attention as a target for drug discovery, as inhibition of its catalytic reaction would result in the inactivation of the proteolytic cleavage of the SARS-CoV-2 S protein. As a result, the inactivation prevents viral cell entry to the host’s cell. In this work, we screened and identified two potent molecules that interact and inhibit the catalytic reaction by using computational approaches. Two docking screening experiments were performed utilizing the crystal structure and holo ensemble structure obtained from molecular dynamics in bound form. There is enhancement and sensitivity of docking results to the holo ensemble as compared to the crystal structure. Compound 1 demonstrated a similar inhibition value to nafamostat by interacting with catalytic triad residues His296 and Ser441, thereby disrupting the already established hydrogen bond interaction. The stability of the ligand–TMPRSS2 complexes was studied by molecular dynamics simulation, and the binding energy was re-scored by using molecular mechanics Poisson-Boltzmann surface area (MM-PBSA) binding free energy. The obtained compounds may serve as an initial point toward the discovery of potent TMPRSS2 inhibitors upon further in vivo validation. Communicated by Ramaswamy H. Sarma

Luteolin: a blocker of SARS-CoV-2 cell entry based on relaxed complex scheme, molecular dynamics simulation, and metadynamics

Natural products have served human life as medications for centuries. During the outbreak of COVID-19, a number of naturally derived compounds and extracts have been tested or used as potential remedies against COVID-19. Tetradenia riparia extract is one of the plant extracts that have been deployed and claimed to manage and control COVID-19 by some communities in Tanzania and other African countries. The active compounds isolated from T. riparia are known to possess various biological properties including antimalarial and antiviral. However, the underlying mechanism of the active compounds against SARS-CoV-2 remains unknown. Results in the present work have been interpreted from the view point of computational methods including molecular dynamics, free energy methods, and metadynamics to establish the related mechanism of action. Among the constituents of T. riparia studied, luteolin inhibited viral cell entry and was thermodynamically stable. The title compound exhibit residence time and unbinding kinetics of 68.86 ms and 0.014 /ms, respectively. The findings suggest that luteolin could be potent blocker of SARS-CoV-2 cell entry. The study shades lights towards identification of bioactive constituents from T. riparia against COVID-19, and thus bioassay can be carried out to further validate such observations.Supplementary InformationThe online version contains supplementary material available at 10.1007/s00894-021-04833-x.

Identification of Novel Cyclin A2 Binding Site and Nanomolar Inhibitors of Cyclin A2-CDK2 Complex.

Given the diverse roles of cyclin A2 both in cell cycle regulation and in DNA damage response, identifying small molecule regulators of cyclin A2 activity carries significant potential to regulate diverse cellular processes in both ageing/neurodegeneration and in cancer. Based on cyclin A2's recently discovered role in DNA repair, we hypothesized that small molecule inhibitors that were predicted to bind to both cyclin A2 and CDK2 will be useful as a radiosensitizer of cancer cells. In this study, we used structure-based drug discovery to find inhibitors that target both cyclin A2 and CDK2. Molecular dynamics simulations were used to generate diverse binding pocket conformations for application of the relaxed complex scheme. We then used structure-based virtual screening to find potential dual cyclin A2 and CDK2 inhibitors. Based on a consensus score of docked poses from Glide and AutoDock Vina, we identified about 40 promising hit compounds, where all PAINS scaffolds were removed from consideration. A biochemical luminescence assay of cyclin A2-CDK2 function was used for experimental verification. Four lead inhibitors of cyclin A2-CDK2 complex have been identified using a relaxed complex scheme virtual screen have been verified in a biochemical luminescence assay of cyclin A2- CDK2 function. Two of the four lead inhibitors had inhibitory concentrations in the nanomolar range. The four cyclin A2-CDK2 complex inhibitors are the first reported inhibitors that were specifically designed not to target the cyclin A2-CDK2 protein-protein interface. Overall, our results highlight the potential of combined advanced computational tools and biochemical verification to discover novel binding scaffolds.

Identification of Novel Cyclin A2 Binding Site and Nanomolar Inhibitors

It has been shown that dysfunction in tight regulation of DNA repair pathways can induce various syndromes, increase the risk of cancer, and trigger neurological defect. However, there are cases where inhibition of DNA repair process is necessary. For example, after treating cancer cells with radiotherapy, it is essential to inhibit DNA repair function of the radiation-induced cancer cells for successful apoptosis. Therefore, the key is to target a protein that is responsible for controlling the rapid and proper resolution of DNA strand breaks. The recent discovery of CCNA2 (cyclin A2), the main mammalian S-phase cyclin, as a regulator of neuronal genomic stability and DNA repair positioned cyclin A2 as a potential therapeutic target for DNA repair dysfunction and as a radiation sensitizer. Thus, identifying small molecule regulators of cyclin A2 activity carries significant potential to regulate diverse cellular processes in both ageing/neurodegeneration and in cancer. No functional modulators of cyclin A2 are known to date. Here, we identified a potential allosteric cyclin A2 ligand binding pocket based on high-resolution structural data. Molecular dynamics simulations were used to generate diverse binding pocket conformations for application of the relaxed complex scheme. We then used structure-based virtual screening to find potential cyclin A2 inhibitors. Based on a consensus score of docked poses from Glide and AutoDock Vina, we identified about 60 promising hit compounds, where all PAINS scaffolds were removed from consideration. A biochemical luminescence assay of cyclin A2 function was used for experimental verification and identified three nanomolar inhibitors of cyclin A2. These novel cyclin A2 inhibitors are the first reported cyclin A2 inhibitors that do not target the cyclin A2 - CDK 2 protein-protein interface.

Successful Identification of Cardiac Troponin Calcium Sensitizers Using a Combination of Virtual Screening and ROC Analysis of Known Troponin C Binders.

Calcium-dependent cardiac muscle contraction is regulated by the protein complex troponin. Calcium binds to the N-terminal domain of troponin C (cNTnC) which initiates the process of contraction. Heart failure is a consequence of a disruption of this process. With the prevalence of this condition, a strong need exists to find novel compounds to increase the calcium sensitivity of cNTnC. Desirable are small chemical molecules that bind to the interface between cTnC and the cTnI switch peptide and exhibit calcium sensitizing properties by possibly stabilizing cTnC in an open conformation. To identify novel drug candidates, we employed a structure-based drug discovery protocol that incorporated the use of a relaxed complex scheme (RCS). In preparation for the virtual screening, cNTnC conformations were identified based on their ability to correctly predict known cNTnC binders using a receiver operating characteristics analysis. Following a virtual screen of the National Cancer Institute's Developmental Therapeutic Program database, a small number of molecules were experimentally tested using stopped-flow kinetics and steady-state fluorescence titrations. We identified two novel compounds, 3-(4-methoxyphenyl)-6,7-chromanediol (NSC600285) and 3-(4-methylphenyl)-7,8-chromanediol (NSC611817), that show increased calcium sensitivity of cTnC in the presence of the regulatory domain of cTnI. The effects of NSC600285 and NSC611817 on the calcium dissociation rate was stronger than that of the known calcium sensitizer bepridil. Thus, we identified a 3-phenylchromane group as a possible key pharmacophore in the sensitization of cardiac muscle contraction. Building on this finding is of interest to researchers working on development of drugs for calcium sensitization.

Drug search for leishmaniasis: a virtual screening approach by grid computing.

The trypanosomatid protozoa Leishmania is endemic in ~100 countries, with infections causing ~2 million new cases of leishmaniasis annually. Disease symptoms can include severe skin and mucosal ulcers, fever, anemia, splenomegaly, and death. Unfortunately, therapeutics approved to treat leishmaniasis are associated with potentially severe side effects, including death. Furthermore, drug-resistant Leishmania parasites have developed in most endemic countries. To address an urgent need for new, safe and inexpensive anti-leishmanial drugs, we utilized the IBM World Community Grid to complete computer-based drug discovery screens (Drug Search for Leishmaniasis) using unique leishmanial proteins and a database of 600,000 drug-like small molecules. Protein structures from different Leishmania species were selected for molecular dynamics (MD) simulations, and a series of conformational "snapshots" were chosen from each MD trajectory to simulate the protein's flexibility. A Relaxed Complex Scheme methodology was used to screen ~2000 MD conformations against the small molecule database, producing >1 billion protein-ligand structures. For each protein target, a binding spectrum was calculated to identify compounds predicted to bind with highest average affinity to all protein conformations. Significantly, four different Leishmania protein targets were predicted to strongly bind small molecules, with the strongest binding interactions predicted to occur for dihydroorotate dehydrogenase (LmDHODH; PDB:3MJY). A number of predicted tight-binding LmDHODH inhibitors were tested in vitro and potent selective inhibitors of Leishmania panamensis were identified. These promising small molecules are suitable for further development using iterative structure-based optimization and in vitro/in vivo validation assays.

Molecular docking to flexible targets.

It is widely accepted that protein receptors exist as an ensemble of conformations in solution. How best to incorporate receptor flexibility into virtual screening protocols used for drug discovery remains a significant challenge. Here, stepwise methodologies are described to generate and select relevant protein conformations for virtual screening in the context of the relaxed complex scheme (RCS), to design small molecule libraries for docking, and to perform statistical analyses on the virtual screening results. Methods include equidistant spacing, RMSD-based clustering, and QR factorization protocols for ensemble generation and ROC analysis for ensemble selection.

LIBSA--a method for the determination of ligand-binding preference to allosteric sites on receptor ensembles.

Incorporation of receptor flexibility into computational drug discovery through the relaxed complex scheme is well suited for screening against a single binding site. In the absence of a known pocket or if there are multiple potential binding sites, it may be necessary to do docking against the entire surface of the target (global docking). However no suitable and easy-to-use tool is currently available to rank global docking results based on the preference of a ligand for a given binding site. We have developed a protocol, termed LIBSA for LIgand Binding Specificity Analysis, that analyzes multiple docked poses against a single or ensemble of receptor conformations and returns a metric for the relative binding to a specific region of interest. By using novel filtering algorithms and the signal-to-noise ratio (SNR), the relative ligand-binding frequency at different pockets can be calculated and compared quantitatively. Ligands can then be triaged by their tendency to bind to a site instead of ranking by affinity alone. The method thus facilitates screening libraries of ligand cores against a large library of receptor conformations without prior knowledge of specific pockets, which is especially useful to search for hits that selectively target a particular site. We demonstrate the utility of LIBSA by showing that it correctly identifies known ligand binding sites and predicts the relative preference of a set of related ligands for different pockets on the same receptor.

Discovery of Staphylococcus aureus Sortase A Inhibitors Using Virtual Screening and the Relaxed Complex Scheme

Staphylococcus aureus is the leading cause of hospital-acquired infections in the United States. The emergence of multidrug-resistant strains of S. aureus has created an urgent need for new antibiotics. Staphylococcus aureus uses the sortase A enzyme to display surface virulence factors suggesting that compounds that inhibit its activity will function as potent anti-infective agents. Here, we report the identification of several inhibitors of sortase A using virtual screening methods that employ the relaxed complex scheme, an advanced computer-docking methodology that accounts for protein receptor flexibility. Experimental testing validates that several compounds identified in the screen inhibit the activity of sortase A. A lead compound based on the 2-phenyl-2,3-dihydro-1H-perimidine scaffold is particularly promising, and its binding mechanism was further investigated using molecular dynamics simulations and conducting preliminary structure-activity relationship studies.

Farnesyl Diphosphate Synthase Inhibitors fromIn SilicoScreening

The relaxed complex scheme is an in silico drug screening method that accounts for receptor flexibility using molecular dynamics simulations. Here, we used this approach combined with similarity searches and experimental inhibition assays to identify several low micromolar, non-bisphosphonate inhibitors, bisamidines, of farnesyl diphosphate synthase (FPPS), an enzyme targeted by some anticancer and antimicrobial agents and for the treatment of bone resorption diseases. This novel class of farnesyl diphosphate synthase inhibitors have more drug-like properties than existing bisphosphonate inhibitors, making them interesting pharmaceutical leads.

Utilizing Experimental Data for Reducing Ensemble Size in Flexible-Protein Docking

Efficient and sufficient incorporation of protein flexibility into docking is still a challenging task. Docking to an ensemble of protein structures has proven its utility for docking, but using a large ensemble of structures can reduce the efficiency of docking and can increase the number of false positives in virtual screening. In this paper, we describe the application of our new methodology, Limoc, to generate an ensemble of holo-like protein structures in combination with the relaxed complex scheme (RCS), to virtual screening. We describe different schemes to reduce the ensemble of protein structures to increase efficiency and enrichment quality. Utilizing experimental knowledge about actives for a target protein allows the reduction of ensemble members to a minimum of three protein structures, increasing enrichment quality and efficiency simultaneously.

Non‐Bisphosphonate Inhibitors of Isoprenoid Biosynthesis Identified via Computer‐Aided Drug Design

The relaxed complex scheme, a virtual-screening methodology that accounts for protein receptor flexibility, was used to identify a low-micromolar, non-bisphosphonate inhibitor of farnesyl diphosphate synthase. Serendipitously, we also found that several predicted farnesyl diphosphate synthase inhibitors were low-micromolar inhibitors of undecaprenyl diphosphate synthase. These results are of interest because farnesyl diphosphate synthase inhibitors are being pursued as both anti-infective and anticancer agents, and undecaprenyl diphosphate synthase inhibitors are antibacterial drug leads.

Molecular Recognition in the Case of Flexible Targets

A protein's flexibility is well recognized to underlie its capacity to engage in critical functions, such as signal transduction, biomolecular transport and biochemical reactivity. Molecular recognition is also tightly linked to the dynamics of the binding partners, yet protein flexibility has largely been ignored by the growing field of structure-based drug design (SBDD). In combination with experimentally determined structures, a number of computational methods have been proposed to model protein movements, which may be important for small molecule binding. Such techniques have the ability to expose new binding site conformations, which may in turn recognize and lead to the discovery of more potent and selective drugs through molecular docking. In this article, we discuss various methods and focus on the Relaxed Complex Scheme (RCS), which uses Molecular Dynamics (MD) simulations to model full protein flexibility and enhance virtual screening programmes. We review practical applications of the RCS and use a recent study of the HIV-1 reverse transcriptase to illustrate the various phases of the scheme. We also discuss some encouraging developments, aimed at addressing current weaknesses of the RCS.

Accommodating Protein Flexibility for Structure-Based Drug Design

Proper incorporation of protein flexibility for prediction of binding poses and affinities of small compounds has attracted increasing attention recently in computational drug design. Various approaches have been proposed to accommodate protein flexibility in the prediction of binding modes and the binding free energy of ligands in an efficient manner. In this review, the significance of incorporating protein flexibility is discussed from the structural biophysical point of view, and then various approaches of generating protein conformation ensembles, as well as their successes and limitations, are introduced and compared. Special emphasis is on how to generate a proper ensemble of conformation for a specific purpose, as well as the computational efficiency of various approaches. Different searching algorithms for the prediction of optimal binding poses of ligands, which are the core engines of docking programs, are accounted for. Scoring functions for evaluation of protein-ligand complexes are compared. Two end-point methods of free energy calculation, Molecular Mechanics/Poisson-Boltzmann Surface Area (MM/PBSA) and the Linear Interaction Energy (LIE) method, are briefly reviewed. Finally, we also provide an example for the extension of the conventional protein-ligand docking algorithm for prediction of multiple binding sites and ligand translocation pathways.

Relaxed complex scheme suggests novel inhibitors for the lyase activity of DNA polymerase beta

DNA polymerase beta (pol β), the error-prone polymerase of base excision repair, plays a significant role in chemotherapeutic agent resistance. Its over expression reduces the efficacy of anticancer drug therapies including ionizing radiation, bleomycin, monofunctional alkylating agents and cisplatin. Small-scale studies on different types of cancer showed that pol β is mutated in approximately 30% of tumors. These mutations further lower pol β fidelity in DNA synthesis exposing the genome to serious mutations. These findings suggested pol β as a promising therapeutic target for cancer treatment. More than 60 pol β-inhibitors have been identified so far, however, most of them are either not potent or specific enough to become a drug. Here, we applied the relaxed complex scheme virtual screening (RCSVS) to allow for the full receptor flexibility in filtering the NCI diversity set, DrugBank compounds and a library of ∼9000 fragmental compounds for novel pol β inhibitors. In this procedure we screened the set of ∼12,500 compounds against an ensemble of 11 dominant-receptor structures representing the essential backbone dynamics of the 8 kDa domain of pol β. Our results predicted new compounds that can bind with higher affinity to the lyase active site compared to pamoic acid (PA), a well-known inhibitor of DNA pol β.

DOCKING OF RALTEGRAVIR TO HIV-1 INTEGRASE STRUCTURE ENSEMBLE

Docking of the drug raltegravir to HIV-1 integrase (IN) was performed based on the established Relaxed Complex Scheme (RCS) method which accounts for the flexibility of both receptor and ligand in molecular docking. Two representative butterfly-like structures of raltegravir were identified and both of them mimicked the binding mode of 5CITEP with similar ligand-receptor interactions. Furthermore, the results that raltegravir interacted with magnesium by intermediate water molecules indicate the importance of water molecules at the binding site which has always been ignored in the docking studies of IN inhibitors. Taking these water molecules into consideration gives more insight into the design and development of the second generation IN inhibitors.

Computer-Aided Identification ofTrypanosoma bruceiUridine Diphosphate Galactose 4′-Epimerase Inhibitors: Toward the Development of Novel Therapies for African Sleeping Sickness

Trypanosoma brucei, the causative agent of human African trypanosomiasis, affects tens of thousands of sub-Saharan Africans. As current therapeutics are inadequate due to toxic side effects, drug resistance, and limited effectiveness, novel therapies are urgently needed. UDP-galactose 4′-epimerase (TbGalE), an enzyme of the Leloir pathway of galactose metabolism, is one promising T. brucei drug target. We here use the relaxed complex scheme, an advanced computer-docking methodology that accounts for full protein flexibility, to identify inhibitors of TbGalE. An initial hit rate of 62% was obtained at 100 μM, ultimately leading to the identification of 14 low-micromolar inhibitors. Thirteen of these inhibitors belong to a distinct series with a conserved binding motif that may prove useful in future drug design and optimization.

Emerging Methods for Ensemble-Based Virtual Screening

Ensemble based virtual screening refers to the use of conformational ensembles from crystal structures, NMR studies or molecular dynamics simulations. It has gained greater acceptance as advances in the theoretical framework, computational algorithms, and software packages enable simulations at longer time scales. Here we focus on the use of computationally generated conformational ensembles and emerging methods that use these ensembles for discovery, such as the Relaxed Complex Scheme or Dynamic Pharmacophore Model. We also discuss the more rigorous physics-based computational techniques such as accelerated molecular dynamics and thermodynamic integration and their applications in improving conformational sampling or the ranking of virtual screening hits. Finally, technological advances that will help make virtual screening tools more accessible to a wider audience in computer aided drug design are discussed.

Ensemble-based virtual screening reveals dual-inhibitors for the p53–MDM2/MDMX interactions

The p53 protein, a guardian of the genome, is inactivated by mutations or deletions in approximately half of human tumors. While in the rest of human tumors, p53 is expressed in wild-type form, yet it is inhibited by over-expression of its cellular regulators MDM2 and MDMX proteins. Although the p53-binding sites within the MDMX and MDM2 proteins are closely related, known MDM2 small-molecule inhibitors have been shown experimentally not to bind to its homolog, MDMX. As a result, the activity of these inhibitors including Nutlin3 is compromised in tumor cells over-expressing MDMX, preventing these compounds from fully activating the p53 protein. Here, we applied the relaxed complex scheme (RCS) to allow for the full receptor flexibility in screening for dual-inhibitors that can mutually antagonize the two p53-regulator proteins. First, we filtered the NCI diversity set, DrugBank compounds and a derivative library for MDM2-inhibitors against 28 dominant MDM2-conformations. Then, we screened the MDM2 top hits against the binding site of p53 within the MDMX target. Results described herein identify a set of compounds that have been computationally predicted to ultimately activate the p53 pathway in tumor cells retaining the wild-type protein.